Therapeutic Potential of Optogenetic Treatment for Individuals with Multiple Sclerosis

doi:10.22186/jyi.33.4.77-82

Abstract | Introduction | Future Directions and Conclusion | References | PDF

Full Issue: September 2017 Special Edition

Abstract

Multiple Sclerosis (MS) is a chronic neuroautoimmune condition characterized by neurodegeneration and demyelination throughout the central nervous system. While the pathology of MS is largely unknown, its symptoms are well defined. Current MS therapies such as intravenous corticoid injection, disease modifying treatments (DMTs) and neuro-rehabilitation exist; however most are ineffective as they do not manage symptoms efficeiently, leading to many adverse side effects. Optogenetic stimulation of demyelinated regions may serve as the needed therapy to effectively treat symptoms given the advances achieved in its rapid mechanisms and accurate cell-type-specific delivery strategies. In fact, the hallmark of optogenetic technology is the fast and accurate activation of specific neurons. Current evidence supports optogenetics as a means of controlling or enhancing neural circuitry involved in specific symptoms. This is done by targeting specific cells implicated in their respective neural circuits and activating them, or activating interneurons that inhibit the target pathway. Moreover, continuous photostimulation has been found to strengthen neuronal circuitry by promoting long-term potentiation (LTP). This review analyzes several studies that utilize optogenetics to alleviate MS-related symptoms such as cognitive impairment, visual impairment, bladder/bowel dysfunction, and tremors by controlling their specific pathways. It will also assess how these studies may translate to MS patients. Possible challenges in creating such a treatment will also be discussed. Given literature on the application of optogenetic treatment in neurodegenrative models is limited, this review presents a theoretical means of creating optogenetics treatment for MS and other neurodegenerative disorders.

Introduction

Multiple Sclerosis (MS) is a chronic autoimmune disease that leads to focal and diffuse neurodegenration and myelination throughout the nervous system (Kolasinski et al., 2012; Siffrin, Vogt, Radbruch, Nitsch, & Zipp, 2010). In its most common form, relapse-remitting MS, it is characterized by high inflammation levels that lead to a continuous cycle of relapse and remission (Raffel, Wakerley, & Nicholas, 2016). These relapses, called exacerbations, may come in the form of new or worsening of old symptoms that are largely neurological such as visual impairment and imbalance that worsen over days or weeks, then recover spontaneously (Wingerchuk et al., 2014). Other common symptoms are cognitive impairment, loss of bladder control, leg weakness and sensory symptoms (Raffel et al., 2016).
Genetic and environmental factors both have a role in MS development; however, a specific link to the disease has not been found (Harbo, Gold, & Tintoré, 2013). Genetically, MS is best characterized by a mutation on the human leukocyte antigen (HLA) gene locus, which causes abnormal antigen recognition of T cells leading to attacks on myelin proteins (Raffel et al., 2016). These findings have not been conclusive, as many other genes involved in immunological roles have also been found to play a role in contributing to MS. Environmental risk factors include smoking ,sunlight exposure, and vitamin D deficiency (Raffel et al., 2016).
Currently, there are no treatments that cure MS (Ziemssen et al., 2016). Instead, treatments target symptom management to increase patients’ quality of life. These include high doses of corticosteroids such as methylprednisolone (Jongen et al., 2016), Disease modifying Treatments (DMTs) such as interferon β-1a, interferon β-1b, alemtuzumab, fingolimod and natalizumab (Carrithers et al., 2014; Gajofatto & Benedetti, 2015), and neuro-rehabilitation (Dasari, Wootla, Warrington, & Rodriguez, 2016). All of these treatment options have adverse effects or are not particularly effective in the long term (Jongen et al., 2016; Ontaneda, Fox, & Chataway, 2015; Schäcke, Döcke, & Asadullah, 2002; Ziemssen et al., 2016). There is a considerable need for new treatment options that are more effective, while reducing the adverse side-effects. A potential therapy for MS-affected individuals may be the therapeutic application of optogenetics.
Optogenetics is a novel method that utilizes photoreceptors to selectively activate neurons (Hegemann & Nagel, 2013). The genetic code of these receptors is delivered either virally or non-virally to be expressed on the cells of interest. Once expressed, light is shone directly on these cells through an optic fiber inserted into the brain or spinal cord to be activated. Advances in this technology allow the photoreceptors to be selectively expressed on specific cell types, and in turn enable the control of specific neural pathways. Although largely used in research applications (Namboodiri & Stuber, 2016), literature describing the therapeutic potential in neurodegenerative diseases is lacking. More recently, there has been a spike in literature demonstrating the therapeutic applications of optogenetics in the context of various disorders and symptoms. For example, evidence has shown optogenetic stimulation enhances cognitive function (Goshen, 2014), visual ability (Jazayeri & Remington, 2016), bladder/bowel dysfunction (Stamp et al., 2017), and tremors (Tønnesen, 2013) through neuromodulatory effects.
While many of these studies have been conducted on specific symptoms, the focus of the optogenetic treatment has not been on any neurodegenerative models that express similar symptomology. Indeed, the current literature on the topic does not present any research on the translation of optogenetic treatment into any neurogenerative models expressing similar symptomology, requiring further research in this field (Ahmad, Ashraf, & Komai, 2015; Bordia, Perez, Heiss, Zhang, & Quik, 2016; Bryson, Machado, Lieberam, & Greensmith, 2016; Jazayeri & Remington, 2016). This review paper will assess the potential use of optogenetics in the development of therapies for MS related symptoms such as cognitive impairment, visual impairment, bladder/bowel dysfunction, and tremors.

Development of Optogenetic Mechanisms

Initial studies investigating the use of photoreceptors invovled metabotropic photoreceptors of vertebrate and invertebrate eyes (Zemelman, Lee, Ng, & Miesenbö Ck, 2002). However, these systems were too complex to manipulate and the delay between light exposure and action potential firing was highly variable ranging from a few hundred milliseconds to tens of seconds (Lyon, 2013). Focus shifted to ionotropic microbial opsins as they exhibit fast, direct light-dependent ion conduction across the cell membrane (Mudiayi, Wong, & Gruber, 2015). Furthermore, microbial opsins allow reversible control of neurons on the timescale of individual action potentials, which was lacking in earlier methods (Boyden Zhang, Bamberg, Nagel, & Deisseroth, 2005). From a therapeutic perspective, however, the difference in seconds and milliseconds between the speed of activation of these cells is not significant. The rapid control of these cells does not necessarily affect the overall efficiency of the treatment. It is critical to understand that most optogenetic developments were directed as a means to enhance research tools. For example, creating faster optical controls allow remote control of individual spikes or synaptic events and enabling genetically targeted photostimulation with finer temporal resolution (Boyden et al., 2005). While the increased control speed is welcomed, it holds no major significance other than that symptoms would be halted seconds earlier. However, as it stands today, most studies use the microbial channelrhodopsin-2 (Nagel et al., 2003), warranting focus on this protein as a primary candidate for developing an optogenetic treatment.
ChR2 is isolated from the genome of the single celled algae Chlamydomonas reinhardtii (Nagel et al., 2003). ChR2 application was further developed by inserting the protein via viral vectors into mammalian hippocampal (HPC) neurons (Boyden et al., 2005). Once imbedded, high-speed optical switching photostimulates neurons, impressively responding in one to two milliseconds. Furthermore, neural activity was controlled by simply switching the optical blue light on or off (Boyden et al., 2005). This control can also be used by activating inhibitory circuitries, creating an antagonist effect on the region or function of interest. Molecularly, once the optical light is shone on the brain region of interest, photostimulation increased ion transport across the cellular membrane by either opening an ion channel or by actively pumping ions (Mudiayi et al., 2015).

Current Delivery Strategies and Therapeutic Obstacles

Non-viral delivery methods of expressing ChR2 in cells include in utero electroporation, transgenic models, chemical lipofection, and laser-assisted cellular poration (Boyden et al., 2005; Carter & de Lecea, 2011; Mohanty & Lakshminarayananan, 2015). Although beneficial for research, these methods are not viable translational strategies for human treatment. Moreover, these methods possess limitations such as not being able to specifically target cells, posing a risk to cellular components or the foreign DNA, and association with axonal pathology (Bryson et al., 2016; Mohanty & Lakshminarayananan, 2015). Due to the lack in cell specific targeting and the lack of lateralization to humans of non-viral methods, it seems viral delivery methods provide the most sensible means of creating an optogenetic treatment, especially when studied in non-human primate models.
The most common method of expressing ChR2 in a nervous system is to infect neurons with a deficient virus replication, typically an adeno-associated virus (AAV) or lentivirus (LV), containing the transgene of interest driven by a short promoter or enhancer element (Carter & de Lecea, 2011). AAVs are small viruses that efficiently transduce neurons while inducing minimal immune responses in the host brain (Blits et al., 2010). LV vectors are derived from a genus of retroviruses that cause chronic diseases characterized by long incubation periods such as the human immunodeficiency virus (HIV; Dull et al., 1998). In both methods, once ChR2 is expressed in the region of interest, illuminating the neurons with blue light at a bandwidth of 450–490 nm induces rapid depolarizing currents. However, literature has shown a difference in efficacy when used in non-human primates. One study has shown transduction with AAV yields positive functional and behavioral results, but not LV, indicating that AAV may be a more effective viral delivery method in primates compared to LV (Gerits et al., 2012). Moreover, in a recent breakthrough study, successful cell-type-specific expression of ChR2 in midbrain dopamine neurons of wild-type Rhesus macaques utilized AAVs, not LVs (Stauffer et al., 2016). A vector delivering Cre recombinase under the control of a tyrosine hydroxylase (TH) promoter fragment and a vector delivering a Cre-recombinase-dependent ChR2 were mixed and injected to attain cell-type-specific expression of ChR2 (Stauffer et al., 2016). The TH promoter can be substituted in the first vector to other neuron-subtype-specific promoters to optogenetically control other neuron types in a monkey brain. For example, in an MS patient with lesions in the spinal cord affecting γ-aminobutyric acid (GABA) neurons, the Cre-recombinase vector being develived would require a glutamate decarboxylase (GAD) promoter fragment. This is because GAD is the enzyme that catalyzes the decarboxylation of glutamate to GABA and is only found in GABAergic cells, ensuring ChR2 expression is limited these cells. Further applications of this technique can be found in treatment of various MS symptoms utilizing the specific pathways and neural circuitry they operate through.

Evidence of Therapeutic Potential for Multiple Sclerosis Related Symptoms

Photostimulation may serve as a factor in dealing with MS symptoms such as cognitive impairment (Goshen, 2014), visual impairment (Jazayeri & Remington, 2016), bladder/bowel dysfunction (Stamp et al., 2017), and tremors (Tønnesen, 2013) by controlling their specific pathways. This especially possible once coupled with stem cell therapy (Bryson et al., 2016). However, while optogenetics may treat these symptoms, this review does not intend to demonstrate the effect of photostimulation on the autoimmune function of the disorder. To our knowledge, literature documenting immunomodulation using optogenetics is lacking, and what has been published only discusses proof-of-concept and designs for future development (Tan, He, Han, & Zhou, 2017). The approaches involve optogenetic control of immune responses with novel tools that modulate lymphocyte trafficking, inflammasome activation, dendritic cell (DC) maturation, and antitumor immunity (Tan et al., 2017). Further information on the theoretical methods involving the combination of optogenetics and immunoengineering, termed optoimmunoengineering, can be found in the review conducted by Tan et al. (2017)
The most common cognitive impairment seen in MS is visual learning and memory (Chiaravalloti & Deluca, 2008). Evidence has shown the problem lies in the initial learning of the memories as memory recall in MS patients is equal to healthy individuals, indicating that long-term memory systems are relatively intact (Chiaravalloti & Deluca, 2008). The theoretical construct suggested to treat cognitive impairment in MS patients is to utilize induced pluripotent stem cells to derive oligodendrocyte progenitor cells and mature oligodendrocytes for remyelination of regions displaying degeneration that process working memory. While theroretically, stem cell transplantation should be able to resolve the issue with neuronal loss, clinical trials are showing unsuccessful results that are not entirely understood (Zhang et al., 2011). Recent studies suggest there is limited success due to the complexity involved with degrading glial scarring (Mallory, Grahn, Hachmann, Lujan, & Lee, 2015). It is hypothesized phototimulation of oligodendrocytes after differentiation would strengthen the remylination process as well as neural circuitry within that brain region through long-term potentiation (Lignani et al., 2013; Takeuchi et al., 2016). Takeuchi et al. (2016) were able to demonstrate optogenetic stimulation of the locus coeruleus (LC) enhances consolidation of everyday memory. The study electrophysiologically recorded LC firing rates in novel enivronments and stimuli and recreated this effect with photostimulation alone. Moreover, LTP was observed with repeated stimulation. This demonstration of LTP due to optogenetics is significant in providing contact for how optogenetics may affect neural circuitry with repeated stimulation. In this function and in the rest of the symptoms that will be discussed, we hypothesize that not only will optogenetics control the symptom by decreasing or inhibiting its presence, photostimulation may also lead to enhanced management of symptoms without the need for simulation in the long term.
Visual impairment is often seen in MS patients, commonly manifesting as optic neuritis, which is an acute inflammatory disorder of the optic nerve typically presenting with sudden monocular visual loss and eye pain (Garcia-Martin et al., 2017). Macaques were used to study visual information processing mechanisms in the lateral geniculate nucleus (LGN) and primary visual cortex (V1) by administering an AAV with an effective CamKII promoter into koniocellular cells (K-cells) at the LGN (Klein et al., 2016). The LGN is made up of K-cells, parvo cells and magno cells, each distinct in their circuitry, function and biochemistry, despite all passing through the V1. K-cells however were used as they are especially different form the other two cells. The vectors used were able to target K-cells, nearby CamKII-positive cells, as well as transduce distant layer 6 pyramidal cells of V1 and retinal ganglion cells (Klein et al., 2016). Measurements were conducted using average local field potential (LFP) responses across stimulation trials and current source-density (CSD) profiles were calculated for the visual flicker and optogenetic conditions to assess V1 laminar activation. Of the total population of LGN neurons recorded, the authors identified 23% as being directly affected by the optogenetic stimulation, in comparison to the ~10% observed in the literature (Klein et al., 2016). Although less than 50% of the cells were activated, the authors were able to confirm that at the neuronal circuit level, the amount of selectively recruited K-cells was sufficient to drive short-latency activity in the supra-granular layers of downstream area V1 (Klein et al., 2016).
In translating these findings for an MS treatment, a more enhanced outcome may be observed if all cells of LGN are recuited. This is especially since this study only sought to assess the ability of optogenetic stimulation in the visual cortex to understand the visual pathway, not with the intention of developing a therapy for visual impairment. No mention was made on the level of enhancement observed in the visual ability of the monkeys, warranting further studies on optogenetic stimulation of this brain region. Moreover, an optogenetic treatement for this function coupled with stem cell therapy may provide a means to alter visual impairment in MS. Similar to the function described in treating cognitive impairment, photostimulation of these pathways may treat visual impairment by strengthening and expanding the neural circuitry and remyelination processes. Interestingly, clinical trials are being conducted for a fascinating treatment option for retinitis pigmentosa (RP) using ChR2 and the concept of optogenetic stimulation (Birch, 2016).
Bladder and bowel dysfunctions are commonly seen in MS cases, causing some of the most distressing symptoms with as many as 75% MS of patients presenting the symptom (Andretta, Simeone, Ostardo, Pastorello, & Zuliani, 2014). The most frequent bladder symptoms seen are storage symptoms such as urinary frequency, urgency, and urge incontinence (Andretta et al., 2014). Voiding symptoms such as hesitancy, incomplete voiding and urinary retention are present as well, although to a lesser extent (Andretta et al., 2014).
Enteric neural cells from fetal or postnatal mouse bowels expressing ChR2 were transplanted into the distal colon of 3-4 week old wild-type mice (Stamp et al., 2017). The transplanted neural cells were able to differentiate into multiple functional types of neurons, integrating and providing functional innervation of the smooth muscle of the bowel wall (Stamp et al., 2017). In the study, optogenetics was used to to selectively stimulate graft-dervied neurons to identify that enteric neural cells isolated from the embryonic and postnatal bowels, giving rise to functional inhibitory motor neurons, excitatory motor neurons, and interneurons following transplantation into the distal colon of recipient mice (Stamp et al., 2017). While optogenetic stimulation was not the primary cause of the functional recovery, when used as a tool, photostimulation can control how these new cells operate. In a disorder that leads to a loss of function due to continuous degeneration, optogenetic stimulation can speed the recovery period as cells are continuously destroyed. Moreover, we hypothesize continuous photostimulation will lead to LTP and strengthening of these networks faster than without the stimulation. These findings are significant as they illuminate a fundamental limitation in almost all the current gold-standard nerve-targeted treatment approaches which do not specifically address isolated neural circuits and lead to undesirable side effects such as unwanted bowel movements or sexual function (Park et al., 2017).
Tremors are believed to occur in up to 75% of MS patients appearing in various forms such as postural, kinetic, proximal, distal tremors, and internal tremors (IT; Ayache et al., 2015). Dysfunction in inhibitory cerebellar efferent projections likely play a role in the generation of tremors during posture or movement in MS patients, however, additional lesions of other cerebral pathways might be involved (Ayache et al., 2015). Optogenetic treatment for tremors would function similarly to those documented in Parkinson’s disease (PD). Cell-type specific targeting of dopaminergic neurons in the substantia nigra pars compacta (SNc) has shown to be a viable means of treating denervation of striatal target areas (Stauffer et al., 2016; Tønnesen, 2013). This process is thoroughly described in the study by Stauffer et al. (2016). Applying photostimulation to the regions found to underlie tremor development and motor dysfunction in MS, such as gait, would be a feasible means of treating these symptoms, given its documented applications in similar cases (Kravitz et al., 2010).

Future Directions and Conclusion

Optogenetics has been reported to be a revolutionary technique in neurobiology research. As such, the objective of this review is to assess the potential use of optogenetics in developing therapies for MS related symptoms that include cognitive impairment, visual impairment, bladder/bowel dysfunction, and tremors. Studies for each of these symptoms have been discussed and analyzed and two primary conclusions have been found. Intially, optogenetics remains a tool to enhance treatment. For example, in the study by Stamp et al. (2017), the primary function of the study was to understand how implanted enteric cells functionally integrate into endogenous cells. Optogenetics was merely a tool to control this function to further study it. While it was not used as a treatment, this function of controlling the circuitry may be manipulated into a therapy for those with bladder dysfunction and other illnesses observed in MS.
Secondly, while this control does require manually intiating photostimulation, continuous stimulation may lead to enhancement in circuitry through neuroplastic and LTP effects  as seen in Takeuchi et al. (2016). We hypothesize the manual function of turning on photostimulation in the brain may work similarly to a pacemaker where optic fibers are connected internally in the body. Of course these concepts remain theoretical and require extensive research to validate this possibility.
Ultimately, furthering this therapeutic tool is limited by the knowledge present for specific symptoms as well as their mechanisms (Bryson et al., 2016; Jazayeri & Remington, 2016; Mohanty & Lakshminarayananan, 2015; Mudiayi et al., 2015). Just as optogenetics may be used as a therapeutic tool, it can be utilized to understand these symptoms as it is currently used as an investigative tool (Carter & de Lecea, 2011; Mohanty & Lakshminarayananan, 2015; Mudiayi et al., 2015). A first step to identifying how photostimulation can lead to therapeutic effects could ultimately be using optogenetics to understand individual symptoms by experimenting with its circuitry and inhibiting or activating symptom pathways. Once this knowledge has been attained, more specific and accurate targets can be found to control MS symptomology.

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Application of Neuroscience Principles for Evidence-based Design in Architectural Education

doi:10.22186/jyi.33.4.71-76

Abstract | Introduction | Evidence-Based DesignConclusions | References | PDF

Full Issue: September 2017 Special Edition

Abstract

We spend approximately 90% of our time within a built environment, whether it is in our homes, offices, schools, city parks, or public spaces. This bears significance, as we are equally shaped by both our genetic makeup as well as our environment, which brings into question of how we experience space, and in turn how these experiences impact our behaviour. To gain a greater understanding of these impacts, neuroscience seeks to root out the principles of biological mechanisms involved in consciousness, spatial navigation and environmental stressors. However, the use of these principles is not discussed extensively within the curriculum of undergraduate or graduate architecture programs in North America. This paper aims to highlight that such information is critical to the advancement of evidence-based design by acknowledging the role of conscious awareness within space. An observable shift in the design community in collaborative neuroscience research can be seen in multi-sensory and virtual reality labs being constructed into design firms within North America. This review stipulates that architecture students should be prepared for the changes in quantifiable research and perceptual data collection coming to their field by examining the importance of neuroscience research in perception and consciousness. Architecture students who can interpret scientific research will not only have the advantage of a greater understanding of the human condition within space, but they will also be able to evolve the standard of design.

Introduction

Architects have long sought to inspire creativity, ingenuity, worship, community and awe using the tools at their disposal. Homo faber, “Man the Maker”, crafts his environment, thereby controlling his fate. As a result of human ingenuity, we now spend over 90% of our time within a built environment crafted to suit our needs (Janda & Janda, 2017). Design is inspired by societal reform and scientific exploration expressed as an art form in itself. If architecture is an expression of creativity as a mean to reflect on the human condition, one might argue that such a reflection can also be found within neuroscientific exploration of the mind. As we come to understand the biological mechanisms of perception, consciousness and their residual impacts on mental and physical health, there is question of how our environment might in turn affect those mechanisms.
Perception of space relies upon conscious awareness: the ability to receive and comprehend exterior and interior stimuli through the use of the Global Workspace Theory. A good example of the interjection of neuroscience and architecture can be found in spatial navigation research. Scientific authors are capable of identifying floor patterns that are most and least useful to way-finding. Studies have also found that computer game and virtual reality architects may play an integral role in retaining memory and attention in elderly populations (Optale et al., 2010). Architectural students can benefit from a greater understanding of the impact of environmental stressors on biological mechanisms. Chronic stress response is one of the most pressing design problems as it may increase the risk of psychobiological disorders such as immune deficiencies, irritable bowel syndrome, depression, and anxiety (Hammen, 2015).
Neuroscience research permits an objective review of the usability and mental health impacts of space. “An informed architect could use this research as a means for evidence-based design (EBD), a concept which seeks to ratify design standards of the built environment by incorporating research from multiple disciplines into the design process.” However, of the 113 post-secondary architecture institutions in North America, only the New School of San Diego offers students a certification program, which applies neuroscience principles to evidence-based practice (“Certificate in Neuroscience for Architecture” 2017). Although EBD is currently taught in many programs geared towards renewable/sustainable/green buildings, a truly multidisciplinary approach to EBD involves neuroscientific, psychological and economic research to guide design, a method commonly used in healthcare facilities today (Ulrich, Zimring, & Zhu, 2008).
Students in architecture are entering a field which is now exploring ways to make use of neurobiological data analysis involving environmental stimuli to achieve EBD. This review stipulates that architecture students will benefit from a greater understanding of conscious perception towards health-centric design. This will also allow them to collaborate with multisensory and virtual reality labs along with other cutting edge design firms and academic institutions merging neuroscience research into design.

Neurological Influences of the Environment on Health

Consciousness is perhaps the most important existential question that has yet to be solved. It is described in a number of ways in relation to philosophical, psychological, and neuroscientific interpretation. It is broadly defined as “the mind”, the perceptual awareness of external and internal stimuli, which influence cognitive activity (Searle, 2000). Consciousness is often considered separate from other neurological mechanisms that humans share due to its qualitative and subjective nature. The majority of consciousness research has been conducted on the verbal and behavioural assessment of participants. These findings can be questionable as we all experience our environment, our personalities, and our memories differently thereby increasing the chance of error in experimental findings. However, consciousness is an entirely biological phenomenon and subjective ontology challenges, but does not prevent an objective scientific research. The breadth of this field touches upon multisensory interpretation, memory recall, attention and various cognitive mechanisms; however, this section will focus on the conscious effects of our environment on way-finding and stress.
Through the use of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), neuroscientists attempt to identify the neuronal pathways, which produce the conscious experience. The Global Workspace Theory (GWT) is widely accepted in the scientific community to be representative of conscious and unconscious processes (Prakash et al., 2008). It is similar to the concept of working memory in that GWT proposes experience to be momentary and subjective. Multisensory stimuli (conscious) are initially interpreted by various cognitive processes (unconscious), which is referred to as the “receiving process”. This information can then be used to produce a movement, emotion, or behaviour. GWT lends itself quite readily to computational modeling and can distinguish the brain regions impacted by competition of sensory modalities (e.g., a video and its audio being out of sync).

Way-Finding and Spatial Awareness

There are a multitude of research initiatives involving the brain and behaviour within the environment. Way-finding will be used as a practical example to showcase the power of design as a psychobiological influencer on behaviour and health.Way-finding is the neurophysiological experience of self while navigating the environment. This biological mechanism allows us to locate ourselves within space by taking in information from visual and auditory cues while simultaneously utilizing stored spatial memories. The environmental cues paired with spatial memory then allow for a decision to be made via limb movement and body axis direction (Macagno, 2014). Way-finding is a particularly relevant tool in design as spatial alignment efficiency can either aid navigation or cause confusion and unease within the built environment.
Way-finding can be categorized by the activation of neuronal pathways that create a cognitive mapping system. Nobel Prize laureate John O’Keefe and Lynn Nadel researched hippocampal cell signalling in rats. They found that specific groups of neurons, termed “place cells”, fired when rats either tasked with location recall or object recall (O’Keefe & Nadel, 1978). The authors stipulated that place representations within the hippocampus were activated together depending on the physical and perceived distances between places. Later on these findings formed the basis of the theory of “grid cells”, place-modulated cells in the presubiculum and hippocampus which fire in a crystal-like fashion in conjunction with head-direction neurons (Boccara et al., 2010). The discovery of hippocampal involvement of place cells and grid cells has offered a fascinating insight on the way we understand geometric boundaries, spatial memory and directional movement. These findings may be especially significant to architects when considering the effects of floor misalignment on the perception of our environment. Designers may also take advantage of research involving the deterioration of the aging hippocampus which impacts spatial memory in the geriatric population.
One of the ways that a building is considered a success is in the functional ease of navigation. There is a positive correlation between the perceived figural complexity of space and how the actual space reflects that perception (Weisman, 1981). If misaligned, the spatial structure of the built environment can be known to cause cognitive dissonance with way-finding. A study performed in 2004 by Werner and Schindler studied this effect via the use of a computer program simulating various aligned, misaligned, connected and disconnected floor plans (Figure 1).

NP Figure 1

Figure 1. 16 floor plans, the top two rows are connected (at 0° and 45°), the two rows at the bottom are disconnected floor plans (at 0° and 45°) (Werner & Schindler, 2004). Findings suggest that aligned floorplans reduce effort to establish spatial navigation.

Fifty-six participants familiarized themselves with a digital interface and an assigned floor plan. They were then instructed to find five target objects within the span of five minutes (Werner & Schindler, 2004). The authors found that misalignment to a central reference frame reduced the speed of accuracy in finding objects by 25% as compared to aligned floor plans. When participants were asked to point in the direction they believed an object might be according to a specific floor plan their pointing error was on average greater for misaligned than aligned floor plans (Werner & Schindler, 2004). These findings represent an exciting example of how neuroscience can interject itself into architectural education. The orientation of a floor plan can directly impact the usability and positive experience within space, this information can help disseminate patterns of design that are more efficient, thereby reducing spatial dissonance.
Finding our position within space is directly impacted by our ability to recall the layout and landmarks of our environment, and this ability deteriorates significantly with age. From approximately 50 years onwards, MRI scans reveal a decline in white matter volume, reaching up to 26% in reduction at 90 years old (Gunning-Dixon, Brickman, Cheng, & Alexopoulos, 2009). This cell loss is detrimental to hippocampal functioning, the principle region responsible for spatial memory in regards to navigation and orientation. However, research suggests that enriched environments have positive neurological benefits for the geriatric community. Researchers took a novel approach of using virtual reality (VR) to determine the possible effects on cognition and memory (Optale et al., 2010). The participants, a median age of 80 years old, were placed in either a VR memory training experimental group or control group for 6 months. The VR training involved simulated visuo-auditory environments and focused on way-finding scenes. The authors found that participants treated with VR memory training had better long term memory and cognitive functioning than the control group which they theorized may have been caused by a boost in attention capabilities. Way-finding and memory training using virtual reality environments designed using perception based learning programs can be used to reinvigorate spatial memory recall.
How we design our built environment influences the ways that we behave within that environment. There should be an educational focus on tested principles in way-finding to promote evidence-based design. Using research, we can disseminate the floor plans that generate the greatest positive response to navigation within space. When considering aging populations architects can assist virtual reality programmers in creating enriched environments that can improve spatial memory.

Impact of Environmental Stressors on Health

The stressors within our environment can shape our health. This is particularly true of how chronic stress can cause immune deficiencies and increase susceptibility to psychobiological disorders. The hypothalamic-pituitary-adrenal (HPA) axis is the pathway which mediates stress response. As a survival tactic, HPA axis activation causes physiological changes such as disruption of the digestive system, vasodilation and the release of adrenaline. The HPA axis secretes glucocorticoid cortisol, an anti-inflammatory response hormone, to suppress inflammatory cytokine production. This can be accomplished by inhibiting pro-inflammatory gene promoters, blocking in cell cascades effects, and antagonizing protein-protein interactions which mediate cytokine production (Slavich & Irwin, 2014). Under chronic stress circumstances we can observe a glucocorticoid resistance, as immune cells become less sensitive to anti-inflammatory mechanisms, causing an inability to properly regulate rising cytokine levels (Schleimer, 1993). Inflammation also causes an up regulation of enteroendocrine cells which produce serotonin, permeating the sympathetic response of the HPA axis (Spiller et al., 2000). Therefore, chronic stress can cause immune response irregularities, which can in turn increase susceptibility to common viral attacks and functional disorders, and diminish our capacity to mitigate future stress responses.
The immune system is the body’s first line of defense against viral, pathogenic and bacterial infections. This is accomplished by first detecting the agent, and then sending neural and endocrine signals to the brain. These signals up regulate the creation of inflammatory response cytokines IL-6, IL-1, and TNF-α to the affected area in an effort to contain the infection (Slavich & Irwin, 2014). Genetic predispositions towards inflammation and stress response inhibition combined with the impact of environmental stressors have been connected to an increased risk to functional disorders such as irritable bowel syndrome (IBS) (Drossman, Camilleri, Mayer, & Whitehead, 2002). It is estimated that approximately 10-25% of the population is affected at some point but only 30% of those suffering from IBS are likely to seek out treatment (Drossman et al., 2002). Overexposure of proinflammatory cytokines and cortisol may also increase susceptibility to heightened states of anxiety and depression. Furthermore, deregulation of the HPA axis can impact synaptic plasticity as well as dopaminergic and serotonin output within the striatal areas, the amygdala, and the hippocampus (Hammen, 2015).
Furthermore, maladaptive stress response can be transmitted through transgenerational epigenetic modification. In rodent and primate models, we can observe prevalence in genetic expression instigated by stress response across multiple generations (Franklin et al., 2010). Studies have shown that unpredictable home environments in rats can reduce 5HT1A receptor expression in the dorsal raphe nucleus in descendants (Franklin et al., 2010). This change in receptor expression is akin to the pathogenesis seen in antisocial behaviours and personality disorders (Gudsnuk & Champagne, 2012). Vulnerability to stress induced psychobiological disorders is perhaps the most urgent health contingency that neuroscience research can address in the greater development of evidence-based design architecture.

Evidence-Based Design

Evidence-based design (EBD) involves the use of clinical research in the design concept of the built environment to improve health, productivity, and economic outcomes. It is a relatively new approach as it prioritizes objective and quantifiable results. EBD utilizes mounting research from neuroscience, environmental psychology, architecture, and behavioural economics to produce a framework of desired outcomes from our buildings. This section will review the process of EBD in addition to the architecture curriculums integrating of neuroscience and architecture. Furthermore, there will be an observation of the benefit of EBD in the design of health care facilities.

EBD and Neuroscience

There are a multitude of comparisons in the way science and design curriculums measure feasibility of findings and outcomes. Scientific concepts must be grounded within specific methods intrinsic to their validity. Publication of findings is critical to the advancement of research as it allows for objective review. The architectural approach differs as the interpretation of design is often subjective when considering the cultural and artistic ramifications of a structural landmark. Design is often led by trend or form, a novel build is often praised for its avant-garde design and emphasis on function can be perceived as a detriment to creativity. However, neuroscience research involving perceptual stimuli and its impacts on behaviour and health can be used to improve the current practice. As in scientific exploration, architecture may see its greatest advancements once design research is integral from building conception to measured impact and publication of findings.
A truly progressive curriculum expands onto scientific dialogue, which seeks to validate how to best enhance the human experience and eliminate the designs that are not beneficial. Students must understand the components which are conducive to those human experiences in order to conduct an evidence-based practice of responsible design. One post-secondary curriculum which stands out amongst others in terms of neuroscience and architecture integration is the New School of Architecture in San Diego. This is the first educational institution in the world to offer a certificate program in Neuroscience for Architecture (“Certificate in Neuroscience for Architecture” 2017). The courses focus on four areas that involve evidence based design practice. Students learn about environmental psychology, which is the quantifiable relationship between environment and behaviour. There is also an overview of the neurological components responsible for sensory and cognitive responses, which permit human experience within space. Students have access to neuroscience seminars focus on how to best improve health care facilities, educational, spiritual, and corporate environments using neuroscience principles. The integration of these concepts is further solidified with studio time geared towards applying these principles towards the built environment.
This program was developed by fellow of AIA and founder of the Academy of Neuroscience for Architecture (ANFA) John Eberhard, along with Dr. Eve Edelstein, PhD in Neuroscience and MA in Architecture. Both have extensive backgrounds in research and practical application of neuroscience within the built environment. Eberhard is the author of such behavioural neuroscience and architecture books such as “Inquiry by Design”(with John Zeisel, 2006), “Architecture and the Brain” (2007), and “Brain Landscape” (2008). His involvement in promoting neuroscience based EBD led to the creation of ANFA, a nexus of both fields in collaboration and research. Dr. Edelstein is the world’s first PhD Neuroscientist with a master in Architecture. She has contributed to over 43 scientific papers involving the impact of the environment on the body and brain. As a faculty member of the New School, Dr. Edelstein is educating architecture students on the concept of the built environment as a psychobiological influencer on behaviour and health. She is also the founder of Innovative Design Science, which is a design firm that specializes in implementing neuroscience research, virtual reality mock-ups, on-site design studies, as well as pre- and post-occupancy evaluations of the build. Students in San Diego are privileged to take part in a new approach towards architectural education, as they will come to understand the benefits of neuroscience and EBD in creating better buildings for its occupants.

The Role of EBD in Healthcare

EBD is most commonly used in the design of healthcare facilities. This may be due to the higher risks associated with hospitals which demand informed design to minimize loss. The concept of EBD first emerged in the 1960s as American and British health care providers measured the impact of spatial alignment and way-finding of floor layouts on staff productivity (Clipson & Johnson, 1987). Today, its method has been widely adopted by health care providers across North America. Notably, the US military Health System has constructed over 70 hospitals totalling $6 billion dollars in construction (Ulrich, Zimring, & Zhu, 2008). EBD in healthcare focuses primarily on four components: mental health improvement for patients and staff, patient recovery, staff productivity, and the use of evidence-based metrics.
The Center for Health and Design has provided a universal list of guidelines to perform EBD in healthcare facilities. The first step involves a literature review of neurological, psychological, architectural and economic research in relation to the problems the project is attempting to solve. Financial operations also need to be considered in association to multi-year investment returns and cost-effectiveness of design options. SWOT analysis is used as a decision-making tool in the placement of technical and safety healthcare features. Furthermore, the design team is heavily involved with patients and staff in regards to surveys, simulations, and pre- and post-occupancy evaluations. The goal of this method is to acquire as much information as possible in regards to healing environments to guide the construction of the facility.
The impact of EBD in healthcare is that of a measureable improvement in health outcomes, which leads to a reduced chance of infection and medical error, thereby reducing the length and cost of a patient’s stay. Researchers performed a meta-analysis of healthcare facility layouts and patient recovery time (Ulrich et al., 2008). The findings suggested that single patient rooms reduced the chance of infection, allowed for better communication with staff, and length of stay (Ulrich et al., 2008). The Agency for Healthcare Research and Quality (AHRQ) is currently leading the way in EBD by lobbying for the health and economic research in hospital design. The center advocated the use of EBD as a means to reduce avoidable incidences by using single patient room layouts, acuity-adaptable rooms and accessible nursing stations (Shoemaker & Kazley, 2010). The AHRQ also mentioned that too often there are no clear, measurable or expected outcomes for large design projects. Although EBD demonstrates these features readily, it is not widely adopted throughout the field of design (Shoemaker & Kazley, 2010). These concepts are beneficial to more than just the healthcare community as the use of EBD can transfer over to all building types and occupancy groups to improve living standards.
An understanding of scientific analysis impacts the ability for designers to implement the important research of perceptual awareness, behavioral interaction and consciousness into the conception of various structures. Educating architecture students in neuroscience allows for an EBD approach to be implemented in all areas of design. If students are more experienced with research and foster a greater awareness of the use of measurable impacts on health, they will be equipped with the knowledge to push design standards forward.

Conclusion

The future of architectural design will depend upon the advancement of evidence-based design and the inclusion neuroscientific research regarding the human experience within space. Studies involving consciousness and the Global Workplace Theory can be used to teach design students about neural correlates which permit conscious awareness (Mallgrave, 2010). A fitting example of neuroscience in architecture is found in the research involving spatial navigation and way-finding. The alignment of floor plans and their feasibility can be monitored and designed to permit the greatest ease in locating one’s self within a build environment. The aging population may also be presented with virtual reality experiences designed by computer game architects to improve memory and attention capacity (Optale et al., 2010). Neuroscience research may also be used to study the effect of environmental stressors on mental health. Students, receiving an overview of chronic HPA axis activation and its role in psychobiological disorders such as IBS, depression, anxiety and transgenerational modifications, have a responsibility to minimize the impact of stress in our daily lives through responsible design. Should students be more aware of the influence of design on the health mechanisms that allow conscious interpretation to take place, they would be more capable to participate in evidence-based design practices.
There is only one architectural program in North America which offers a Certificate in Neuroscience for Architecture; it is offered at the New School of San Diego. Students come into contact with the benefits of EBD with courses on environment and behavior, an overview of the conscious response within space, neuroscience seminars, as well as studio time dedicated to the merger of both disciplines (“Certificate in Neuroscience for Architecture” 2017). EBD is currently taught in many Architectural programs, but the course work only relates to the use of energy efficiency research to increase sustainability rather than neurobiological research to enhance perceptual experience. However, the application of neuroscience principles in EBD is widely accepted in one area of architecture today, healthcare facilities. The multi-disciplinary approach involves extensive background research, patient and staff health, and economic feasibility by implementing design standards that will reduce the length and cost of a patient’s stay. The methods used in the design of healthcare facilities and their measurable outcomes can be applied to any building type. Designers working specifically within EBD using neuroscience research demonstrate that the methods can be taught in architectural programs to promote responsible design.
The limitations of the present research involve the subjective nature of the conscious experience. The greatest challenge to the application of neuroscience as a tool in EBD involves its acceptance within the architectural community. Neuroscience and EBD are generally found within healthcare design as the planning, financial, and life risk implications are extensive. The design process is much greater and more time consuming than other builds on average. However, students stand to benefit from scientific incorporation within design, if only to have a better understanding of the impact of their work.
The future directions of the merger of these two fields involve the use of interactive labs funded by governmental agencies and architecture firms in collaboration with academic institutions. Public access to design research will improve social welfare by eliminating the design standards that are not conducive to occupant health and wellbeing. Architecture firms will need to look at the impact of their builds and become accountable for their health impacts. This may be accomplished by performing post-hoc analyses, animal and human lab research, retrieving foot traffic sensor data, satisfaction surveys and virtual reality prototyping. Before, we could look at architecture as a balance between form and function, which mostly based on what we feel rather than what we can prove as the science was not present. Allowing design to go on without accountable measures of perceptual adaptation when they are now becoming available through research negates advancement within the field and students should be ready for the changes to come in their profession.

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Chronic Traumatic Encephalopathy: Connecting Mechanisms to Diagnosis and Treatment

doi:10.22186/jyi.33.4.83-86

Abstract | Introduction |Discussion | Conclusions | References | PDF

Full Issue: September 2017 Special Edition

Abstract

Chronic traumatic encephalopathy is a progressive neurodegenerative disease that has been linked to the incidence of repetitive mild traumatic brain injuries. As chronic traumatic encephalopathy has no formal diagnosis or treatment, current research is striving to better understand its neuropathology in order to develop effective diagnostic and treatment strategies. This review will outline recent research findings in the understanding of the neuropathological mechanisms of chronic traumatic encephalopathy, and connect these findings to advancements in the diagnosis and treatment of the disease. With the emergence of more sophisticated technology, neuroimaging techniques have shown promise as prospective diagnostic tools. Functional neuroimaging techniques that allow for the observation of task-related brain activity such as functional magnetic resonance imaging (fMRI) and positron emission tomography (PET) imaging have provided significant insight into the progression of chronic traumatic encephalopathy. Additionally, a branch of magnetic resonance imaging (MRI) called diffusion tensor imaging (DTI) is currently being used to assess white matter integrity, which is often compromised in cases of repetitive mild traumatic brain injury and may be indicative of an increased risk for developing chronic traumatic encephalopathy and other neurodegenerative diseases. Several forms of pharmacotherapy, including lithium treatment and monoacylglycerol antagonists, have been suggested to target the common neuropathological markers of chronic traumatic encephalopathy. Recent research suggests that a combination of pharmacotherapy and cognitive therapy may effectively reduce symptoms and improve the quality of life in individuals with chronic traumatic encephalopathy.

Introduction

Chronic traumatic encephalopathy (CTE) is a neurodegenerative disease that is commonly observed in professional athletes, military veterans, and other individuals who have been subjected to repetitive brain injuries. Approximately 42 million people worldwide suffer from brain injury every year, which increases their risk of developing chronic traumatic encephalopathy later in life (Gardner & Yaffe, 2015).
The main symptoms associated with the disease are profound memory loss, motor deterioration, unexplained aggression, depression, and suicidality. These cognitive and behavioral symptoms are also accompanied by biological changes in the brain. Similar to Alzheimer’s disease, CTE is primarily characterized by an accumulation of tangles of protein, although the distribution of these tangles throughout the brain is unique to each disease (Walker & Tesco, 2013).
Significant attention was directed towards chronic traumatic encephalopathy when Dr. Bennet Omalu discovered the disease in a brain autopsy of former National Football League athlete Mike Webster, whose cognitive abilities had drastically declined following his retirement. Numerous indicators of significant brain deterioration were observed in Webster’s autopsy, which was suggested to be accountable for his cognitive dysfunction in his later years (Omalu et al., 2005). Since this initial autopsy, 96% of professional athletes who have been examined for CTE by autopsy have been tested positive for the disease. Although CTE appears to be most prevalent among American football athletes, it is not restricted to this group of individuals. It is suggested that any individual who has been subjected to extensive brain injury throughout their life, including victims of abuse, can develop CTE (Baugh et al., 2012).
Although many great strides have been made in the progression of research on CTE, there is still much that remains unclear about the disease. Currently, there is no formal diagnosis that can be made while the individual is still alive. A post-mortem diagnosis can be performed by an autopsy, which allows for the identification of neuropathological markers of the disease. These markers include the presence of TAR DNA-binding protein 43 (TDP-43), a diffuse spread of hyperphosphorylated tau protein, and enlarged ventricles (Gavett, Stern, & McKee, 2011). Furthermore, there are no established treatment or rehabilitation protocols for individuals who are suspected to have the disease. The goal of current research on chronic traumatic encephalopathy is to investigate prospective solutions to these gaps in knowledge, and this review will discuss recent findings in this area.

Diagnosing Chronic Traumatic Encephalopathy

Although there have been numerous suggested guidelines for diagnosing CTE in vivo based on neuropsychological observations and life history, there are currently no widely accepted pre-mortem diagnostic criteria for the disease. The emergence of more sophisticated technology is creating opportunities for advancing in vivo diagnostic methods, particularly with regards to advancements in neuroimaging techniques. These advancements enable more detailed evaluations of the features of CTE, which are greatly beneficial for further understanding the neuropathological correlation of the disease and how they are unique from other neurodegenerative diseases.
Traditional structural neuroimaging techniques such as computed tomography (CT) and MRI that are often used in clinical assessments to evaluate gross anatomical changes are unable to effectively detect many of the pathological features of the disease that can only be observed at the cellular level, such as the aforementioned TDP-43 and hyperphosphorylated tau protein. However, DTI has become a popular tool for assessing brain injury as it is specialized for detecting abnormalities in brain white matter, which are common in cases of CTE as a result of the mechanical stress on axons following injury (Sundman, Doraiswamy, & Morey, 2015). Assessing white matter integrity can provide insight into the severity of brain damage, and may be a useful tool in identifying individuals at risk of developing CTE.
In addition to DTI, functional neuroimaging techniques have demonstrated great promise in establishing connections between the neuropathology and symptomatology of CTE. Functional neuroimaging uses various techniques to assess brain activity, typically during the performance of a specific task. Positron emission tomography, or a PET scan, uses radioisotopes to measure the amount of glucose being taken up by regions of the brain, which is indicative of activity level. Barrio et al. (2015) used PET scans to investigate the differences in brain activity between retired football players who exhibited symptomatology associated with CTE, confirmedly diagnosed Alzheimer’s patients, and normal controls. The study employed the radioisotope [F-18]FDDNP because it has a high affinity for insoluble protein aggregates, which are trademark features of both CTE and Alzheimer’s disease. The neuroimaging results revealed significantly different signaling patterns across all three conditions. In the group of retired football players suspected to be tested positive for CTE, tau protein aggregates were observed to congregate in subcortical areas and limbic structures, namely in the amygdala. In contrast, the results of the Alzheimer’s group indicated tau protein aggregates predominantly in medial temporal regions, with minimal involvement of subcortical structures. These findings are highly valuable as they not only demonstrate that neuroimaging techniques can potentially be used in the detection of chronic traumatic encephalopathy in vivo, but also to distinguish the neuropathology of CTE from other neurodegenerative disorders.
Another functional neuroimaging technique that has shown promise in identifying features of CTE is fMRI, which measures the levels of oxygen concentration in regions of the brain in response to a certain task or external stimuli. Brain regions with increased oxygen concentrations are suggested to respond with increased activity in comparison to regions with lower oxygen concentrations. Ford, Giovanello, and Guskiewicz’s experiment (2013) was the first to use fMRI to assess differences in brain activity during memory tasks in football players who had been subjected to multiple concussions. The study compared two groups: football players who had experienced more than three concussions during their careers in sports and football players who had experienced less than three concussions. The results indicated no significant differences in performance on memory tasks between the two groups, although notable differences in neural activity were observed in the fMRI results. The low-frequency concussion group displayed more neural activity during relational memory tasks in the parahippocampal gyrus and the inferior parietal cortex. Previous research has suggested that these regions are associated with relational memory tasks in typical individuals. In contrast, the high-frequency concussion group recruited more neural activity from regions of the prefrontal cortex for the same relational memory tasks. The authors hypothesized that this may be due to the fact that the brain regions that are typically active during relational memory tasks were damaged in the high-frequency concussion group, thus explaining the lack of activity in these regions. Further investigation into the long-term effects of this differential neural activity during memory tasks is warranted, as this study did not observe any significant differences in functionality. These findings suggest that the restructuring of neural connections are likely to occur following repetitive brain injury, and support the hypothesis that there are discrepancies in the neurobiology of repetitive versus acute brain injury. This may have implications for the in vivo imaging of neural functioning in individuals who have been subjected to repetitive brain injury and who are suspected to test positive for CTE.

Prospective Treatment Methods for Chronic Traumatic Encephalopathy

Just as there is a lack of pre-mortem diagnostic criteria for CTE, the same is true for treatment methods. The prospective treatment methods for CTE are predominantly preventative in nature by aiming to target and alleviate the adverse neurobiological outcomes of brain injury before they can become pathological and manifest as neurodegeneration. The investigation of pharmacological agents as candidates for the treatment of concussive brain injury has been a popular area of research, and there are several studies that have begun to investigate the use of pharmacological agents to directly target the neuropathology of chronic traumatic encephalopathy itself, rather than the preliminary features of brain injury.
Zhang and colleagues observed that pharmacologically inhibiting the enzyme monoacylglycerol lipase, which plays an important role in degrading endocannabinoid neurotransmitters, significantly reduced the release of pro-inflammatory cytokines and suppressed the phosphorylation of tau protein in a mouse model with repetitive brain injury (Zhang, Teng, Song, Hu, & Chen, 2015). Endocannabinoid neurotransmitters such as 2-arachidonoylglycerol are known to have anti-inflammatory properties, and these findings suggest implications of the endocannabinoid system in the management and reversal of CTE-like neuropathology. Additional research has demonstrated that administering the pharmacological agent JZL184, another monoacylglycerol lipase inhibitor, to rats which had undergone experimental mild traumatic brain injury significantly reduced neuroinflammation, glutamate excitotoxicity, and behavioural impairments associated with brain injury (Mayeux, Katz, Edwards, Middleton, & Molina, 2017). These animal studies provide evidence for the neuroprotective role of the endocannabinoid system in cases of repetitive brain injury. Despite these promising findings, these types of drugs have yet to progress into human clinical trials as enhancing neurotransmission in the endocannabinoid system may have adverse effects including cognitive and sensorimotor impairments (Di Marzo, 2008).
Another experiment using a mouse model of traumatic brain injury revealed that administering lithium significantly reduced tau neuropathology in the thalamus and improved performance on spatial learning tasks (Yu, Zhang, & Chuang, 2012). Although this study chiefly focused on the ability of lithium to reduce the presence of beta-amyloid plaques in the brain, a feature that is more consistent with Alzheimer’s disease, the fact that an attenuation of tau neuropathology was also observed suggests that these findings may also be relevant to CTE. Additional research on using lithium as a treatment for brain injury and CTE is warranted as lithium is known to have psychotropic effects, including producing symptoms of dysphoria and cognitive slowing (Moncrieff, Cohen, & Porter, 2013). Considering that cognitive disturbances and depression, which are often accompanied by dysphoria, are symptoms of brain injury and CTE, these effects of lithium may pose obstacles for its usage as a treatment method. These experiments are notable as they indicate that neurodegenerative markers of CTE may have the capacity to be reversed pharmacologically.

Discussion

There have been many relevant research findings concerning the underlying mechanisms of CTE and implications for diagnosis and treatment. Functional neuroimaging techniques have drastically altered the way that the components of the disease can be investigated, and research has demonstrated a potential role for certain pharmacological agents in the treatment of the disease. In particular, several researchers are focusing on agents that enhance the anti-inflammatory properties of the endocannabinoid system.
Several limitations exist in terms of investigating prospective treatment methods for CTE. For one, the lack of a standardized pre-mortem diagnostic criteria for the disease makes it difficult to formulate a suitable treatment. Furthermore, there are obstacles with translating the existing pharmacological treatment research to human populations due to the known side effects of the proposed drugs. The aforementioned findings are promising, however there is still much that is largely unknown. There are some established hypotheses that aim to explain how brain injury can predispose an individual to developing CTE, although the specific mechanisms by which this occurs remain unclear. Moreover, there is currently no pre-mortem diagnostic protocol for the disease, despite the fact that there is substantial evidence suggesting that in vivo diagnoses are possible. Future research on the relationship between repetitive brain injury and disease progression is warranted, in addition to further investigation into the formation of a standardized diagnostic criteria and effective treatment methods for the disease.

References

Barrio, J. R., Small, G. W., Wong, K.-P., Huang, S.-C., Liu, J., Merrill, D. A., … Kepe, V. (2015). In vivo characterization of chronic traumatic encephalopathy using [F-18]FDDNP PET brain imaging. Proceedings of the National Academy of Sciences of the United States of America, 112(16), E2039-47. doi:10.1073/pnas.1409952112
Baugh, C. M., Stamm, J. M., Riley, D. O., Gavett, B. E., Shenton, M. E., Lin, A., … Stern, R. A. (2012). Chronic traumatic encephalopathy: neurodegeneration following repetitive concussive and subconcussive brain trauma. Brain Imaging and Behavior, 6(2), 244–254. doi:10.1007/s11682-012-9164-5
Di Marzo, V. (2008). Targeting the endocannabinoid system: to enhance or reduce? Nature Reviews Drug Discovery, 7(5), 438–455. doi:10.1038/nrd2553
Ford, J. H., Giovanello, K. S., & Guskiewicz, K. M. (2013). Episodic memory in former professional football players with a history of concussion: an event-related functional neuroimaging study. Journal of Neurotrauma, 30(20), 1683–701. doi:10.1089/neu.2012.2535
Gardner, R. C., & Yaffe, K. (2015). Epidemiology of mild traumatic brain injury and neurodegenerative disease. Molecular and Cellular Neurosciences, 66, 75–80. doi:10.1016/j.mcn.2015.03.001
Gavett, B. E., Stern, R. A., & McKee, A. C. (2011). Chronic traumatic encephalopathy: a potential late effect of sport-related concussive and subconcussive head trauma. Clinics in Sports Medicine, 30(1), 179–88. doi:10.1016/j.csm.2010.09.007
Mayeux, J., Katz, P., Edwards, S., Middleton, J. W., & Molina, P. E. (2017). Inhibition of Endocannabinoid Degradation Improves Outcomes from Mild Traumatic Brain Injury: A Mechanistic Role for Synaptic Hyperexcitability. Journal of Neurotrauma, 34(2), 436–443. doi:10.1089/neu.2016.4452
Moncrieff, J., Cohen, D., & Porter, S. (2013). The psychoactive effects of psychiatric medication: the elephant in the room. Journal of Psychoactive Drugs, 45(5), 409–15. doi:10.1080/02791072.2013.845328
Omalu, B. I., DeKosky, S. T., Minster, R. L., Kamboh, M. I., Hamilton, R. L., & Wecht, C. H. (2005). Chronic traumatic encephalopathy in a National Football League player. Neurosurgery, 57(1), 128-34-34. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/15987548
Sundman, M., Doraiswamy, P. M., & Morey, R. A. (2015). Neuroimaging assessment of early and late neurobiological sequelae of traumatic brain injury: implications for CTE. Frontiers in Neuroscience, 9, 334. doi:10.3389/fnins.2015.00334
Walker, K. R., & Tesco, G. (2013). Molecular mechanisms of cognitive dysfunction following traumatic brain injury. Frontiers in Aging Neuroscience, 5, 29. doi:10.3389/fnagi.2013.00029
Yu, F., Zhang, Y., & Chuang, D.-M. (2012). Lithium reduces BACE1 overexpression, β amyloid accumulation, and spatial learning deficits in mice with traumatic brain injury. Journal of Neurotrauma, 29(13), 2342–51. doi:10.1089/neu.2012.2449
Zhang, J., Teng, Z., Song, Y., Hu, M., & Chen, C. (2015). Inhibition of monoacylglycerol lipase prevents chronic traumatic encephalopathy-like neuropathology in a mouse model of repetitive mild closed head injury. Journal of Cerebral Blood Flow and Metabolism, 35(3), 443–53. doi:10.1038/jcbfm.2014.216

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Non-Hermitian Wave Mechanics: An Unorthodox Way into Embedded Systems

doi:10.22186/jyi.33.4.87-90

Abstract | Introduction | Summary and Outlook| References | PDF

Full Issue: September 2017 Special Edition

Abstract

This review outlines an unconventional but timely formulation of quantum dynamics of systems in contact with an environment. This alternative approach to traditional quantum mechanics is generic and is currently gaining attention in a number of fields as, for example, quantum scattering and transport, optical waveguides, devices embedded in an environment, oscillatory classical systems, RLC circuits and other open systems with loss and gain. Here we briefly outline this formulation in which the condition of space-time reflection (PT-symmetry) plays a central role. If PT-symmetry is broken upon parametric change, real energy levels generally turn complex. At the onset of such a symmetry breaking levels coalesce at “Exceptional Points” (EP).

Introduction

In 1926, Erwin Schrödinger formulated his famous non-relativistic equation for matter waves. In this form quantum mechanics (QM) has since then remained a never-ending success. It expands the classical Newtonian mechanics for particle orbitals into the world of quantum matter as atoms, molecules, solid matter, micro- and nano-scale devices, etc., in which particles acquire wave properties. For this reason it is also referred to, particularly in the early years of the new theory, as wave mechanics (WM) with reference to common wave phenomena present in acoustics, electromagnetism, vibrational structures as membranes and drums, hydrodynamics and more. The predictive power of QM is, as well known, overwhelming.
In short, traditional QM as above rests solidly on a number of postulates as (Schiff, 1968):

(a) A physical system is represented by a wave function Φ(r,t) which holds all information of a system;
(b) Physical observables, as for example momentum p, are represented by Hermitian operators meaning that associated eigenvalues are real numbers and equal possible outcomes of measurements;
(c) The operator representing energy, the sum of kinetic energy T and potential energy V, is the usual Hamiltonian

NHWM eq 1 (1)

where m is the mass of a particle which moves under the influence of a real potential V(r) (ℏ is the reduced Planck constant h/2π). When V(r) does not depend on time t the eigenvalues En of the Hermitian Hamiltonian H are the energy levels of system.
(d) The time evolution of the wave function is given by the time-dependent Schrödinger equation

NHWM eq 2 (2)

For the case above one then has

NHWM eq 3 (3)

where ψn(r) is the n:th stationary solution Hψn=Enψn with real eigenvalue En.
In this review we will introduce an extension (PT-symmetry) to the well known Hermitian QM and describe its implications on QM as well as analogous classical systems. After reviewing the background and current state of the field we discuss some open problems and suggest further studies with the goal to inspire new and clever ideas. Today we lack an experimentally realized PT-symmetric QM system, but with new efforts and ideas that will surely change soon.

A new Paradigm: Non-Hermitian QM and Parity-Time (PT) Symmetry

Measurements in QM return the eigenvalues of observables; for example, a measurement of a particle’s energy yields an eigenvalue of the Hamiltonian. The important assumption of Hermitian operators guarantees that eigenvalues are real and that QM is consistent with measurements. However, more lately it has been argued that the requirement of Hermiticity may be too taxing. Can the energy levels be real also for a Hamiltonian that is complex, i.e., a non-Hermitian one? Under certain circumstances, the answer is yes. Bender and Boettcher (1998) showed how this happens when a system is symmetric under the combined PT operations of parity, or mirror symmetry, (P) and time-reversal (T). These symmetry operations translate to p→-p,r→-r for parity and p→-p,r→r,i→-i for time reversal. Enforcing this symmetry implies for the potential to satisfy V(r)=V*(-r) and thus there is a balanced flow, i.e., gain versus loss is harmonized (Bender, 2005, 2007; Weigert, 2004).
To get an understanding of the role of the complex potential V(r)= VRe(r)+ iVIm(r) consider the simple case of a pair of nearby even and odd states that are localized, for example, to the interior of a closed cavity (Figure 1). Let the solutions for the “unperturbed” case VIm(r)=0 be E1 and E2. Under a parametric change such that VIm(r)≠0 the two levels will interact according to the 2×2  matrix equation

NHWM eq 4,5

(4)

(5)

where Vint is the interaction matrix element between the initial states 1 and 2, i.e., Vint= <1│VIm|2>=<2│VIm|1>; c1 and c2 are the mixing coefficients for the two states. The eigenvalues of the mixed states are

NHWM eq 6 (6)

The modified eigenvalues are evidently real as long as energy gap between states 1 an 2 is larger than |2Vint|. There is a balance between gain and loss. However, as the gap becomes equal to abs(2Vint) on further parametric increase a profound change takes place. The eigenvalues coalesce into a common value referred to as an exceptional point (EP); beyond this point the eigenvalues become complex. Rewriting Eq. (6) as

NHWM eq 7 (7)

The time-dependent solutions in Eq. (2) are now

NHWM eq8 (8)

Beyond the exceptional point there may thus be either exponential decay or growth of the states.  The outline above is a rather elementary one but points to the existence of EPs into which states, may coalesce on parametric change. If we consider the exponentially decaying states, which would apply to fermions because of the Pauli principle that forbids double occupancy, one should thus have the possibility of switching a state on and off by playing with Vint.
In the next section we will discuss the specific example of a quantum in contact with an environment. There will be a number states and for this reason one will have to use more refined methods than above to solve the Schrödinger equation, in this case numerical methods based on finite differences. As we will find the occurrence of EPs is a more complicated story than above, they may come and go with the gain/loss parameter Vint.

A Two-Dimensional Quantum Dot in Contact with an Environment

There is a rich variety of quantum dots fabricated from different materials for different purposes. They may be three- or two-dimensional objects embedded in solid materials, colloidal nanocrystals, etc., with intriguing physics and vast applications. A common feature is, as already the name indicates, that states are confined within a dot are quantized because of its smallness, typically in the nanometer regime. Research, basic and applied, remains very dynamic and there is a rich literature with many good monographs, see for example (Klimov 2010) and more.
Here we will focus on a particular kind of quantum dots that may be created in layered semi-conductor hetero-structures like Ga1-xAlxAs/GaAs. Because of a mismatch between the band-gaps of the two materials and modulation doping with donor atoms there will be an effectively two-dimensional electron gas that resides at the interface. A smart step is to add metallic top layer/gate which makes it possible to vary the density of electrons, even to deplete it. Another smart step is to use lithography to shape the electron gas into small structures like one-dimensional wires, dots of various geometries, combinations of such objects into networks, etc., as for example described by Ferry, Goodnick, & Bird (2009).
Here we present a schematic model of a circular two-dimensional quantum dot embedded in a hetero-structure (Figure 1). The dot contains a number of electrons, usually small, that may be varied via the top gate. There are also pairs of ports that serve as emitters and collectors. In Figure 1A, for example, we may let the left port L be purely imaginary with VL=iVIm and VR=-iVIm for the other port R. Evidently there will be a current flowing through the dot. Related configurations have been elaborated for an electron/microwave billiard (Berggren et al., 2010) and, most recently, for interacting Bose-Einstein condensates (Schwartz et al., 2017).

Figure 1. Schematic picture of two-dimensional circular dots. (A) shows the case with two opposite ports with complex potentials VL(x) = VR*(-x). The interior potential is real and may be set equal to zero. The potential in the exterior region may be set to infinity, i.e., wave functions are confined to the circular area and ports. The vertical line is the line of reflection. The two ports serve as source and drain. Because of PT-symmetry, gain and loss can balance each other. (B) shows a dot with several ports with the possibility of combining the corresponding potentials according to the different symmetry lines and PT invariance. The flow of particles between the ports may thus be monitored by flexible pairings of the potentials in the different sections, i.e., the system will act a bit like a switchboard. While retaining PT-symmetry, the imaginary part of the potential may be chosen differently for the pairs giving rise to a more complex two-dimensional landscape of EPs. Obviously we may also consider more ports than just four.

Figure 1. Schematic picture of two-dimensional circular dots. (A) shows the case with two opposite ports with complex potentials VL(x) = VR*(-x). The interior potential is real and may be set equal to zero. The potential in the exterior region may be set to infinity, i.e., wave functions are confined to the circular area and ports. The vertical line is the line of reflection. The two ports serve as source and drain. Because of PT-symmetry, gain and loss can balance each other. (B) shows a dot with several ports with the possibility of combining the corresponding potentials according to the different symmetry lines and PT invariance. The flow of particles between the ports may thus be monitored by flexible pairings of the potentials in the different sections, i.e., the system will act a bit like a switchboard. While retaining PT-symmetry, the imaginary part of the potential may be chosen differently for the pairs giving rise to a more complex two-dimensional landscape of EPs. Obviously we may also consider more ports than just four.

As shown in Figure 2, the pair of levels may change under the parametric change, and we recover the EP discussed in the previous section. In addition we find, however, that there is another EP on further increase of the interaction, i.e., the state with real eigenvalues is restored. The calculations are more cumbersome than the analytic analysis above; a convenient approach is to turn to numerical finite difference methods described previously (Tellander & Berggren, 2017). Indeed, this method allows for a greater number of states, than just two as was discussed above. With a larger number of states one can expect more EPs to appear in the spectrum. However, the EPs only seem to appear over a finite range of VIm (Tellander & Berggren, 2017) which means that the spectrum can, as in Figure 2, be divided into three regions:the left region where VIm is less than the critical values and all eigenvalues are real, the finite critical region where many EPs exist and the rightmost part of the spectrum where most of the eigenvalues are again real. This crossover between different dynamical regimes is called a dynamical crossover and is of great importance for experimental studies of non-Hermitian QM. In the region of many EPs, the transmission through the system should be enhanced and the states that remain complex in the right region of the spectra are believed to be associated to superradiant modes (a collection of emitters, such as atoms, that radiates strongly due to coherence) studied in atomic physics. Whether superradiance really can be viewed as a dynamical crossover is an unanswered question (Rotter and Bird, 2015).
A system with more gates (Figure 1B) allows for a more direct measurement of EPs and has the possibility to settle the long-lived discussion in the field about the geometric phase obtained by a state when an EP is encircled in the parameter space. This phase is geometric in the sense that it is independent of the path that encircles the EP; compare with Cauchy’s theorem for complex curve integrals or the classical experiment using Foucault’s pendulum to prove that the earth rotates around its own axis. The system in Figure 1B can have one independent imaginary potential for each pair of leads and the parameter space is therefore two-dimensional. This system could therefore be transported around an EP and the phase change of the wave function could be extracted. Similar experiments in analogous systems such as microwave (Dembowski, 2001) and exciton-polariton (Gao, 2015) billiards have been preformed but a pure quantum experiment is still in the future.

Summary and Outlook

Above we have outlined in a schematic way how quantum states and currents in a biased PT-symmetric cavity in contact with surrounding reservoirs may be emulated by means of complex potentials for source and drain. This is, for example, of considerable computational convenience when modelling transport in real devices at small source-drain bias. This idea is already found to work well for the analogue case of two-dimensional microwave billiards (Berggren et al., 2010). There is still, however, a challenge to design and implement real semiconductor devices with the above characteristics.
The physics associated with PT-symmetry is common for a number of wave phenomena and there is a rich and rapidly expanding literature. This includes, for example, electromagnetic systems, in particular in the fields of optics and photonics for which many new possibilities have opened up. Complex potentials in terms of complex refractive indices enter here in a natural way. Thus possible systems to study are co-axial waveguides, microwave billiards and more. In classical mechanics the same kind of behavior may be realized by means of a driven and a damped pendulum coupled to each other. Also in electronics when two RLC−circuits are inductively coupled, one with amplification and one with attenuation, a PT-symmetric system is obtained with EPs that can be studied in details. This shows that PT-symmetry phenomena are ubiquitous in quantum as well as electrical systems. For recent updates and reviews see (Christodoulides et al., 2017; Konotop et al., 2016; Rotter & Bird, 2015) which shows that the present field is an expanding one within fundamental science and technology. Most recently it has also been shown how the formalism for non-Hermitian quantum physics with gain and loss may be used to analyse a very different kind of system, namely photosynthesis (Eleuch & Rotter, 2017).
Finally, it is exciting to find that there is a much older field of physics with its very own traditions and literature that relates to vibrations in string instruments like violins, cellos and pianos (Gough, 1981; Weinreich, 1977, 1979). One thus talks about wolf-notes which are unfortunate facts of life for, for example, cellists who may have to struggle with and tame “wolf cellos.” Wolf notes refer to unwanted interactions of different modes and how these coalesce into damped degenerate states at certain frequencies.  The similarity with EPs that appear in non-Hermitian quantum systems as described above for a quantum dot and illustrated in Figure 2 is obvious. We therefore wish to name such features “quantum wolves.”

References

Bender, C. M., & Boettcher, S. (1998). Real Spectra in Non- Hermitian Hamiltonians Having PT-Symmetry. Physical Review Letters, 80(24), 5243-5246. doi:10.1103/PhysRevLett.80.5243
Bender, C. M. (2005). Introduction to PT-Symmetric Quantum Theory, Contemporary Physics, 46, 277-292. doi:10.1080/00107500072632
Bender, C. M. (2007). Making Sense of Non-Hermitian Hamiltonians. Reports on Progress in Physics, 70, 947-1018. doi:10.1088/0034-4885/70/6/R03
Berggren, K.-F., Yakimenko. I. I., & Hakanen, J. (2010).  Modeling of open quantum dots and wave billiards using imaginary potentials for the source and the sink. New Journal of Physics, 12, 073005-19. doi:10.1088/1367-2630/12/7/073005
Christodoulides, D., El-Ganainy, R., Peschel, U., & Rotter, S. (2017). Focus on Parity-Time Symmetry in Optics and Photonics, New Journal of Physics (A series of selected articles commencing 2014).
Dembowski, C., Gräf, H.-D., Harney, H., Heine, A., Heiss, W., Rehfeld, H., & Richter, A. (2001). Experimental Observation of the Topological Structure of Exceptional Points. Physical Review Letters, 86(5), 787-790. doi:10.1103/PhysRevLett.86.787
Eleuch, H., & Rotter, I. (2017). Gain and loss in open quantum systems. Physical Review E 95, 062109-1-11, doi:10.1103/PhysRevE.95.062109.
Ferry, D. K., Goodnick, S. M., & Bird, J. P. (2009). Transport in Nanostructures. Cambridge University Press, 2nd edition.
Gao, T., Estrecho, E., Bliokh, K. Y., Liew, T. C. H., Fraser, M. D., Brodbeck, S.,… Ostrovskaya E. A. (2015). Observation of non-Hermitian degeneracies in a chaotic exciton-polariton billiard. Nature 526(7574), 554-558. doi:10.1038/nature15522
Gough, C. E. (1981). The theory of string resonances on musical instruments. Acustica 49, 124-141.
Klimov, V. I. (2010). Nanocrystal Quantum Dots. CRC Press, 2nd edition. CRC Press: ISBN 9781420079265
Konotop, V. V., Yang, J., & Zezyulin, D. A. (2016). Nonlinear waves in PT -symmetric systems. Review of Modern Physics, 88, 035002-59. doi:10.1103/RevModPhys.88.035002
Moiseyev, N. (2011). Non-Hermitian quantum mechanics. Cambridge University Press.
Rotter, I., & Bird, J. P (2015). A review of progress in the physics of open quantum systems: theory and experiment. Reports on Progress in Physics, 78, 114001-37. doi:10.1088/0034-4885/78/11/114001
Tellander, F., & Berggren, K.-F. (2017). Spectra, current flow and wave function morphology in a model PT −symmetric quantum dot with external interactions. Physical Review A, 94(4), 042115-12. doi:10.1103/PhysRevA.95.042115
Schiff, L. I. (1968). Quantum mechanics. International Series in pure and applied physics (New York) ISBN : 0070856435 or other basic textbooks on QM.
Schwarz, L., Cartarius, H., Musslimani, C. H., Main, J., & Wunner, G. (2017). Vortices in Bose-Einstein condensates with PT-symmetric gain and loss, Physical Review A, 95(5), 053613-9. doi:10.1103/PhysRevA.95.053613
Weigert, S. (2004). The physical interpretation of PT -invariant potentials, Czechoslovak Journal of Physics, 54, 1139-11142. doi:10.1023/B:CJOP.0000044016.95629.a7
Weinreich, G. (1977). Coupled piano strings. The Journal of the Acoustical Society of America, 62, 1474-84. oi:10.1121/1.381677;
Weinreich, G. (1979). The coupled motion of piano strings. Scientific American, 240, 118-127. doi:10.1038/scienticamericn0179-118

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Strain Specific: Microbial Strains Involved in Gut-Brain Signaling

doi:10.22186/jyi.33.3.49-54

Abstract | Introduction | Methods | Results | Discussion | Conclusions |Acknowledgements | 
References | PDF

Abstract

Exploration into the microbial role within behavior and neurologic regulation has been an area of growing interest and research. While in-vitro and in-vivo experimentation has suggested that commensal microbiota play a role within behavioral and neurologic functioning, little distinction has been made about the specific microbes inducing change. In order to understand and potentially utilize this complex gut-microbe-brain connection, it is imperative to distinguish between which microbes are inducing behavioral and or neurologic effects, and which biologic mechanisms are mediating said effects. To enhance the current understanding of neurologically influential microbes, this review will analyze eight microbial strains belonging to the genus types Lactobacillus and Bifidobacterium, and note the similarities and dissimilarities pertaining to modulation of inflammatory response, intestinal permeability, neurochemical concentrations, and interaction with the vagus nerve expressed amongst included microbial strains. Analysis of the selected microbes demonstrated significant distinction regarding neurochemical, inflammatory, and immunological effect amongst microbial strains belonging to the genus types Lactobacillus and Bifidobacterium. Interestingly, despite the expressed biologic variation, behavioral influence was largely uniform amongst the included microbial strains and expressed almost exclusively through a reduction in typified anxious and depressive behavior.

Introduction

Despite the myriad of pills and procedures aiming to treat psychiatric abnormalities and conditions, there is still much to be discovered about the brain. Fortunately, exploration into the effect upon commensal microbiota within behavioral and neurologic regulation has created a path in which to further decode and explore this enigmatic terrain. Recent in vitro and in vivo experimentation has demonstrated microbial influence within complex emotive states such as depression, chronic stress, anxiety, and psychiatric disorder (Bailey et al., 2011; Bercik et al., 2010; Maes, Kubera, Leunis, & Berk, 2012; Rook & Lowry, 2008). While this field is emerging and many mechanistic factors facilitating the microbial influence within gut-brain axis regulation have yet to be identified, the work done thus far suggest a future in which the brain can be indirectly targeted for therapeutic benefit through manipulation of commensal microbiota (Clarke et al., 2014; Cryan & Dinan, 2012). At a time when neuropsychiatric disorders are the leading cause of disability in the U.S (USBDC, 2013), the importance of this research cannot be overstated.
Although the blueprint outlining the microbial role within gut-brain axis regulation is far from maturation, the current understanding is that certain microbial strains are able to induce measurable neurologic and behavioral effect through the modulation of inflammatory response, neurochemical concentration, barrier-integrity, and interaction with the vagus nerve.  In order to understand, and potentially utilize these microbial capabilities, it is essential to distinguish between which microbes are inducing behavioral and or neurologic effect, and which pathway each microbe is using to do so. The complexity of this task resides in the significant microbial distinction expressed not only on a species level, but amongst microbial strains (Greenblum, Rogan, & Borenstein, 2015).
Among the more than 7,000 microbial strains (Ley, Peterson, & Gordon, 2006), majority have not demonstrated direct behavioral or neurologic effect. The collection of strains that have been shown to induce measurable neurologic and behavioral manipulation belong to one of the three genus types Lactobacillus, Bifidobacterium, and Bacteroides (Mayer, Knight, Mazmanian, Cryan, & Tillisch, 2014).  Amongst these genus types, a plethora of biologic and behavioral variances have been expressed on both a species and strain level. While variation across differing genus and species type is expected, differences expressed between microbial strains belonging to the same genus and species type is a surprising find in light of the genomic similarity expressed between them. Further investigation into these microbial variances can explain questions such as why, despite genomic similarities, only certain microbial strains are able to induce behavioral and neurologic effect. Why the microbial strains that do induce measurable effect, do so in a variety of ways that are often dissimilar from other strains belonging to the same genus and species type. And whether or not these strain mediated effects can be utilized for therapeutic benefit within neurologic and psychiatric disorders.

Lactobacillus rhamnosus JB-1.

L. rhamnosus JB-1 induces effect within gut-brain signaling through modulation of GABA receptors and inflammatory response. In an experimental study by Bravo et al. (2001), chronic treatment of L. rhamnosus JB-1 in a healthy mice model significantly increased GABA-B receptor concentrations in the cingulate and pre-limbic cortical regions, increased the concentration of GABA-A receptors in the hippocampus, decreased GABA-B receptor concentrations in the hippocampus, amygdala, and locus coerulus, and decreased GABA-A receptors concentrations in the pre-frontal cortex and amygdala. The influence over GABA receptors is supported to have psychiatric impact that is demonstrated through work by Cryan and Kaupmann (2005), whom found a reduced concentration of GABA-B receptors in the frontal cortices of a depression induced mouse model, and Jacobson-Pick, Elkobi, Vander, Rosenblum, and Richter-Levin (2008) whom found an increase of GABA-A receptors in the amygdala of a chronically stressed mice model.
Inflammatory affect was demonstrated in a study by Forsythe and Bienstock (2004), which found that L. rhamnosus JB-1 reduced intestinal inflammation through an upregulation of nerve growth factor, and inhibition of IL-8 synthesis. The neurologic impact of these noted effects is supported in work done by Angelucci, Aloe, Vasquez, and Mathé (2000), showing an altered concentration of brain derived neurotropic factor and nerve growth factor in a depression induced mice model. As well as in work done by Janelidze et al. (2015), showing an association between low serum levels of IL-8 and anxiety in suicidal patients.
L. rhamnosus JB-1 demonstrated behavioral impact in the abovementioned study by Bravo et al. (2001) through a significant decrease in typified anxious and depressive behavior in mice chronically administered with L. rhamnosus JB-1. In addition to modulation of GABA receptors, this effect was deemed to be in relation to interaction with the vagus nerve, for behavioral effect was not observed in vagotamized mice (Bravo et al., 2001). Due to the noted associating between nerve growth factor and depression, the increased concentration of nerve growth factor by L. rhamnosus JB-1 could also play a role within the noted decrease of typified anxious and depressive behavior.

Lactobacillus rhamnosus GG.

L. rhamnosus GG induced neurologic influence primarily through modulation of inflammatory processes. In an experimental study by Turner (2009), children with atopic dermatitis administered with L. rhamnosus GG resulted in significant reductions of serum levels of IL-10, which has been shown to reduce intestinal inflammation through the suppression of regulatory T cells (Park et al., 2005). The behavioral impact of this effect is suggested in a previous study by Dhabhar et al. (2009), which observed a decreased concentration of IL-10 levels in adults with major depression syndrome. Additional inflammatory effect was observed in an experimental study by Pessi et al. (2001), which noted a decreased concentration of regulatory T cells in casein degraded by L. rhamnosus GG. While no direct associations between regulatory T cell concentration and behavioral and or neurologic impact was observed, an indirect link pertaining to decreased inflammation by regulatory T cells (Park et al., 2005) which has been correlated with depression and anxiety (Bercik et al., 2010; Maes, Kubera, Leunis, & Berk, 1999; Smith & Rudolph, 1991;) supports the psychiatric influence of this inflammatory effect.
Behavioral impact was observed in a study by Kantak, Bobrow, and Nyby (2013), which observed an attenuation of obsessive compulsive disorder (OCD) typified behaviors in a house mice model administered with L. rhamnosus GG, that worked as well as the positive study control, fluoxetine, which is common medication used in OCD treatment (Bandelow et al., 2012). The noted behavioral affect was presumed to be in relation to a decrease in the anxiety often preceding or accompanying OCD, and not from a direct modulation of the neurologic mediators associated with OCD typified behavior (Kantak et al., 2013). In reference to the abovementioned effects upon inflammation, it is plausible to infer that the noted behavioral modulation could be mediated, at least partially, through inflammatory modulation which has been previously associated with anxiety (Maes et al., 1999; Smith & Rudolph, 1991).

Lactobacillus helveticus NS8.

L. helveticus NS8 induces behavioral and neurologic impact through modulation of neurotransmitters and inflammatory response. Research conducted by Liang et al. (2015) found that when administered in a pathogen free rat model, L. helveticus NS8 restored hippocampal concentrations of serotonin and norepinephrine. The psychological significance of this effect can be noted in previous work by Stanton and Sarvey (1985), which found that hippocampal depletion of norepinephrine reduces the frequency and magnitude of long term potentiation, which is a synaptic mechanism associated with cognitive functions pertaining to learning and memory (Eichenbaum & Otto, 1992), as well as attention and arousal (Shors & Matzel, 1997). Hippocampal effect was also noted in a study by Martinowich et al (2007), which observed an increase of hippocampal brain derived neurotrophic factor mRNA, which has been noted to play a role within depression and psychiatric disorders such as schizophrenia and bi-polar disorder (Martinowich et al., 2007; Palomino et al., 2006). L. helveticus NS8 was also shown to induce inflammatory effect through the attenuation of LPS induced inflammation which was mediated through an increased synthesis of IL-10 (Rong et al., 2015).
L. helveticus NS8 induced behavioral effect in an experimental study by Luo et al. (2014), which observed an attenuation of anxiety and improved cognition in a hyperammonemia induced rat model administered with L. helveticus NS8. These results were supported in a proceeding study by Liang et al. (2015), which observed a significant reduction of chronic stress induced anxiety, depression, and cognitive dysfunction in mice orally administered with L. helveticus NS8. All abovementioned induced effects including the synthesis of serotonin and norepinephrine (Liang et al., 2015), increased concentration of hippocampal brain derived neurotrophic factor mRNA (Martinowich, Manji, and Lu, 2007), and increased synthesis of IL-10 (Rong et al., 2015), appear to be plausible, and likely, mechanisms mediating the observed behavioral impact by L. helveticus NS8.

Lactobacillus helveticus R0052.

L. helveticus R0052 induced cerebral effect through mechanisms pertaining to increased barrier integrity and amelioration of stress induced irregularities in hypothalamic-pituitary-adrenal axis (HPA-axis) and automatic nervous system (ANS) functioning. Influence upon barrier integrity was supported in a study by Johnson-Henry, Hagen, Gordonpour, Tompkins, and Sherman (2007), which observed that L. helveticus R0052 prevented against pathogenic infiltration of Escherichia coli 0157:H7 by binding to epithelial cells and blocking pathogenic entry. This impact suggests that L. helveticus R0052 may play a beneficial immunologic role through the enhancement of intestinal barrier security and protection against pathogenic infection. This is a neurologically relevant action, for previous studies have shown a connection between pathogenic infection and behavior (Quinn et al., 1984) as well as psychological stress and barrier integrity (Ait-Belgnaoui, Bradesi, Fioramonti, Theodorou, & Bueno, 2005). HPA-axis modulation was supported in a study by (Ait-Belgnaoui et al., 2014), which observed a reversal of stress-induced HPA-axis and ANS irregularities, which was mediated through a decreased plasmatic concentration of corticosterone, adrenaline, and noradrenaline in a stress-induced mice model administered with a combination of L. helveticus R0052 and Bifidobacterium longum R0175. The modulation of the HPA-axis presents possible psychological relevance, for the HPA-axis has domain over coordinating all bodily stress responses (Tsigos & Chrousos, 2002).
L. helveticus R0052 induced behavioral effect in a study by Ohland et al. (2013), which observed an amelioration of diet-induced anxiety and memory deficits in mice administered with L. helveticus R0052. Interestingly, this effect appeared to be diet-dependent, for behavioral effect was only noted when mice were followed a high fat “western” diet, but not when following a low fat “chow” diet. These results were supported in another study by Gilbert, Arseneault-Bréard, and Flores Monaco (2013), which noted a diet-dependent decrease in typified depressive behavior in a post-myocardial infarction induced mice model administered with a combination of L. helveticus R0052 and Bifidobacterium longum R0175. Although future experimentation is required to be able to accurately ascertain the likely factors mediating the noted behavioral influence, it is reasonable to conclude that in addition to dietary intake, the abovementioned influence over HPA-axis regulation (Ait-Belgnaoui et al., 2014) could be a contributing factor to the noted behavioral modulation.

Lactobacillus johnsonii N6.2

L. johnsonii N6.2 induced neurologic effect through modulation of neurotransmitters concentrations, gut-barrier integrity, and oxidative stress concentrations. In an experimental study by Valladares et al. (2013), L. johnsonii N6.2 increased ileum and peripheral serotonin concentrations, decreased peripheral kynurenine concentrations, and decreased tryptophan activity when administered to a “BioBreeding” rat model. The significance of this alteration within behavior and neurologic functioning can be seen in previous work showing an association between low levels of serotonin and depression (Lucki et al., 1998), as well as an association between tryptophan depletion and depression and panic disorder symptom relapse (Bell et al., 2001). Further microbial influence was shown in a study by Valladares et al. (2010), which observed that when administered to a diabetic induced rat model, L. johnsonii N6.2 induced effect within barrier integrity by increasing concentrations of tight junction protein claudin and decreasing host oxidative stress response.  In addition to the previously noted association between barrier integrity and psychological stress (Ait-Belgnaoui et al., 2005), the behavioral significance of the modulation of oxidative stress response is supported in a study by Gorrindo, Lane, Lee, McLaughlin, and Levitt (2013), which found a correlation between increased oxidative stress response levels and increased severity of autism spectrum disorder associated behavioral abnormalities pertaining to language impairment, OCD typified behavior, and aversion to social communication. While no studies have tested to see whether or not L. johnsonii N6.2 induces effect within behavior, the noted induced effects pertaining to modulation of neurotransmitters and effect upon oxidative stress levels warrants future research to assess the degree of possible behavioral modulation.

Bifidobacterium longum, subspecies longum JCM1217

Bifidobacterium longum subsp. longum JCM1217 induced effect within gut-brain axis regulation through immunological modulation. In a study by Fukuda et al. (2011), pathogenic infection of Escherichia coli 0157:H7 was prevented in mice administered with B. longum, subspecies longum JCM1217 through production of acetate. Fukuda et al. (2011) proposed that increased acetate production protected against pathogen infection by attaching to epithelial cells and preventing the pathogen from translocating from the gut lumen to host blood supply. In addition to the increased barrier integrity, which has been previously noted to have an association with psychological stress (Ait-Belgnaoui et al., 2005), the induced production of acetate could have possible behavioral ramifications, for experimentation by MacFabe et al. (2007) observed that autism spectrum disorder behavioral abnormalities were induced in a rat model when short chain fatty acid levels were manually increased. More research should be conducted on B. longum, subspecies longum JCM1217 to assess whether or not the noted immunological effect induces behavioral or neurologic modulation.

Bifidobacterium longum NCC3001.

In an experimental study by Bercik et al. (2010), Bifidobacterium longum NCC3001 ameliorated colitis associated behavioral alterations and brain derived neurotrophic factor depletions, which has been previously associated with stress and depression (Martinowich et al., 2007; Angelucci et al., 2000). However, when tested in a follow-up study by Bercik et al. (2011), colitis associated alterations brain derived neurotrophic factor was not observed, which demonstrates that this was likely not a factor mediating the noted behavioral change. Additional neurologic effect was demonstrated in a study Khoshdel et al. (2013), which observed that B. longum NCC3001 significantly reduced the excitability of enteric neurons when applied to ileal segments of adult mice. This effect upon enteric neurons was supported in a study by Bercik et al. (2011), and presumed to be a possible method in which the central nervous system is signaled through activation of vagal pathways within the enteric nervous system.
Behavioral effect was noted in the abovementioned studies (Bercik et al., 2010; Bercik et al., 2011) through the attenuation of colitis associated typified anxious behavior.  Both studies also observed in the abovementioned study by Bercik et al. (2011) through an attenuation of typified anxious behavior and an increase in typified exploratory behavior.  Interaction with the vagus nerve appeared unclear, for behavioral effect was found independent of the vagus nerve in the first study by Bercik et al. (2010) and dependent of the vagus nerve in the follow-up study by Bercik et al. (2011). While the noted effect regarding decreased excitability of the vagus nerve supports interaction with the vagus nerve within behavioral modulation (Bercik et al., 2010; Khoshdel et al., 2013), more research is required to adequately determine the degree of vagal involvement.

Bifidobacterium infantis 35624.

Bifidobacterium infantis 35624 induced both behavioral and neurologic effect through modulation of neurotransmitters, inflammatory response, and intestinal permeability.  Research by Desbonnet, Garrett, Clarke, Bienenstock, and Dinan (2008) observed that B. infantis 35624 reduced frontal cortex serotonin concentrations, increased plasmatic concentrations of noradrenaline and tryptophan, and inhibited the production of IL-10. The significance of these mediated effects are supported in previous work by (Amat et al., 2005; Bland et al., 2003) showing a connection between prefrontal cortex serotonin concentration and the modulation of anxiety, in work by Vijayakumar and Meti (1999) showing a connection between noradrenaline and depression, in work by Myint et al. (2007) showing a connection between decreased plasmatic tryptophan concentrations and depression, and work by (Dhabhar et al., 2009) showing a connection between IL-10 and major depressive syndrome.
Behavioral influence was demonstrated in the abovementioned study by (Desbonnet et al., 2008) which noted an amelioration of typified depressive behavior in rats administered with B. infantis 35624 that worked as effectively as the positive study control Citalopram supporting the effectiveness of B. infantis 35624 as a behavioral regulator.

DISCUSSION

The variation of induced effects expressed by the 8 included microbial strains demonstrate that even amongst strains belonging to the same genus type, generalizations pertaining to induced effects should be avoided. For example, while four out of the five included Lactobacillus strains induced influence over a collection of 9 neurotransmitters, modulation over the same neurotransmitter was only expressed one time in the modulation of serotonin by both L. helveticus NS8 and L. johnsonii N6.2 (Liang et al., 2015; Valladares et al., 2013). Interestingly, in some instances microbial strains belonging to the same genus type induced oppositional effects. For example, while both L. rhamnosus GG and L. helveticus NS8 impacted the concentration of anti-inflammatory cytokine IL-10, L. rhamnosus GG decreased IL-10 concentrations (Turner., 2009) while L. helveticus NS8 increased them (Rong et al., 2015). Oppositional impact was also expressed amongst strains belonging to differing genus types, such as L. johnsonii N6.2, which increased peripheral serotonin concentrations (Valladares et al., 2013), and B. infantis, which reduced peripheral serotonin concentrations (Desbonnet et al., 2008).
Despite the diversity of microbially induced effects, behavioral modulation was largely uniform amongst the included strains. Six out of the eight strains demonstrated behavioral influence through the attenuation of of typified anxious and or depressive behavior. The apparent dichotomy expressed by the divergent mediated effects and uniform behavioral influence demonstrates the complexity of assessing the microbe-brain connection. As with many organically occurring events, no one factor determines whether or not an effect will take place. It is a consortium of many factors, some yet to be identified, and some yet to be understood.
While the noted behavioral modulation is promising and undoubtedly warrants further investigation, it is essential to remember the vast differences between human and animal physiologies and the methodology in which behavioral influence is assessed in animal models. The clinical testing done thus far has suggested promising results. For example, a study examining the effect of a multispecies probiotic supplement upon depressive indicators in healthy individuals found a significant decrease in a cognitive reactivity to sad mood amongst those given the probiotic supplement when compared to participants supplied with the placebo (Steenbergen, Sellaro, Hemert, Bosch, & Colzato, 2015). This effect was attributed to a decrease in frequency of negative and aggressive thoughts which further supports the potential therapeutic benefit of varying microbial strains (Steenbergen et al., 2015). It will be interesting to see whether or not this effect is viable in participants who have pre-existent conditions such as depression or acute anxiety as well as other psychiatric disorders.

Acknowledgements

This review was completed as an exterior project for a graduate level course facilitated by Dr. Colette LaSalle, at San Jose State University.

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Brain Tumor Segmentation Using Morphological Processing and the Discrete Wavelet Transform

doi:10.22186/jyi.33.3.55-62

Abstract | Introduction | Methods | Results | Discussion | Conclusions |Acknowledgements | 
References | PDF

Abstract

Medical imaging is key for the successful diagnosis and treatment of brain tumors, but the initial detection of tumors is, by nature, difficult. Image segmentation, a technique often used to aid detection, is highly dependent on the resolution of the segmented image. Many common morphological segmentation methods often suffer from a lack of resolution which hinders tumor detection. Thus, in this paper, two tumor segmentation techniques are developed and compared using MATLAB – one based on morphological processing, and a second which combines the discrete wavelet transform with morphological processing. Both proposed approaches begin with skull stripping via binary erosion, followed by image contrast enhancement and histogram thresholding. In the wavelet-based technique, the key step is to perform a fourth level discrete wavelet decomposition followed by manipulations of the wavelet. The resulting image is then morphologically opened, contrast enhanced, and gray thresholded. Both approaches were successfully tested on several magnetic resonance images, and it was shown that the wavelet transform method generally produces higher resolution segmented images. Additionally, it was found that the choice of wavelet basis function used plays a key role in the resolution of segmentation, with the Symlet 20 wavelet basis able to segment out almost 18% more pixels on average from an MR image than the Haar wavelet basis. These results can serve as a useful future reference as they provide convincing evidence of the necessity for careful choice of wavelet basis and suggest a basis that seems well suited for this application.

Introduction

Within Magnetic Resonance (MR) image processing, one major problem is the segmentation of brain tumors. Segmentation is the process of partitioning an image into several distinct sections to simplify the image or to focus on a region for further study (Kaur, G., & Rani, 2016). In the last several decades, there has been a push for automating the process of segmentation of pathological regions in the brain in MR scans. Current research on brain tumor segmentation uses a wide variety of methods which can be grouped as “intelligent” or “non-intelligent.” “Intelligent” techniques include machine learning methods such as neural-networks and support vector machine. The focus of this investigation, however, was on non-intelligent techniques, which include local and global thresholding, histogram operations, and morphology (Kaur & Banga, 2013).
Each of these methods has certain deficiencies. For example, global thresholding is not localized enough to produce segmentations with the desired resolution, but local thresholding is often not robust enough because of variations in how tumors present on MR images. Statistical models and morphological processing can also struggle to differentiate tissues in complex cases (Kaus et al., 1999). Wavelet-based techniques have become more popular in recent years because of the robustness they provide, and many hybrid wavelet methods are present in the literature (e.g., Sawakare & Chaudhari, 2014). When the correct method is found for a specific application, image segmentation can be a highly effective and important process because it allows clinicians to better understand the nature of a tumor and to plan more effective treatments (Xuan & Liao, 2007). Non-intelligent segmentation techniques are particularly important because they are often used for refining and improving intelligent segmentation methods (Kaur & Banga, 2013). In this research, a non-intelligent segmentation method, different from but inspired by those that are currently in the literature (Saini & Singh, 2015), was created based on morphology. Additionally, enhancements to this technique were developed using the discrete wavelet transform. These improvements were tested using several different wavelet basis functions. The major result of this investigation shows the key role that the choice of wavelet basis function plays in the resolution of the segmented image, a notion generally not discussed in the literature.

Morphology

The first of the two main mathematical concepts underlying this research is morphological image processing. Morphology consists of several operations that can be performed on a given image, represented by an image matrix, using other matrices called structuring elements (SE’s) in order to alter the image in desirable ways. Morphological processing is driven by operations performed by the SE’s on the image matrix, which use ones and zeroes to perform geometrical transformations based on the distributions of said ones and zeroes. The morphological operation used for segmentation in this investigation is called morphological opening. Morphological opening is made up of the successive operations of morphological erosion and dilation, which are both performed using the same SE.
Morphological erosion is defined in terms of set notation as follows. Given image A and structuring element B, both sets in Euclidean N-space, then the erosion of A by B, denoted A A B, “is the set of all elements x for which (x+b) ϵ A for every b ϵ B” (Sternberg, Haralick, & Zhuang, 1987):

BT equation 1 (1)

Essentially, erosion shrinks the geometric features within an image based on the distribution of ones and zeroes within the SE. Morphological dilation, denoted A A B (where A and B are the same as above), is defined as (Sternberg et al., 1987):

BT eq 2 (2)

Essentially, dilation inflates the geometric features within an image based on the nature of the SE.
The combination of these operations in succession, denoted  A o B, is called morphological opening, and it is defined as (Sternberg et al., 1987):

BT eq 3 (3)

Discrete Wavelet Transform

The second concept central to this investigation is the discrete wavelet transform. Traditionally, Fourier processing is used in most signal and image processing applications. Fourier bases are frequency localized however, meaning that small changes in space produce great changes in frequency and vice versa. As a result, Fourier based processing methods work very well for analyzing periodic signals, but abrupt changes are not easily detected through Fourier transform based analysis (Ingale, 2014). Due to these limitations, the decision was made to use the wavelet transform in support of morphological segmentation instead of the Fourier transform. The most important property of wavelets, the localization of their basis functions, sharply contrasts with the nature of Fourier basis functions; wavelet basis functions provide a degree of localization in both the space and frequency domains, meaning that small changes in space create small changes in frequency and vice versa.
Wavelet basis functions consist of a father wavelet (scaling function) notated φ(x), and a mother wavelet function, the first level of which is notated ψ(x). These mother wavelet functions can be scaled and shifted so that they cover the entire x-axis. These shifted, scaled functions are used to decompose a signal into its component parts. This decomposition, which allows for a more in-depth analysis of a particular region of the signal, is known as the discrete wavelet transform (DWT).
The DWT in one dimension is used to decompose and analyze signals such as an electrocardiogram or audio signal (a signal which can be represented by a single row or column vector). However, an image is not a one-dimensional signal like an EKG, but can instead be thought of as a two-dimensional signal (represented by a matrix instead of a column or row vector). Thus, for the computation of the DWT of an image, the first step is to extend the wavelet basis function to two dimensions, which is done using both the father wavelet φ(x) and the mother wavelet ψ(x). The wavelet function is extended to two dimensions in the following manner (Tolba, Mostafa, Gharib, & Megeed, 2001):

 Screen Shot 2017-07-29 at 7.46.16 PM

(4)

 

 

(5)

 

 

(6)

 

 

(7)

where the superscripts denote horizontal (h), vertical (v), and diagonal (d) basis functions. These new wavelet functions are used to define high and low pass decomposition and reconstruction filters (Lo-D and Hi-D in the above figure represent said decomposition filters), which are used to compute the DWT of the image by the convolution algorithm pictured in Figure 1 (“DWT2,” n.d.). This decomposition creates sub-images, the “CA,” “CD-horizontal,” “CD-vertical,” and “CD-diagonal,” in Figure 1. These sub-images each contain unique data about the original image; the approximation image, “CA,” contains a smaller, lower resolution version of the original image, and the detail (“CD”) images contain information about the vertical, horizontal, and diagonal aspects of the original image. Manipulation of these sub-images allows for effective analysis of important data, such as a tumor region, and has proved to be the powerful analysis tool that enhances morphological segmentation in this investigation.

Figure 1. Algorithm for DWT decomposition computation.

Figure 1. Algorithm for DWT decomposition computation.

Methods

Step 1: Skull Stripping

For both segmentation methods, the first step is to remove the skull from the original MR image. This is an important step because in many MR images, the skull appears as one of the brightest regions of the image, and is sharply contrasted with other regions of the brain, such as grey matter. In the types of MR images used in this investigation, tumors also appear as bright regions, and thus to limit false positive segmentations from occurring, the skull must be removed from the image. To do this, the original Red, Green, and Blue (RGB) or Grayscale image was converted to a binary image. Next, the pixels that corresponded to the skull were eroded away (i.e. removed from the outside in, until the skull was eliminated). Then, the smaller, eroded binary image was used as a mask and placed over top of the original image, so that only the pixels in the original image that correspond to ones in the eroded binary image are kept as they are in the original image, and all other pixels (those of the skull) are set to 0 (eliminated or set to black). The result is a skull stripped version of the original MR image. This is shown in Figure 2 (Clark et al., 2013).

Figure 2. The results of performing skull stripping. A. Original brain MR image obtained from The Cancer Imaging Archive. B. The results of skull stripping the image a via the processes described in Methods: Step 1.

Figure 2. The results of performing skull stripping. A. Original brain MR image obtained from The Cancer Imaging Archive. B. The results of skull stripping the image a via the processes described in Methods: Step 1.

Step 2: Contrast Enhancement and Thresholding

The next step in the proposed segmentation method is to perform contrast enhancement and thresholding based on Otsu’s thresholding method (Otsu, 1979). These operations are performed as preliminary, global segmentation steps which help to illuminate the tumor region. The contrast enhancement method used is based on the shape of a specified curve. All the MR images used in this investigation are weighted such that pathological regions appear as brighter than other regions of the brain. Thus, to illuminate the tumor region and fade other regions, the general shape of the curve used made light regions lighter and dark regions darker. The results of contrast enhancement are shown in Figure 3.

Figure 3. The results of performing contrast enhancement on the skull-stripped image shown in Figure 2B.

Figure 3. The results of performing contrast enhancement on the skull-stripped image shown in Figure 2B.

After contrast enhancement is performed, the next step is to perform thresholding by Otsu’s method. The goal of thresholding is to decide which pixels in the image correspond to the foreground and which correspond to the background. Once the background and foreground pixels have been determined based on the distribution of pixel values within the image, the image is converted to binary, sending the background pixels to a value of 0 and the foreground pixels to a value of 1. The skull stripped image is then masked with this thresholded binary image to produce the final image for this step in the segmentation (Figure 4).

Figure 4. The results of performing Otsu thresholding on the image shown in Figure 3.

Figure 4. The results of performing Otsu thresholding on the image shown in Figure 3.

Step 3: The DWT

For the technique involving the discrete wavelet transform, the next step is the wavelet step (for the technique not involving the DWT, the next step is morphological opening, which will be discussed in Step 4). The first aspect of this step is the choice of wavelet basis function. Since different basis functions provide different degrees of localization in the space and frequency domains, they also allow for different degrees of resolution in segmentation. The four main bases tested in this investigation are shown in Figure 5.

Figure 5. Wavelet Basis Functions Tested. A-D from left to right, top to bottom. A. Haar Basis. B. Daubechies 2 Basis (‘db2’). C. Symlet 4 Basis (‘sym4’). D. Symlet 20 Basis (‘sym20’).

Figure 5. Wavelet Basis Functions Tested. A-D from left to right, top to bottom. A. Haar Basis. B. Daubechies 2 Basis (‘db2’). C. Symlet 4 Basis (‘sym4’). D. Symlet 20 Basis (‘sym20’).

After much testing, it was found that the best wavelet basis for this application was the Symlet 20 wavelet, pictured in Figure 6 with the corresponding high and low pass filters. Comparisons between bases will be examined in the results section.

Figure 6. Father and mother wavelet functions, as well as the high and low pass decomposition and reconstruction filters, for the Symlet 20 wavelet.

Figure 6. Father and mother wavelet functions, as well as the high and low pass decomposition and reconstruction filters, for the Symlet 20 wavelet.

Once the wavelet basis is chosen, the DWT can be performed on the image. The computation of the DWT in MATLAB decomposes the image into four outputs: the approximation image and the three detail images (“CA,” “CD-horizontal,” “CD-vertical,” and “CD-diagonal). Once the first DWT is computed, a second level DWT is computed using the first level approximation image as the input, and the small magnitude coefficients of the approximation matrix are set to 0. This pattern is repeated two more times for a total of four operations of the DWT.
Then, the detail sub-images are set to 0. The first reconstruction produces an image which is then used to reconstruct the second image and so on until the final image is the result of four reconstructive processes using the inverse DWT (IDWT) (four operations of the IDWT are needed for reconstruction to “undo” the four operations of the DWT used for deconstruction). The resultant image is then contrast enhanced and thresholded, for a second time, via the methods used in Step 2 above. The results of these operations are used as a mask which is overlaid on the original image (Figure 7).

Figure 7. The results of performing wavelet decomposition and reconstruction on the image pictured in Figure 4.

Figure 7. The results of performing wavelet decomposition and reconstruction on the image pictured in Figure 4.

Step 4: Morphological Opening

In this step, the two approaches converge again. For the hybrid, wavelet-morphology based approach, the next step is to morphologically open the results of the wavelet processing step (Figure 7) to remove all regions that do not correspond to the tumor. For the morphological (non-wavelet) approach, the step is to morphologically open the skull-stripped, thresholded image (Figure 4). After much testing, the most suitable structuring element for this application was found to be a “disk” (i.e. a circle of 1’s with 0’s outside of the circle in the SE matrix). The radius of the SE used in this research was 14 pixels.
The results of morphologically opening the wavelet reconstructed image with the above structuring element are shown below in Figure 8a, and the results of morphologically opening the skull-stripped, thresholded image without the wavelet step are pictured in Figure 8b.

Figure 8. A. The results of morphologically opening the image shown in Figure 7. B. The results of morphologically opening the image shown in Figure 4.

Figure 8. A. The results of morphologically opening the image shown in Figure 7. B. The results of morphologically opening the image shown in Figure 4.

Step 5: Final Contrast Enhancement and Thresholding

The final step is to perform another contrast enhancement and thresholding on the morphologically opened images created in the previous step. This makes it so that the only object left in the image after this step is the segmented tumor region (Figure 9). This region is shown in red (Figure 10) overlaid on the original MR image for qualitative comparison.

Figure 9. A. The results of contrast enhancing and thresholding the image shown in Figure 8A. B. The results of contrast enhancing and thresholding the image shown in Figure 8B.

Figure 9. A. The results of contrast enhancing and thresholding the image shown in Figure 8A. B. The results of contrast enhancing and thresholding the image shown in Figure 8B.

Results

This section will present two sets of results:  a comparison of the two segmentation methods developed in this paper (i.e. segmentation with and without the DWT) and a comparison of the resolutions produced when using the different wavelet bases which shown in Figure 5.
The comparisons made in this section show the difference in the ability of each technique to segment out data. They indicate the percent difference in how much data was segmented out of the image by each technique (they are shown in the form of percent difference instead of actual pixel numbers because the size of each tumor varies greatly from image to image, making raw pixel number comparisons meaningless).

Comparison Between Segmentation Methods

Morphological segmentation was successfully used as a baseline for tumor segmentation in this paper. With the addition of the wavelet transform step, the resolution of segmentation (i.e. the number of correct pixels that were partitioned from the image) fluctuated based on the choice of wavelet basis. The following tables shows comparisons between morphological segmentation and hybrid wavelet-morphological segmentation for each image tested and each of the four wavelet bases shown in Figure 5 above.

Comparison Between Wavelet Bases

From the comparisons made in Table 1, it is clear that certain wavelet bases perform better than others. Since the Symlet 20 basis consistently outperformed the other three in comparison to morphological processing, the following section serves to compare the resolution of the Symlet 20 basis with the Symlet 4, Daubechies 2, and Haar bases. The following table illustrates how the Symlet 20 wavelet basis compared with each of the wavelet bases used above for each of the images tested.

Table 1. Comparisons Between Techniques. The percent difference in resolution represents the number of pixels that were segmented using the given wavelet basis for the DWT compared with the number of pixels.

Table 1. Comparisons Between Techniques. The percent difference in resolution represents the number of pixels that were segmented using the given wavelet basis for the DWT compared with the number of pixels.

Discussion

As the data shows, the hybrid wavelet-morphological technique performs consistently better segmentation than just morphological segmentation when using the Symlet 4 and Symlet 20 wavelet bases, but is inconsistent when using the Daubechies 2 and Haar bases. Table 1 indicates that the Symlet 20 basis is the best suited basis tested, as the worst resolution that it produced was still about thirteen percent better than the morphological approach. Additionally, the Symlet 20 basis consistently outperformed each other wavelet basis, with an average of seventeen percent more data segmented when compared with the Haar basis and two and a half percent better resolution when compared with the Symlet 4 basis. This underscores the importance of the choice of wavelet basis function for tumor segmentation, a result not previously reported in the literature. Thus, with the right choice of wavelet basis, using a combination of wavelet processing and morphological techniques instead of just morphological processing can help to eliminate data loss in tumor segmentation. On average, the Symlet 20 wavelet basis could segment out about 20 percent more data than morphological processing alone.
Even though it is clear that the Symlet 20 basis is best suited for this technique, it is still uncertain as to exactly why this is the case. One thought, at least when it comes to comparing the Haar and Symlet 20 bases, is that the Haar basis is more ‘rigid’ and is less able to detect smaller changes in pixel characteristics than the Symlet 20 basis. This is an unproven idea, meaning that one main area of future work is to develop a more concrete theory as to why some wavelet bases perform so much better than others. An additional area of future work is to improve on the skull stripping method used in this technique. This skull stripping method is somewhat “primitive” and not highly adaptable, meaning that for tumors near the skull region, significant data loss is a distinct possibility. As a result, another highly important area of future work would be to develop a more robust, wavelet-based skull stripping method.

Conclusion

Brain tumor segmentation is an inherently difficult problem because of the widely varying nature of pixel distributions of pathological tissues in MR images. The segmentation methods and results presented in this paper are just two of many methods that have been developed over the past several decades with the goal of automating and improving brain tumor segmentation. The results underscore the effectiveness of the wavelet transform, as well as present novel findings about the impact of basis function choice on the resolution of the segmented image. Although many techniques exist that use the wavelet transform in some way, none that combine morphology and the DWT in the way presented in this paper have been reported in the literature. Additionally, there have never been clear results reported on the impact of the wavelet basis function choice on the results of segmentation. The results of the investigation in this paper can therefore serve as a useful guide for the development of future segmentation techniques involving the wavelet transform because they provide convincing evidence that the choice of wavelet basis can be vital to the resolution of a segmented image, as well as point to a basis with useful properties for this application.

Acknowledgments

The author would like to thank his mentors, Dr. Marcus Fries, Dr. Pierre-Richard Cornely, and Dr. Jill Macko for their invaluable ideas and support.

References

Clark, K., Vendt, B., Smith, K., Freymann, J., Kirby, J., Koppel, P., Moorse, S., Phillips, S., Maffit, D., Pringle, M., Tarbox, L., & Prior, F. (2013). The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository. Journal of Digital Imaging, 26(6), 1045-1057. doi:10.1007/s10278-013-9622-7.  DWT2. (n.d.). Retrieved from https://www.mathworks.com/help/wavelet/ref/dwt2.html. x
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Kaur, M., & Banga, V. K. (2013). Thresholding and Level Set Based Brain Tumor Detection Using Bounding Box as Seed. International Journal of Engineering Research & Technology, 2(4). Retrieved from https://www.ijert.org.
Kaus, M. R., Warfield, S. K., Nabavi, A., Chatzidakis, E., Black, P. M., Jolesz, F. A., & Kikinis, R. (1999). Segmentation of Meningiomas and Low Grade Gliomas in MRI. In Medical Image Computing and Computer-Assisted Intervention – MICCAI’99: Second International Conference, Cambridge, UK, September 19-22, 1999 (Vol. 1679, Lecture Notes in Computer Science, pp. 1-10). Springer Berlin Heidelberg.
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Prevalence and Outcomes of Electrolytes Deficiency in Children under Five with Diarrhea in Mwanza, Tanzania

doi:10.22186/jyi.33.2.46-48

Abstract | Introduction | Methods | Results | Discussion | Conclusions |Acknowledgements | 
References | PDF

Abstract

Dehydration from diarrhea leads to a loss of vital electrolytes in the body. The prevalence of electrolytes deficiency and its outcomes due to diarrhea among children under five in Mwanza, Tanzania was not clearly known, thus this study was performed to determine this statistic. A cohort study was conducted among 66 children less than five years old suffering from diarrhea attended and admitted to health centers in Mwanza, Tanzania. Vein puncture was performed to obtain peripheral blood, processed, and analyzed for two major electrolytes, Potassium and Sodium. This study was conducted because the loss of vital electrolytes (sodium and potassium) from diarrhea can be fatal if poorly treated. The median age of study participants was 1 year, ranged from 0.6 to 3 years. The prevalence of electrolytes deficiency in the cohort was determined to be 54.5%. Sodium deficiency (Hyponatremia) was the most prevalent (37.9%). After medication and oral rehydration therapy, all of the diarrheagenic children recovered, and those with electrolytes deficiency had their electrolytes balanced. Proper medication with oral rehydration therapy ensures complete recovery from diarrhea and electrolytes balance.

Introduction

Diarrhea is the passage of three or more loose or liquid stools per day; it may be a result of eating contaminated food and water or from food poisoning and is a common symptom of gastrointestinal infections caused by a wide range of pathogens, including bacteria, viruses and protozoa (Black et al., 1980; Kothari VR, & Thakur NA, 2014). Dehydration can be identified by experiencing dizziness, thirst, fatigue, infrequent urination and dark colored urine, nausea and headaches can leave the body without the electrolytes necessary for survival (Hirschhorn, 1980; Mackenzie, Barnes, & Shann, 1989). The electrolytes found in the body are potassium, calcium, sodium, magnesium, bicarbonate and chloride for cells functioning and signaling. According to WHO estimates; diarrheal disease is the leading cause of under-five mortality and is responsible for killing around 760,000 children every year (Kothari VR, & Thakur NA, 2014).
Epidemiological studies have shown that in developing countries, there are an estimated 1.3 billion episodes and 3.2 million deaths  of those under age five each year due to diarrhea (Rahman, 2014). Overall, these children experience an average of 3.3 episodes of diarrhea per year, but in some areas, primarily in developing countries, the average exceeds 9 episodes per year (Rahman, 2014). Where episodes are frequent, children may spend more than 15% of their days with diarrhea and about 80% of deaths that occur in the first two years of life are due to the condition. In developing countries 50% of pediatric hospitalizations  are due to acute diarrhea (Rahman, 2014).
A study carried out  by the BP Koirala Institute of Health Sciences in Dharan, Nepal that examined acid, base, and electrolyte disturbance in diarrhea showed 56% sodium  deficiency (hyponatremia), 46% potassium deficiency (hypokalemia) and 26% combined (hyponatremia and hypokalemia) (Shah, Das, Kumar, Singh, & Bhandari, 2007). The same study reported five children out of 57 had died due to electrolytes loss from diarrhea (Shah et al., 2007).
Statistical information about the prevalence of electrolyte deficiency and the outcomes among children under five years old with diarrhea that attended or was admitted to healthcare centers in Mwanza, Tanzania was not clearly known. We hypothesized that, vital electrolytes (sodium and potassium) are lost together with water due to excessive diarrhea among children under five years old. The outcome of vital electrolytes lost can be fatal, so this study was designed to guide management of children under five years old with diarrhea for early and complete recovery.

Materials and Methods

A cohort study was conducted between July and August 2016. All children less than five years old suffering from diarrhea who was admitted at the pediatric wards in Mwanza Healthcare centers and whose parents or guardians gave their consent to take part in this study were used in the study. A serial sampling method was used to determine eligibility of these study participants. About 2.5 to 5ml of two blood samples were collected from each participant and placed in a plain vacutainer tubes whereby the serum was extracted for electrolytes (sodium and potassium) analysis. Blood sample A was collected on the first day of participant admission or visit and sample B, as a follow up to sample A, was collected three days after administering oral rehydration solution (ORS) or antibiotics to all participants with electrolyte(s) [sodium and/or potassium] deficiency results.
Laboratory Procedure
Extracted sera were analyzed within two hours after specimen collection for sodium and potassium following the internal standard operating procedures, and as per reagents manufacturer guidelines for the SP Twin Electrolytes Test Kit (ARKRAY Healthcare Pvt. Ltd, India) in the Corolimeter manual analyzer (CL 157 Colorimeter).

Results

Demographic and Clinical Characteristics of Participants

During this study, a total of 66 children were enrolled. Out of those, 53.0% (35/66) were females. The median age of study participant was 1 (IQR: 0.6-3) year (Table 1).

Table 1. Demographic and clinical information of study participants.

Table 1. Demographic and clinical information of study participants.

Electrolyte Deficiency Results

The overall prevalence of electrolytes deficiency in diarrheagenic under-five children was 54.5% (36/66). Hyponatremia, hypokalemia and both (hyponatremia and hypokalemia) electrolytes deficiency were observed in 37.9% (25/66), 16.7% (11/66) and 15.2% (10/66) of the cohort respectively.

Factors Associated with Electrolytes Deficiency

Factors found to be connected with electrolytes deficiency among diarrheagenic under-five children in the bivariate analysis were 1) Present of symptoms like fever, vomiting and dehydration, 2) Duration of diarrhea, and 3) Diarrhea treatment. Children with symptoms such as fever, vomiting and dehydration showed electrolyte deficiency; 20/58 (34.5%) had hyponatremia, 10/58 (17.2%) had hypokalemia, and 8/58 (13.8%) had both (p = .707) (Table 2).
Considering the duration of diarrhea, most of children showed electrolyte deficiency during the early three up to seven days of diarrhea; 13/36 (36.1%) had hyponatremia, 6/36 (16.7%) had hypokalemia, and 8/36 (22.2%) had both hypokalemia and hyponatremia (p = .651).
Following diarrhea treatment with ORS, antibiotics or both, for those who did not received any treatment; 12/34 (35.3%) had hyponatremia, 4/34 (11.8%) had hypokalemia and 9/34 (26.5%) had both hypokalemia and hyponatremia (p = .031) (Table 2).

Table 2. Factors associated with electrolytes deficiency.

Table 2. Factors associated with electrolytes deficiency.

Electrolyte Deficiency Outcomes

Out of 66 diarrheagenic children, 40 recovered completely, 18 were still suffering from diarrhea and 8 were lost prior to follow-up (discharged or did not attend next visit) with no record of death. Among the cohort, 32 received management with antibiotics, ORS or both, whereby 62.5% (20/32) recovered completely from diarrhea (p = .0069). All diarrheagenic children who had recovered after treatment, 20/20 (100%) had balanced electrolytes from day three of follow up (Table 3).

Table 3. Outcome of electrolytes deficiency from day three after diarrhea treatment with ORS/antibiotics.

Table 3. Outcome of electrolytes deficiency from day three after diarrhea treatment with ORS/antibiotics.

Discussion

In this study, the prevalence of electrolytes deficiency among under-five diarrheagenic children was 54.5%, with the most prevalent depleted electrolyte being sodium (hyponatremia), 37.9% followed by potassium depletion (hypokalemia), 16.7%. This is comparable to another study done in Dharan, Nepal which found that the most prevalent depleted electrolyte among children with diarrhea was sodium (hyponatremia), 56% (Shah et al., 2007). Another study done in Nigeria in 2015 on serum electrolyte profiles in children admitted with dehydration due to diarrhea showed that hyponatremia and hypokalemia ranked first and second by 60.5% and 44.3% respectively (Onyiriuka, & Iheagwara, 2015). Sodium and potassium are the major lost electrolytes in diarrhea because they form intracellular and extracellular fluids respectively at the sodium-potassium pump (Skou, 1989).
The current study found that, electrolytes deficiency among diarrheagenic children to be associated with clinical symptoms like fever, duration of diarrhea and treatment type as previously reported (Bahl et al., 2002; Donowitz, Kokke, & Saidi, 1995; Thapar, & Sanderson, 2004; Weiner, & Epstein, 1970). The more episodes of diarrhea a child experiences, the greater amount of water and electrolytes are lost (Thapar, & Sanderson, 2004). Lack of treatment therapy to replace water and electrolytes results  in a high level of deficiency (Thapar, & Sanderson, 2004).
This study found that most of the children experienced electrolyte deficiency after suffering from diarrhea during the early three to seven days. This may be because during the early days they had not yet received treatment; thus, the results showed electrolytes had decreased. However, as the days went on they underwent treatment and their levels began to rise as ORS replaced the lost electrolytes. Diarrhea treatment either with ORS or antibiotics ensures recovery and a rise in electrolyte  levels (Hirschhorn, 1980). But for those children who received antibiotic treatment and ORS, still in diarrhea may be the exact aetiological cause of diarrhea was not bacteria (Black et al., 1980; Hirschhorn, 1980).
Most patients with electrolyte deficiency recovered completely after receiving treatment; those who had not received any treatment but recovered may have been affected by a bacterial toxin, in which case the diarrhea usually stops itself after some time (self-limiting) (Challapalli, Tess, Cunningham, Chopra, & Houston, 1988).

Conclusion

The current study found high prevalence of electrolytes deficiency, 54.5% among children under five years old with diarrhea. Electrolytes deficiency was connected with fever, vomiting and dehydration. The use of ORS as part of diarrhea management to replace water and the lost electrolytes is recommended. This study was unable to determine the aetiological causative agent of diarrhea among children under five years old. Further studies should attempt to determine the aetiological causative agent of diarrhea cases.

References

Bahl, R., Bhandari, N., Saksena, M., Strand, T., Kumar, G. T., Bhan, M. K., &
Sommerfelt, H. (2002). Efficacy of zinc-fortified oral rehydration solution in 6-to 35-month-old children with acute diarrhea. The Journal of Pediatrics, 141(5), 677-682.
Black, R. E., Merson, M., Rahman, A. M., Yunus, M., Alim, A. A., Huq, I., Curlin,
G. (1980). A two-year study of bacterial, viral, and parasitic agents associated with diarrhea in rural Bangladesh. Journal of Infectious Diseases, 142(5), 660-664.
Challapalli, M., Tess, B. R., Cunningham, D. G., Chopra, A. K., & Houston, C. W.
(1988). Aeromonas-associated diarrhea in children. The Pediatric Infectious Disease Journal, 7(10), 693-697.
Donowitz, M., Kokke, F. T., & Saidi, R. (1995). Evaluation of patients with chronic
 diarrhea. New England Journal of Medicine, 332(11), 725-729.
Hirschhorn, N. (1980). The treatment of acute diarrhea in children. An historical
and physiological perspective. The American Journal of Clinical Nutrition, 33(3), 637-663.
Hsiao, A. L., & Baker, M. D. (2005). Fever in the new millennium: a review of
recent studies of markers of serious bacterial infection in febrile children. Current Opinion in Pediatrics, 17(1), 56-61.
Mackenzie, A., Barnes, G., & Shann, F. (1989). Clinical signs of dehydration in
 children. The Lancet, 334(8663), 605-607.
Onyiriuka, A., & Iheagwara, E. (2015). Serum electrolyte profiles of under-five
Nigerian children admitted for severe dehydration due to acute diarrhea. Nigerian Journal of Health Sciences, 15(1), 14.
Rahman, H. (2014). Molecular characterization of Necrotoxigenic Escherichia Coli
NTEC of man and animals.
Shah, G., Das, B., Kumar, S., Singh, M., & Bhandari, G. (2007). Acid base and
electrolyte disturbance in diarrhoea.
Skou, J. C. (1989). Sodium-potassium pump Membrane transport (pp. 155-185):
Springer.
Thapar, N., & Sanderson, I. R. (2004). Diarrhoea in children: an interface between
 developing and developed countries. The Lancet, 363(9409), 641-653.
VR, Kothari., & NA, Thakur. (2014). A Cross Sectional Study of Risk Factors for
Development of Dehydration in Children under 5 Years Having Acute Watery Diarrhea.
Weiner, M., & Epstein, F. (1970). Signs and symptoms of electrolyte disorders. The
 Yale Journal of bBology and Medicine, 43(2), 76.

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Varying Sugars and Sugar Concentrations Influence In Vitro Pollen Germination and Pollen Tube Growth of Cassia alata L.

doi:10.22186/jyi.33.1.42-45

Abstract | Introduction | Methods | Results | Discussion | Conclusions |Acknowledgements | 
References | PDF

Abstract

This study investigates the effects of varying sugars and sugar concentrations on the in vitro germination and tube growth of pollens of Cassia alata L., a known Philippine ornamental and medicinal plant. This aims to add information on the pollination fertilization mechanism of the plant for its possible extensive cultivation. Using a pollination germination medium with different sugar concentrations (2.5, 5.0, 7.5 and 10.0%), pollen germination and pollen tube growth is highly influenced by all sucrose concentrations and by certain glucose (2.5%) and lactose (2.5 and 7.5%) concentrations. Maltose and fructose, on the other hand, are determined to be inhibitory sugars for pollen germination.

Introduction

The total count of pollen grains on a stigma usually surpasses the number required to fertilize all ovules; thus, the process of pollen growth in the carpel is highly competitive (Okusaka & Hiratsuka, 2009). In higher plants, the elongation of pollen tube is extremely fast making the pollen tube the plant cell with the fastest growth rate. Accordingly, this swift growth of pollen tubes is essential for male reproductive success (Okusaka, & Hiratsuka, 2009) and for the subsequent plant development.
Pollen development and tube growth (due to its high growth rate) are high energy-requiring processes (Selinski, & Scheibe, 2014). Carbohydrates act as energy source during the two processes (Okusaka, & Hiratsuka, 2009). The storage compounds and sugars stored in mature pollen can adequately sustain survival of pollen and germination; however, the rapid pollen tube elongation requires secretions of carbohydrates (exogenous sugars) from the stylar canal to proceed (Reinders, 2016). Exogenous sugars also provide and maintain suitable osmotic environment not only for germination of pollen but also for sustained pollen tube growth (Baloch & Lakho, 2001).
Most of the studies conducted on C. alata L. are on its therapeutic properties. Leaves of C. alata L. contain anthraquinone derivatives which exhibit antimicrobial, antitumor, antioxidant, cytotoxic and hypoglycemic activities (Alalor, Igwilo, & Jeroh, 2012). Crude extracts of the plant are being used to treat various skin diseases (Balinado, & Chan, 2017) and are effective against Staphylococcus aureus and Bacillus subtilis (Alalor, Igwilo, & Jeroh, 2012). Also, C. alata L. based soap was proven effective against opportunistic yeasts (Esimone, 2007).
Preliminary investigation of the developmental morpho-anatomy of the male gametophyte of C. alata L. was already conducted (Tolentino, 2011), but limited information is known regarding its sugar metabolism and investigating this will immensely contribute to the extensive cultivation of the plant taking into consideration its medicinal properties. This study, therefore, would add light to the developmental biology of C. alata particularly to its pollen germination and pollen tube growth.
The study specifically aims to determine the effect of varying sugars and sugar concentrations on the in vitro pollen germination and tube growth of C. alata by calculating the germination percentage and measuring the pollen tube length after exposure to different sugars. In numerous studies on in vitro pollen germination of different plant species, sucrose exhibited strong stimulatory effects (Baloch, & Lakho, 2001; Patel, 2017; Zhang, & Croes, 1982), together with glucose and lactose (Ismail, 2014); thus, may also promote pollen germination in C. alata. Maltose and fructose, on the other hand, were reported to have varied effects on pollen germination of various plant species (Ismail, 2014; Okusaka, & Hiratsuka, 2009; Nakamura, & Suzuki, 1985).  

Methods

Pollen Collection

Cassia alata L. flowers at anthesis were collected randomly from Cavite State University, Indang, Cavite during daytime. Flowers were immediately transported to the Department of Biological Sciences of the same institution for the conduct of the experiment. Pollen grains were collected by carefully tapping and brushing the anthers of each flower on a clean petri dish.

Preparation of Pollen Germination Medium

A Brewbaker and Kwack medium was used as pollen germination medium. It was composed of 100mg 1-1 boric acid, 200mg 1-1 magnesium sulfate, 100mg 1-1potassium nitrate, 300-mg 1-1 calcium nitrate, 1% agar and sugars (Jayaprakash, & Sarla, 2000). Five sugars were utilized, namely; fructose, glucose, lactose, maltose and sucrose. For each sugar, four different concentrations were prepared: 2.5%, 5.0%, 7.5%, and 10.0%. A medium with no sugar added was used as negative control. The resulting medium was finally autoclaved to maintain sterility.

Preparation of a Humid Chamber and Germination Slides

A filter paper was placed in each petri dish before pouring distilled water sufficient enough to obtain a moist environment for the pollen. A glass slide with several (two to three) drops of hot liquid pollen germination medium at the center was then placed in each petri dish. This allowed the agar to completely cool and harden. With the aid of a nylon brush, pollen grains were transferred onto the solidified agar medium. Resulting petri dishes were then incubated in the dark for a total of three hours. This was performed in triplicate.

Observation of Pollen Germination and Pollen Tube Growth

Observation for signs of pollen germination and pollen tube growth was done by microscopy thrice at one-hour interval. A single field of view per replicate that contained at least 30 solitary pollen grains was observed and photographed. A pollen grain was considered germinated when its tube length doubled the diameter of the pollen grain.  The total number of pollens that germinated was determined and percent germination was calculated using the following formula.

VS equation 1 (1)

Pollen tube lengths were then measured (in μm) with the aid of ImageJ free software using the images obtained from microscopy.

Statistical Treatment

Descriptive statistics, such as means and percentages, were utilized in determining pollen germination percentage and mean pollen tube lengths. One-way Analysis of Variance (ANOVA) was used to determine the significant differences in pollen tube growth among sugar concentrations.

Results

Examination of Pollen Germination

Humid chambers containing germination slides with pollen grains were incubated for a total of three hours. The total number of germinated pollen grains per sugar concentration was obtained as shown in Figure 1. As presented, pollen grains only germinated in media containing glucose (i.e. 2.50%) and lactose (i.e. 2.50% and 7.50%) and all concentrations of sucrose (with 100% germination in 5.00-10.00% sucrose concentrations). On the other hand, germination was not observed in solitary pollen grains exposed to fructose and maltose.

Figure 1. Mean number of germinated pollen grains per sugar concentration after 3 h of incubation.

Figure 1. Mean number of germinated pollen grains per sugar concentration after 3 h of incubation.

As shown in Table 1 and Figure 2, pollen tube growth of C. alata L. was only observed in 2.5- and 7.5-% lactose concentrations. Increase in pollen tube length under 7.5-% concentration was found to be directly proportional to increasing time of incubation and was significantly different from other concentrations.

Table 1. Mean pollen tube lengths (in μm) in response to increasing lactose concentrations.

Table 1. Mean pollen tube lengths (in μm) in response to increasing lactose concentrations.

 

Figure 2. Graph showing mean pollen tube lengths (in μm) in response to increasing lactose concentrations.

Figure 2. Graph showing mean pollen tube lengths (in μm) in response to increasing lactose concentrations.

In addition, as presented in Table 2 and Figure 3, C. alata pollens only responded to 2.5-% glucose concentration. Pollen tube lengths increased as incubation time also lengthened. No pollen tube length was observed in glucose concentrations higher than 2.5%.

Table 2. Mean pollen tube lengths (in μm) in response to increasing glucose concentrations.

Table 2. Mean pollen tube lengths (in μm) in response to increasing glucose concentrations.

 

Figure 3. Mean pollen tube lengths (in μm) in response to increasing glucose concentrations.

Figure 3. Mean pollen tube lengths (in μm) in response to increasing glucose concentrations.

Varying sucrose concentrations differently influenced pollen tube growth, results were statistically significant (Table 3, Figure 4). In all concentrations, an increase in pollen tube length was observed in response to increasing time of incubation. A representative photograph of pollen tube growth on germination medium with sucrose is shown in Figure 5.

Table 3. Mean pollen tube lengths (in μm) in response to increasing sucrose concentrations.

Table 3. Mean pollen tube lengths (in μm) in response to increasing sucrose concentrations.

 

Figure 4. Mean pollen tube lengths (in μm) in response to increasing sucrose concentrations.

Figure 4. Mean pollen tube lengths (in μm) in response to increasing sucrose concentrations.

 

Figure 5. Pollen germination on sucrose.

Figure 5. Pollen germination on sucrose.

Discussion

Varying sugars and sugar concentrations differently influenced pollen germination and pollen tube growth of C. alata L. Pollens successfully germinated in the sugar sucrose and acted more effectively than glucose and lactose; while fructose and maltose strongly inhibited germination on agar medium.
The observation that glucose permitted pollen tube growth could be explained by the fact that glucose is natural pollen constituent, together with other sugars, such as arabinose and galactose (Loo & Hwan, 1944). This sugar acts as an essential signaling molecule that controls plant growth and development and gene expression (Zhou et al., 1998). In addition, the effect of lactose in this study was similarly reported by Bishop (2009) and Ismail (2014). Most significant pollen tube growth on lactose compared to other sugars was also observed by Takao et al. (2006). Bishop (2009) even suggested that a higher concentration of lactose could be used as substitute for the normally used sucrose. The positive influence of sucrose to pollen germination and growth, on the other hand, could be attributed to the condition it provides to pollen that is similar to the condition of the stigmatic tissue of a flower; this stigma that secretes a fluid substance to rehydrate the pollen (Zhang, & Croes, 1982). Sucrose is the most common sugar form found in the translocation stream and is transported to other non-photosynthetic plant tissues, such as flowers, for direct metabolic use (Hopkins, & Huner, 2009).The growth of pollen tube on sugar-free medium, in addition, could be attributed to the use of endogenous carbohydrates of the pollen without the influence—be it stimulatory or inhibitory—of other sugars present in the medium.
Similarly to the results obtained by Nakamura and Suzuki (1985), maltose strongly inhibited pollen tube growth in Camella japonica. Okusaka and Hiratsuka (2009), in addition, reported that fructose causes pollen inhibition. It was suggested that the pollen on fructose medium predominantly uses other sugars (e.g. sucrose and glucose) as respiration substrates and cannot maintain the constant level of these sugars.
This study reveals that different sugars have a considerable influence on pollen germination and pollen tube growth in C. alata L. Pollen tube growth is influenced by glucose, lactose and sucrose sugars; the latter being the most effective. Maltose and fructose were, on the other hand, found inhibitory of germination. This study therefore adds information on the developmental biology of pollens of C. alata L., a known ornamental and medicinal plant in the Philippines, which can further be used for its extensive cultivation in the country.

Acknowledgement

The researchers would like to acknowledge with deep and warm gratitude the Department of Biological Sciences, College of Arts and Sciences, Cavite State University for the laboratory materials and equipment used in the study.

References

Okusaka, K., & Hiratsuka, S. (2009). Fructose inhibits pear pollen germination on agar medium without loss of viability. Scientia Horticulturae, 122(1):51-55. doi:10.1016/j.scienta.2009.03.024
Selinski, J., & Scheibe, R. (2014, November 3). Pollen tube growth: Where does the energy come from? Plant Signaling and Behavior, 9(12). Retrieved November 23, 2016, from  doi: 10.4161/15592324.2014.977200
Reinders, A. (2016). Fuel for the road – sugar transport and pollen tube growth. Journal of Experimental Botany,67(8):2121-2123. doi:10.1093/jxb/erw113
Baloch, M. J., & Lakho, A. R. (2001). Impact of sucrose concentrations on in vitro pollen germination of okra, Hibiscus esculentus.Pakistan Journal of Biological Sciences, 4(5):402-403.
Alalor, C., Igwilo, C., & Jeroh, E. (2012). Evaluation of the antibacterial properties of aqueous and methanol extracts of Cassia alata. Journal of Pharmacy and Allied Health Sciences, 2(2):40-46. doi:10.3923/jpahs.2012.40.46
Balinado, L., & Chan, M. (2017). An ethnomedicinal study of plants and traditional health care practices in District 7, Cavite, Philippines.2017 International Conference on Chemical, Agricultural, Biological and Medical Sciences (CABMS-17).doi: 10.17758/URUAE.AE0117622
Esimone, C. (2007). Evaluation of the Antiseptic properties of Cassia alata-based herbal soap.International Journal of Alternative Medicine, 6(1).
Jayaprakash, P., & Sarla, N. (2000). Development of an improved medium for germination of Cajanuscajan (L.) Millsp.Pollen in vitro.Journal of Experimental Botany, 52(357):851-855
Loo, T., & Hwang, T. (1944). Growth stimulation by manganese sulphate, indole-3-acetic acid and colchicine in pollen germination and pollen tube growth.American Journal of Botany, 31(6):356-367
Zhou, Li, Jang, Jang-chyun, Jones, Tamara Sheen. (April 1998). Glucose and ethylene signal transduction crosstalk revealed by an Arabidopsis glucose-insensitive mutant. Harvard Medical School, Boston, MA.
Bishop, C. J. (2009). Pollen tube culture on a lactose medium. Stain Technology, 24(1):9-12. doi: 10.3109/10520294909139572
Ismail, O. M. (2014). In vitro germination of date palm pollen grains affected by different sugar types.Research Journal of Pharmaceutical, Biological, and Chemical Sciences, 5(1):880-886.
Takao, S., Yoshiomi, S., & Norio, N. (2006). Japanese Journal of Palynology, 52(2):97-105
Zhang, H. Q., Croes, A. F. (1982). A New Medium for Pollen Germination in vitro. 31(1|2):113-119
Hopkins, W., & Huner, N., 2009, Introduction to plant physiology: 4th ed, John Wiley & Sons, Inc: USA, 503 pp.
Nakamura, N., & Suzuki, H. (1985). Inhibition of Camellia japonica pollen tube growth by maltose.Plant and Cell Physiology, 26(6):1011-1018
Patel, E. (2015). Sucrose Needs for Pollen Germination of Impatiens balsamina L. International Journal of Innovative Research in Science, Engineering and Technology, 4(10). doi:10.15680/IJIRSET.2015.0410104
Tolentino, V. (2011). A preliminary study on the developmental morpho-anatomy of the male gametophyte of Cassia alata L. Retrieved March 16, 2017, from http://rcw-portal.ateneo.edu/rvp/details.php?id=2011-C0393

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A Transcriptome Study of Borrelia burgdorferi Infection in Murine Heart and Brain Tissues

doi:10.22186/jyi.33.1.28-41

Abstract | Introduction | Methods | Results | Discussion | Conclusions |Acknowledgements | 
References | PDF

Abstract

Lyme disease is the most common vector-borne disease in the United States and is typically caused by the bacterium Borrelia burgdorferi. Although often curable, delayed diagnosis due to nonspecific symptoms risks systemic complications, and some patients experience symptoms despite bacterial clearance from the body. We hypothesized that B. burgdorferi infection induces a self-perpetuating cascade of immunological responses such that symptoms remain after infection or causes residual damage to patients’ immune system and tissues. We present a transcriptome study of B. burgdorferi infection in murine heart and brain tissues using the Next Generation Sequencing technology and computational methods to identify differentially expressed genes, particularly for evidence of active inflammatory pathways. Our results reveal differential expression of five genes in an infected heart. These differentially expressed genes are enriched in pathways related to immune functions in heart tissue. Our study indicated that B. burgdorferi infection triggers immune response pathways similar to other pathogens, and some genes were found to be unique to infection by B. burdorferi, suggesting the potential for development of specific therapeutic targets to treat B. burgdorferi infection. In the brain, 66 genes were differentially expressed. These genes were enriched in pathways that facilitate the pathogen’s crossing of the blood-brain barrier. Although the mouse model of B. burgdorferi infection fails to recapitulate human neuroborreliosis, we observed damage to the integrity of the blood-brain barrier upon peripheral infection. This study elucidates mechanism of infection unique to Borrelia and clarifies the role of a mouse model of Lyme disease.

Introduction

Lyme disease is prevalent from southern Scandinavia to the northern Mediterranean countries and in the northeastern United States (U.S.). In the U.S., Lyme disease is the most common vector-borne disease: over 251,000 cases were reported between 2005 and 2014, with about 25,000 confirmed cases each year. Most cases occur in the northeast; however, notable expansion was observed in the Great Lakes region (CDC 2014). Lyme disease is caused by the infection of Borrelia burgdorferi sensu lato (family Spirochaetaceae), a diderm, microaerophilic spirochete bacteria (Wang et al., 1999). Within the genus Borrelia, three other species (B. afzelii, B. garinii, and possibly B. valaisiana) can cause the disease, but are more prevalent on the European continent (WHO, 2006). Other Borrelia species are carried by soft-bodied ticks and cause relapsing fevers (Garcia-Monco et al., 1997). All four pathogenic species of Borrelia are spread to humans by the bite of an infected tick. In the U.S., two blacklegged, or deer, tick species (Ixodes scapularis and Ixodes pacificus) are known to carry B. burgdorferi. The bacteria infect several mammal and bird species and are transmitted during the tick’s blood meals (Rosa et al., 2005).
Although Lyme disease is usually curable with prompt antibiotic treatment, nonspecific symptoms make early diagnosis difficult, and untreated infection can induce rheumatic, cardiac, and neurologic complications. The current screening test is still suboptimal in detecting Lyme reliably (Centers for Disease, & Prevention, 1995; Dressler et al., 1993). Lyme is often diagnosed after the emergence of the classic bulls-eye-shaped rash at the site of the tick bite, which occurs in over 70% of patients (McConville, 2014). The infection spreads throughout the body, causing general inflammation during the early dissemination stage, and years after initial infection, painful arthritis and joint swelling are observed among 60% of patients (McConville, 2014). Borrelia are transported throughout the body, and persistent infections are established in the skin, joint, heart, bladder, and, in only humans and primates, the central nervous system (Rosa et al., 2005).
Some of these tissues are particularly affected by infection-induced inflammation. Lyme carditis (inflammation of the heart tissue, interfering with its electrical activity) occurs in 4-10% of infections during the early dissemination stage. Carditis responds well to antibiotic treatment; however, because it occurs so early in the infection process and Lyme disease is difficult to diagnose, it can be fatal (McAlister et al., 1989). Additionally, 10-15% of Lyme disease cases manifest neurological conditions, such as pain caused by temporary or permanent inflammation of the nerves, meningitis, memory and anxiety problems, depression, and both cranial and peripheral neuritis (Narasimhan et al., 2003; Pachner, & Steere, 1984; Rupprecht et al., 2008).
Some patients will experience Post-Treatment Lyme Disease Syndrome (PTLDS), a chronic manifestation of Lyme disease. PTLDS is diagnosed when symptoms continue despite bacterial clearance from the body (McConville 2014). Unlike many other gram-negative bacteria, little epidemiological evidence shows antibiotic-resistant Borrelia infections to be a threat; however, the prevalence of persistent symptoms is concerning. Because antibiotic treatment does not necessarily resolve PTLDS, understanding how Borrelia affects the body, especially the heart and brain tissues, is crucial in reducing the burden of this disease. We hypothesize that Borrelia infection induces a self-perpetuating cascade of immunological responses, such that symptoms remain after infection. The B31 B. burgdorferi genome has been fully sequenced, consisting a small linear chromosome (~900kb) and 21 unique plasmids (5-56kb) (Fraser et al., 1997), but does not reveal any obvious virulent elements (Rosa et al., 2005). Thus, looking at the transcriptional activities of the infected host rather than the genome of B31 B. burgdorferi may shed light the immune response and on its pathogenesis.
A microarray study of Borrelia genes during infection of heart and CNS tissue in non-human primates revealed elevated expression of over 90 genes in bacteria in the CNS when compared to bacteria in the heart (Narasimhan et al., 2003), indicating that parasite-host responses are different in the two tissues. Infection induces a macrophage response and upregulated cytokine expression in the murine macrophage cell line (Wang et al., 2008). However, little is know about the host’s transcriptional response at tissue level upon Borrelia infection. Here, we present a transcriptome study that integrates experimental and computational methods to probe for the effect of B. burgdorferi infection on gene expression, and subsequently, biological pathways of inflammation in murine heart and brain tissues. We have designed a dual-method redundant pipeline to overcome issues arising from the lack of replicates owing to the scarcity of samples and the high cost of RNA-sequencing (RNA-seq). This method will allow us to better study and characterize acute and persistent Borrelia infection.

Materials and Methods

Culture and Infection

B31-MI B. burgdorferi, from ATCC (Manassas, VA), was grown in BSK-H (Sigma BSK-H Complete, St. Louis, MO) at 37°C to a concentration of 7.2×107 viable spirochetes/mL at the Baumgarth lab at University of California Davis and shipped on ice for next-day infections.
Six female C3H/HeJ mice (The Jackson Laboratory, Bar Harbor, ME), aged 6-8 weeks old, were infected, and four female C3H/HeJ mice, also aged 6-8 weeks old, were used as controls. Two injections of approximately 0.5mL each were injected into each mouse subcutaneously in the mid-back with a 21-gauge needle. Control mice were injected with BSK-H media via the same protocol. C3H/HeJ mice carry a chromosomal inversion on Chromosome 6 (Chang, 2015), which yields no phenotypic change, as well as mutations in the Pde6b and Tlr4 genes. The Pde6b mutation causes retinal degeneration and eventual blindness. The Tlr4 mutation makes these mice more tolerant to endotoxin in bacterial infections. Higher than the minimum dose (3.6×105 times higher) (Barthold et al., 1993; Rego et al., 2014) of spirochetes was injected to the mice to ensure infection. Arthritic swelling was observed in all three experimental mice collected on day 14, and in one mouse collected on day 42. All mice were used in accordance with Lafayette College’s Institutional Animal Care and Use Committee approved protocol that followed the guidelines for ethical conduct in care and use of animals.

RNA Extraction

Only mice infected for 14 days were selected for RNA-seq to explore the acute phase of the disease. They were sacrificed with carbon dioxide gas and then cervical dislocation. Samples of heart and brain tissue were collected at 14 and 42 days. RNA extraction using TRIzol Reagent (Ambion, Austin, TX) was conducted, following the manufacturer’s protocol, from sample tissues. A preliminary analysis of one sample from control and experiment was conducted. Both samples, brain and heart, were extracted from control and experimental animals after 14 days of infection. These samples were chosen as a condition-constant (day) control-experimental pair for their high concentrations and 260/280 ratios indicative of higher RNA purity (Table S1).

RNA-Seq

One sample was selected from control and experimental conditions from heart and brain tissues for RNA-seq. Each sample consisted of 5ug of poly(A)+ total RNA. Single-end RNA-seq was performed in Illumina HiSeq platform offsite by GENEWIZ (GENEWIZ 2013). Sequencing results were returned in FASTQ files in which short read was about 50 bps long on average. The total number of short reads ranged from 47 million to 59 million per sample. The quality of short reads was checked by FASTQC (Andrews); average Q-score was 37 and over 94% of the short reads was above 30 (Table S2).

Differentially Expressed Gene Analysis

We built a dual, redundant pipeline to circumvent the scarcity of replicates, in which each dataset was processed twice by two principally distinct methods. The advantages of this pipeline include the elimination of method bias and the confidence of identifying truly differentially expressed genes (DEGs).
DEGs were identified largely by the Tuxedo pipeline (Trapnell et al., 2012) with some modifications (Figure 1A-B). Before making DEG calls, short reads obtained from Next Generation Sequencing (NGS) were mapped to the mouse genome (mm10 (Browser)) by Tophat (v2.0.10) (Trapnell et al., 2009) via alignment engine bowtie2 (v2.2.1.0) (Langmead, & Salzberg 2012). Following short reads mapping was the assembly of overlapping short reads into long transcripts. By counting the number of transcripts mapped to genes, gene expression levels were determined.

Figure 1. Workflow of the dual-method approach to differential gene expression analysis and signaling pathway identification. (A) Short reads mapping and differentially expressed gene (DEG) identification using DESeq2. (B) RNA-seq short reads mapping and DEG identification using the Tuxedo pipeline. (C) Signaling pathway analysis of DEGs using WebGestalt and SPIA.

Figure 1. Workflow of the dual-method approach to differential gene expression analysis and signaling pathway identification. (A) Short reads mapping and differentially expressed gene (DEG) identification using DESeq2. (B) RNA-seq short reads mapping and DEG identification using the Tuxedo pipeline. (C) Signaling pathway analysis of DEGs using WebGestalt and SPIA.

Two DEGs callers were used in our dual-method pipeline: cufflinks (v2.1.1) (Trapnell et al., 2010) and DESeq2 (v3.2.1) (Love et al., 2014). Figure 1A illustrates the overview of the DESeq2 pipeto line. A slight alteration was done the Tuxedo pipeline in which the number of transcripts mapped to each gene (raw count) was prepared by htseq-count (v0.6.1p1) (Anders et al., 2015) per sample before running DESeq2. This pipeline identified 365 (p < 0.10) and 168 (p < .04) DEGs in heart and brain, respectively (Supplemental File 2, Tables S4 & S6). To corroborate with the DEGs found by DESeq2, we also used the standard Tuxedo cufflinks package as an alternative method to analyze the genome-wide gene expression levels between the two conditions. This package comprises of three programs, namely cufflinks, cuffmerge, and cuffdiff. The result is a list of DEGs that show statistical significance expression patterns between control and infection.
For quality assurance purpose, RNA-seq and DEG results were inspected by a visualization method CummeRbund (v2.10.0), an R package (cummeRbund). Bias in harvesting RNA samples from control and experimental conditions may cause misleading conclusion in gene differential expression analysis. Thus, we used CummeRbund to reveal genome-wide expression distribution plots under two conditions of two tissues. Figure S1 shows similar distributions of genes in control and experimental conditions, meaning the absence of sequencing bias among our samples and both control and experimental mice of each tissue type had a similar quantity of total reads on a genome scale. Thus, expression levels are comparable on locus-focused basis.
CummeRbund also generates scatterplot to show the widespread of DEGs in experiments. Scatterplots of differential gene expression (Figures S2 and S3) showed the presence of a small set of differentially expressed genes between the two conditions in the brain and heart tissues. By using cuffdiff, 136 and 100 genes in heart tissue and brain tissue were discovered to express differentially, respectively (Supplemental File 1, Tables S3 & 35).

Signaling Pathway Analysis

Similar to the discovery of DEGs, two distinct signaling pathway analysis tools were used to search for biological pathways perturbed by DEGs due to B. burgdorferi infection: WebGestalt (Zhang et al., 2005), and SPIA (v3.2.1) (Tarca, 2013). Both methods sourced biological pathway information from KEGG pathway database (Kanehisa, & Goto, 2000; Kanehisa et al., 2014). WebGestalt detects enriched pathways by identifying over-represented Gene Ontology (GO) (Ashburner et al., 2000) terms associated with DEGs. The underlying statistical test used to substantiate over-representation of GO terms is the hypergeometric test. Thus, it assumes DEGs are independent of each other. Such a condition may not hold, as DEGs belonging to the same pathway inherently interact directly or indirectly with each other.
We used SPIA to cross-examine results obtained from WebGestalt. SPIA harnesses genes’ topological relationship in assessing the degree of perturbation exerted on the network by DEGs. More DEGs in a pathway indicates greater significance that the experimental condition induced a perturbation in that pathway. The location of the gene in the pathway is also taken into consideration by SPIA. For example, insulin receptor anchored at the cell surface functions as an on/off switch in the insulin signaling pathway. Thus, its differential expression induces a larger ripple effect to the downstream cellular processes than genes situated at the end of the cascades.
In our dual-method approach, each pathway analysis tool received two lists of DEGs, one from each aforementioned DEG calling methods, and produced four lists of predicted pathways for each tissue (Figure 1C). We then overlapped these lists to reliably identify pathways perturbed by B. burgdorferi infection. Pathways found in at least three out of four lists were selected for analysis (Table 1).

Table 1.  Altered pathways associated with differentially expressed genes (DEGs). Top ten pathways ordered by the number of DEGs are listed in below. Only nine pathways in brain tissue were identified by WebGestalt and DESeq2. pPERT is the p-value for a pathway to be perturbed by DEGs. Pathways shared by at least three datasets are in bold.

Table 1. Altered pathways associated with differentially expressed genes (DEGs). Top ten pathways ordered by the number of DEGs are listed in below. Only nine pathways in brain tissue were identified by WebGestalt and DESeq2. pPERT is the p-value for a pathway to be perturbed by DEGs. Pathways shared by at least three datasets are in bold.

 

Table 1.  Altered pathways associated with differentially expressed genes (DEGs). Top ten pathways ordered by the number of DEGs are listed in below. Only nine pathways in brain tissue were identified by WebGestalt and DESeq2. pPERT is the p-value for a pathway to be perturbed by DEGs. Pathways shared by at least three datasets are in bold.

Table 1. Altered pathways associated with differentially expressed genes (DEGs). Top ten pathways ordered by the number of DEGs are listed in below. Only nine pathways in brain tissue were identified by WebGestalt and DESeq2. pPERT is the p-value for a pathway to be perturbed by DEGs. Pathways shared by at least three datasets are in bold.

Results

Differentially Expressed Genes

Cufflinks and DESeq2 identified 136, and 365 DEGs in heart tissue, respectively (Tables S3 and S4). Surprisingly, these two sets of DEGs overlapped meagerly. We then checked whether the two sets of DEGs still pertained coherent biological functions. We grouped DEGs by molecular functions using WebGestalt’s GO Slim Classification function. This function virtually determines molecular function GO terms enrichment among genes. As seen in Figure 2A, the two sets of DEGs exhibited highly similar GO molecular function profile; 15 out of 17 molecular functions were shared between the two sets. Moreover, the order of five functions was preserved between the two profiles. These five functions are protein binding, ion binding, molecular transducer activity, transporter activity, and chromatic binding. Furthermore, we repeated the same analysis using DAVID (Huang da et al., 2009a; Huang da et al., 2009b), a similar method but independently developed by a different research group. The two sets shared the top two biological process GO terms: immune response, and defense response (Tables S7 and S8).
In brain tissue, cufflinks and DESeq2 identified 100 and 168 DEGs, respectively (Tables S5 and S6). The two sets of brain DEGs shared 67 genes or 67% of cufflinks’s predictions. Out of the 14 molecular functions of DEGs, 12 functions were common between the two groups (Figure 2B). Additionally, the two methods found the same top six functions in the two datasets but in a slightly different order. Similarly, the two sets of brain DEGs were analyzed using DAVID. Biological processes behavior and locomotive behavior were shared between the two sets (Tables S9 and S10).

Figure 2. Comparison of Gene Ontology (GO) molecular function terms. (A ) Molecular function GO terms of heart DEGs generated by DESeq2 (left) and cufflinks (right). In both panels, the numbers below the captions of the bars represent the order sorted by the number of GO terms in each group. Underlined numbers on the right panel signify the conservation of their order on both panels. (B) Molecular function GO terms of brain DEGs generated by DESeq2 (left) and cufflinks (right).

Figure 2. Comparison of Gene Ontology (GO) molecular function terms. (A ) Molecular function GO terms of heart DEGs generated by DESeq2 (left) and cufflinks (right). In both panels, the numbers below the captions of the bars represent the order sorted by the number of GO terms in each group. Underlined numbers on the right panel signify the conservation of their order on both panels. (B) Molecular function GO terms of brain DEGs generated by DESeq2 (left) and cufflinks (right).

Immune Response to B. burgdorferi Infection in Heart Tissue

As genes do not function alone, the infected host is expected to launch concerted biological processes to battle against B. burgdorferi. Thus, we examined whether or not the list of DEGs originated from common pathways in response to B. burgdorferi infection. We used a dual-method approach to overcome the issue of replicate-depletion in biological pathway analysis in which four sets of predicted pathways were generated for each tissue (Figure 1C). The top ten pathways, by the highest number of DEGs with applicable p-values, were selected for analysis in this study (Table 1). Ten genes belonging to the chemokine signaling pathway were up-regulated in B. burgdorferi infection (Figure 3A). Upregulation of β-arrestin 1 (Arrb1) was detected and is upstream of a myriad of downstream factors in response to infection. This result suggests that B. burgdorferi infection activated Arrb1, which stimulated a broad inflammatory response.

Figure 3. Biological pathways altered by B. burgdorferi infection in heart tissue. Pathway diagrams were generated by Pathview (Luo, & Brouwer 2013). (A) Chemokine signaling pathway (mmu04062).

Figure 3. Biological pathways altered by B. burgdorferi infection in heart tissue. Pathway diagrams were generated by Pathview (Luo, & Brouwer 2013). (A) Chemokine signaling pathway (mmu04062).

 

Figure 3. Biological pathways altered by B. burgdorferi infection in heart tissue. Pathway diagrams were generated by Pathview (Luo, & Brouwer 2013). (B) FcγR-mediated phagocytosis (mmu04666).

Figure 3. Biological pathways altered by B. burgdorferi infection in heart tissue. Pathway diagrams were generated by Pathview (Luo, & Brouwer 2013). (B) FcγR-mediated phagocytosis (mmu04666).

Our enrichment results indicated that Borrelia infection in heart also perturbs the same set of genes as Staphylococcus aureus (Figure 3C) and Leishmaniasis (Figure 3E). Unlike Borrelia, Staphylococcus aureus is a gram-positive bacterium and Leishmaniasis is caused by parasites (genus Leishmania). We have found that similar to S. aureus infection (as defined by a gene cluster in DAVID), the complement genes C3 and C1Q were up-regulated in B. burgdorferi infection (Figure 3C). Similarly, three genes from the complement system (C3b, C3bi, CR3) were up-regulated by B. burgdorferi infection and Leishmaniasis (Figure 3E). The complement system supplements the activities of antibodies and aforementioned phagocytosis to remove pathogenic particles and cells.

Figure 3. Biological pathways altered by B. burgdorferi infection in heart tissue. Pathway diagrams were generated by Pathview (Luo, & Brouwer 2013). (C) Response to S. aureus infection (mmu05150).

Figure 3. Biological pathways altered by B. burgdorferi infection in heart tissue. Pathway diagrams were generated by Pathview (Luo, & Brouwer 2013). (C) Response to S. aureus infection (mmu05150).

 

Figure 3. Biological pathways altered by B. burgdorferi infection in heart tissue. Pathway diagrams were generated by Pathview (Luo, & Brouwer 2013). (D) Osteoclast differentiation (mmu04380).

Figure 3. Biological pathways altered by B. burgdorferi infection in heart tissue. Pathway diagrams were generated by Pathview (Luo, & Brouwer 2013). (D) Osteoclast differentiation (mmu04380).

 

Figure 3. Biological pathways altered by B. burgdorferi infection in heart tissue. Pathway diagrams were generated by Pathview (Luo, & Brouwer 2013). (E) Response to Leishmanias infection (mmu05140).

Figure 3. Biological pathways altered by B. burgdorferi infection in heart tissue. Pathway diagrams were generated by Pathview (Luo, & Brouwer 2013). (E) Response to Leishmanias infection (mmu05140).

Calcium Signaling in Response to B. burgdorferi Infection in Brain Tissue

When compared with heart tissue, only three pathways in brain tissue were identified by SPIA and WebGestalt: calcium signaling, genes involved in gap junction, and melanogenesis (Table 1). Two G-Protein Coupled Receptors (GPCRs) implicated in calcium signaling, glutamate metabotropic receptor 5 (Grm5) and adenosine A2a receptor (Adora2a) showed differential expression (Figure 4A). Upregulation of Grm5 triggered a higher expression of a downstream factor PLCβ (phospholipase C beta) in the pathway. In contrast, Adora2a was down-regulated compared to heart tissue.
The second neurological pathway perturbed by B. burgdorferi infection was the gap junction (Figure 4B). The gap junction serves intercellular exchange of ions or small molecules between neighboring cells’ cytosolic compartments. Inflammatory response attributed to infection is often associated with the loss of such an exchange channel (Eugenin et al., 2012). Five genes in this pathway were perturbed, with subpathways both up- and down-regulated (Figure 4B). To our knowledge, no literature suggests an association between melanogenesis and bacterial infection. Two genes from this pathway, adenylate cyclase 4 (Adcy4) and phospholipase C beta 1 (Plcb1; Figures 4A-C), also participate in calcium signaling and gap junction pathways discussed above.

Figure 4. Biological pathways altered by B. burgdorferi infection in brain tissue. (A) Calcium signaling pathway (mmu04020).

Figure 4. Biological pathways altered by B. burgdorferi infection in brain tissue. (A) Calcium signaling pathway (mmu04020).

 

Figure 4. Biological pathways altered by B. burgdorferi infection in brain tissue. (A) Calcium signaling pathway (mmu04020). (B) Gap junction (mmu04540). Circled are Adcy4 and Plcb1 genes, discussed in text.

Figure 4. Biological pathways altered by B. burgdorferi infection in brain tissue. (B) Gap junction (mmu04540). Circled are Adcy4 and Plcb1 genes, discussed in text.

 

Figure 4. Biological pathways altered by B. burgdorferi infection in brain tissue. (C) Melanogenesis (mmu04916). Circled are Adcy4 and Plcb1 genes, discussed in text.

Figure 4. Biological pathways altered by B. burgdorferi infection in brain tissue. (C) Melanogenesis (mmu04916). Circled are Adcy4 and Plcb1 genes, discussed in text.

Discussion

Differentially Expressed Genes Identification

We built a dual, redundant pipeline to identify DEGs associated with B. burgdorferi infection in heart and brain tissue, in which each dataset analyzed by two principally distinct methods (cufflinks and DESeq2) and interpreted with multiple enrichment approaches. We found hundreds of genes to be differentially expressed via the two methods in each tissue.
The set of DEGs identified in heart tissue by our two methods (Cufflinks and DESeq2) overlapped meagerly. This could be partly attributed to the difference of bowtie2 and htseq-count in mapping of non-unique short reads to genes/genome. Bowtie2 considers short reads to be mappable if the number of mismatches against genome falls below a specified threshold. This permits the possibility of double-counting non-unique reads in multiple genomic locations. Besides mismatch factor, htseq-count only counts short reads that can be mapped to a single location in the genome. Thus, fewer reads are mapped by htseq-count than bowtie2, and this difference in mapping strategy likely contributed to the difference in DEGs being identified. Intriguingly, regardless of which differentially expressed gene calling methods we used, results from WebGestalt and DAVID coherently point to the activation of immune system despite the meagerly overlapping of the two DEG lists.

Immune Response to Borrelia Infection in Heart Tissue

In heart tissue, chemokine signaling, Fc gamma R-mediated phagocytosis, osteoclast differentiation, and both S. aureus and Leishmania infection-response are associated with B. burgdorferi infection. Chemokine signaling and phagocytosis events are to be expected, as B. burgdorferi actively infects heart tissue during early stages of the disease (Armstrong et al., 1992). Our results indicated that B. burgdorferi infection activated Arrb1, which is known to stimulate a broad innate and adaptive inflammatory responses (Jiang et al., 2013). Little is known about the difference in pathogenicity between S. aureus, Leishmania, and Borrelia; however, it is not surprising to see similar genes and biological pathways are mobilized to defend the host against pathogens as many innate (early) immune responses are non-specific. Osteoclast differentiation was likely perturbed because S. aureus infects osteoblasts (osteomyelitis) (Rasigade et al., 2013; Webb et al., 2007) and associates with osteoblast differentiation pathways (Figure 3D). Although Borrelia does not infect osteoclasts, the similarities in infection response may produce this observation. The shared pathways predicted by the two distinct pathway methods unequivocally indicate upregulation of phagocytosis and pathways associated with response to infection in heart tissue. The altered gene expression indicates activation of white blood cells, induction of the complement system, and cellular targeting for immune destruction of tissue cells through alterations in receptor proteins. We observed these immunological reactions in heart only, suggesting tissue-specific targeting of B. burgdorferi primarily in the heart. However, the number of DEGs (>100) may be too extensive to draw any actionable therapeutic conclusions at this stage. Further investigation is needed to elucidate essential symptomatic genes.

Blood-Brain Barrier Disruption in Response to Borrelia Infection in Brain Tissue

Only three consensus pathways were perturbed in the brain tissue by our dual-method pipeline. Moreover, these pathways had fewer differentially expressed genes compared to the heart tissue results (Table 1). This is expected: because B. burgdorferi does not actively infect murine brain tissue (Radolf et al., 2012), a less cohesive response occurs upon host infection as a variety of cell types are responding to inflammation, not generating an inflammatory response. We observed perturbations in calcium signaling, gap junction, and melanogenesis. Calcium signaling has been shown to influence bacterial infection (Soderblom et al., 2005; TranVan Nhieu et al., 2004). We propose that this phenomenon is exploited by B. burgdorferi to cross the blood-brain barrier (Coureuil et al., 2013; Grab et al. 2005; Halperin, 2015), even if these bacteria fail to establish infection (Radolf et al., 2012) once across the barrier. This perturbation of the blood-brain barrier could be used to study human neuroborreliosis. Previous studies indicate that neurological symptoms exhibited by Borrelia infection in humans may be attributed to the success of Borrelia in crossing the blood-brain barrier and attacking the CNS (Grab et al., 2009). Our results are consistent with these findings, suggesting that the bacterium may also disrupt the blood-brain barrier in mice by dysregulated calcium signaling and gap junctions. This suggests the potential of targeting bacterial crossing of blood-brain barrier for therapeutic use.
The GPCR Grm5 and a downstream factor PLCβ in the calcium signaling pathway show elevation of transcriptional activities in response to infection. Infection of the bacterium Neisseria meningitidis (meningococci) has also been shown to activate calcium signaling (Asmat et al., 2014). It was found that elevation of cytoplasmic calcium concentration elevated in N. meningitides-infected cells is for the adherence of the bacteria to the cells. The activity of PLCβ facilitates the adherence of N. meningitidis through the upregulation of cytoplasmic calcium concentration. This result suggests that B. burgdorferi infection may also harness similar regulatory mechanism used by N. meningitides in elevating cytoplasmic calcium concentration in order to achieve high adherence to blood vessels, facilitating the crossing of the blood-brain barrier for subsequent CNS infection.
Additionally, the activation of Adora2a reveals the dampening of immune response. Adora2a has been shown to be involved in the infection of Plasmodium falciparum, a common pathogen of malaria (Auburn et al., 2010; Gupta et al., 2015). The ligand adenosine activates the Adora2a receptor, which in turn triggers other downstream processes. To prevent cells from over-stimulation, a negative feedback mechanism is launched to impede further excitation by mediating the dissociation of a subunit from Adora2a (Auburn et al., 2010; Metaye et al., 2005). This down-regulation of Adora2a may be to shield the cells from over-excitation. This indicates Adora2a expression could be a biomarker of infection and that anti-inflammatory drugs may exacerbate Lyme treatment.
We also found perturbations in the expression of genes involved in gap junctions. Inflammatory responses due to infection often associate with increased expression of ion channels like gap junctions to facilitate cellular communication (Eugenin et al., 2012). Moreover, studies have shown that gap function regulation plays a role in triggering cell death in virus-infected cells in the CNS (Eugenin et al. 2012). Our results reveal that some neurological responses caused by B. Burgdorferi, including the role of gap junctions,  are similar to bacterial and viral infections.
We found differential expression of genes involved in melanogenesis. There is no evidence suggesting melanogenesis and bacterial infection are linked. However, two genes from this pathway, Adcy4 and Plcb1, are also involved with calcium signaling and gap junction pathways. We propose that melanogenesis was highlighted by the two signaling pathway discovery methods because of this overlap.
Enzymes involved in cAMP synthesis, like Adcy4, were perturbed; this likely affects cellular signaling. (Tanaka et al., 2013) conducted a transcriptome analysis of murine brain tissue infected with Toxoplasma gondii, an intracellular pathogenic protozoan. The parasite causes systemic infection and persists in the brain and muscle tissue. They found over 30 genes to be significantly upregulated, including Cxcl9, H2-Eb1, Ccl8, H2-Aa, Zbp1 and Igtp. We observed these genes to be also upregulated in Lyme heart infection. However, no genes were found in both the T. gondii study and on our list of DEGs in the brain. This suggests more work needs to be done to understand the molecular basis of neuroborreliosis.
In conclusion, we present a dual-method pipeline to analyze the host transcriptome Borrelia infection using RNA-seq. Many immune response-related genes were differentially expressed in heart tissue and far fewer were identified in the brain. We propose that Borrelia may disrupt the blood-brain barrier in mice and induces a peripheral inflammatory cascade.
First, although infection was not established in the brain, the tissue is affected as many genes are differentially expressed and we found that neuronal gap junctions and calcium signaling are disrupted. This is a hallmark of loss of integrity of the blood-brain barrier. Thus, the damage is occurring irrespective of direct brain infection. Moreover, this suggests that in human infection, the crossing of the blood-brain barrier and infection of the central nervous system are two events. It may be possible to study Borrelia’s effect on the blood-brain barrier in mice, even though the central nervous system is not infected in a mouse model of the disease.
Second, none of the predicted cytokine genes were significantly differentially expressed in this experiment even though the chemokine pathway was perturbed by Borrelia infection. This indicates that these cytokines are induced by the peripheral immune response. However, cytokine-cytokine receptor interaction via Gm2023 (Figure 3A) and receptor CD45 were over-expressed in the infected heart tissue (Figure 3B), allowing phagocyte recruitment to destroy infected cells. Thus, the heart tissue is responding to inflammation but is not producing these cytokines. These results not only elucidate the transcriptional basis of self-perpetuating cascade alluded to immunological responses found in Borrelia infection but also affirm the utility of the dual-method approach proposed in our study.
Challenges facing diagnosis and treatment of Lyme are significant. Prolonged symptoms after antibiotic treatment are still afflicting a small percentage of patients, making the topic of “chronic Lyme disease” interesting but understudied. Although the mouse is not a perfect model of human Lyme disease, we show that the mouse can be used to examine unique features of Borrelia infection and the crossing of the blood-brain barrier. A thorough molecular study to explore these pathways over time is needed to elucidate the etiology of lingering Lyme symptoms in the host in order to improve patient outcome.

Acknowledgments

We thank the financial support of Lafayette College for MC and EH. Thanks to Drs. Laurie Caslake, Elaine Reynolds, and Robert Kurt for lab facilities, assistance in the infection process, and discussion. Lastly, thank you to Kimberly Olsen of the Baumgarth lab at the University of California, Davis, for providing the Borrelia samples.

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Development of a Methodology to Determine Antibiotic Concentrations in Water Samples Using High-Pressure Liquid Chromatography

doi:10.22186/jyi.33.1.19-27

Abstract | Introduction | Methods | Results | Discussion | Conclusions |Acknowledgements | 
References | PDF

Abstract

Antibiotic concentrations are typically measured using solid-phase extraction along with liquid chromatography, but this process is not practical due to a large number of man hours involved. The use of a lyophilizer with high-pressure liquid chromatography (HPLC) is an accurate and cost-effective method of analyzing antibiotics in water samples. An initial antibiotic analysis methodology was developed with the goal of concentrating antibiotics in water samples for greater detection; however, it was observed that the methodology required additional refinement to improve accuracy, particularly when manure was present in the water samples. Based on prior tetracycline antibiotic research, we hypothesized that sample preparation techniques and HLPC characteristics would influence our ability to detect these antibiotics in water samples. We anticipated that analysis of larger sample volumes would improve antibiotic detection while higher manure concentrations would decrease detection capabilities. The objective of this study was to examine the effects of a secondary sample preparation step (filtration), mobile phase solution, HPLC column, sample volumes, wavelengths, and manure concentrations on the recovery rates of three common antibiotics, specifically chlortetracycline (CTC), tetracycline (TC), and oxytetracycline (OTC). The study examined three filtration methods, two mobile phase solutions, two HPLC columns, five sample volumes, three wavelengths, and four manure concentrations. Best results were obtained with a mobile phase solution of acetonitrile with 0.05% formic acid, the Acclaim® RSLC C18 PA2 column, smaller sample volumes, and a wavelength of 356nm. This study highlighted some of the challenges associated with detecting antibiotics in water samples. The accurate detection of antibiotics in water samples is an important step in developing and testing methods to reduce antibiotic transport in the environment.

Introduction

The U.S. Environmental Protection Agency (USEPA) classifies antibiotics as a contaminant of emerging concern (CEC) because they are detected in the environment at higher than expected levels and may negatively impact human and aquatic ecosystems (USEPA, 2013). The risk these antibiotics pose to humans and aquatic life is not known; however, the primary concern is that the antibiotic-resistant strains of bacteria will develop. Utilization in human healthcare and livestock care are the two main sources of antibiotics in the environment. Unlike human waste, which is treated via treatment plants or septic systems, livestock waste is oftentimes directly applied to the land as part of a nutrient management plan (NRCS, 2012). Baguer, Jensen, and Krogh (2000) noted that land application of manure is the main pathway for veterinary antibiotic introduction into the terrestrial and aquatic environments. In agriculture, antibiotics are used for both therapeutic as well as non-therapeutic purposes. The two main non-therapeutic uses of antibiotics in livestock are growth additives and illness prevention (Shore, & Pruden, 2009). Estimates are that 11 million kg of antibiotics were used in 2002 along for non-therapeutic uses (Davis et al., 2006). Unfortunately, large amounts of administered antibiotics are not metabolized by animals but instead are excreted in manure. Rates of unmetabolized antibiotics are as high 70-90% as in the case of tetracyclines, which are one of the most used classes of antibiotics (Kumar Gupta, Chander, & Singh, 2005; USEPA, 2013).
Manures are commonly applied across croplands as part of farm nutrient management plans. Hence, the antibiotics in these manures are land applied as well. Once applied to the land, antibiotics are transported to surface waters, via runoff, or ground waters, through infiltration. To date, only a limited amount of research has been conducted on the transport of antibiotics in the runoff, but this research indicates that the mechanisms of transport vary with antibiotic type. Some antibiotics bind to and are transported with soil, while others do not (Tolls, 2001). Limited studies have examined the use of best management practices (BMPs), such as vegetated filter strips, and the addition of alum to minimize antibiotic transport (Enlow, 2014; DeLaune, & Moore, 2013; Lin et al., 2011).
One challenge, in studies involving antibiotics, is the sensitivity and reliability of the methods used to detect the antibiotics. Another is the time required, and hence labor costs, associated with performing antibiotic analyses. Because antibiotic concentrations are so low, they require concentration before extraction. Typically, solid-phase extraction is used along with liquid chromatography. However, when a study requires analyzing many samples, solid-phase extraction is impractical due to the high amount of human labor involved. To address this issue, Enlow (2014) developed a methodology using a lyophilizer for use in the analysis of the antibiotic oxytetracycline. The lyophilizer was used to concentrate antibiotics in water samples with the goal of improving antibiotic detection. Results indicated the methodology worked well at high oxytetracycline concentrations but performed somewhat poorly at low levels in the presence of manure. The poorer performance was due to the presence of one or more unknown constituents which appeared on the chromatograph near the peak of chlortetracycline. Enlow (2014) hypothesized that a secondary filtration step, larger sample volumes, and different wavelengths on the HPLC would improve antibiotic recovery rates. These assumptions were made based on the presence of visible solids in samples following one filtration, which was thought to interfere with antibiotic detection, total suspended solids methodology, which uses larger sample volumes to improve accuracy in the presence of low concentrations (Eaton et al., 1998), and a subsequent literature review which identified the use of a range of wavelengths to measure tetracycline antibiotics (personal communication). Wavelengths are significant to the determination of the substance in a sample because different compounds absorb different wavelengths of UV light (Kay, Blackwell, & Boxall, 2005). Questions regarding the effects of different manure concentrations, in water samples, on antibiotic recovery rates remained, as did the effects of different mobile phase solutions and HPLC columns.
Based on prior tetracycline antibiotic research, we hypothesized that sample preparation techniques, namely an additional filtration step to remove remaining particulates that can interfere with HPLC performance (CDER, 1994), and HLPC characteristics, such as mobile phase solution (Jia, Xiao, Hu, Asami, & Kunikane, 2009), column type (Ritorto et al., 2014) and wavelength (Ng, & Linder, 2003), would influence antibiotic detection in water samples. We anticipated that analysis of larger sample volumes would improve antibiotic detection, as we would have a more material from which to develop a concentrate, while higher manure concentrations would decrease detection capabilities due to the presence of more impurities requiring removal to not inhibit HPLC performance. This study aimed to examine the effects of a secondary sample preparation step (filtration), mobile phase solution (mobile phases), HPLC column, sample volumes, wavelengths, manure concentrations on the recovery rates of three common antibiotics, specifically chlortetracycline (CTC), tetracycline (TC), and oxytetracycline (OTC). The laboratory analyses were first conducted and refined on manure-free samples prior to examining samples with manure.

Materials and Methods

Antibiotics

Three commonly used antibiotics were examined: CTC, TC, and OTC. Antibiotics (chlortetracycline hydrochloride ≥ 75% HPLC; tetracycline hydrochloride ≥ 95% European Pharmacopeia HPLC assay; oxytetracycline hydrochloride ≥ 95% (HPLC) crystalline) were obtained from Sigma-Aldrich (St. Louis, Mo.). These antibiotics were evaluated at concentrations of 1, 10, 20, 100 and 200 μg/mL. Additionally, an equal combination of the three antibiotics (COMBO) was examined at final concentrations of 1, 10, 20, 100 and 200μg/mL (individual antibiotic concentrations of 0.33, 3.33, 6.67, 33.3, 66.7μL/mL, respectively, were used to create COMBO).

Secondary Sample Preparation Step (Filtration)

Three sample preparation methods were examined: solid-phase extraction (SPE), lyophilization (LYO), and a combination of the SPE and lyophilization (BOTH). Prior to SPE, samples were centrifuged for 10 minutes at 1500RPM using a Thermo Scientific Sorvall Legend XTR Centrifuge. Three replications of all antibiotics (CTC, TC, OTC, and COMBO) at all five concentrations were used to examine the three filtration methods. One replication was used per filtration method.
In SPE, the sample is manually pulled through a SPE cartridge; it is the SPE cartridge that retains the antibiotics. First, SPE cartridges are preconditioned prior to use with 1mL of Methanol(MeOH) followed by 4mL of deionized water. Samples are then manually loaded into the SPE cartridges using a 10mL syringe at 2mL/min, a rate which is quite slow especially for large sample volumes. Next, the SPE cartridge is washed with 0.05% MeOH in deionized water. This step is important when analyzing samples containing particulates as they can inhibit sample movement through the cartridges. Finally, the sample is eluted from the SPE cartridge using 2mL MeOH. To conduct the SPE, 60 mg bed weight, 3 mL column volume Thermo Scientific Hypersep Retain PEP was used.
LYO, or freeze drying, instead removes the liquid from a sample to concentrate any remaining constituents. LYO is especially beneficial for large sample volumes as it can greatly reduce their size without impacting constituents in the sample. For the LYO, SP Scientific VirTis Wizard 2.0 lyophilizer (Gardiner, New York) was used.
For the LYO and BOTH filtration methods, two replications were frozen at a temperature of -44°C until the sample was completely solid and then placed in the lyophilizer until all liquid was removed (approximately six days). For the LYO filtration method, samples were rehydrated with 2mL of methanol (MeOH) and then analyzed on the A Dionex Ultimate 3000 HPLC along with an Ultimate 3000RS Variable Wavelength detector (Sunnyvale, California) (0.05% formic acid in acetonitrile mobile phase solution; RSLC PAC column; wavelengths of 230, 290 and 356nm). For the BOTH filtration method, samples were rehydrated with 5mL of deionized water and analyzed via SPE following standard procedures (Sigma-Aldrich, 1998).

Mobile Phase Solution

Mobile phase solutions are used with HPLC methodologies to dissolve and transport constituents, improve constituent separation, and maintain pH as to improve accuracy and precision (Shimadzu, n.d.). Two mobile phase solutions were examined: 0.05% acetic acid solution in methanol (MeOH) and 0.05% formic acid (C2H4O2) in acetonitrile (C2H3N). These weakly acidic solutions were chosen for their compatibility with antibiotics extraction from the solid phase to liquid phase (Kim and Carlson, 2007; Suárez, Santos, Simonet, Cárdenas, & Valcárcel, 2007) and from their prior use in other research focused on HPLC use to evaluate antibiotics (Hernádez, Sancho, Ibáñez, & Guerrero, 2007; Lindberg, Jarnheimer, Olson, Johansson, & Tysklind, 2005; Yang, Cha, & Carlson, 2005). Manure free water samples were spiked with one of three types of antibiotics (CTC, TC, and OTC) to final concentrations of 10, 50, 100, and 1000μg/mL to see how the mobile phase solutions worked with a range of concentrations. Spiked water samples were used to ensure distinctly visible antibiotic peaks on the chromatogram. When examining the influence of mobile phase solution type on antibiotic recovery rates, only the RSLC column was used; however, all three wavelengths examined in this study (section 2.6) were examined.

HPLC Column

In the HPLC process, the solution passes through a column composed of unique material. The interaction between sample constituents and column material allows for the separation of the constituents as their pass-through rate varies. A Dionex Ultimate 3000 HLPC (Sunnyvale, CA) and an Ultimate 3000RS Variable Wavelength Detector (Sunnyvale, CA) were used. Two HPLC columns were examined: Acclaim® Rapid Liquid Separation Liquid Chromatography (RSLC) C18 Polar Advantage II (PA2) (polar-embedded reversed-phase, 3µm particle size, 2.1mm diameter, 150mm length, 120Å average pore diameter) and Acclaim® 120 C18 (conventional reversed-phase, 3µm particle size, 2.1mm diameter, 100mm length, 120Å average pore diameter). The Acclaim® 120 C18 was chosen because of its use in other studies involving tetracycline antibiotics (Enlow, 2014; Haghedooren et al., 2008; Yang et al., 2004; Tong, Wang, & Zhu, 2009). The Acclaim® RSLC C18 PA2 is a newer column type, so its uses in antibiotic studies is less documented (Bean et al., 2016). As with the mobile phase solution, manure free water samples were spiked with one of three types of antibiotics (CTC, TC, and OTC) to concentrations of 10, 50, 100, and 1000μg/mL.

Sample Volume

Five sample volumes were examined: 100, 200, 300, 400 and 500mL. Each sample volume was spiked to create a final OTC concentration of 20µg/mL. This concentration was chosen based on work done in Enlow (2014). Due to budget and time constraints, multiple antibiotics at multiple concentrations were not examined. All samples were frozen for at -80°C and then placed in the lyophilizer for two weeks. Samples were then reconstituted with 2mL of MeOH and analyzed on the HPLC at 356nm using a mobile phase of 0.05% formic acid in acetonitrile and a RSLC PAC column.

Wavelength

Three wavelengths (230, 290 and 356nm) were examined using water samples with containing 0.01, 0.05, 0.15, and 0.25g/mL swine manure that had been spiked with antibiotics (Table 1). Briefly, antibiotic-free swine manure was collected from a nearby small heritage hog farm and transported to the Biosystems and Agricultural Engineering Department at the University of Kentucky and stored at 0°C until analysis. Once thawed, antibiotics (CTC, TC, OTC, and COMBO) were added to subsamples at concentrations of 10 and 20µg/mL. For the COMBO samples, equal parts CTC, TC, and OTC were added to the manure to arrive at final antibiotic concentrations of 10 and 20µg/mL. All water samples (20mL deionized water; n=96) were created in triplicate to evaluate the three methods of filtration (SPE, LYO, and BOTH). The small sample volume (20mL) allowed for more rapid analysis as it decreased the time required for the filtration process.

Table 1. Manure concentrations for tested water samples.

Table 1. Manure concentrations for tested water samples.

Manure Concentration

The effect of manure concentration (0.01, 0.05, 0.15, and 0.25g/mL) on antibiotic recovery rate was examined. Wet manure was weighed and then placed in 20mL of deionized water and vigorously mixed. An initial antibiotic concentration of 20µg/mL, LYO filtration, Acclaim® RSLC C18 PA2 column, and a wavelength of 356nm, were used. A secondary filtration step was not used.

Statistical Analysis

An Analysis of Covariance (ANCOVA) was used to compare the parameters wavelength, antibiotic type, antibiotic concentration, and manure concentration to antibiotic recovery rates (%) in SAS (p > .05). Both wavelength and antibiotic type served as class (categorical) variables.

Results

Secondary Sample Preparation Step (Filtration)

As the antibiotic analysis methodology was first developed on samples without manure, the effects of a secondary sample preparation step (filtration) were not examined until later in the experiment due to funding limitations. The time required to filter the samples was substantial. Filtering one 100mL sample required nearly one hour. Preliminary results from this study indicated that samples containing large amounts of manure (e.g. > 5% by volume) will likely require a third filtration step to remove solids before lyophilization. Without this step, a lot of solids remains after lyophilization. Ideally, after lyophilization, the only desired remnants are the antibiotics, which can be easily saturated with a mobile phase solution and tested directly in the HPLC.

Mobile Phase Solution

When 0.05% acetic acid in MeOH was used as a mobile phase solution, the peaks for TC and OTC overlapped while the peak for CTC was distinct (Figure 1). Using 0.05% formic acid in acetonitrile as the mobile phase solution improved peak separation between the OTC and TC while maintaining the clear distinction in CTC. Thus, 0.05% formic acid in acetonitrile was used as a mobile phase solution in the remainder of the experiments.

Screen Shot 2017-05-31 at 12.05.46 AM

Figure 1. (A) The peaks for oxytetracycline (OTC) and tetracycline (TC) overlap when a MeOH with 0.05% acetic acid mobile phase solution is used. (B). Using a mobile phase solution of acetonitrile with 0.05% formic acid, the peaks between TC and OTC are distinct.

HPLC Column

Peak separation amongst the antibiotics was better using the Acclaim® RSLC C18 PA2 column as compared to the Acclaim® 120 C18 column. Figure 2a shows the clear and symmetric peaks associated with Acclaim® RSLC C18 PA2 column while Figure 2b shows that the peaks associated with the Acclaim® 120 column are less distinct.

Figure 2. (A) Clear, symmetric peaks of tetracycline (TC) and chlortetracycline (CTC) were seen with the Acclaim® RSLC C18 PA2 column. (B) The Acclaim® 120 C18 column produced slightly less distinct and symmetric peaks.

Figure 2. (A) Clear, symmetric peaks of tetracycline (TC) and chlortetracycline (CTC) were seen with the Acclaim® RSLC C18 PA2 column. (B) The Acclaim® 120 C18 column produced slightly less distinct and symmetric peaks.

Sample Volume

Smaller sample volumes are more efficient to analyze due to lesser times required for filtration. With LYO, for example, large sample volumes can require multiple weeks to dry. Oxytetracycline was evaluated at a concentration of 20µg/mL in clean, deionized water. Samples were run on the Acclaim® RSLC C18 PA2 column and with a mobile phase solution of 0.05% formic acid in acetonitrile. Sample volume had no significant effect on antibiotic recovery rates (α = .05) (Table 2).

Table 2. Antibiotic recovery (%) associated with sample size.

Table 2. Antibiotic recovery (%) associated with sample size.

Wavelength

Results indicated that the most distinct peaks on the chromatograms occurred using a wavelength of 356nm. Figure 3 shows a sample with a 20µg/mL of COMBO and 1mg/L manure at the wavelengths 230, 290, and 356nm. The baseline of Figure 3c is close to zero, and the peaks for OTC and TC are clear and defined at 356nm, which cannot be said of the other two wavelengths.

Figure 3. Chromatographs showing peaks for oxytetracycline (OTC), tetracycline (TC), and chlortetracycline (CTC) at different wavelengths. (A) 230 nm, (B) 290 nm, and (C) 356 nm.

Figure 3. Chromatographs showing peaks for oxytetracycline (OTC), tetracycline (TC), and chlortetracycline (CTC) at different wavelengths. (A) 230 nm, (B) 290 nm, and (C) 356 nm.

Manure Concentration

The recovery rates for TC and CTC were quite low across all lev
els of manure concentration, averaging 0.5% for TC and 1.5% for CTC. As the concentration of manure increased, the recovery rates of OTC decreased, as seen in Figure 4. The decreasing trend does not appear in CTC. This impurity was seen in the control (manure, no antibiotics) and in OTC and TC only (manure) samples (Figure 5). The presence of this impurity makes determining the amount of CTC in a sample challenging.

Figure 4. Antibiotic recovery rates (y-axis) decreased for oxytetracycline (OTC) as the concentration of manure (x-axis) increased. No significant trends were noted for tetracycline (TC) or chlortetracycline (CTC).

Figure 4. Antibiotic recovery rates (y-axis) decreased for oxytetracycline (OTC) as the concentration of manure (x-axis) increased. No significant trends were noted for tetracycline (TC) or chlortetracycline (CTC).

 

Figure 5. (A) This chromatogram shows the control, which contained manure and deionized water. (B) The impurity in the control peaks at the same time as chlortetracycline (CTC), making it difficult to discern the CTC in the CTC spiked sample.

Figure 5. (A) This chromatogram shows the control, which contained manure and deionized water. (B) The impurity in the control peaks at the same time as chlortetracycline (CTC), making it difficult to discern the CTC in the CTC spiked sample.

Discussion

Measurement of antibiotics in water samples containing manure, using the HPLC, was best accomplished by the following methodology.

.  Mobile phase solution of acetonitrile (C2H3N) with 0.05% formic acid (C2H4O2) (best separation between OTC and TC),

.  Acclaim® RSLC C18 PA2 column,

.  Smaller sample volumes (more time-efficient, especially for lyophilization), and

.  Wavelength of 356nm.

.  While we hypothesized that the factors mobile phase solution, HPLC column, sample volume, and wavelength would influence the measurement of antibiotics in   water samples, we did not know which treatment would yield the best results for OTC, TC, and CTC.

Mobile Phase Solution

Using a mobile phase solution comprised of 0.05% formic acid in acetonitrile produced the best separation between OTC, TC, and CTC. These results agreed with other studies that found that the ability to detect antibiotics increased when using formic acid. Jia et al. (2009) examined the effect of formic acid on HPLC sensitivity in antibiotic detection and found that formic acid increased signal intensities for OTC and CTC but not TC. Suárez et al. (2007) recommended using a volatile acid mobile phase solution for detecting tectracyline compounds. The researchers examined a 1:1 (v:v) methanol to water mixture, with different percentages of formic acid (from 0.2% to 2%) as a sheath liquid and found formic acid at 0.5% yielded the best results in terms of mass spectrometry signal intensity. Improved antibiotic identification using acetonitrile may be linked to methanol’s role in TC degradation. Liang, Denton, and Bates (1998) found that the degradation of TC is increased in methanol solutions via functional group substitutions or additions on TC. The results of this study agreed with findings from these prior studies.

HPLC Column

Of the two HPLC columns examined, separation of OTC, TC, and CTC was best when using the Acclaim® RSLC C18 PA2 column.
Similar results were found by Ritorto et al. (2014) who compared the performance of the Acclaim® 120 C18 and the Acclaim® RSLC C18 PA2 to separate tryptic digested proteins from cell lysate. The researchers found that the Acclaim® RSLC C18 PA2 had higher efficiencies and exhibited higher polarity of selectivity. Unlike the Acclaim® 120 C18, the Acclaim® RSLC C18 PA2 is compatible with 100% aqueous environments and has a wider pH range (1.5-10.0) (Thermo Fisher Scientific Inc., 2016). HPLC columns are stable over a specific pH range. The presence of manure can influence pH levels in streams, though such waters are likely to have a pH range between 4 and 8 (Harden, 2015). Haghedooren et al. (2008) examined the performance of 65 reversed-phase liquid chromatographic (RP-LC) C18 columns, including the Acclaim 120 C18 but not the Acclaim® RSLC C18 PA2, to separate antibiotics, one of which was TC, from impurities. The Acclaim 120 C18 was a lower performing column for separation of TC.

Wavelength

Acquiring the most distinct peaks at 356nm agreed with results from other studies. Ng and Linder (2003) reported minimal differences in maximum peak absorption between TC, OTC, and CTC, with wavelengths of 369, 358, and 374nm, respectively. Liang et al. (1998) found peak absorbance of TC standards mixture at 269nm and peak absorbance of the degraded TC sample (e.g. OTC, CTC, and other such components) at 303 and 338nm. Kay et al. (2005) used a wavelength of 355nm for OTC. The agreement of our findings with these studies is viewed as positive. Our methodology, with respect to the other factors examined, differed from these studies. Our results confirmed that a wavelength of 356nm is appropriate for tetracycline antibiotic detection.

Manure Concentrations

The actual amount of manure in the sample impacted antibiotic recovery rates. Higher manure concentrations yielded significantly lower antibiotic recovery rates for OTC (Figure 4). The reason for this relationship is not known but possibly related to affinity for OTC to bind to manure (Loke, Tjørnelund, & Halling-Sørensen, 2002). The addition of larger amounts of manure to the water samples would mean more potential for OTC-manure binding. Manure concentrations did not have a significant effect on TC and CTC recovery rates. The low levels of recovery of antibiotics from these manure-laced samples are concerning and indicate the methodology requires further refinement. We hypothesize that an impurity, possibly chloride, in swine manure is appearing at the same time as the CTC in the chromatograph, and thus is influencing this result.

Secondary Sample Preparation Step (Filtration)

Additional work is needed to evaluate the benefits of a secondary filtration step on antibiotic recovery rates. If these constraints were not present, additional sample analyses would improve our ability to draw more definitive conclusions regarding the effect of a secondary filtration on antibiotic recovery rates. We could conclude that the method of secondary filtration chosen must consider the time allotted for the study. While lyophilization takes several days, it is a process that can be left unattended. In contrast, SPE can be done immediately; however, the process of pulling a sample through the cartridges at 2mL/min is very time-consuming. For example, a 100mL sample required 50 minutes to filter while a 500mL sample required over 4 hours. We noted that a third filtration step may be needed when analyzing samples with high manure concentrations (e.g. > 5% by volume). However, a balance is needed between removing sufficient amounts of impurities to maximize HPLC performance and removing antibiotics. With each filtration, the potential exists to remove significant amounts of antibiotics from the sample.

Acknowledgements

The authors would like to thank the University of Kentucky’s Office of Sustainability for funding the project, Brent Howard and Hoods Heritage Hogs for donating the antibiotic-free swine manure used in this study, and the entire Biosystems and Agricultural Engineering Department for their understanding when an odorous bucket of swine manure exploded in the laboratory.

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