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bioRxiv2018

PBiochemical and physiological investigations on adenosine 5’ monophosphate deaminase from Plasmodium spp

AbbreviationsHGXPRT - Hypoxanthine-guanine-xanthine phosphoribosyltransferase, ADSS - Adenylosuccinate synthetase, ASL - Adenylosuccinate lyase, GMPS - Guonosine monophosphate synthetase, IMPDH - Inosine monophosphate dehydrogenase, ISN1 - Inosine monophosphate specific nucleotidase, PNP - Purine nucleoside phosphorylase\n\nSummaryInterplay between ATP generating and utilizing pathways in a cell is responsible for maintaining cellular ATP/energy homeostasis that is reflected by Adenylate Energy Charge (AEC) ratio. Adenylate kinase (AK), that catalyzes inter-conversion of ADP, ATP and AMP, plays a major role in maintaining AEC, and is regulated by cellular AMP levels. Hence, the enzymes AMP deaminase (AMPD) and nucleotidases, which catabolize AMP, indirectly regulate AK activity and in-turn affect AEC. Here, we present the first report on AMPD from Plasmodium, the causative agent of malaria. The recombinant enzyme expressed in Saccharomyces cerevisiae was studied using functional complementation assay and residues vital for enzyme activity have been identified. Similarities and differences between Plasmodium falciparum AMPD (PfAMPD) and its homologs from yeast, Arabidopsis and humans are also discussed. The AMPD gene was deleted in the murine malaria parasite P. berghei and was found to be non-essential for intra-erythrocytic growth of the knockout parasites. However, when episomal expression was attempted, viable parasites were not obtained, suggesting that perturbing AMP homeostasis by over-expressing AMPD might be lethal. As AMPD is known to be allosterically modulated by ATP, GTP and phosphate, allosteric activators of PfAMPD could be developed as anti-parasitic agents.

biochemistry↗

bioRxiv2026

Predicting Cerebral Pericyte Contractility Across Experimental and Physiological Conditions: an in-silico framework

Pericytes (PCs) have recently emerged as critical regulators of cerebral blood flow (CBF) and represent a promising therapeutic target for various cerebrovascular pathologies. Given the complex array of biochemical and mechanical stimuli these cells integrate, a multiscale modeling framework is essential to quantify the impact of selective interventions on pericyte contractile machinery and blood flow restoration. Here, we introduce a computational framework to evaluate capillary pericyte responses across diverse experimental interventions and conditions (ex vivo and in vivo). To capture pharmacological modulation of the contractile apparatus, we developed a homogeneous intracellular model that incorporates key properties of robust control systems. In this framework, vascular tone generation depends strictly on intracellular calcium concentration (Ca2+), which emerges from a complex electrochemical equilibrium established by transmembrane ion (Na+, K+, Cl-) gradients, luminal mechanical forces, and external ligand concentrations. The resulting fraction of phosphorylated cross-bridges generates contractility, which is integrated into the strain energy function governing the constitutive behavior of the vascular wall. The model was successfully validated across four distinct experimental and pharmacological interventions (including pinacidil, high external K+, U46619, and nimodipine), demonstrating close agreement with observed ex vivo and in vivo vascular responses. By establishing a quantitative bridge between pericyte electrophysiology and microvascular mechanics, this framework provides a valuable foundation for evaluating targeted therapeutic strategies to alleviate tissue ischemia in stroke and vascular dementia.

systems biology↗

bioRxiv2016

A functional analysis of the contribution of climatic niche divergence to adaptive radiation

Elucidating how ecological and evolutionary mechanisms interact to produce and maintain biodiversity is a fundamental problem in evolutionary ecology. We investigate this issue by focusing on how physiological evolution affects performance and species coexistence along the thermal niche axis in replicated radiations of Anolis lizards, groups best known for resource partitioning based on morphological divergence. We find repeated divergence in thermal physiology within these radiations, and that this divergence significantly affects performance within natural thermal environments. Morphologically similar species that co-occur invariably differ in their thermal physiology, providing evidence that physiological divergence facilitates species co-existence within anole communities. Despite repeated divergence in traits of demonstrable ecological importance, phylogenetic comparative analyses indicate that physiological traits have evolved more slowly than key morphological traits related to the structural niche. Phylogenetic analyses also reveal that physiological divergence is correlated with divergence in broad-scale habitat climatic features commonly used to estimate thermal niche evolution, but that the latter incompletely predicts variation in the former. We provide comprehensive evidence for repeated adaptive evolution of physiological divergence within Anolis adaptive radiations, including the complementary roles of physiological and morphological divergence in promoting community-level diversity. We recommend greater integration of performance-based traits into analyses of climatic niche evolution, as they facilitate a more complete understanding of the phenotypic and ecological consequences of climatic divergence.

Evolutionary Biology↗

bioRxiv2018

A Comprehensive Mathematical Model of Surface Electromyography and Force Generation

The purpose of this article is to provide a unified description of a comprehensive mathematical model of surface electromyographic (EMG) measurements and the corresponding force signal in skeletal muscles. The model comprises motor unit pool organization, recruitment and rate coding, intracellular action potential generation and the resulting EMG measurements, as well as the generated muscular force during voluntary isometric contractions. It consolidates and extends the results of several previous publications that proposed mathematical models for the individual model components. A parameterization of the electrical and mechanical components of the model is proposed that ensures a physiologically meaningful EMG-force relation in the simulated signals. Moreover, a novel nonlinear transformation of the excitation model input is proposed, which ensures that the model force output equals the desired target force. Finally, an alternative analytical formulation of the EMG model is proposed, which renders the physiological meaning of the model more clear and facilitates a mathematical proof that muscle fibers in this model at no point in time represent a net current source or sink.\n\nNeuromuscular physiology is a vibrant research field that has recently seen exciting advances. Many previous publications have focused on thorough analyses of particular aspects of neuromuscular physiology, yet an integration of the various novel findings into a single, comprehensive model is missing. A consistent description of a complete physiological model as presented here, including thorough justification of model component choices, will facilitate the use of these advanced models in future research. Results of a numerical simulation highlight the models capability to reproduce many physiological effects observed in experimental measurements, and to produce realistic synthetic data that are useful for the validation of signal processing algorithms. The model is based on recent advances in the understanding of muscular physiology and hence also applicable for analyzing the influence of various physiological and measurement setup parameters on the measured force and EMG signals.

systems biology↗

bioRxiv2018

Verifying, Challenging, and Discovering New Synapses among Fully EM-Reconstructed Neurons in the Leech Ganglion

Neural circuits underpin the production of animal behavior, largely based upon the precise pattern of synaptic connectivity among the neurons involved. For large numbers of neurons, determining such \"connectomes\" by direct physiological means is difficult, as physiological accessibility is ultimately required to verify and characterize the function of synapses. We collected a volume of images spanning an entire ganglion of the juvenile leech nervous system via serial blockface electron microscopy (SBEM). We validated this approach by reconstructing a well-characterized circuit of motor neurons involved in the swimming behavior of the leech by locating the synapses among them. We confirm that there are multiple synaptic contacts between connected pairs of neurons in the leech, and that these synapses are widely distributed across the region of neuropil in which the neurons arbors overlap. We verified the anatomical existence of connections that had been described physiologically among longitudinal muscle motor neurons. We also found that some physiological connections were not present anatomically. We then drew upon the SBEM dataset to design additional physiological experiments. We reconstructed an uncharacterized neuron and one of its presynaptic partners identified from the SBEM dataset. We subsequently interrogated this cell pair via intracellular electrophysiology in an adult ganglion and found that the anatomically-discovered synapse was also functional physiologically. Our findings demonstrate the value of combining a connectomics approach with electrophysiology in the leech nervous system.\n\nSignificance StatementThe function of any nervous system depends on the arrangement of its component neurons into circuits. Determining this precise pattern requires an account of which neurons are linked by synapses, and where. Here we use serial electron microscopy to confirm, challenge, and discover synapses in the neuropil of one ganglion from a juvenile leech. Relying on the homology of the ganglion from animal to animal, we demonstrate that we can identify synapses we knew existed from previous physiological work, and that we can confirm a new anatomically-discovered synapse by subsequently recording from the same neurons in a different animal. Here we show how analyses of anatomical detail and physiologically determined interactions complementarily yield insight into how neural circuits produce behavior.

neuroscience↗

bioRxiv2018

An Escherichia coli nitrogen starvation response is important for mutualistic coexistence with Rhodopseudomonas palustris

Microbial mutualistic cross-feeding interactions are ubiquitous and can drive important community functions. Engaging in cross-feeding undoubtedly affects the physiology and metabolism of individual species involved. However, the nature in which an individuals physiology is influenced by cross-feeding and the importance of those physiological changes for the mutualism have received little attention. We previously developed a genetically tractable coculture to study bacterial mutualisms. The coculture consists of fermentative Escherichia coli and phototrophic Rhodopseudomonas palustris. In this coculture, E. coli anaerobically ferments sugars into excreted organic acids as a carbon source for R. palustris. In return, a genetically-engineered R. palustris constitutively converts N2 into NH4+, providing E. coli with essential nitrogen. Using RNA-seq and proteomics, we identified transcript and protein levels that differ in each partner when grown in coculture versus monoculture. When in coculture with R. palustris, E. coli gene-expression changes resembled a nitrogen starvation response under the control of the transcriptional regulator NtrC. By genetically disrupting E. coli NtrC, we determined that a nitrogen starvation response is important for a stable coexistence, especially at low R. palustris NH4+ excretion levels. Destabilization of the nitrogen starvation regulatory network resulted in variable growth trends and in some cases, extinction. Our results highlight that alternative physiological states can be important for survival within cooperative cross-feeding relationships.\n\nImportanceMutualistic cross-feeding between microbes within multispecies communities is widespread. Studying how mutualistic interactions influence the physiology of each species involved is important for understanding how mutualisms function and persist in both natural and applied settings. Using a bacterial mutualism consisting of Rhodopseudomonas palustris and Escherichia coli growing cooperatively through bidirectional nutrient exchange, we determined that an E. coli nitrogen starvation response is important for maintaining a stable coexistence. The lack of an E. coli nitrogen starvation response ultimately destabilized the mutualism and, in some cases, led to community collapse after serial transfers. Our findings thus inform on the potential necessity of an alternative physiological state for mutualistic coexistence with another species compared to the physiology of species grown in isolation.

microbiology↗

bioRxiv2017

Metabolic Constraints And Quantitative Design Principles In Gene Expression During Adaption Of Yeast To Heat Shock

Microorganisms evolved adaptive responses that enable them to survive stressful challenges in ever changing environments by adjusting metabolism through the modulation of gene expression, protein levels and activity, and flow of metabolites. More frequent challenges allow natural selection ampler opportunities to select from a larger number of phenotypes that are compatible with survival. Understanding the causal relationships between physiological and metabolic requirements that are needed for cellular stress adaptation and gene expression changes that are used by organisms to achieve those requirements may have a significant impact in our ability to interpret and/or guide evolution.\n\nHere, we study those causal relationships during heat shock adaptation in the yeast Saccharomyces cerevisiae. We do so by combining dozens of independent experiments measuring whole genome gene expression changes during stress response with a nonlinear simplified kinetic model of central metabolism.\n\nThis combination is used to create a quantitative, multidimensional, genotype-to-phenotype mapping of the metabolic and physiological requirements that enable cell survival to the feasible changes in gene expression that modulate metabolism to achieve those requirements. Our results clearly show that the feasible changes in gene expression that enable survival to heat shock are specific for this stress. In addition, they suggest that genetic programs for adaptive responses to desiccation/rehydration and to pH shifts might be selected by physiological requirements that are qualitatively similar, but quantitatively different to those for heat shock adaptation. In contrast, adaptive responses to other types of stress do not appear to be constrained by the same qualitative physiological requirements. Our model also explains at the mechanistic level how evolution might find different sets of changes in gene expression that lead to metabolic adaptations that are equivalent in meeting physiological requirements for survival. Finally, our results also suggest that physiological requirements for heat shock adaptation might be similar between unicellular ascomycetes that live in similar environments. Our analysis is likely to be scalable to other adaptive response and might inform efforts in developing biotechnological applications to manipulate cells for medical, biotechnological, or synthetic biology purposes.

systems biology↗

bioRxiv2018

Using composite phenotypes to reveal heterogeneity and model SpO2 of altitude acclimatization

Altitude acclimatization is the physiological process of the human body adjusting to the decreased availability of oxygen. Since several physiological processes are involved and the relation among them is complicated, analyses of single-traits is insufficient in revealing the complex mechanism of altitude acclimatization. In this study, we examined whether these physiological responses could be studied as composite phenotypes which are represented by a linear combination of physiological traits. We developed a strategy which combines both spectral clustering and PLSPM to define composite phenotypes. We captured 14 composite phenotypes from 28 physiological traits of altitude acclimatization. Using these composite phenotypes, we applied k-means to reveal hidden physiological heterogeneity in altitude acclimatization. Furthermore, we employed linear regression to systematically model oxygen saturation (SpO2) changes in altitude acclimatization and evaluated the model fitness performance. And composite phenotypes based Model 2 has better fitness than single-traits based Model 1 in all measurement indices. Therefore, this new strategy of defining and applying composite phenotypes can be considered as a general strategy of complex traits.

systems biology↗

bioRxiv2017

Fragile dynamics enable diverse genomic determinants to influence arrhythmia propensity

Genotype-phenotype relationships are determinants of human diseases. Often, we know little about why so many genes are involved in complex common diseases. We hypothesized that this multigene effect arises from the relationship between genes and physiological dynamics. We tested this hypothesis for arrhythmias as physiological dynamics define this disease. We integrated graph theory analysis of genomic and protein-protein interaction networks with dynamical models of ion channel function to identify the physiological dynamics of genome wide variation for five different arrhythmias. Regulatory networks for the cardiac conduction system and arrhythmias were constructed from GWAS and known disease genes. Electrophysiological models of myocyte action potentials were used to conduct extensive parameter variations to identify robust and fragile kinetic parameters that were then, using regulatory networks, associated with genomic determinants. We find that genome-wide determinants of arrhythmias that represent many cellular processes are selectively associated with fragile physiological dynamics of ion channel kinetics. This association predicts disease propensity. Deep RNA sequencing from human left ventricular tissue of arrhythmia and control subjects confirmed the predictive relationship. Taken together these studies show that the varied multigene effects of arrhythmias arises because of associations with fragile kinetic parameters of cardiac electrophysiology.\n\nSignificance StatementOur understanding of the genetics of common diseases has advanced exponentially over the past decade. We now know that differences and variation in multiple genes contribute to disease susceptibility with significant heterogeneity in the phenotype. However, how genetic variation contributes to disease phenotypes remains unknown. We hypothesized that the relationships between physiological dynamics and genetic architecture is a fundamental determinant of disease susceptibility and genetic heterogeneity. To test our hypothesis, we integrated mathematical models of cardiac electrophysiology with genetic network models of cardiac arrhythmias. We found that disease related genome variants were selectively associated with fragile kinetic parameters that predict disease propensity and identified several novel cellular processes associated with arrhythmogenesis.

systems biology↗

bioRxiv2017

Transcriptomic profiling of high-density Giardia foci encysting in the murine proximal intestine

Giardia is a highly prevalent, understudied protistan parasite causing significant diarrheal disease worldwide. Its life cycle consists of two stages: infectious cysts ingested from contaminated food or water sources, and motile trophozoites that colonize and attach to the gut epithelium, later encysting to form new cysts that are excreted into the environment. Current understanding of parasite physiology in the host is largely inferred from transcriptomic studies using Giardia grown axenically or in co-culture with mammalian cell lines. The dearth of information about the diversity of host-parasite interactions occurring within distinct regions of the gastrointestinal tract has been exacerbated by a lack of methods to directly and non-invasively interrogate disease progression and parasite physiology in live animal hosts. By visualizing Giardia infections in the mouse gastrointestinal tract using bioluminescent imaging (BLI) of tagged parasites, we recently showed that parasites colonize the gut in high-density foci that may cause localized pathology to the epithelium. Encystation is also initiated in these foci throughout the entire course of infection, yet how the physiology of parasites within high-density foci in the host gut differs from that of cells in laboratory culture is unclear. Here we use BLI to precisely select parasite samples from high-density foci in the proximal intestine to interrogate in vivo Giardia gene expression in the host. Relative to axenic culture, we noted significantly higher expression (> 10-fold) of oxidative stress, membrane transporter, and metabolic and structural genes associated with encystation in the high-density foci. These differences in gene expression within parasite foci in the host may reflect physiological changes associated with high-density growth in localized regions of the gut. We also identified and verified six novel cyst-specific proteins, including new components of the cyst wall that were highly expressed in these foci. Our in vivo transcriptome data support an emerging view that parasites encyst early in localized regions in the gut, possibly as a consequence of nutrient limitation, and also impact local metabolism and physiology.

microbiology↗

bioRxiv2017

Degeneracy in the robust expression of spectral selectivity, subthreshold oscillations and intrinsic excitability of entorhinal stellate cells

Biological heterogeneities are ubiquitous and play critical roles in the emergence of physiology at multiple scales. Although neurons in layer II (LII) of the medial entorhinal cortex (MEC) express heterogeneities in their channel properties, the impact of such heterogeneities on the robustness of cellular-scale physiology has not been assessed. Here, we performed a 55-parameter stochastic search spanning 9 voltage- or calcium-activated channels to assess the impact of channel heterogeneities on the concomitant emergence of 10 electrophysiological characteristics of LII stellate cells (SCs). We generated 50,000 models and found a heterogeneous subpopulation of 155 valid models to robustly match all electrophysiological signatures. We employed this heterogeneous population to demonstrate the emergence of cellular-scale degeneracy in LII SCs, whereby disparate parametric combinations expressing weak pairwise correlations resulted in similar models. We then assessed the impact of virtually knocking out each channel from all valid models and demonstrate that the mapping between channels and measurements was many-to-many, a critical requirement for the expression of degeneracy. Finally, we quantitatively predict that the spike-triggered average of LII SCs should be endowed with theta-frequency spectral selectivity and coincidence detection capabilities in the fast gamma-band. We postulate this fast gamma-band coincidence detection as an instance of cellular-scale efficient coding, whereby SC response characteristics match the dominant oscillatory signals in LII MEC. The heterogeneous population of valid SC models built here unveils the robust emergence of cellular-scale physiology despite significant channel heterogeneities, and forms an efficacious substrate for evaluating the impact of biological heterogeneities on entorhinal network function.\n\nKEY POINTSO_LIStellate cells (SC) in layer II (LII) of the medial entorhinal cortex express cellular-scale degeneracy in the concomitant manifestation of several of their unique physiological signatures.\nC_LIO_LISeveral disparate parametric combinations expressing weak pairwise correlations resulted in models with very similar physiological characteristics, including robust theta-frequency membrane potential oscillations spanning several levels of subthreshold depolarization.\nC_LIO_LIElectrophysiological measurements of LII SCs exhibited differential and variable dependencies on underlying channels, and the mapping between channels and measurements was many-to-many.\nC_LIO_LIQuantitative predictions point to theta-frequency spectral selectivity and fast gamma-range coincidence detection capabilities in class II/III spike-triggered average of LII SCs, with the postulate for this to be an instance of cellular-scale efficient coding.\nC_LIO_LIA heterogeneous cell population that accounts for both channel and intrinsic heterogeneities in LII SCs, which could be employed by network models of entorhinal function to probe the impact of several biological heterogeneities on spatial navigation circuits.\nC_LI

neuroscience↗

bioRxiv2026

Detection of Stress in Naturalistic Settings Through Passive Mobile Sensing

Unobtrusive stress detection using wearable sensors could enable scalable, continuous mental-health monitoring. However, stress is an inherently subjective state that can only be inferred indirectly from physiological signals, making generalizable detection in naturalistic settings challenging. Although prior work has focused on improving model performance, it remains unclear whether wearable physiology supports a shared cross-individual mapping to subjective stress or whether this relationship is fundamentally person-specific. We evaluated feature-based and deep-learning models across multiple physiological modalities using ecological momentary assessment (EMA) as the reference standard, comparing within- and between-individual modeling approaches. Within-individual models achieved modest but consistent improvements in stress detection, whereas between-individual models consistently failed to generalize, yielding negative R2 values despite multimodal fusion and high-capacity architectures. Error analyses revealed regression to the mean, reduced sensitivity to high-stress states, and residual associations with general physiological activation, highlighting the limited stress specificity of wearable physiology. These findings suggest that wearable stress detection is fundamentally a personalized inference problem and that future systems should prioritize individual adaptation and contextual modeling over universal stress predictors.

neuroscience↗

bioRxiv2018

Exploring the mechanistic link between corticosterone and insulin-like growth factor-1 in a wild passerine bird

BackgroundPhysiological regulators of life history trade-offs need to be responsive to sudden changes of resource availability. When homeostasis is challenged by unpredictable stressors, vertebrates respond through a set of physiological reactions, which can promote organismal survival. Glucocorticoids have been traditionally recognized as one of the main regulators of the physiological stress response, but the role of an evolutionarily more conserved pathway, the hypothalamic-pituitary-somatotropic (HPS) axis producing insulin-like growth factor-1 (IGF-1) has received much less attention. Although IGF-1 is known to affect several life history traits, little is known about its role in the physiological stress response and it has never been studied directly in adult wild animals.\n\nMethodsIn this study, we combined field observations with a controlled experiment to investigate how circulating levels of IGF-1 change in response to stress and whether this change is due to concomitant change in glucocorticoids in a free-living songbird, the bearded reedling Panurus biarmicus. We used a standard capture-restraint protocol in field observation, in which we took first and second (stress induced: 15 minutes later) samples. In a follow-up experiment, we used a minimally invasive oral corticosterone manipulation.\n\nResultsWe showed that corticosterone levels significantly increased while IGF-1 levels significantly decreased during capture and handling stress. However, change in corticosterone levels were not related to change in IGF-1 levels. We found that experimentally elevated corticosterone levels did not affect IGF-1 levels.\n\nDiscussionOur results are the first to highlight that circulating IGF-1 levels are responsive to stress independently from glucocorticoids and suggest that the HPS axis is an autonomous physiological pathway that may play an important role as regulator of life-history decisions.

physiology↗

bioRxiv2018

Instant Automated Inference of Perceived Mental Stress through Smartphone PPG and Thermal Imaging

BackgroundA smartphone is a promising tool for daily cardiovascular measurement and mental stress monitoring. Photoplethysmography (PPG) and low-cost thermography can be used to create cheap, convenient and mobile systems. However, to achieve robustness, a person has to remain still for several minutes while a measurement is being taken. This is very cumbersome, and limits the usage in applications such producing instant measurements of stress.\n\nObjectiveWe propose to use smartphone-based mobile PPG and thermal imaging to provide a fast binary measure of stress responses to an event using dynamical physiological changes which occur within 20 seconds of the event finishing.\n\nMethodsWe propose a system that uses a smartphone and its physiological sensors to reliably and continuously measure over a short window of time a persons blood volume pulse, the time interval between heartbeats (R-R interval) and the 1D thermal signature of the nose tip. 17 healthy participants, involved in a series of stress-inducing mental activities, measured their physiological response to stress in the 20 second-window immediately following each activity. A 10-cm Visual Analogue Scale was used by them to self-report their level of mental stress. As a main labeling strategy, normalized K-means clustering is used to better treat interpersonal differences in ratings. By taking an array of the R-R intervals and thermal directionality as a low-level feature input, we mainly use an artificial neural network to enable the automatic feature learning and the machine learning inference process. To compare the automated inference performance, we also extracted widely used high level features from HRV (e.g., LF/HF ratio) and the thermal signature and input them to a k-nearest neighbor to infer perceived stress levels.\n\nResultsFirst, we tested the physiological measurement reliability. The measured cardiac signals were considered highly reliable (signal goodness probability used, Mean=0.9584, SD=0.0151). The proposed 1D thermal signal processing algorithm effectively minimized the effect of respiratory cycles on detecting the apparent temperature of the nose tip (respiratory signal goodness probability Mean=0.8998 to Mean=0). Second, we tested the 20 seconds instant perceived stress inference performance. The best results were obtained by using automatic feature learning and classification using artificial neural networks rather than using pre-crafted features. The combination of both modalities produced higher accuracy on the binary classification task using 17-fold leave-one-subject-out (LOSO) cross-validation (accuracy: HRV+Thermal: 76.96%; HRV: 60.29%; Thermal: 61.37%). The results are comparable with the state of the art automatic stress recognition methods requiring long term measurements (a minimum of 2 minutes for up to around 80% accuracy from LOSO). Lastly, we explored the impact of different data labeling strategies used in the field on the sensitivity of our inference methods and the need for normalization within individual.\n\nConclusionsResults demonstrate the capability of smartphone biomedical imaging in instant mental stress recognition. Given that this approach does not require long measurements requiring attention and reduced mobility, it is more feasible for mobile mental healthcare solution in the wild.

physiology↗

bioRxiv2017

Migration Of Human Mesenchymal Stem Cells Stimulated With Pulsed Electric Field And The Dynamics Of The Cell Surface Glycosylation

The objective of our study was to develop novel techniques for investigations of cell motility, and to assess whether the electric field of the therapeutic spinal cord stimulation system used in vivo contributes to the migration of human mesenchymal stem cells (hMSCs) in vitro.\n\nWe have investigated electrotaxis of bone marrow-derived MSCs using pulsed electric field (PEF) in range 16-80 mV/mm and frequency 130 Hz and 240 Hz. The PEF-related dynamics of the cell surface glycosylation was evaluated using six plant lectins.\n\nPEF at physiological levels (10mV/mm; 130 Hz) did not influence cellular motility in vitro, what may correspond to the maintenance of the transplanted cells at the lesion site in vivo. Increase of the PEF intensity and frequency above physiological levels resulted in the increase in the cellular migration rate in vitro. PEF elevated above physiological intensity and frequency (40-80 mV/mm; 240 Hz), but not at physiological levels, resulted in changes of the cell surface glycosylation.\n\nWe find the described approach as convenient for investigations and for the in vitro modeling of the cellular systems intended for the regenerative cell transplantations in vivo. Probing cell surface glycomes may provide valuable biomarkers to assess competence of transplanted cells.

cell biology↗

bioRxiv2017

Recording action potential propagation in single axons using multi-electrode arrays

The small caliber of central nervous system (CNS) axons makes routine study of axonal physiology relatively difficult. However, while recording extracellular action potentials from neurons cultured on planer multi-electrode arrays (MEAs) we found activity among groups of electrodes consistent with action potential propagation in single neurons. Action potential propagation was evident as widespread, repetitive cooccurrence of extracellular action potentials (eAPs) among groups of electrodes. These eAPs occurred with invariant sequences and inter-electrode latencies that were consistent with reported measures of action potential propagation in unmyelinated axons. Within co-active electrode groups, the inter-electrode eAP latencies were temperature sensitive, as expected for action potential propagation. Our data are consistent with these signals primarily reflecting axonal action potential propagation, from axons with a high density of voltage-gated sodium channels. Repeated codetection of eAPs by multiple electrodes confirmed these eAPs are from individual neurons and averaging these eAPs revealed sub-threshold events at other electrodes. The sequence of electrodes at which eAPs co-occur uniquely identifies these neurons, allowing us to monitor spiking of single identified neurons within neuronal ensembles. We recorded dynamic changes in single axon physiology such as simultaneous increases and decreases in excitability in different portions of single axonal arbors over several hours. Over several weeks, we measured changes in inter-electrode propagation latencies and ongoing changes in excitability in different regions of single axonal arbors. We recorded action potential propagation signals in human induced pluripotent stem cell-derived neurons which could thus be used to study axonal physiology in human disease models.\n\nSignificance StatementStudying the physiology of central nervous system axons is limited by the technical challenges of recording from axons with pairs of patch or extracellular electrodes at two places along single axons. We studied action potential propagation in single axonal arbors with extracellular recording with multi-electrode arrays. These recordings were non-invasive and were done from several sites of small caliber axons and branches. Unlike conventional extracellular recording, we unambiguously identified and labelled the neuronal source of propagating action potentials. We manipulated and quantified action potential propagation and found a surprisingly high density of axonal voltage-gated sodium channels. Our experiments also demonstrate that the excitability of different portions of axonal arbors can be independently regulated on time scales from hours to weeks.

neuroscience↗

bioRxiv2017

Recent Advancement in Biosensors Technology for Animal and Livestock Health Management

The term biosensors encompasses devices that have the potential to quantify physiological, immunological and behavioural responses of livestock and multiple animal species. Novel biosensing methodologies offer highly specialised monitoring devices for the specific measurement of individual and multiple parameters covering an animals physiology as well as monitoring of an animals environment. These devices are not only highly specific and sensitive for the parameters being analysed, but they are also reliable and easy to use, and can accelerate the monitoring process. Novel biosensors in livestock management provide significant benefits and applications in disease detection and isolation, health monitoring and detection of reproductive cycles, as well as monitoring physiological wellbeing of the animal via analysis of the animals environment. With the development of integrated systems and the Internet of Things, the continuously monitoring devices are expected to become affordable. The data generated from integrated livestock monitoring is anticipated to assist farmers and the agricultural industry to improve animal productivity in the future. The data is expected to reduce the impact of the livestock industry on the environment, while at the same time driving the new wave towards the improvements of viable farming techniques. This review focusses on the emerging technological advancements in monitoring of livestock health for detailed, precise information on productivity, as well as physiology and well-being. Biosensors will contribute to the 4th revolution in agriculture by incorporating innovative technologies into cost-effective diagnostic methods that can mitigate the potentially catastrophic effects of infectious outbreaks in farmed animals

bioengineering↗

bioRxiv2017

Side Effects And The Need For Secrecy: Characterising Discontinuation Of Modern Contraception And Its Causes In Ethiopia Using Mixed Methods

BackgroundContraceptive discontinuation is a major barrier to reducing global unmet needs for family planning, but the reasons why women discontinue contraception are poorly understood. Here we use data from Ethiopia to investigate (i) the magnitude of contraceptive discontinuation in 2005-2011, (ii) how the risk of discontinuation varies with method type and education level and (iii) the barriers to continuation. Our main hypothesis is that contraceptive discontinuation is driven by the experience of physiological side-effects associated with the use of hormonal contraception, rather than a lack of education.\n\nMethodsWe used a mixed methods explanatory sequential design to explain the quantitative results in more details through the qualitative data. First, we analysed quantitative data from the 2011 Ethiopian Demographic and Health Survey to study patterns of contraceptive discontinuation and method choice using multilevel multiprocess models. Second, we conducted semi-structured interviews and focus group discussions in the 3 most populated regions of Ethiopia with individuals of reproductive age and health professionals.\n\nResultsThe analysis of EDHS data shows that the rate of discontinuation has not reduced in the period 2005-2011 and remains high. Discontinuation mainly takes the form of abandonment, and is a function of method type and wealth but not of educational level. Interviews with women and health professionals reveal that the experience of debilitating physiological side effects, the need for secrecy and poverty are important barriers to continuation.\n\nConclusionsOur findings together suggest that physiological and social side-effects of contraceptive use, not education, are the root causes of contraceptive discontinuation in Ethiopia. We argue that to tackle discontinuation due to side-effects, dispelling misconceptions through educating women is not addressing the root causes of discontinuation, and that priority should be given to both engaging men and questioning the appropriateness of medical technology to the physiology of Ethiopian women, especially those living in poverty.

epidemiology↗