Simple, Fast and Accurate Implementation of the Diffusion Approximation Algorithm for Stochastic Ion Channels with Multiple States

The phenomena that emerge from the interaction of the stochastic opening and closing of ion channels (channel noise) with the non-linear neural dynamics are essential to our understanding of the operation of the nervous system. The effects that channel noise can have on neural dynamics are generally studied using numerical simulations of stochastic models. Algorithms based on discrete Markov Chains (MC) seem to be the most reliable and trustworthy, but even optimized algorithms come with a non-negligible computational cost. Diffusion Approximation (DA) methods use Stochastic Differential Equations (SDE) to approximate the behavior of a number of MCs, considerably speeding up simulation times. However, model comparisons have suggested that DA methods did not lead to the same results as in MC modeling in terms of channel noise statistics and effects on excitability. Recently, it was shown that the difference arose because MCs were modeled with coupled activation subunits, while the DA was modeled using uncoupled activation subunits. Implementations of DA with coupled subunits, in the context of a specific kinetic scheme, yielded similar results to MC. However, it remained unclear how to generalize these implementations to different kinetic schemes, or whether they were faster than MC algorithms. Additionally, a steady state approximation was used for the stochastic terms, which, as we show here, can introduce significant inaccuracies. We derived the SDE explicitly for any given ion channel kinetic scheme. The resulting generic equations were surprisingly simple and interpretable - allowing an easy and efficient DA implementation. The algorithm was tested in a voltage clamp simulation and in two different current clamp simulations, yielding the same results as MC modeling. Also, the simulation efficiency of this DA method demonstrated considerable superiority over MC methods.Comment: 32 text pages, 10 figures, 1 supplementary text + figur

A Model of Late Long-Term Potentiation Simulates Aspects of Memory Maintenance

Late long-term potentiation (L-LTP) appears essential for the formation of long-term memory, with memories at least partly encoded by patterns of strengthened synapses. How memories are preserved for months or years, despite molecular turnover, is not well understood. Ongoing recurrent neuronal activity, during memory recall or during sleep, has been hypothesized to preferentially potentiate strong synapses, preserving memories. This hypothesis has not been evaluated in the context of a mathematical model representing biochemical pathways important for L-LTP. I incorporated ongoing activity into two such models: a reduced model that represents some of the essential biochemical processes, and a more detailed published model. The reduced model represents synaptic tagging and gene induction intuitively, and the detailed model adds activation of essential kinases by Ca. Ongoing activity was modeled as continual brief elevations of [Ca]. In each model, two stable states of synaptic weight resulted. Positive feedback between synaptic weight and the amplitude of ongoing Ca transients underlies this bistability. A tetanic or theta-burst stimulus switches a model synapse from a low weight to a high weight stabilized by ongoing activity. Bistability was robust to parameter variations. Simulations illustrated that prolonged decreased activity reset synapses to low weights, suggesting a plausible forgetting mechanism. However, episodic activity with shorter inactive intervals maintained strong synapses. Both models support experimental predictions. Tests of these predictions are expected to further understanding of how neuronal activity is coupled to maintenance of synaptic strength.Comment: Accepted to PLoS One. 8 figures at en

Consumer exposure to biocides - identification of relevant sources and evaluation of possible health effects

<p>Abstract</p> <p>Background</p> <p>Products containing biocides are used for a variety of purposes in the home environment. To assess potential health risks, data on products containing biocides were gathered by means of a market survey, exposures were estimated using a worst case scenario approach (screening), the hazard of the active components were evaluated, and a preliminary risk assessment was conducted.</p> <p>Methods</p> <p>Information on biocide-containing products was collected by on-site research, by an internet inquiry as well as research into databases and lists of active substances. Twenty active substances were selected for detailed investigation. The products containing these substances were subsequently classified by range of application; typical concentrations were derived. Potential exposures were then estimated using a worst case scenario approach according to the European Commission's Technical Guidance Document on Risk Assessment. Relevant combinations of scenarios and active substances were identified. The toxicological data for these substances were compiled in substance dossiers. For estimating risks, the margins of exposure (MOEs) were determined.</p> <p>Results</p> <p>Numerous consumer products were found to contain biocides. However, it appeared that only a limited number of biocidal active substances or groups of biocidal active substances were being used. The lowest MOEs for dermal exposure or exposure by inhalation were obtained for the following scenarios and biocides: indoor pest control using sprays, stickers or evaporators (chlorpyrifos, dichlorvos) and spraying of disinfectants as well as cleaning of surfaces with concentrates (hydrogen peroxide, formaldehyde, glutardialdehyde). The risk from aggregate exposure to individual biocides via different exposure scenarios was higher than the highest single exposure on average by a factor of three. From the 20 biocides assessed 10 had skin-sensitizing properties. The biocides isothiazolinone (mixture of 5-chloro-2-methyl-2H-isothiazolin-3-one and 2-methyl-2H-isothiazolin-3-one, CMI/MI), glutardialdehyde, formaldehyde and chloroacetamide may be present in household products in concentrations which have induced sensitization in experimental studies.</p> <p>Conclusions</p> <p>Exposure to biocides from household products may contribute to induction of sensitization in the population. The use of biocides in consumer products should be carefully evaluated. Detailed risk assessments will become available within the framework of the EU Biocides Directive.</p

Abstinence-Only Education and Teen Pregnancy Rates: Why We Need Comprehensive Sex Education in the U.S

The United States ranks first among developed nations in rates of both teenage pregnancy and sexually transmitted diseases. In an effort to reduce these rates, the U.S. government has funded abstinence-only sex education programs for more than a decade. However, a public controversy remains over whether this investment has been successful and whether these programs should be continued. Using the most recent national data (2005) from all U.S. states with information on sex education laws or policies (N = 48), we show that increasing emphasis on abstinence education is positively correlated with teenage pregnancy and birth rates. This trend remains significant after accounting for socioeconomic status, teen educational attainment, ethnic composition of the teen population, and availability of Medicaid waivers for family planning services in each state. These data show clearly that abstinence-only education as a state policy is ineffective in preventing teenage pregnancy and may actually be contributing to the high teenage pregnancy rates in the U.S. In alignment with the new evidence-based Teen Pregnancy Prevention Initiative and the Precaution Adoption Process Model advocated by the National Institutes of Health, we propose the integration of comprehensive sex and STD education into the biology curriculum in middle and high school science classes and a parallel social studies curriculum that addresses risk-aversion behaviors and planning for the future

Mindfulness based cognitive therapy improves frontal control in bipolar disorder: a pilot EEG study

<p>Abstract</p> <p>Background</p> <p>Cognitive processing in Bipolar Disorder is characterized by a number of attentional abnormalities. Mindfulness Based Cognitive Therapy combines mindfulness meditation, a form of attentional training, along with aspects of cognitive therapy, and may improve attentional dysfunction in bipolar disorder patients.</p> <p>Methods</p> <p>12 euthymic BD patients and 9 control participants underwent record of electroencephalography (EEG, band frequency analysis) during resting states (eyes open, eyes closed) and during the completion of a continuous performance task (A-X version, EEG event-related potential (ERP) wave component analysis). The individuals with BD completed an 8-week MBCT intervention and record of EEG was repeated.</p> <p>Results</p> <p>(1) Brain activity, individuals with BD showed significantly decreased theta band power, increased beta band power, and decreased theta/beta ratios during the resting state, eyes closed, for frontal and cingulate cortices. Post MBCT intervention improvement over the right frontal cortex was seen in the individuals with BD, as beta band power decreased. (2) Brain activation, individuals with BD showed a significant P300-like wave form over the frontal cortex during the cue. Post MBCT intervention the P300-like waveform was significantly attenuated over the frontal cortex.</p> <p>Conclusions</p> <p>Individuals with BD show decreased attentional readiness and activation of non-relevant information processing during attentional processes. These data are the first that show, MBCT in BD improved attentional readiness, and attenuated activation of non-relevant information processing during attentional processes.</p

Processing of oat: the impact on oat's cholesterol lowering effect

Epidemiological and interventional studies have clearly demonstrated the beneficial impact of consuming oat and oat-based products on serum cholesterol and other markers of cardiovascular disease. The cholesterol-lowering effect of oat is thought to be associated with the β-glucan it contains. However, not all food products containing β-glucan seem to lead to the same health outcome. Overall, highly processed β-glucan sources (where the oat tissue is highly disrupted) appear to be less effective at reducing serum cholesterol, but the reasons are not well understood. Therefore, the mechanisms involved still need further clarification. The purpose of this paper is to review current evidence of the cholesterol-lowering effect of oat in the context of the structure and complexity of the oat matrix. The possibility of a synergistic action and interaction between the oat constituents promoting hypocholesterolaemia is also discussed. A review of the literature suggested that for a similar dose of β-glucan, (1) liquid oat-based foods seem to give more consistent, but moderate reductions in cholesterol than semi-solid or solid foods where the results are more variable; (2) the quantity of β-glucan and the molecular weight at expected consumption levels (∼3 g day−1) play a role in cholesterol reduction; and (3) unrefined β-glucan rich oat-based foods (where some of the plant tissue remains intact) often appear more efficient at lowering cholesterol than purified β-glucan added as an ingredient

Spatial Bistability Generates hunchback Expression Sharpness in the Drosophila Embryo

During embryonic development, the positional information provided by concentration gradients of maternal factors directs pattern formation by providing spatially dependent cues for gene expression. In the fruit fly, Drosophila melanogaster, a classic example of this is the sharp on–off activation of the hunchback (hb) gene at midembryo, in response to local concentrations of the smooth anterior–posterior Bicoid (Bcd) gradient. The regulatory region for hb contains multiple binding sites for the Bcd protein as well as multiple binding sites for the Hb protein. Some previous studies have suggested that Bcd is sufficient for properly sharpened Hb expression, yet other evidence suggests a need for additional regulation. We experimentally quantified the dynamics of hb gene expression in flies that were wild-type, were mutant for hb self-regulation or Bcd binding, or contained an artificial promoter construct consisting of six Bcd and two Hb sites. In addition to these experiments, we developed a reaction–diffusion model of hb transcription, with Bcd cooperative binding and hb self-regulation, and used Zero Eigenvalue Analysis to look for multiple stationary states in the reaction network. Our model reproduces the hb developmental dynamics and correctly predicts the mutant patterns. Analysis of our model indicates that the Hb sharpness can be produced by spatial bistability, in which hb self-regulation produces two stable levels of expression. In the absence of self-regulation, the bistable behavior vanishes and Hb sharpness is disrupted. Bcd cooperative binding affects the position where bistability occurs but is not itself sufficient for a sharp Hb pattern. Our results show that the control of Hb sharpness and positioning, by hb self-regulation and Bcd cooperativity, respectively, are separate processes that can be altered independently. Our model, which matches the changes in Hb position and sharpness observed in different experiments, provides a theoretical framework for understanding the data and in particular indicates that spatial bistability can play a central role in threshold-dependent reading mechanisms of positional information

An empirical Bayesian approach for model-based inference of cellular signaling networks

Background A common challenge in systems biology is to infer mechanistic descriptions of biological process given limited observations of a biological system. Mathematical models are frequently used to represent a belief about the causal relationships among proteins within a signaling network. Bayesian methods provide an attractive framework for inferring the validity of those beliefs in the context of the available data. However, efficient sampling of high-dimensional parameter space and appropriate convergence criteria provide barriers for implementing an empirical Bayesian approach. The objective of this study was to apply an Adaptive Markov chain Monte Carlo technique to a typical study of cellular signaling pathways. Results As an illustrative example, a kinetic model for the early signaling events associated with the epidermal growth factor (EGF) signaling network was calibrated against dynamic measurements observed in primary rat hepatocytes. A convergence criterion, based upon the Gelman-Rubin potential scale reduction factor, was applied to the model predictions. The posterior distributions of the parameters exhibited complicated structure, including significant covariance between specific parameters and a broad range of variance among the parameters. The model predictions, in contrast, were narrowly distributed and were used to identify areas of agreement among a collection of experimental studies. Conclusion In summary, an empirical Bayesian approach was developed for inferring the confidence that one can place in a particular model that describes signal transduction mechanisms and for inferring inconsistencies in experimental measurements

Passerine Exposure to Primarily PCDFs and PCDDs in the River Floodplains Near Midland, Michigan, USA

House wren (Troglodytes aedon), tree swallow (Tachycineta bicolor), and eastern bluebird (Sialia sialis) tissues collected in study areas (SAs) downstream of Midland, Michigan (USA) contained concentrations of polychlorinated dibenzofurans (PCDFs) and polychlorinated dibenzo-p-dioxins (PCDDs) greater than in upstream reference areas (RAs) in the region. The sum of concentrations of PCDD/DFs (ΣPCDD/DFs) in eggs of house wrens and eastern bluebirds from SAs were 4- to 22-fold greater compared to those from RAs, whereas concentrations in tree swallow eggs were similar among areas. Mean concentrations of ΣPCDD/DFs and sum 2,3,7,8-tetrachlorodibenzo-p-dioxin equivalents (ΣTEQsWHO-Avian), based on 1998 WHO avian toxic equivalency factors, in house wren and eastern bluebird eggs ranged from 860 (430) to 1500 (910) ng/kg wet weight (ww) and 470 (150) to 1100 (510) ng/kg ww, respectively, at the most contaminated study areas along the Tittabawassee River, whereas mean concentrations in tree swallow eggs ranged from 280 (100) to 760 (280) ng/kg ww among all locations. Concentrations of ΣPCDD/DFs in nestlings of all studied species at SAs were 3- to 50-fold greater compared to RAs. Mean house wren, tree swallow, and eastern bluebird nestling concentrations of ΣPCDD/DFs and ΣTEQsWHO-Avian ranged from 350 (140) to 610 (300) ng/kg ww, 360 (240) to 1100 (860) ng/kg ww, and 330 (100) to 1200 (690) ng/kg ww, respectively, at SAs along the Tittabawassee River. Concentrations of ΣTEQsWHO-Avian were positively correlated with ΣPCDD/DF concentrations in both eggs and nestlings of all species studied. Profiles of relative concentrations of individual congeners were dominated by furan congeners (69–84%), primarily 2,3,7,8-tetrachlorodibenzofuran and 2,3,4,7,8-pentachlorodibenzofuran, for all species at SAs on the Tittabawassee and Saginaw rivers but were dominated by dioxin congeners at upstream RAs

Calibration of ionic and cellular cardiac electrophysiology models

© 2020 The Authors. WIREs Systems Biology and Medicine published by Wiley Periodicals, Inc. Cardiac electrophysiology models are among the most mature and well-studied mathematical models of biological systems. This maturity is bringing new challenges as models are being used increasingly to make quantitative rather than qualitative predictions. As such, calibrating the parameters within ion current and action potential (AP) models to experimental data sets is a crucial step in constructing a predictive model. This review highlights some of the fundamental concepts in cardiac model calibration and is intended to be readily understood by computational and mathematical modelers working in other fields of biology. We discuss the classic and latest approaches to calibration in the electrophysiology field, at both the ion channel and cellular AP scales. We end with a discussion of the many challenges that work to date has raised and the need for reproducible descriptions of the calibration process to enable models to be recalibrated to new data sets and built upon for new studies. This article is categorized under: Analytical and Computational Methods > Computational Methods Physiology > Mammalian Physiology in Health and Disease Models of Systems Properties and Processes > Cellular Models