Robustness of Reconstructed Ancestral Protein Functions to Statistical Uncertainty.

PubMed

Eick, Geeta N; Bridgham, Jamie T; Anderson, Douglas P; Harms, Michael J; Thornton, Joseph W

2017-02-01

Hypotheses about the functions of ancient proteins and the effects of historical mutations on them are often tested using ancestral protein reconstruction (APR)-phylogenetic inference of ancestral sequences followed by synthesis and experimental characterization. Usually, some sequence sites are ambiguously reconstructed, with two or more statistically plausible states. The extent to which the inferred functions and mutational effects are robust to uncertainty about the ancestral sequence has not been studied systematically. To address this issue, we reconstructed ancestral proteins in three domain families that have different functions, architectures, and degrees of uncertainty; we then experimentally characterized the functional robustness of these proteins when uncertainty was incorporated using several approaches, including sampling amino acid states from the posterior distribution at each site and incorporating the alternative amino acid state at every ambiguous site in the sequence into a single "worst plausible case" protein. In every case, qualitative conclusions about the ancestral proteins' functions and the effects of key historical mutations were robust to sequence uncertainty, with similar functions observed even when scores of alternate amino acids were incorporated. There was some variation in quantitative descriptors of function among plausible sequences, suggesting that experimentally characterizing robustness is particularly important when quantitative estimates of ancient biochemical parameters are desired. The worst plausible case method appears to provide an efficient strategy for characterizing the functional robustness of ancestral proteins to large amounts of sequence uncertainty. Sampling from the posterior distribution sometimes produced artifactually nonfunctional proteins for sequences reconstructed with substantial ambiguity. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Selection, calibration, and validation of models of tumor growth.

PubMed

Lima, E A B F; Oden, J T; Hormuth, D A; Yankeelov, T E; Almeida, R C

2016-11-01

This paper presents general approaches for addressing some of the most important issues in predictive computational oncology concerned with developing classes of predictive models of tumor growth. First, the process of developing mathematical models of vascular tumors evolving in the complex, heterogeneous, macroenvironment of living tissue; second, the selection of the most plausible models among these classes, given relevant observational data; third, the statistical calibration and validation of models in these classes, and finally, the prediction of key Quantities of Interest (QOIs) relevant to patient survival and the effect of various therapies. The most challenging aspects of this endeavor is that all of these issues often involve confounding uncertainties: in observational data, in model parameters, in model selection, and in the features targeted in the prediction. Our approach can be referred to as "model agnostic" in that no single model is advocated; rather, a general approach that explores powerful mixture-theory representations of tissue behavior while accounting for a range of relevant biological factors is presented, which leads to many potentially predictive models. Then representative classes are identified which provide a starting point for the implementation of OPAL, the Occam Plausibility Algorithm (OPAL) which enables the modeler to select the most plausible models (for given data) and to determine if the model is a valid tool for predicting tumor growth and morphology ( in vivo ). All of these approaches account for uncertainties in the model, the observational data, the model parameters, and the target QOI. We demonstrate these processes by comparing a list of models for tumor growth, including reaction-diffusion models, phase-fields models, and models with and without mechanical deformation effects, for glioma growth measured in murine experiments. Examples are provided that exhibit quite acceptable predictions of tumor growth in laboratory animals while demonstrating successful implementations of OPAL.

Adverse outcome pathway (AOP) development I: Strategies and principles

EPA Science Inventory

An adverse outcome pathway (AOP) is a conceptual framework that organizes existing knowledge concerning biologically plausible, and empirically-supported, links between molecular-level perturbation of a biological system and an adverse outcome at a level of biological organizatio...

Fractional Brownian motion and multivariate-t models for longitudinal biomedical data, with application to CD4 counts in HIV-positive patients.

PubMed

Stirrup, Oliver T; Babiker, Abdel G; Carpenter, James R; Copas, Andrew J

2016-04-30

Longitudinal data are widely analysed using linear mixed models, with 'random slopes' models particularly common. However, when modelling, for example, longitudinal pre-treatment CD4 cell counts in HIV-positive patients, the incorporation of non-stationary stochastic processes such as Brownian motion has been shown to lead to a more biologically plausible model and a substantial improvement in model fit. In this article, we propose two further extensions. Firstly, we propose the addition of a fractional Brownian motion component, and secondly, we generalise the model to follow a multivariate-t distribution. These extensions are biologically plausible, and each demonstrated substantially improved fit on application to example data from the Concerted Action on SeroConversion to AIDS and Death in Europe study. We also propose novel procedures for residual diagnostic plots that allow such models to be assessed. Cohorts of patients were simulated from the previously reported and newly developed models in order to evaluate differences in predictions made for the timing of treatment initiation under different clinical management strategies. A further simulation study was performed to demonstrate the substantial biases in parameter estimates of the mean slope of CD4 decline with time that can occur when random slopes models are applied in the presence of censoring because of treatment initiation, with the degree of bias found to depend strongly on the treatment initiation rule applied. Our findings indicate that researchers should consider more complex and flexible models for the analysis of longitudinal biomarker data, particularly when there are substantial missing data, and that the parameter estimates from random slopes models must be interpreted with caution. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Plausibility and parameter sensitivity of micro-finite element-based joint load prediction at the proximal femur.

PubMed

Synek, Alexander; Pahr, Dieter H

2018-06-01

A micro-finite element-based method to estimate the bone loading history based on bone architecture was recently presented in the literature. However, a thorough investigation of the parameter sensitivity and plausibility of this method to predict joint loads is still missing. The goals of this study were (1) to analyse the parameter sensitivity of the joint load predictions at one proximal femur and (2) to assess the plausibility of the results by comparing load predictions of ten proximal femora to in vivo hip joint forces measured with instrumented prostheses (available from www.orthoload.com ). Joint loads were predicted by optimally scaling the magnitude of four unit loads (inclined [Formula: see text] to [Formula: see text] with respect to the vertical axis) applied to micro-finite element models created from high-resolution computed tomography scans ([Formula: see text]m voxel size). Parameter sensitivity analysis was performed by varying a total of nine parameters and showed that predictions of the peak load directions (range 10[Formula: see text]-[Formula: see text]) are more robust than the predicted peak load magnitudes (range 2344.8-4689.5 N). Comparing the results of all ten femora with the in vivo loading data of ten subjects showed that peak loads are plausible both in terms of the load direction (in vivo: [Formula: see text], predicted: [Formula: see text]) and magnitude (in vivo: [Formula: see text], predicted: [Formula: see text]). Overall, this study suggests that micro-finite element-based joint load predictions are both plausible and robust in terms of the predicted peak load direction, but predicted load magnitudes should be interpreted with caution.

MRI Proton Density Fat Fraction Is Robust Across the Biologically Plausible Range of Triglyceride Spectra in Adults With Nonalcoholic Steatohepatitis

PubMed Central

Hong, Cheng William; Mamidipalli, Adrija; Hooker, Jonathan C.; Hamilton, Gavin; Wolfson, Tanya; Chen, Dennis H.; Dehkordy, Soudabeh Fazeli; Middleton, Michael S.; Reeder, Scott B.; Loomba, Rohit; Sirlin, Claude B.

2017-01-01

Background Proton density fat fraction (PDFF) estimation requires spectral modeling of the hepatic triglyceride (TG) signal. Deviations in the TG spectrum may occur, leading to bias in PDFF quantification. Purpose To investigate the effects of varying six-peak TG spectral models on PDFF estimation bias. Study Type Retrospective secondary analysis of prospectively acquired clinical research data. Population Forty-four adults with biopsy-confirmed nonalcoholic steatohepatitis. Field Strength/Sequence Confounder-corrected chemical-shift-encoded 3T MRI (using a 2D multiecho gradient-recalled echo technique with magnitude reconstruction) and MR spectroscopy. Assessment In each patient, 61 pairs of colocalized MRI-PDFF and MRS-PDFF values were estimated: one pair used the standard six-peak spectral model, the other 60 were six-peak variants calculated by adjusting spectral model parameters over their biologically plausible ranges. MRI-PDFF values calculated using each variant model and the standard model were compared, and the agreement between MRI-PDFF and MRS-PDFF was assessed. Statistical Tests MRS-PDFF and MRI-PDFF were summarized descriptively. Bland–Altman (BA) analyses were performed between PDFF values calculated using each variant model and the standard model. Linear regressions were performed between BA biases and mean PDFF values for each variant model, and between MRI-PDFF and MRS-PDFF. Results Using the standard model, mean MRS-PDFF of the study population was 17.9±8.0% (range: 4.1–34.3%). The difference between the highest and lowest mean variant MRI-PDFF values was 1.5%. Relative to the standard model, the model with the greatest absolute BA bias overestimated PDFF by 1.2%. Bias increased with increasing PDFF (P < 0.0001 for 59 of the 60 variant models). MRI-PDFF and MRS-PDFF agreed closely for all variant models (R2=0.980, P < 0.0001). Data Conclusion Over a wide range of hepatic fat content, PDFF estimation is robust across the biologically plausible range of TG spectra. Although absolute estimation bias increased with higher PDFF, its magnitude was small and unlikely to be clinically meaningful. Level of Evidence 3 Technical Efficacy Stage 2 PMID:28851124

Hyperpolarization-Activated Current Induces Period-Doubling Cascades and Chaos in a Cold Thermoreceptor Model

PubMed Central

Xu, Kesheng; Maidana, Jean P.; Caviedes, Mauricio; Quero, Daniel; Aguirre, Pablo; Orio, Patricio

2017-01-01

In this article, we describe and analyze the chaotic behavior of a conductance-based neuronal bursting model. This is a model with a reduced number of variables, yet it retains biophysical plausibility. Inspired by the activity of cold thermoreceptors, the model contains a persistent Sodium current, a Calcium-activated Potassium current and a hyperpolarization-activated current (Ih) that drive a slow subthreshold oscillation. Driven by this oscillation, a fast subsystem (fast Sodium and Potassium currents) fires action potentials in a periodic fashion. Depending on the parameters, this model can generate a variety of firing patterns that includes bursting, regular tonic and polymodal firing. Here we show that the transitions between different firing patterns are often accompanied by a range of chaotic firing, as suggested by an irregular, non-periodic firing pattern. To confirm this, we measure the maximum Lyapunov exponent of the voltage trajectories, and the Lyapunov exponent and Lempel-Ziv's complexity of the ISI time series. The four-variable slow system (without spiking) also generates chaotic behavior, and bifurcation analysis shows that this is often originated by period doubling cascades. Either with or without spikes, chaos is no longer generated when the Ih is removed from the system. As the model is biologically plausible with biophysically meaningful parameters, we propose it as a useful tool to understand chaotic dynamics in neurons. PMID:28344550

A Local Learning Rule for Independent Component Analysis

PubMed Central

Isomura, Takuya; Toyoizumi, Taro

2016-01-01

Humans can separately recognize independent sources when they sense their superposition. This decomposition is mathematically formulated as independent component analysis (ICA). While a few biologically plausible learning rules, so-called local learning rules, have been proposed to achieve ICA, their performance varies depending on the parameters characterizing the mixed signals. Here, we propose a new learning rule that is both easy to implement and reliable. Both mathematical and numerical analyses confirm that the proposed rule outperforms other local learning rules over a wide range of parameters. Notably, unlike other rules, the proposed rule can separate independent sources without any preprocessing, even if the number of sources is unknown. The successful performance of the proposed rule is then demonstrated using natural images and movies. We discuss the implications of this finding for our understanding of neuronal information processing and its promising applications to neuromorphic engineering. PMID:27323661

Ionic liquid pretreatment of biomass for sugars production: Driving factors with a plausible mechanism for higher enzymatic digestibility.

PubMed

Raj, Tirath; Gaur, Ruchi; Dixit, Pooja; Gupta, Ravi P; Kagdiyal, V; Kumar, Ravindra; Tuli, Deepak K

2016-09-20

In this study, five ionic liquids (ILs) have been explored for biomass pretreatment for the production of fermentable sugar. We also investigated the driving factors responsible for improved enzymatic digestibility of various ILs treated biomass along with postulating the plausible mechanism thereof. Post pretreatment, mainly two factors impacted the enzymatic digestibility (i) structural deformation (cellulose I to II) along with xylan/lignin removal and (ii) properties of ILs; wherein, K-T parameters, viscosity and surface tension had a direct influence on pretreatment. A systematic investigation of these parameters and their impact on enzymatic digestibility is drawn. [C2mim][OAc] with β-value 1.32 resulted 97.7% of glucose yield using 10 FPU/g of biomass. A closer insight into the cellulose structural transformation has prompted a plausible mechanism explaining the better digestibility. The impact of these parameters on the digestibility can pave the way to customize the process to make biomass vulnerable to enzymatic attack. Copyright © 2016 Elsevier Ltd. All rights reserved.

Organic Matter in SNC Meteorites: Is It Time to Re-Evaluate the Viking Biology Experimental Data?

NASA Technical Reports Server (NTRS)

Warmflash, D.; Clemett, S. J.; McKay, D. S.

2001-01-01

New data from SNC meteorites suggests that organic material may be present in the martian upper crust. This adds to possibility that the Viking biology experiments may have plausible biological interpretations as well as inorganic chemical interpretations Additional information is contained in the original extended abstract..

Phosphorylation, oligomerization and self-assembly in water under potential prebiotic conditions

NASA Astrophysics Data System (ADS)

Gibard, Clémentine; Bhowmik, Subhendu; Karki, Megha; Kim, Eun-Kyong; Krishnamurthy, Ramanarayanan

2018-02-01

Prebiotic phosphorylation of (pre)biological substrates under aqueous conditions is a critical step in the origins of life. Previous investigations have had limited success and/or require unique environments that are incompatible with subsequent generation of the corresponding oligomers or higher-order structures. Here, we demonstrate that diamidophosphate (DAP)—a plausible prebiotic agent produced from trimetaphosphate—efficiently (amido)phosphorylates a wide variety of (pre)biological building blocks (nucleosides/tides, amino acids and lipid precursors) under aqueous (solution/paste) conditions, without the need for a condensing agent. Significantly, higher-order structures (oligonucleotides, peptides and liposomes) are formed under the same phosphorylation reaction conditions. This plausible prebiotic phosphorylation process under similar reaction conditions could enable the systems chemistry of the three classes of (pre)biologically relevant molecules and their oligomers, in a single-pot aqueous environment.

Phosphorylation, oligomerization and self-assembly in water under potential prebiotic conditions

NASA Astrophysics Data System (ADS)

Gibard, Clémentine; Bhowmik, Subhendu; Karki, Megha; Kim, Eun-Kyong; Krishnamurthy, Ramanarayanan

2017-11-01

Prebiotic phosphorylation of (pre)biological substrates under aqueous conditions is a critical step in the origins of life. Previous investigations have had limited success and/or require unique environments that are incompatible with subsequent generation of the corresponding oligomers or higher-order structures. Here, we demonstrate that diamidophosphate (DAP)-a plausible prebiotic agent produced from trimetaphosphate - efficiently (amido)phosphorylates a wide variety of (pre)biological building blocks (nucleosides/tides, amino acids and lipid precursors) under aqueous (solution/paste) conditions, without the need for a condensing agent. Significantly, higher-order structures (oligonucleotides, peptides and liposomes) are formed under the same phosphorylation reaction conditions. This plausible prebiotic phosphorylation process under similar reaction conditions could enable the systems chemistry of the three classes of (pre)biologically relevant molecules and their oligomers, in a single-pot aqueous environment.

Optimal design of stimulus experiments for robust discrimination of biochemical reaction networks.

PubMed

Flassig, R J; Sundmacher, K

2012-12-01

Biochemical reaction networks in the form of coupled ordinary differential equations (ODEs) provide a powerful modeling tool for understanding the dynamics of biochemical processes. During the early phase of modeling, scientists have to deal with a large pool of competing nonlinear models. At this point, discrimination experiments can be designed and conducted to obtain optimal data for selecting the most plausible model. Since biological ODE models have widely distributed parameters due to, e.g. biologic variability or experimental variations, model responses become distributed. Therefore, a robust optimal experimental design (OED) for model discrimination can be used to discriminate models based on their response probability distribution functions (PDFs). In this work, we present an optimal control-based methodology for designing optimal stimulus experiments aimed at robust model discrimination. For estimating the time-varying model response PDF, which results from the nonlinear propagation of the parameter PDF under the ODE dynamics, we suggest using the sigma-point approach. Using the model overlap (expected likelihood) as a robust discrimination criterion to measure dissimilarities between expected model response PDFs, we benchmark the proposed nonlinear design approach against linearization with respect to prediction accuracy and design quality for two nonlinear biological reaction networks. As shown, the sigma-point outperforms the linearization approach in the case of widely distributed parameter sets and/or existing multiple steady states. Since the sigma-point approach scales linearly with the number of model parameter, it can be applied to large systems for robust experimental planning. An implementation of the method in MATLAB/AMPL is available at http://www.uni-magdeburg.de/ivt/svt/person/rf/roed.html. flassig@mpi-magdeburg.mpg.de Supplementary data are are available at Bioinformatics online.

Biology Teachers' Conceptions of the Diversity of Life and the Historical Development of Evolutionary Concepts

ERIC Educational Resources Information Center

da Silva, Paloma Rodrigues; de Andrade, Mariana A. Bologna Soares; de Andrade Caldeira, Ana Maria

2015-01-01

Biology is a science that involves study of the diversity of living organisms. This diversity has always generated questions and has motivated cultures to seek plausible explanations for the differences and similarities between types of organisms. In biology teaching, these issues are addressed by adopting an evolutionary approach. The aim of this…

Basic research on design analysis methods for rotorcraft vibrations

NASA Technical Reports Server (NTRS)

Hanagud, S.

1991-01-01

The objective of the present work was to develop a method for identifying physically plausible finite element system models of airframe structures from test data. The assumed models were based on linear elastic behavior with general (nonproportional) damping. Physical plausibility of the identified system matrices was insured by restricting the identification process to designated physical parameters only and not simply to the elements of the system matrices themselves. For example, in a large finite element model the identified parameters might be restricted to the moduli for each of the different materials used in the structure. In the case of damping, a restricted set of damping values might be assigned to finite elements based on the material type and on the fabrication processes used. In this case, different damping values might be associated with riveted, bolted and bonded elements. The method itself is developed first, and several approaches are outlined for computing the identified parameter values. The method is applied first to a simple structure for which the 'measured' response is actually synthesized from an assumed model. Both stiffness and damping parameter values are accurately identified. The true test, however, is the application to a full-scale airframe structure. In this case, a NASTRAN model and actual measured modal parameters formed the basis for the identification of a restricted set of physically plausible stiffness and damping parameters.

The Anthropocene concept in ecology and conservation.

PubMed

Corlett, Richard T

2015-01-01

The term 'Anthropocene' was first used in the year 2000 to refer to the current time period in which human impacts are at least as important as natural processes. It is currently being considered as a potential geological epoch, following on from the Holocene. While most environmental scientists accept that many key environmental parameters are now outside their Holocene ranges, there is no agreement on when the Anthropocene started, with plausible dates ranging from the Late Pleistocene megafaunal extinctions to the recent globalization of industrial impacts. In ecology, the Anthropocene concept has focused attention on human-dominated habitats and novel ecosystems, while in conservation biology it has sparked a divisive debate on the continued relevance of the traditional biocentric aims. Copyright © 2014 Elsevier Ltd. All rights reserved.

Theories and models on the biological of cells in space

NASA Technical Reports Server (NTRS)

Todd, P.; Klaus, D. M.

1996-01-01

A wide variety of observations on cells in space, admittedly made under constraining and unnatural conditions in may cases, have led to experimental results that were surprising or unexpected. Reproducibility, freedom from artifacts, and plausibility must be considered in all cases, even when results are not surprising. The papers in symposium on 'Theories and Models on the Biology of Cells in Space' are dedicated to the subject of the plausibility of cellular responses to gravity -- inertial accelerations between 0 and 9.8 m/sq s and higher. The mechanical phenomena inside the cell, the gravitactic locomotion of single eukaryotic and prokaryotic cells, and the effects of inertial unloading on cellular physiology are addressed in theoretical and experimental studies.

Polymer translocation under time-dependent driving forces: resonant activation induced by attractive polymer-pore interactions.

PubMed

Ikonen, Timo; Shin, Jaeoh; Sung, Wokyung; Ala-Nissila, Tapio

2012-05-28

We study the driven translocation of polymers under time-dependent driving forces using N-particle Langevin dynamics simulations. We consider the force to be either sinusoidally oscillating in time or dichotomic noise with exponential correlation time, to mimic both plausible experimental setups and naturally occurring biological conditions. In addition, we consider both the case of purely repulsive polymer-pore interactions and the case with additional attractive polymer-pore interactions, typically occurring inside biological pores. We find that the nature of the interaction fundamentally affects the translocation dynamics. For the non-attractive pore, the translocation time crosses over to a fast translocation regime as the frequency of the driving force decreases. In the attractive pore case, because of a free energy well induced inside the pore, the translocation time can be a minimum at the optimal frequency of the force, the so-called resonant activation. In the latter case, we examine the effect of various physical parameters on the resonant activation, and explain our observations using simple theoretical arguments.

An argument for mechanism-based statistical inference in cancer

PubMed Central

Ochs, Michael; Price, Nathan D.; Tomasetti, Cristian; Younes, Laurent

2015-01-01

Cancer is perhaps the prototypical systems disease, and as such has been the focus of extensive study in quantitative systems biology. However, translating these programs into personalized clinical care remains elusive and incomplete. In this perspective, we argue that realizing this agenda—in particular, predicting disease phenotypes, progression and treatment response for individuals—requires going well beyond standard computational and bioinformatics tools and algorithms. It entails designing global mathematical models over network-scale configurations of genomic states and molecular concentrations, and learning the model parameters from limited available samples of high-dimensional and integrative omics data. As such, any plausible design should accommodate: biological mechanism, necessary for both feasible learning and interpretable decision making; stochasticity, to deal with uncertainty and observed variation at many scales; and a capacity for statistical inference at the patient level. This program, which requires a close, sustained collaboration between mathematicians and biologists, is illustrated in several contexts, including learning bio-markers, metabolism, cell signaling, network inference and tumorigenesis. PMID:25381197

Testing biological effects of hand-washing grey water for reuse in irrigation on an urban farm: a case study.

PubMed

Khan, Mohammad Zain; Sim, Yei Lin; Lin, Yang Jian; Lai, Ka Man

2013-01-01

The feasibility of reusing hand-washing grey water contaminated with antibacterial hand-washing liquid for irrigation purposes in an urban farm is explored in this case study. Experiments are carried out to investigate if the quality of this grey water allows for its reuse in agriculture as per the guidelines established by the World Health Organization (WHO). However, there is no guideline to test the biological effect of grey water prior to agricultural use. It is plausible that the antibacterial property of the grey water can harm the soil microbial system and plants when applied to land, even if all other water quality parameters satisfy the WHO limit. We use algae (Chlorella vulgaris) and indigenous soil bacteria as initial plant and soil bacteria indicators, respectively, to test the potential inhibition of the water on plants and soil bacteria. Results show that the chemical oxygen demand (COD) of the grey water is 10% higher than the WHO permissible level, while all other water quality parameters are within the limits after four days of our experimental period. An inhibitory effect is observed in all of the biological tests. However, the inhibitory effect on algae and soil bacteria is not observed after the four-day period. The case study demonstrates a new approach for testing the biological effect of grey water, which can be used in conjunction with the WHO guideline, and provides data for this urban farm to set up a future water treatment system for grey-water reuse in irrigation.

Dormancy and Recovery Testing for Biological Wastewater Processors

NASA Technical Reports Server (NTRS)

Hummerick, Mary F.; Coutts, Janelle L.; Lunn, Griffin M.; Spencer, LaShelle; Khodadad, Christina L.; Birmele, Michele N.; Frances, Someliz; Wheeler, Raymond

2015-01-01

Resource recovery and recycling waste streams to usable water via biological water processors is a plausible component of an integrated water purification system. Biological processing as a pretreatment can reduce the load of organic carbon and nitrogen compounds entering physiochemical systems downstream. Aerated hollow fiber membrane bioreactors, have been proposed and studied for a number of years as an approach for treating wastewater streams for space exploration.

Mathematical Modeling of RNA-Based Architectures for Closed Loop Control of Gene Expression.

PubMed

Agrawal, Deepak K; Tang, Xun; Westbrook, Alexandra; Marshall, Ryan; Maxwell, Colin S; Lucks, Julius; Noireaux, Vincent; Beisel, Chase L; Dunlop, Mary J; Franco, Elisa

2018-05-08

Feedback allows biological systems to control gene expression precisely and reliably, even in the presence of uncertainty, by sensing and processing environmental changes. Taking inspiration from natural architectures, synthetic biologists have engineered feedback loops to tune the dynamics and improve the robustness and predictability of gene expression. However, experimental implementations of biomolecular control systems are still far from satisfying performance specifications typically achieved by electrical or mechanical control systems. To address this gap, we present mathematical models of biomolecular controllers that enable reference tracking, disturbance rejection, and tuning of the temporal response of gene expression. These controllers employ RNA transcriptional regulators to achieve closed loop control where feedback is introduced via molecular sequestration. Sensitivity analysis of the models allows us to identify which parameters influence the transient and steady state response of a target gene expression process, as well as which biologically plausible parameter values enable perfect reference tracking. We quantify performance using typical control theory metrics to characterize response properties and provide clear selection guidelines for practical applications. Our results indicate that RNA regulators are well-suited for building robust and precise feedback controllers for gene expression. Additionally, our approach illustrates several quantitative methods useful for assessing the performance of biomolecular feedback control systems.

Magnetic field effects in proteins

NASA Astrophysics Data System (ADS)

Jones, Alex R.

2016-06-01

Many animals can sense the geomagnetic field, which appears to aid in behaviours such as migration. The influence of man-made magnetic fields on biology, however, is potentially more sinister, with adverse health effects being claimed from exposure to fields from mobile phones or high voltage power lines. Do these phenomena have a common, biophysical origin, and is it even plausible that such weak fields can profoundly impact noisy biological systems? Radical pair intermediates are widespread in protein reaction mechanisms, and the radical pair mechanism has risen to prominence as perhaps the most plausible means by which even very weak fields might impact biology. In this New Views article, I will discuss the literature over the past 40 years that has investigated the topic of magnetic field effects in proteins. The lack of reproducible results has cast a shadow over the area. However, magnetic field and spin effects have proven to be useful mechanistic tools for radical mechanism in biology. Moreover, if a magnetic effect on a radical pair mechanism in a protein were to influence a biological system, the conditions necessary for it to do so appear increasing unlikely to have come about by chance.

Chasing Perfection: Should We Reduce Model Uncertainty in Carbon Cycle-Climate Feedbacks

NASA Astrophysics Data System (ADS)

Bonan, G. B.; Lombardozzi, D.; Wieder, W. R.; Lindsay, K. T.; Thomas, R. Q.

2015-12-01

Earth system model simulations of the terrestrial carbon (C) cycle show large multi-model spread in the carbon-concentration and carbon-climate feedback parameters. Large differences among models are also seen in their simulation of global vegetation and soil C stocks and other aspects of the C cycle, prompting concern about model uncertainty and our ability to faithfully represent fundamental aspects of the terrestrial C cycle in Earth system models. Benchmarking analyses that compare model simulations with common datasets have been proposed as a means to assess model fidelity with observations, and various model-data fusion techniques have been used to reduce model biases. While such efforts will reduce multi-model spread, they may not help reduce uncertainty (and increase confidence) in projections of the C cycle over the twenty-first century. Many ecological and biogeochemical processes represented in Earth system models are poorly understood at both the site scale and across large regions, where biotic and edaphic heterogeneity are important. Our experience with the Community Land Model (CLM) suggests that large uncertainty in the terrestrial C cycle and its feedback with climate change is an inherent property of biological systems. The challenge of representing life in Earth system models, with the rich diversity of lifeforms and complexity of biological systems, may necessitate a multitude of modeling approaches to capture the range of possible outcomes. Such models should encompass a range of plausible model structures. We distinguish between model parameter uncertainty and model structural uncertainty. Focusing on improved parameter estimates may, in fact, limit progress in assessing model structural uncertainty associated with realistically representing biological processes. Moreover, higher confidence may be achieved through better process representation, but this does not necessarily reduce uncertainty.

Mean-field models for heterogeneous networks of two-dimensional integrate and fire neurons.

PubMed

Nicola, Wilten; Campbell, Sue Ann

2013-01-01

We analytically derive mean-field models for all-to-all coupled networks of heterogeneous, adapting, two-dimensional integrate and fire neurons. The class of models we consider includes the Izhikevich, adaptive exponential and quartic integrate and fire models. The heterogeneity in the parameters leads to different moment closure assumptions that can be made in the derivation of the mean-field model from the population density equation for the large network. Three different moment closure assumptions lead to three different mean-field systems. These systems can be used for distinct purposes such as bifurcation analysis of the large networks, prediction of steady state firing rate distributions, parameter estimation for actual neurons and faster exploration of the parameter space. We use the mean-field systems to analyze adaptation induced bursting under realistic sources of heterogeneity in multiple parameters. Our analysis demonstrates that the presence of heterogeneity causes the Hopf bifurcation associated with the emergence of bursting to change from sub-critical to super-critical. This is confirmed with numerical simulations of the full network for biologically reasonable parameter values. This change decreases the plausibility of adaptation being the cause of bursting in hippocampal area CA3, an area with a sizable population of heavily coupled, strongly adapting neurons.

Mean-field models for heterogeneous networks of two-dimensional integrate and fire neurons

PubMed Central

Nicola, Wilten; Campbell, Sue Ann

2013-01-01

We analytically derive mean-field models for all-to-all coupled networks of heterogeneous, adapting, two-dimensional integrate and fire neurons. The class of models we consider includes the Izhikevich, adaptive exponential and quartic integrate and fire models. The heterogeneity in the parameters leads to different moment closure assumptions that can be made in the derivation of the mean-field model from the population density equation for the large network. Three different moment closure assumptions lead to three different mean-field systems. These systems can be used for distinct purposes such as bifurcation analysis of the large networks, prediction of steady state firing rate distributions, parameter estimation for actual neurons and faster exploration of the parameter space. We use the mean-field systems to analyze adaptation induced bursting under realistic sources of heterogeneity in multiple parameters. Our analysis demonstrates that the presence of heterogeneity causes the Hopf bifurcation associated with the emergence of bursting to change from sub-critical to super-critical. This is confirmed with numerical simulations of the full network for biologically reasonable parameter values. This change decreases the plausibility of adaptation being the cause of bursting in hippocampal area CA3, an area with a sizable population of heavily coupled, strongly adapting neurons. PMID:24416013

On the biological plausibility of Wind Turbine Syndrome.

PubMed

Harrison, Robert V

2015-01-01

An emerging environmental health issue relates to potential ill-effects of wind turbine noise. There have been numerous suggestions that the low-frequency acoustic components in wind turbine signals can cause symptoms associated with vestibular system disorders, namely vertigo, nausea, and nystagmus. This constellation of symptoms has been labeled as Wind Turbine Syndrome, and has been identified in case studies of individuals living close to wind farms. This review discusses whether it is biologically plausible for the turbine noise to stimulate the vestibular parts of the inner ear and, by extension, cause Wind Turbine Syndrome. We consider the sound levels that can activate the semicircular canals or otolith end organs in normal subjects, as well as in those with preexisting conditions known to lower vestibular threshold to sound stimulation.

A case study of evolutionary computation of biochemical adaptation

NASA Astrophysics Data System (ADS)

François, Paul; Siggia, Eric D.

2008-06-01

Simulations of evolution have a long history, but their relation to biology is questioned because of the perceived contingency of evolution. Here we provide an example of a biological process, adaptation, where simulations are argued to approach closer to biology. Adaptation is a common feature of sensory systems, and a plausible component of other biochemical networks because it rescales upstream signals to facilitate downstream processing. We create random gene networks numerically, by linking genes with interactions that model transcription, phosphorylation and protein-protein association. We define a fitness function for adaptation in terms of two functional metrics, and show that any reasonable combination of them will yield the same adaptive networks after repeated rounds of mutation and selection. Convergence to these networks is driven by positive selection and thus fast. There is always a path in parameter space of continuously improving fitness that leads to perfect adaptation, implying that the actual mutation rates we use in the simulation do not bias the results. Our results imply a kinetic view of evolution, i.e., it favors gene networks that can be learned quickly from the random examples supplied by mutation. This formulation allows for deductive predictions of the networks realized in nature.

A Biologically Plausible Action Selection System for Cognitive Architectures: Implications of Basal Ganglia Anatomy for Learning and Decision-Making Models

ERIC Educational Resources Information Center

Stocco, Andrea

2018-01-01

Several attempts have been made previously to provide a biological grounding for cognitive architectures by relating their components to the computations of specific brain circuits. Often, the architecture's action selection system is identified with the basal ganglia. However, this identification overlooks one of the most important features of…

On the biological plausibility of grandmother cells: implications for neural network theories in psychology and neuroscience.

PubMed

Bowers, Jeffrey S

2009-01-01

A fundamental claim associated with parallel distributed processing (PDP) theories of cognition is that knowledge is coded in a distributed manner in mind and brain. This approach rejects the claim that knowledge is coded in a localist fashion, with words, objects, and simple concepts (e.g. "dog"), that is, coded with their own dedicated representations. One of the putative advantages of this approach is that the theories are biologically plausible. Indeed, advocates of the PDP approach often highlight the close parallels between distributed representations learned in connectionist models and neural coding in brain and often dismiss localist (grandmother cell) theories as biologically implausible. The author reviews a range a data that strongly challenge this claim and shows that localist models provide a better account of single-cell recording studies. The author also contrast local and alternative distributed coding schemes (sparse and coarse coding) and argues that common rejection of grandmother cell theories in neuroscience is due to a misunderstanding about how localist models behave. The author concludes that the localist representations embedded in theories of perception and cognition are consistent with neuroscience; biology only calls into question the distributed representations often learned in PDP models.

COLLABORATION ON NHEERL EPIDEMIOLOGY STUDIES

EPA Science Inventory

This task will continue ORD's efforts to develop a biologically plausible, quantitative health risk model for particulate matter (PM) based on epidemiological, toxicological, and mechanistic studies using matched exposure assessments. The NERL, in collaboration with the NHEERL, ...

Empiricists are from Venus, modelers are from Mars: Reconciling experimental and computational approaches in cognitive neuroscience.

PubMed

Cowell, Rosemary A; Bussey, Timothy J; Saksida, Lisa M

2012-11-01

We describe how computational models can be useful to cognitive and behavioral neuroscience, and discuss some guidelines for deciding whether a model is useful. We emphasize that because instantiating a cognitive theory as a computational model requires specification of an explicit mechanism for the function in question, it often produces clear and novel behavioral predictions to guide empirical research. However, computational modeling in cognitive and behavioral neuroscience remains somewhat rare, perhaps because of misconceptions concerning the use of computational models (in particular, connectionist models) in these fields. We highlight some common misconceptions, each of which relates to an aspect of computational models: the problem space of the model, the level of biological organization at which the model is formulated, and the importance (or not) of biological plausibility, parsimony, and model parameters. Careful consideration of these aspects of a model by empiricists, along with careful delineation of them by modelers, may facilitate communication between the two disciplines and promote the use of computational models for guiding cognitive and behavioral experiments. Copyright © 2012 Elsevier Ltd. All rights reserved.

The role of selective predation in harmful algal blooms

NASA Astrophysics Data System (ADS)

Solé, Jordi; Garcia-Ladona, Emilio; Estrada, Marta

2006-08-01

A feature of marine plankton communities is the occurrence of rapid population explosions. When the blooming species are directly or indirectly noxious for humans, these proliferations are denoted as harmful algal blooms (HAB). The importance of biological interactions for the appearance of HABs, in particular when the proliferating microalgae produce toxins that affect other organisms in the food web, remains still poorly understood. Here we analyse the role of toxins produced by a microalgal species and affecting its predators, in determining the success of that species as a bloom former. A three-species predator-prey model is used to define a criterion that determines whether a toxic microalga will be able to initiate a bloom in competition against a non-toxic one with higher growth rate. Dominance of the toxic species depends on a critical parameter that defines the degree of feeding selectivity by grazers. The criterion is applied to a particular simplified model and to numerical simulations of a full marine ecosystem model. The results suggest that the release of toxic compounds affecting predators may be a plausible biological factor in allowing the development of HABs.

Bringing metabolic networks to life: convenience rate law and thermodynamic constraints

PubMed Central

Liebermeister, Wolfram; Klipp, Edda

2006-01-01

Background Translating a known metabolic network into a dynamic model requires rate laws for all chemical reactions. The mathematical expressions depend on the underlying enzymatic mechanism; they can become quite involved and may contain a large number of parameters. Rate laws and enzyme parameters are still unknown for most enzymes. Results We introduce a simple and general rate law called "convenience kinetics". It can be derived from a simple random-order enzyme mechanism. Thermodynamic laws can impose dependencies on the kinetic parameters. Hence, to facilitate model fitting and parameter optimisation for large networks, we introduce thermodynamically independent system parameters: their values can be varied independently, without violating thermodynamical constraints. We achieve this by expressing the equilibrium constants either by Gibbs free energies of formation or by a set of independent equilibrium constants. The remaining system parameters are mean turnover rates, generalised Michaelis-Menten constants, and constants for inhibition and activation. All parameters correspond to molecular energies, for instance, binding energies between reactants and enzyme. Conclusion Convenience kinetics can be used to translate a biochemical network – manually or automatically - into a dynamical model with plausible biological properties. It implements enzyme saturation and regulation by activators and inhibitors, covers all possible reaction stoichiometries, and can be specified by a small number of parameters. Its mathematical form makes it especially suitable for parameter estimation and optimisation. Parameter estimates can be easily computed from a least-squares fit to Michaelis-Menten values, turnover rates, equilibrium constants, and other quantities that are routinely measured in enzyme assays and stored in kinetic databases. PMID:17173669

Prognostic factors of methotrexate-associated lymphoproliferative disorders associated with rheumatoid arthritis and plausible application of biological agents.

PubMed

Katsuyama, Takayuki; Sada, Ken-Ei; Yan, Minglu; Zeggar, Sonia; Hiramatsu, Sumie; Miyawaki, Yoshia; Ohashi, Keiji; Morishita, Michiko; Watanabe, Haruki; Katsuyama, Eri; Takano-Narazaki, Mariko; Toyota-Tatebe, Noriko; Sunahori-Watanabe, Katsue; Kawabata, Tomoko; Miyake, Kohei; Kiguchi, Toru; Wada, Jun

2017-09-01

To determine prognostic factors of methotrexate-associated lymphoproliferative disorder (MTX-LPD) and evaluate the efficacy and safety of biological therapy in rheumatoid arthritis (RA) complicated with MTX-LPD. Thirty RA patients who developed MTX-LPD were investigated in this study. We compared the clinical and laboratory parameters of patients who achieved regression of LPD by MTX withdrawal with those who required chemotherapy and evaluated the clinical course of RA after LPD development. Twenty-three patients (76.7%) achieved regression of LPD by MTX withdrawal. Chemotherapy-free patients had a tendency of shorter RA duration (13.1 vs. 22.0 years, p = 0.108) and higher doses of MTX at LPD diagnosis (8.0 vs. 5.3 mg/w, p = 0.067) than patients who required chemotherapy. A significantly higher positive rate of peripheral blood Epstein-Barr virus (EBV)-DNA was observed in the chemotherapy-free group (9/9 vs. 0/3, p = 0.0002). Of 15 patients that received biological agents after LPD development, 14 patients (93.3%) demonstrated an improved disease activity of RA and persistent remission of LPD, whereas only one patient experienced relapse of LPD during tocilizumab therapy. Peripheral blood EBV-DNA positivity is a potential prognostic marker of better outcome in MTX-LPD. Biological agents could be an option for the treatment of RA patients with MTX-LPD.

Stimulants and sudden death: what is a physician to do?

PubMed

Wilens, Timothy E; Prince, Jefferson B; Spencer, Thomas J; Biederman, Joseph

2006-09-01

Recently, a US Food and Drug Administration advisory committee raised concerns about cardiovascular risks and sudden death in children and adolescents with attention-deficit/hyperactivity disorder who are receiving stimulants. We comment on the risk of sudden death in children/adolescents taking stimulants compared with population rates, biological plausibility, and known cardiovascular effects of stimulants to determine specific risk. There does not seem to be higher risk of sudden death in stimulant-treated individuals compared with the general population. Although there is evidence of biological plausibility, the known effects of the stimulants on cardiovascular electrophysiology and vital signs seem to be benign. There does not seem to be compelling findings of a medication-specific risk necessitating changes in our stimulant treatment of children and adolescents with attention-deficit/hyperactivity disorder. The use of existing guidelines on the use of stimulants (and psychotropic agents) may identify children, adolescents, and adults who are vulnerable to sudden death.

A Biologically Plausible Transform for Visual Recognition that is Invariant to Translation, Scale, and Rotation.

PubMed

Sountsov, Pavel; Santucci, David M; Lisman, John E

2011-01-01

Visual object recognition occurs easily despite differences in position, size, and rotation of the object, but the neural mechanisms responsible for this invariance are not known. We have found a set of transforms that achieve invariance in a neurally plausible way. We find that a transform based on local spatial frequency analysis of oriented segments and on logarithmic mapping, when applied twice in an iterative fashion, produces an output image that is unique to the object and that remains constant as the input image is shifted, scaled, or rotated.

A Biologically Plausible Transform for Visual Recognition that is Invariant to Translation, Scale, and Rotation

PubMed Central

Sountsov, Pavel; Santucci, David M.; Lisman, John E.

2011-01-01

Visual object recognition occurs easily despite differences in position, size, and rotation of the object, but the neural mechanisms responsible for this invariance are not known. We have found a set of transforms that achieve invariance in a neurally plausible way. We find that a transform based on local spatial frequency analysis of oriented segments and on logarithmic mapping, when applied twice in an iterative fashion, produces an output image that is unique to the object and that remains constant as the input image is shifted, scaled, or rotated. PMID:22125522

Parameters, Journal of the U.S. Army War College. Volume 17, Number 1, Spring 1987

DTIC Science & Technology

1987-01-01

way that makes sense to a reader and then explaining them. Enter the clement of judgment, which immediately puts the reporter on a slippery slope ...reformers support something they call maneuver warfare. The concept of maneuver is itself a slippery one that the reformers describe using terms such as...nuclear euthanasia . So just as the military power must have a plausible enemy, so also it must have a plausible design for countering the public threat

More on Grandmother Cells and the Biological Implausibility of PDP Models of Cognition: A Reply to Plaut and McClelland (2010) and Quian Quiroga and Kreiman (2010)

ERIC Educational Resources Information Center

Bowers, Jeffrey S.

2010-01-01

Plaut and McClelland (2010) and Quian Quiroga and Kreiman both challenged my characterization of localist and distributed representations. They also challenged the biological plausibility of grandmother cells on conceptual and empirical grounds. This reply addresses these issues in turn. The premise of my argument is that grandmother cells in…

IN VIVO MECHANISMS OF PARTICULATE MATTER (PM)-INDUCED LUNG AND VASCULAR INJURY

EPA Science Inventory

Insight into the mechanisms by which ambient particulate matter (PM) mediates its adverse cardiopulmonary effects can provide biological plausibility to epidemiological associations between PM exposure and health effects. Current information on mechanisms of pulmonary injury have...

An ecological valence theory of human color preference.

PubMed

Palmer, Stephen E; Schloss, Karen B

2010-05-11

Color preference is an important aspect of visual experience, but little is known about why people in general like some colors more than others. Previous research suggested explanations based on biological adaptations [Hurlbert AC, Ling YL (2007) Curr Biol 17:623-625] and color-emotions [Ou L-C, Luo MR, Woodcock A, Wright A (2004) Color Res Appl 29:381-389]. In this article we articulate an ecological valence theory in which color preferences arise from people's average affective responses to color-associated objects. An empirical test provides strong support for this theory: People like colors strongly associated with objects they like (e.g., blues with clear skies and clean water) and dislike colors strongly associated with objects they dislike (e.g., browns with feces and rotten food). Relative to alternative theories, the ecological valence theory both fits the data better (even with fewer free parameters) and provides a more plausible, comprehensive causal explanation of color preferences.

Reporting Confidence Intervals and Effect Sizes: Collecting the Evidence

ERIC Educational Resources Information Center

Zientek, Linda Reichwein; Ozel, Z. Ebrar Yetkiner; Ozel, Serkan; Allen, Jeff

2012-01-01

Confidence intervals (CIs) and effect sizes are essential to encourage meta-analytic thinking and to accumulate research findings. CIs provide a range of plausible values for population parameters with a degree of confidence that the parameter is in that particular interval. CIs also give information about how precise the estimates are. Comparison…

OXIDATIVE STRESS MEDIATES AIR POLLUTION PARTICLE-INDUCED ACUTE LUNG INJURY AND MOLECULAR PATHOLOGY

EPA Science Inventory

Abstract
Insight into the mechanism(s) by which ambient air particulate matter (PM) mediates adverse health effects is needed to provide biological plausibility to epidemiological studies demonstrating associations between PM exposure and increased morbidity and mortality. Alt...

THE ROLE OF PROTEIN BINDING OF TRIVALENT ARSENICALS IN ARSENIC CARCINOGENESIS AND TOXICITY

EPA Science Inventory

Three of the most plausible biological theories of arsenic carcinogenesis are protein binding, oxidative stress and altered DNA methylation. This review presents the role of trivalent arsenicals binding to proteins in arsenic carcinogenesis. Using vacuum filtration based receptor...

Efficient design based on perturbed parameter ensembles to identify plausible and diverse variants of a model for climate change projections

NASA Astrophysics Data System (ADS)

Karmalkar, A.; Sexton, D.; Murphy, J.

2017-12-01

We present exploratory work towards developing an efficient strategy to select variants of a state-of-the-art but expensive climate model suitable for climate projection studies. The strategy combines information from a set of idealized perturbed parameter ensemble (PPE) and CMIP5 multi-model ensemble (MME) experiments, and uses two criteria as basis to select model variants for a PPE suitable for future projections: a) acceptable model performance at two different timescales, and b) maintaining diversity in model response to climate change. We demonstrate that there is a strong relationship between model errors at weather and climate timescales for a variety of key variables. This relationship is used to filter out parts of parameter space that do not give credible simulations of historical climate, while minimizing the impact on ranges in forcings and feedbacks that drive model responses to climate change. We use statistical emulation to explore the parameter space thoroughly, and demonstrate that about 90% can be filtered out without affecting diversity in global-scale climate change responses. This leads to identification of plausible parts of parameter space from which model variants can be selected for projection studies.

Photoinduced catalytic synthesis of biologically important metabolites from formaldehyde and ammonia under plausible "prebiotic" conditions

NASA Astrophysics Data System (ADS)

Delidovich, I. V.; Taran, O. P.; Simonov, A. N.; Matvienko, L. G.; Parmon, V. N.

2011-08-01

The article analyzes new and previously reported data on several catalytic and photochemical processes yielding biologically important molecules. UV-irradiation of formaldehyde aqueous solution yields acetaldehyde, glyoxal, glycolaldehyde and glyceraldehyde, which can serve as precursors of more complex biochemically relevant compounds. Photolysis of aqueous solution of acetaldehyde and ammonium nitrate results in formation of alanine and pyruvic acid. Dehydration of glyceraldehyde catalyzed by zeolite HZSM-5-17 yields pyruvaldehyde. Monosaccharides are formed in the course of the phosphate-catalyzed aldol condensation reactions of glycolaldehyde, glyceraldehyde and formaldehyde. The possibility of the direct synthesis of tetroses, keto- and aldo-pentoses from pure formaldehyde due to the combination of the photochemical production of glycolahyde and phosphate-catalyzed carbohydrate chain growth is demonstrated. Erythrulose and 3-pentulose are the main products of such combined synthesis with selectivity up to 10%. Biologically relevant aldotetroses, aldo- and ketopentoses are more resistant to the photochemical destruction owing to the stabilization in hemiacetal cyclic forms. They are formed as products of isomerization of erythrulose and 3-pentulose. The conjugation of the concerned reactions results in a plausible route to the formation of sugars, amino and organic acids from formaldehyde and ammonia under presumed 'prebiotic' conditions.

A race-specific interaction between vitamin K status and statin use

USDA-ARS?s Scientific Manuscript database

The oral anticoagulant warfarin is a vitamin K antagonist. Phylloquinone, the primary circulating form of vitamin K, is transported by triglyceride-rich lipoproteins and shares a metabolic pathway with cholesterol. Thus, there is biological plausibility for an interaction between serum phylloquinone...

CAUSAL ANALYSIS AND PROBABILITY DATA: EXAMPLES FOR IMPAIRED AQUATIC CONDITION

EPA Science Inventory

Causal analysis is plausible reasoning applied to diagnosing observed effect(s), for example, diagnosing

cause of biological impairment in a stream. Sir Bradford Hill basically defined the application of causal

analysis when he enumerated the elements of causality f...

An epidemiological examination of the subluxation construct using Hill's criteria of causation.

PubMed

Mirtz, Timothy A; Morgan, Lon; Wyatt, Lawrence H; Greene, Leon

2009-12-02

Chiropractors claim to locate, analyze and diagnose a putative spinal lesion known as subluxation and apply the mode of spinal manipulation (adjustment) for the correction of this lesion. The purpose of this examination is to review the current evidence on the epidemiology of the subluxation construct and to evaluate the subluxation by applying epidemiologic criteria for it's significance as a causal factor. The databases of PubMed, Cinahl, and Mantis were searched for studies using the keywords subluxation, epidemiology, manipulation, dose-response, temporality, odds ratio, relative risk, biological plausibility, coherence, and analogy. The criteria for causation in epidemiology are strength (strength of association), consistency, specificity, temporality (temporal sequence), dose response, experimental evidence, biological plausibility, coherence, and analogy. Applied to the subluxation all of these criteria remain for the most part unfulfilled. There is a significant lack of evidence to fulfill the basic criteria of causation. This lack of crucial supportive epidemiologic evidence prohibits the accurate promulgation of the chiropractic subluxation.

An epidemiological examination of the subluxation construct using Hill's criteria of causation

PubMed Central

2009-01-01

Background Chiropractors claim to locate, analyze and diagnose a putative spinal lesion known as subluxation and apply the mode of spinal manipulation (adjustment) for the correction of this lesion. Aim The purpose of this examination is to review the current evidence on the epidemiology of the subluxation construct and to evaluate the subluxation by applying epidemiologic criteria for it's significance as a causal factor. Methods The databases of PubMed, Cinahl, and Mantis were searched for studies using the keywords subluxation, epidemiology, manipulation, dose-response, temporality, odds ratio, relative risk, biological plausibility, coherence, and analogy. Results The criteria for causation in epidemiology are strength (strength of association), consistency, specificity, temporality (temporal sequence), dose response, experimental evidence, biological plausibility, coherence, and analogy. Applied to the subluxation all of these criteria remain for the most part unfulfilled. Conclusion There is a significant lack of evidence to fulfill the basic criteria of causation. This lack of crucial supportive epidemiologic evidence prohibits the accurate promulgation of the chiropractic subluxation. PMID:19954544

Eco-friendly synthesis, physicochemical studies, biological assay and molecular docking of steroidal oxime-ethers

PubMed Central

Alam, Mahboob; Lee, Dong-Ung

2015-01-01

The aim of this study was to report the synthesis of biologically active compounds; 7-(2′-aminoethoxyimino)-cholest-5-ene (4), a steroidal oxime-ether and its derivatives (5, 6) via a facile microwave assisted solvent free reaction methodology. This new synthetic, eco-friendly, sustainable protocol resulted in a remarkable improvement in the synthetic efficiency (85-93 % yield) and high purity using basic alumina. The synthesized compounds were screened for their antibacterial against six bacterial strains by disc diffusion method and antioxidant potential by DPPH assay. The binding capabilities of a compound 6 exhibiting good antibacterial potential were assessed on the basis of molecular docking studies and four types of three-dimensional molecular field descriptors. Moreover the structure-antimicrobial activity relationships were studied using some physicochemical and quantum-chemical parameters with GAMESS interface as well as WebMO Job Manager by using the basic level of theory. Hence, this synthetic approach is believed to provide a better scope for the synthesis of steroidal oxime-ether analogues and will be a more practical alternative to the presently existing procedures. Moreover, detailed in silico docking studies suggested the plausible mechanism of steroidal oxime-ethers as effective antimicrobial agents. PMID:27330525

Automated Oligopeptide Formation Under Simple Programmable Conditions

NASA Astrophysics Data System (ADS)

Suárez-Marina, I.; Rodriguez-Garcia, M.; Surman, A. J.; Cooper, G. J. T.; Cronin, L.

2017-07-01

Traditionally, prebiotic chemistry has investigated the formation of life's precursors under very specific conditions thought to be "plausible". Herein, we explore peptide formation studying several parameters at once by using an automated platform.

Role of the locus coeruleus in the emergence of power law wake bouts in a model of the brainstem sleep-wake system through early infancy.

PubMed

Patel, Mainak; Rangan, Aaditya

2017-08-07

Infant rats randomly cycle between the sleeping and waking states, which are tightly correlated with the activity of mutually inhibitory brainstem sleep and wake populations. Bouts of sleep and wakefulness are random; from P2-P10, sleep and wake bout lengths are exponentially distributed with increasing means, while during P10-P21, the sleep bout distribution remains exponential while the distribution of wake bouts gradually transforms to power law. The locus coeruleus (LC), via an undeciphered interaction with sleep and wake populations, has been shown experimentally to be responsible for the exponential to power law transition. Concurrently during P10-P21, the LC undergoes striking physiological changes - the LC exhibits strong global 0.3 Hz oscillations up to P10, but the oscillation frequency gradually rises and synchrony diminishes from P10-P21, with oscillations and synchrony vanishing at P21 and beyond. In this work, we construct a biologically plausible Wilson Cowan-style model consisting of the LC along with sleep and wake populations. We show that external noise and strong reciprocal inhibition can lead to switching between sleep and wake populations and exponentially distributed sleep and wake bout durations as during P2-P10, with the parameters of inhibition between the sleep and wake populations controlling mean bout lengths. Furthermore, we show that the changing physiology of the LC from P10-P21, coupled with reciprocal excitation between the LC and wake population, can explain the shift from exponential to power law of the wake bout distribution. To our knowledge, this is the first study that proposes a plausible biological mechanism, which incorporates the known changing physiology of the LC, for tying the developing sleep-wake circuit and its interaction with the LC to the transformation of sleep and wake bout dynamics from P2-P21. Copyright © 2017 Elsevier Ltd. All rights reserved.

Rapid Debris Analysis Project Task 3 Final Report - Sensitivity of Fallout to Source Parameters, Near-Detonation Environment Material Properties, Topography, and Meteorology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Goldstein, Peter

2014-01-24

This report describes the sensitivity of predicted nuclear fallout to a variety of model input parameters, including yield, height of burst, particle and activity size distribution parameters, wind speed, wind direction, topography, and precipitation. We investigate sensitivity over a wide but plausible range of model input parameters. In addition, we investigate a specific example with a relatively narrow range to illustrate the potential for evaluating uncertainties in predictions when there are more precise constraints on model parameters.

Inverse Ising problem in continuous time: A latent variable approach

NASA Astrophysics Data System (ADS)

Donner, Christian; Opper, Manfred

2017-12-01

We consider the inverse Ising problem: the inference of network couplings from observed spin trajectories for a model with continuous time Glauber dynamics. By introducing two sets of auxiliary latent random variables we render the likelihood into a form which allows for simple iterative inference algorithms with analytical updates. The variables are (1) Poisson variables to linearize an exponential term which is typical for point process likelihoods and (2) Pólya-Gamma variables, which make the likelihood quadratic in the coupling parameters. Using the augmented likelihood, we derive an expectation-maximization (EM) algorithm to obtain the maximum likelihood estimate of network parameters. Using a third set of latent variables we extend the EM algorithm to sparse couplings via L1 regularization. Finally, we develop an efficient approximate Bayesian inference algorithm using a variational approach. We demonstrate the performance of our algorithms on data simulated from an Ising model. For data which are simulated from a more biologically plausible network with spiking neurons, we show that the Ising model captures well the low order statistics of the data and how the Ising couplings are related to the underlying synaptic structure of the simulated network.

Multiple biomarkers and risk of clinical and subclinical vascular brain injury: the framingham offspring study

USDA-ARS?s Scientific Manuscript database

Several biomarkers have been individually associated with vascular brain injury, but no prior study has explored the simultaneous association of a biologically plausible panel of biomarkers with the incidence of stroke/transient ischemic attack and the prevalence of subclinical brain injury. In 3127...

Detection of Low-order Curves in Images using Biologically-plausible Hardware

DTIC Science & Technology

2012-09-29

the intersections of iso-eccentricity and iso-polar contours were entered into the computer via a graphics tablet . In regions where there was...functional mri . Cerebral Cortex, 7:181 – 192, 1997. [25] Jacob Feldman. Bayesian contour integration. Perception and Psychophysics, 63:1171 – 1182, 2001. [26

Fibromyalgia at an Educational Facility--Is There a Link to Indoor Air Quality?

ERIC Educational Resources Information Center

Wilson, Emily J.

1999-01-01

Discusses whether it is biologically plausible for an environmental laboratory contaminant to cause fibromyalgia. Presents a study of two populations which indicated that fibromyalgia was occurring at an elevated rate in a building where ventilation was deemed inadequate for laboratory activities. (Author/WRM)

THE EFFECT OF RELATIVE HUMIDITY ON THE UPTAKE OF AROMATIC OXIDATION PRODUCTS ON SUBMICRON AMMONIUM SULFATE AEROSOL

EPA Science Inventory

Epidemiological studies have suggested that fine particulate matter (<2.5 um) is correlated with daily mortality and morbidity in urban areas. At present, no plausible biological or chemical mechanism explains these correlations. Thus, a more complete understanding of the compo...

APPLICATION OF LASER CAPTURE MICRODISSECTION AND PROTEIN MICROARRAY TECHNOLOGIES IN THE MOLECULAR ANALYSIS OF AIRWAY INJURY FOLLOWING POLLUTION PARTICLE EXPOSURE

EPA Science Inventory

Understanding the mechanisms by which various types of air pollution particles (PM) mediate adverse health effects would provide biological plausibility to epidemiological associations of increased rates of morbidity and mortality. The majority of information regarding the means ...

Evaluation of neural reflex activation as a mode of action for the acute respiratory effects of ozone.

PubMed

Prueitt, Robyn L; Goodman, Julie E

2016-09-01

Exposure to elevated levels of ozone has been associated with a variety of respiratory-related health endpoints in both epidemiology and controlled human exposure studies, including lung function decrements and airway inflammation. A mode of action (MoA) for these effects has not been established, but it has been proposed that they may occur through ozone-induced activation of neural reflexes. We critically reviewed experimental studies of ozone exposure and neural reflex activation and applied the International Programme on Chemical Safety (IPCS) mode-of-action/human relevance framework to evaluate the biological plausibility and human relevance of this proposed MoA. Based on the currently available experimental data, we found that the proposed MoA of neural reflex activation is biologically plausible for the endpoint of ozone-induced lung function decrements at high ozone exposures, but further studies are needed to fill important data gaps regarding the relevance of this MoA at lower exposures. A role for the proposed MoA in ozone-induced airway inflammation is less plausible, as the evidence is conflicting and is also of unclear relevance given the lack of studies conducted at lower exposures. The evidence suggests a different MoA for ozone-induced inflammation that may still be linked to the key events in the proposed MoA, such that neural reflex activation may have some degree of involvement in modulating ozone-induced neutrophil influx, even if it is not a direct role.

Thermodynamically consistent model calibration in chemical kinetics

PubMed Central

2011-01-01

Background The dynamics of biochemical reaction systems are constrained by the fundamental laws of thermodynamics, which impose well-defined relationships among the reaction rate constants characterizing these systems. Constructing biochemical reaction systems from experimental observations often leads to parameter values that do not satisfy the necessary thermodynamic constraints. This can result in models that are not physically realizable and may lead to inaccurate, or even erroneous, descriptions of cellular function. Results We introduce a thermodynamically consistent model calibration (TCMC) method that can be effectively used to provide thermodynamically feasible values for the parameters of an open biochemical reaction system. The proposed method formulates the model calibration problem as a constrained optimization problem that takes thermodynamic constraints (and, if desired, additional non-thermodynamic constraints) into account. By calculating thermodynamically feasible values for the kinetic parameters of a well-known model of the EGF/ERK signaling cascade, we demonstrate the qualitative and quantitative significance of imposing thermodynamic constraints on these parameters and the effectiveness of our method for accomplishing this important task. MATLAB software, using the Systems Biology Toolbox 2.1, can be accessed from http://www.cis.jhu.edu/~goutsias/CSS lab/software.html. An SBML file containing the thermodynamically feasible EGF/ERK signaling cascade model can be found in the BioModels database. Conclusions TCMC is a simple and flexible method for obtaining physically plausible values for the kinetic parameters of open biochemical reaction systems. It can be effectively used to recalculate a thermodynamically consistent set of parameter values for existing thermodynamically infeasible biochemical reaction models of cellular function as well as to estimate thermodynamically feasible values for the parameters of new models. Furthermore, TCMC can provide dimensionality reduction, better estimation performance, and lower computational complexity, and can help to alleviate the problem of data overfitting. PMID:21548948

Multiple regimes of robust patterns between network structure and biodiversity

NASA Astrophysics Data System (ADS)

Jover, Luis F.; Flores, Cesar O.; Cortez, Michael H.; Weitz, Joshua S.

2015-12-01

Ecological networks such as plant-pollinator and host-parasite networks have structured interactions that define who interacts with whom. The structure of interactions also shapes ecological and evolutionary dynamics. Yet, there is significant ongoing debate as to whether certain structures, e.g., nestedness, contribute positively, negatively or not at all to biodiversity. We contend that examining variation in life history traits is key to disentangling the potential relationship between network structure and biodiversity. Here, we do so by analyzing a dynamic model of virus-bacteria interactions across a spectrum of network structures. Consistent with prior studies, we find plausible parameter domains exhibiting strong, positive relationships between nestedness and biodiversity. Yet, the same model can exhibit negative relationships between nestedness and biodiversity when examined in a distinct, plausible region of parameter space. We discuss steps towards identifying when network structure could, on its own, drive the resilience, sustainability, and even conservation of ecological communities.

Multiple regimes of robust patterns between network structure and biodiversity

PubMed Central

Jover, Luis F.; Flores, Cesar O.; Cortez, Michael H.; Weitz, Joshua S.

2015-01-01

Ecological networks such as plant-pollinator and host-parasite networks have structured interactions that define who interacts with whom. The structure of interactions also shapes ecological and evolutionary dynamics. Yet, there is significant ongoing debate as to whether certain structures, e.g., nestedness, contribute positively, negatively or not at all to biodiversity. We contend that examining variation in life history traits is key to disentangling the potential relationship between network structure and biodiversity. Here, we do so by analyzing a dynamic model of virus-bacteria interactions across a spectrum of network structures. Consistent with prior studies, we find plausible parameter domains exhibiting strong, positive relationships between nestedness and biodiversity. Yet, the same model can exhibit negative relationships between nestedness and biodiversity when examined in a distinct, plausible region of parameter space. We discuss steps towards identifying when network structure could, on its own, drive the resilience, sustainability, and even conservation of ecological communities. PMID:26632996

Does sufficient evidence exist to support a causal association between vitamin D status and cardiovascular disease risk? An assessment using Hill's criteria for causality.

PubMed

Weyland, Patricia G; Grant, William B; Howie-Esquivel, Jill

2014-09-02

Serum 25-hydroxyvitamin D (25(OH)D) levels have been found to be inversely associated with both prevalent and incident cardiovascular disease (CVD) risk factors; dyslipidemia, hypertension and diabetes mellitus. This review looks for evidence of a causal association between low 25(OH)D levels and increased CVD risk. We evaluated journal articles in light of Hill's criteria for causality in a biological system. The results of our assessment are as follows. Strength of association: many randomized controlled trials (RCTs), prospective and cross-sectional studies found statistically significant inverse associations between 25(OH)D levels and CVD risk factors. Consistency of observed association: most studies found statistically significant inverse associations between 25(OH)D levels and CVD risk factors in various populations, locations and circumstances. Temporality of association: many RCTs and prospective studies found statistically significant inverse associations between 25(OH)D levels and CVD risk factors. Biological gradient (dose-response curve): most studies assessing 25(OH)D levels and CVD risk found an inverse association exhibiting a linear biological gradient. Plausibility of biology: several plausible cellular-level causative mechanisms and biological pathways may lead from a low 25(OH)D level to increased risk for CVD with mediators, such as dyslipidemia, hypertension and diabetes mellitus. Experimental evidence: some well-designed RCTs found increased CVD risk factors with decreasing 25(OH)D levels. Analogy: the association between serum 25(OH)D levels and CVD risk is analogous to that between 25(OH)D levels and the risk of overall cancer, periodontal disease, multiple sclerosis and breast cancer. all relevant Hill criteria for a causal association in a biological system are satisfied to indicate a low 25(OH)D level as a CVD risk factor.

Boolean network inference from time series data incorporating prior biological knowledge.

PubMed

Haider, Saad; Pal, Ranadip

2012-01-01

Numerous approaches exist for modeling of genetic regulatory networks (GRNs) but the low sampling rates often employed in biological studies prevents the inference of detailed models from experimental data. In this paper, we analyze the issues involved in estimating a model of a GRN from single cell line time series data with limited time points. We present an inference approach for a Boolean Network (BN) model of a GRN from limited transcriptomic or proteomic time series data based on prior biological knowledge of connectivity, constraints on attractor structure and robust design. We applied our inference approach to 6 time point transcriptomic data on Human Mammary Epithelial Cell line (HMEC) after application of Epidermal Growth Factor (EGF) and generated a BN with a plausible biological structure satisfying the data. We further defined and applied a similarity measure to compare synthetic BNs and BNs generated through the proposed approach constructed from transitions of various paths of the synthetic BNs. We have also compared the performance of our algorithm with two existing BN inference algorithms. Through theoretical analysis and simulations, we showed the rarity of arriving at a BN from limited time series data with plausible biological structure using random connectivity and absence of structure in data. The framework when applied to experimental data and data generated from synthetic BNs were able to estimate BNs with high similarity scores. Comparison with existing BN inference algorithms showed the better performance of our proposed algorithm for limited time series data. The proposed framework can also be applied to optimize the connectivity of a GRN from experimental data when the prior biological knowledge on regulators is limited or not unique.

A preliminary and qualitative study of resource ratio theory to nitrifying lab-scale bioreactors

PubMed Central

Bellucci, Micol; Ofiţeru, Irina D; Beneduce, Luciano; Graham, David W; Head, Ian M; Curtis, Thomas P

2015-01-01

The incorporation of microbial diversity in design would ideally require predictive theory that would relate operational parameters to the numbers and distribution of taxa. Resource ratio-theory (RRT) might be one such theory. Based on Monod kinetics, it explains diversity in function of resource-ratio and richness. However, to be usable in biological engineered system, the growth parameters of all the bacteria under consideration and the resource supply and diffusion parameters for all the relevant nutrients should be determined. This is challenging, but plausible, at least for low diversity groups with simple resource requirements like the ammonia oxidizing bacteria (AOB). One of the major successes of RRT was its ability to explain the ‘paradox of enrichment’ which states that diversity first increases and then decreases with resource richness. Here, we demonstrate that this pattern can be seen in lab-scale-activated sludge reactors and parallel simulations that incorporate the principles of RRT in a floc-based system. High and low ammonia and oxygen were supplied to continuous flow bioreactors with resource conditions correlating with the composition and diversity of resident AOB communities based on AOB 16S rDNA clone libraries. Neither the experimental work nor the simulations are definitive proof for the application of RRT in this context. However, it is sufficient evidence that such approach might work and justify a more rigorous investigation. PMID:25874592

Increased scientific rigor will improve reliability of research and effectiveness of management

USGS Publications Warehouse

Sells, Sarah N.; Bassing, Sarah B.; Barker, Kristin J.; Forshee, Shannon C.; Keever, Allison; Goerz, James W.; Mitchell, Michael S.

2018-01-01

Rigorous science that produces reliable knowledge is critical to wildlife management because it increases accurate understanding of the natural world and informs management decisions effectively. Application of a rigorous scientific method based on hypothesis testing minimizes unreliable knowledge produced by research. To evaluate the prevalence of scientific rigor in wildlife research, we examined 24 issues of the Journal of Wildlife Management from August 2013 through July 2016. We found 43.9% of studies did not state or imply a priori hypotheses, which are necessary to produce reliable knowledge. We posit that this is due, at least in part, to a lack of common understanding of what rigorous science entails, how it produces more reliable knowledge than other forms of interpreting observations, and how research should be designed to maximize inferential strength and usefulness of application. Current primary literature does not provide succinct explanations of the logic behind a rigorous scientific method or readily applicable guidance for employing it, particularly in wildlife biology; we therefore synthesized an overview of the history, philosophy, and logic that define scientific rigor for biological studies. A rigorous scientific method includes 1) generating a research question from theory and prior observations, 2) developing hypotheses (i.e., plausible biological answers to the question), 3) formulating predictions (i.e., facts that must be true if the hypothesis is true), 4) designing and implementing research to collect data potentially consistent with predictions, 5) evaluating whether predictions are consistent with collected data, and 6) drawing inferences based on the evaluation. Explicitly testing a priori hypotheses reduces overall uncertainty by reducing the number of plausible biological explanations to only those that are logically well supported. Such research also draws inferences that are robust to idiosyncratic observations and unavoidable human biases. Offering only post hoc interpretations of statistical patterns (i.e., a posteriorihypotheses) adds to uncertainty because it increases the number of plausible biological explanations without determining which have the greatest support. Further, post hocinterpretations are strongly subject to human biases. Testing hypotheses maximizes the credibility of research findings, makes the strongest contributions to theory and management, and improves reproducibility of research. Management decisions based on rigorous research are most likely to result in effective conservation of wildlife resources. 

Vitamin K supplementation does not prevent bone loss in ovariectomized Norway rats

USDA-ARS?s Scientific Manuscript database

Despite plausible biological mechanisms, the differential abilities of phylloquinone (PK) and menaquinones (MKn) to prevent bone loss remain controversial. The objective of the current study was to compare the effects of PK, menaquinone-4 (MK-4) and menaquinone-7(MK-7) on the rate of bone loss in o...

Expanding the Role of Connectionism in SLA Theory

ERIC Educational Resources Information Center

Language Learning, 2013

2013-01-01

In this article, I explore how connectionism might expand its role in second language acquisition (SLA) theory by showing how some symbolic models of bilingual and second language lexical memory can be reduced to a biologically realistic (i.e., neurally plausible) connectionist model. This integration or hybridization of the two models follows the…

Fathers, Families, and the Future: A Plethora of Plausible Predictions

ERIC Educational Resources Information Center

Parke, Ross D.

2004-01-01

This commentary focuses on new directions in the study of fathers and families. Several topics that are ripe for more theoretical and empirical scrutiny are outlined. These include the biological determinants of fathering, cultural constraints on fathers, the impact of becoming a father on men?s development as adults, and an intergenerational…

Vibrational soliton: an experimental overview

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bigio, I.J.

1986-03-08

To date the most convincing evidence of vibrational solitons in biopolymers has been found in two very disparate systems: Davydov-like excitations in hydrogen-bonded linear chains (acetanilide and N-methylacetamide) which are not biopolymers but plausible structural paradigms for biopolymers, and longitudinal accoustic modes of possibly nonlinear character in biologically viable DNA. 17 refs., 4 figs.

Breastfeeding and breast cancer risk: an evaluation based on a systematic review of epidemiologic evidence among the Japanese population.

PubMed

Nagata, Chisato; Mizoue, Tetsuya; Tanaka, Keitaro; Tsuji, Ichiro; Tamakoshi, Akiko; Wakai, Kenji; Matsuo, Keitaro; Ito, Hidemi; Sasazuki, Shizuka; Inoue, Manami; Tsugane, Shoichiro

2012-02-01

We reviewed epidemiological studies on breastfeeding and breast cancer among Japanese women. This report is part of a series of articles written by our research group, whose aim was to evaluate the existing evidence concerning the association between health-related lifestyles and cancer. Original data were obtained from MEDLINE searches using PubMed or from searches of the Ichushi database, complemented by manual searches. Evaluation of associations was based on the strength of evidence and the magnitude of association, together with biological plausibility. Three cohort studies and five case-control studies were identified. Cohort studies failed to find a significant inverse association between breastfeeding and the risk of breast cancer. Most of the case-control studies observed a statistically significant or non-significant risk reduction for women who ever had breastfed or for women with a longer duration of breastfeeding. Experimental studies have supported the biological plausibility of a protective effect of breastfeeding on breast cancer risk. We conclude that breastfeeding possibly decreases the risk of breast cancer among Japanese women.

A model of proto-object based saliency

PubMed Central

Russell, Alexander F.; Mihalaş, Stefan; von der Heydt, Rudiger; Niebur, Ernst; Etienne-Cummings, Ralph

2013-01-01

Organisms use the process of selective attention to optimally allocate their computational resources to the instantaneously most relevant subsets of a visual scene, ensuring that they can parse the scene in real time. Many models of bottom-up attentional selection assume that elementary image features, like intensity, color and orientation, attract attention. Gestalt psychologists, how-ever, argue that humans perceive whole objects before they analyze individual features. This is supported by recent psychophysical studies that show that objects predict eye-fixations better than features. In this report we present a neurally inspired algorithm of object based, bottom-up attention. The model rivals the performance of state of the art non-biologically plausible feature based algorithms (and outperforms biologically plausible feature based algorithms) in its ability to predict perceptual saliency (eye fixations and subjective interest points) in natural scenes. The model achieves this by computing saliency as a function of proto-objects that establish the perceptual organization of the scene. All computational mechanisms of the algorithm have direct neural correlates, and our results provide evidence for the interface theory of attention. PMID:24184601

A Biologically Plausible Architecture of the Striatum to Solve Context-Dependent Reinforcement Learning Tasks.

PubMed

Shivkumar, Sabyasachi; Muralidharan, Vignesh; Chakravarthy, V Srinivasa

2017-01-01

Basal ganglia circuit is an important subcortical system of the brain thought to be responsible for reward-based learning. Striatum, the largest nucleus of the basal ganglia, serves as an input port that maps cortical information. Microanatomical studies show that the striatum is a mosaic of specialized input-output structures called striosomes and regions of the surrounding matrix called the matrisomes. We have developed a computational model of the striatum using layered self-organizing maps to capture the center-surround structure seen experimentally and explain its functional significance. We believe that these structural components could build representations of state and action spaces in different environments. The striatum model is then integrated with other components of basal ganglia, making it capable of solving reinforcement learning tasks. We have proposed a biologically plausible mechanism of action-based learning where the striosome biases the matrisome activity toward a preferred action. Several studies indicate that the striatum is critical in solving context dependent problems. We build on this hypothesis and the proposed model exploits the modularity of the striatum to efficiently solve such tasks.

attempted prebiotic synthesis of pseudouridine

NASA Astrophysics Data System (ADS)

DWORKIN, JASON P.

1997-08-01

Pseudouridine is a modified base found in all tRNA and rRNA. Hence, it is reasonable to think that pseudouridine was important in the early evolution, if not the origin, of life. Since uracil reacts rapidly with formaldehyde and other aldehydes at the C-5 position, it is plausible that pseudouridine could be synthesized in a similar way by the reaction of the C-5 of uracil with the C-1 of ribose. The determining factor is whether the ribose could react with the uracil faster than ribose decomposes. However, both rates are determined by the amount of free aldehyde in the ribose. Various plausible prebiotic reactions were investigated and none showed pseudouridine above the detection limit (<0.01%). Only unreacted uracil and ribose decomposition products could be observed. Thus the rate of addition of ribose to uracil is much slower than the decomposition of ribose under any reasonable prebiotic conditions. Unless efficient non-biological catalysts for any of these reactions exist, pseudouridine would not have been synthesized to any significant extent without the use of biologically produced enzymes.

A Biologically Plausible Architecture of the Striatum to Solve Context-Dependent Reinforcement Learning Tasks

PubMed Central

Shivkumar, Sabyasachi; Muralidharan, Vignesh; Chakravarthy, V. Srinivasa

2017-01-01

Basal ganglia circuit is an important subcortical system of the brain thought to be responsible for reward-based learning. Striatum, the largest nucleus of the basal ganglia, serves as an input port that maps cortical information. Microanatomical studies show that the striatum is a mosaic of specialized input-output structures called striosomes and regions of the surrounding matrix called the matrisomes. We have developed a computational model of the striatum using layered self-organizing maps to capture the center-surround structure seen experimentally and explain its functional significance. We believe that these structural components could build representations of state and action spaces in different environments. The striatum model is then integrated with other components of basal ganglia, making it capable of solving reinforcement learning tasks. We have proposed a biologically plausible mechanism of action-based learning where the striosome biases the matrisome activity toward a preferred action. Several studies indicate that the striatum is critical in solving context dependent problems. We build on this hypothesis and the proposed model exploits the modularity of the striatum to efficiently solve such tasks. PMID:28680395

Attempted prebiotic synthesis of pseudouridine

NASA Technical Reports Server (NTRS)

Dworkin, J. P.; Miller, S. L. (Principal Investigator)

1997-01-01

Pseudouridine is a modified base found in all tRNA and rRNA. Hence, it is reasonable to think that pseudouridine was important in the early evolution, if not the origin, of life. Since uracil reacts rapidly with formaldehyde and other aldehydes at the C-5 position, it is plausible that pseudouridine could be synthesized in a similar way by the reaction of the C-5 of uracil with the C-1 of ribose. The determining factor is whether the ribose could react with the uracil faster than ribose decomposes. However, both rates are determined by the amount of free aldehyde in the ribose. Various plausible prebiotic reactions were investigated and none showed pseudouridine above the detection limit (<0.01%). Only unreacted uracil and ribose decomposition products could be observed. Thus the rate of addition of ribose to uracil is much slower than the decomposition of ribose under any reasonable prebiotic conditions. Unless efficient non-biological catalysts for any of these reactions exist, pseudouridine would not have been synthesized to any significant extent without the use of biologically produced enzymes.

Mean-field analysis of an inductive reasoning game: Application to influenza vaccination

NASA Astrophysics Data System (ADS)

Breban, Romulus; Vardavas, Raffaele; Blower, Sally

2007-09-01

Recently we have introduced an inductive reasoning game of voluntary yearly vaccination to establish whether or not a population of individuals acting in their own self-interest would be able to prevent influenza epidemics. Here, we analyze our model to describe the dynamics of the collective yearly vaccination uptake. We discuss the mean-field equations of our model and first order effects of fluctuations. We explain why our model predicts that severe epidemics are periodically expected even without the introduction of pandemic strains. We find that fluctuations in the collective yearly vaccination uptake induce severe epidemics with an expected periodicity that depends on the number of independent decision makers in the population. The mean-field dynamics also reveal that there are conditions for which the dynamics become robust to the fluctuations. However, the transition between fluctuation-sensitive and fluctuation-robust dynamics occurs for biologically implausible parameters. We also analyze our model when incentive-based vaccination programs are offered. When a family-based incentive is offered, the expected periodicity of severe epidemics is increased. This results from the fact that the number of independent decision makers is reduced, increasing the effect of the fluctuations. However, incentives based on the number of years of prepayment of vaccination may yield fluctuation-robust dynamics where severe epidemics are prevented. In this case, depending on prepayment, the transition between fluctuation-sensitive and fluctuation-robust dynamics may occur for biologically plausible parameters. Our analysis provides a practical method for identifying how many years of free vaccination should be provided in order to successfully ameliorate influenza epidemics.

Mean-field analysis of an inductive reasoning game: application to influenza vaccination.

PubMed

Breban, Romulus; Vardavas, Raffaele; Blower, Sally

2007-09-01

Recently we have introduced an inductive reasoning game of voluntary yearly vaccination to establish whether or not a population of individuals acting in their own self-interest would be able to prevent influenza epidemics. Here, we analyze our model to describe the dynamics of the collective yearly vaccination uptake. We discuss the mean-field equations of our model and first order effects of fluctuations. We explain why our model predicts that severe epidemics are periodically expected even without the introduction of pandemic strains. We find that fluctuations in the collective yearly vaccination uptake induce severe epidemics with an expected periodicity that depends on the number of independent decision makers in the population. The mean-field dynamics also reveal that there are conditions for which the dynamics become robust to the fluctuations. However, the transition between fluctuation-sensitive and fluctuation-robust dynamics occurs for biologically implausible parameters. We also analyze our model when incentive-based vaccination programs are offered. When a family-based incentive is offered, the expected periodicity of severe epidemics is increased. This results from the fact that the number of independent decision makers is reduced, increasing the effect of the fluctuations. However, incentives based on the number of years of prepayment of vaccination may yield fluctuation-robust dynamics where severe epidemics are prevented. In this case, depending on prepayment, the transition between fluctuation-sensitive and fluctuation-robust dynamics may occur for biologically plausible parameters. Our analysis provides a practical method for identifying how many years of free vaccination should be provided in order to successfully ameliorate influenza epidemics.

A biologically plausible computational model for auditory object recognition.

PubMed

Larson, Eric; Billimoria, Cyrus P; Sen, Kamal

2009-01-01

Object recognition is a task of fundamental importance for sensory systems. Although this problem has been intensively investigated in the visual system, relatively little is known about the recognition of complex auditory objects. Recent work has shown that spike trains from individual sensory neurons can be used to discriminate between and recognize stimuli. Multiple groups have developed spike similarity or dissimilarity metrics to quantify the differences between spike trains. Using a nearest-neighbor approach the spike similarity metrics can be used to classify the stimuli into groups used to evoke the spike trains. The nearest prototype spike train to the tested spike train can then be used to identify the stimulus. However, how biological circuits might perform such computations remains unclear. Elucidating this question would facilitate the experimental search for such circuits in biological systems, as well as the design of artificial circuits that can perform such computations. Here we present a biologically plausible model for discrimination inspired by a spike distance metric using a network of integrate-and-fire model neurons coupled to a decision network. We then apply this model to the birdsong system in the context of song discrimination and recognition. We show that the model circuit is effective at recognizing individual songs, based on experimental input data from field L, the avian primary auditory cortex analog. We also compare the performance and robustness of this model to two alternative models of song discrimination: a model based on coincidence detection and a model based on firing rate.

Adaptive selection and validation of models of complex systems in the presence of uncertainty

DOE Office of Scientific and Technical Information (OSTI.GOV)

Farrell-Maupin, Kathryn; Oden, J. T.

This study describes versions of OPAL, the Occam-Plausibility Algorithm in which the use of Bayesian model plausibilities is replaced with information theoretic methods, such as the Akaike Information Criterion and the Bayes Information Criterion. Applications to complex systems of coarse-grained molecular models approximating atomistic models of polyethylene materials are described. All of these model selection methods take into account uncertainties in the model, the observational data, the model parameters, and the predicted quantities of interest. A comparison of the models chosen by Bayesian model selection criteria and those chosen by the information-theoretic criteria is given.

Adaptive selection and validation of models of complex systems in the presence of uncertainty

DOE PAGES

Farrell-Maupin, Kathryn; Oden, J. T.

2017-08-01

This study describes versions of OPAL, the Occam-Plausibility Algorithm in which the use of Bayesian model plausibilities is replaced with information theoretic methods, such as the Akaike Information Criterion and the Bayes Information Criterion. Applications to complex systems of coarse-grained molecular models approximating atomistic models of polyethylene materials are described. All of these model selection methods take into account uncertainties in the model, the observational data, the model parameters, and the predicted quantities of interest. A comparison of the models chosen by Bayesian model selection criteria and those chosen by the information-theoretic criteria is given.

Drug-Induced Acute Myocardial Infarction: Identifying ‘Prime Suspects’ from Electronic Healthcare Records-Based Surveillance System

PubMed Central

Coloma, Preciosa M.; Schuemie, Martijn J.; Trifirò, Gianluca; Furlong, Laura; van Mulligen, Erik; Bauer-Mehren, Anna; Avillach, Paul; Kors, Jan; Sanz, Ferran; Mestres, Jordi; Oliveira, José Luis; Boyer, Scott; Helgee, Ernst Ahlberg; Molokhia, Mariam; Matthews, Justin; Prieto-Merino, David; Gini, Rosa; Herings, Ron; Mazzaglia, Giampiero; Picelli, Gino; Scotti, Lorenza; Pedersen, Lars; van der Lei, Johan; Sturkenboom, Miriam

2013-01-01

Background Drug-related adverse events remain an important cause of morbidity and mortality and impose huge burden on healthcare costs. Routinely collected electronic healthcare data give a good snapshot of how drugs are being used in ‘real-world’ settings. Objective To describe a strategy that identifies potentially drug-induced acute myocardial infarction (AMI) from a large international healthcare data network. Methods Post-marketing safety surveillance was conducted in seven population-based healthcare databases in three countries (Denmark, Italy, and the Netherlands) using anonymised demographic, clinical, and prescription/dispensing data representing 21,171,291 individuals with 154,474,063 person-years of follow-up in the period 1996–2010. Primary care physicians’ medical records and administrative claims containing reimbursements for filled prescriptions, laboratory tests, and hospitalisations were evaluated using a three-tier triage system of detection, filtering, and substantiation that generated a list of drugs potentially associated with AMI. Outcome of interest was statistically significant increased risk of AMI during drug exposure that has not been previously described in current literature and is biologically plausible. Results Overall, 163 drugs were identified to be associated with increased risk of AMI during preliminary screening. Of these, 124 drugs were eliminated after adjustment for possible bias and confounding. With subsequent application of criteria for novelty and biological plausibility, association with AMI remained for nine drugs (‘prime suspects’): azithromycin; erythromycin; roxithromycin; metoclopramide; cisapride; domperidone; betamethasone; fluconazole; and megestrol acetate. Limitations Although global health status, co-morbidities, and time-invariant factors were adjusted for, residual confounding cannot be ruled out. Conclusion A strategy to identify potentially drug-induced AMI from electronic healthcare data has been proposed that takes into account not only statistical association, but also public health relevance, novelty, and biological plausibility. Although this strategy needs to be further evaluated using other healthcare data sources, the list of ‘prime suspects’ makes a good starting point for further clinical, laboratory, and epidemiologic investigation. PMID:24015213

Framework for Uncertainty Assessment - Hanford Site-Wide Groundwater Flow and Transport Modeling

NASA Astrophysics Data System (ADS)

Bergeron, M. P.; Cole, C. R.; Murray, C. J.; Thorne, P. D.; Wurstner, S. K.

2002-05-01

Pacific Northwest National Laboratory is in the process of development and implementation of an uncertainty estimation methodology for use in future site assessments that addresses parameter uncertainty as well as uncertainties related to the groundwater conceptual model. The long-term goals of the effort are development and implementation of an uncertainty estimation methodology for use in future assessments and analyses being made with the Hanford site-wide groundwater model. The basic approach in the framework developed for uncertainty assessment consists of: 1) Alternate conceptual model (ACM) identification to identify and document the major features and assumptions of each conceptual model. The process must also include a periodic review of the existing and proposed new conceptual models as data or understanding become available. 2) ACM development of each identified conceptual model through inverse modeling with historical site data. 3) ACM evaluation to identify which of conceptual models are plausible and should be included in any subsequent uncertainty assessments. 4) ACM uncertainty assessments will only be carried out for those ACMs determined to be plausible through comparison with historical observations and model structure identification measures. The parameter uncertainty assessment process generally involves: a) Model Complexity Optimization - to identify the important or relevant parameters for the uncertainty analysis; b) Characterization of Parameter Uncertainty - to develop the pdfs for the important uncertain parameters including identification of any correlations among parameters; c) Propagation of Uncertainty - to propagate parameter uncertainties (e.g., by first order second moment methods if applicable or by a Monte Carlo approach) through the model to determine the uncertainty in the model predictions of interest. 5)Estimation of combined ACM and scenario uncertainty by a double sum with each component of the inner sum (an individual CCDF) representing parameter uncertainty associated with a particular scenario and ACM and the outer sum enumerating the various plausible ACM and scenario combinations in order to represent the combined estimate of uncertainty (a family of CCDFs). A final important part of the framework includes identification, enumeration, and documentation of all the assumptions, which include those made during conceptual model development, required by the mathematical model, required by the numerical model, made during the spatial and temporal descretization process, needed to assign the statistical model and associated parameters that describe the uncertainty in the relevant input parameters, and finally those assumptions required by the propagation method. Pacific Northwest National Laboratory is operated for the U.S. Department of Energy under Contract DE-AC06-76RL01830.

Issues raised by the reference doses for perfluorooctane sulfonate and perfluorooctanoic acid.

PubMed

Dong, Zhaomin; Bahar, Md Mezbaul; Jit, Joytishna; Kennedy, Bruce; Priestly, Brian; Ng, Jack; Lamb, Dane; Liu, Yanju; Duan, Luchun; Naidu, Ravi

2017-08-01

On 25th May 2016, the U.S. EPA released reference doses (RfDs) for Perfluorooctane Sulfonate (PFOS) and Perfluorooctanoic Acid (PFOA) of 20ng/kg/day, which were much more conservative than previous values. These RfDs rely on the choices of animal point of departure (PoD) and the toxicokinetics (TK) model. At this stage, considering that the human evidence is not strong enough for RfD determination, using animal data may be appropriate but with more uncertainties. In this article, the uncertainties concerning RfDs from the choices of PoD and TK models are addressed. Firstly, the candidate PoDs should include more critical endpoints (such as immunotoxicity), which may lead to lower RfDs. Secondly, the reliability of the adopted three-compartment TK model is compromised: the parameters are not non-biologically plausible; and this TK model was applied to simulate gestation and lactation exposures, while the two exposure scenarios were not actually included in the model structure. Copyright © 2017. Published by Elsevier Ltd.

Childhood Adversity, Self-Esteem, and Diurnal Cortisol Profiles across the Lifespan

PubMed Central

Zilioli, Samuele; Slatcher, Richard B.; Chi, Peilian; Li, Xiaoming; Zhao, Junfeng; Zhao, Guoxiang

2016-01-01

Childhood adversity is associated with poor health outcomes in adulthood; the hypothalamic-pituitary-adrenal (HPA) axis has been proposed as a crucial biological intermediary of these long-term effects. Here we tested whether childhood adversity was associated with diurnal cortisol parameters, and whether this link was partially explained by self-esteem. In both adults and children, childhood adversity was associated with lower levels of cortisol at awakening and this association was partially driven by low self-esteem. Further, we found a significant indirect pathway through which greater adversity during childhood was linked to a flatter cortisol slope via self-esteem. Lastly, those youth who had a caregiver with high self-esteem experienced a steeper decline in cortisol throughout the day compared to those youth whose caregiver reported low self-esteem. We conclude that self-esteem is a plausible psychological mechanism through which childhood adversity may get embedded in the activity of the HPA axis across the lifespan. PMID:27481911

Childhood Adversity, Self-Esteem, and Diurnal Cortisol Profiles Across the Life Span.

PubMed

Zilioli, Samuele; Slatcher, Richard B; Chi, Peilian; Li, Xiaoming; Zhao, Junfeng; Zhao, Guoxiang

2016-09-01

Childhood adversity is associated with poor health outcomes in adulthood; the hypothalamic-pituitary-adrenal (HPA) axis has been proposed as a crucial biological intermediary of these long-term effects. Here, we tested whether childhood adversity was associated with diurnal cortisol parameters and whether this link was partially explained by self-esteem. In both adults and youths, childhood adversity was associated with lower levels of cortisol at awakening, and this association was partially driven by low self-esteem. Further, we found a significant indirect pathway through which greater adversity during childhood was linked to a flatter cortisol slope via self-esteem. Finally, youths who had a caregiver with high self-esteem experienced a steeper decline in cortisol throughout the day compared with youths whose caregiver reported low self-esteem. We conclude that self-esteem is a plausible psychological mechanism through which childhood adversity may get embedded in the activity of the HPA axis across the life span. © The Author(s) 2016.

An ecological valence theory of human color preference

PubMed Central

Palmer, Stephen E.; Schloss, Karen B.

2010-01-01

Color preference is an important aspect of visual experience, but little is known about why people in general like some colors more than others. Previous research suggested explanations based on biological adaptations [Hurlbert AC, Ling YL (2007) Curr Biol 17:623–625] and color-emotions [Ou L-C, Luo MR, Woodcock A, Wright A (2004) Color Res Appl 29:381–389]. In this article we articulate an ecological valence theory in which color preferences arise from people’s average affective responses to color-associated objects. An empirical test provides strong support for this theory: People like colors strongly associated with objects they like (e.g., blues with clear skies and clean water) and dislike colors strongly associated with objects they dislike (e.g., browns with feces and rotten food). Relative to alternative theories, the ecological valence theory both fits the data better (even with fewer free parameters) and provides a more plausible, comprehensive causal explanation of color preferences. PMID:20421475

Modeling Avoidance in Mood and Anxiety Disorders Using Reinforcement Learning.

PubMed

Mkrtchian, Anahit; Aylward, Jessica; Dayan, Peter; Roiser, Jonathan P; Robinson, Oliver J

2017-10-01

Serious and debilitating symptoms of anxiety are the most common mental health problem worldwide, accounting for around 5% of all adult years lived with disability in the developed world. Avoidance behavior-avoiding social situations for fear of embarrassment, for instance-is a core feature of such anxiety. However, as for many other psychiatric symptoms the biological mechanisms underlying avoidance remain unclear. Reinforcement learning models provide formal and testable characterizations of the mechanisms of decision making; here, we examine avoidance in these terms. A total of 101 healthy participants and individuals with mood and anxiety disorders completed an approach-avoidance go/no-go task under stress induced by threat of unpredictable shock. We show an increased reliance in the mood and anxiety group on a parameter of our reinforcement learning model that characterizes a prepotent (pavlovian) bias to withhold responding in the face of negative outcomes. This was particularly the case when the mood and anxiety group was under stress. This formal description of avoidance within the reinforcement learning framework provides a new means of linking clinical symptoms with biophysically plausible models of neural circuitry and, as such, takes us closer to a mechanistic understanding of mood and anxiety disorders. Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

On the quantification and efficient propagation of imprecise probabilities resulting from small datasets

NASA Astrophysics Data System (ADS)

Zhang, Jiaxin; Shields, Michael D.

2018-01-01

This paper addresses the problem of uncertainty quantification and propagation when data for characterizing probability distributions are scarce. We propose a methodology wherein the full uncertainty associated with probability model form and parameter estimation are retained and efficiently propagated. This is achieved by applying the information-theoretic multimodel inference method to identify plausible candidate probability densities and associated probabilities that each method is the best model in the Kullback-Leibler sense. The joint parameter densities for each plausible model are then estimated using Bayes' rule. We then propagate this full set of probability models by estimating an optimal importance sampling density that is representative of all plausible models, propagating this density, and reweighting the samples according to each of the candidate probability models. This is in contrast with conventional methods that try to identify a single probability model that encapsulates the full uncertainty caused by lack of data and consequently underestimate uncertainty. The result is a complete probabilistic description of both aleatory and epistemic uncertainty achieved with several orders of magnitude reduction in computational cost. It is shown how the model can be updated to adaptively accommodate added data and added candidate probability models. The method is applied for uncertainty analysis of plate buckling strength where it is demonstrated how dataset size affects the confidence (or lack thereof) we can place in statistical estimates of response when data are lacking.

Religious groups as adaptive units.

PubMed

Wilson, D S

2001-01-01

This essay provides a sketch of religion as a set of biologically and culturally evolved adaptations that enable human groups to function as adaptive units. Recent developments in evolutionary biology make such a group-level interpretation of religion more plausible than in the past. A brief survey of relevant concepts is followed by a relatively detailed interpretation of Calvinism as a religious system in which explicit behavioral prescriptions, beliefs about God and his relationship with people, and numerous social control mechanisms combined to change the city of Geneva from a collection of warring factions to a unified population.

Anxiety and anxiety disorders. Toward a conceptual reorientation.

PubMed

Curtis, G C

1985-03-01

Traditionally, it has been assumed that there is only one type of anxiety; recent pharmacologic evidence suggests that there may be several. The psychoanalytic concept of "neurotic" symptoms as depressurizing mechanisms is out of keeping with most evidence now available. Spontaneous or "free-floating" anxiety may be partly biologic and genetic in origin. Anxiety symptoms evoked by specific stimuli behave in part like conditioned responses. Where conditioning theory has failed to propose a plausible unconditioned stimulus for pathologic anxiety, biology, ethology, and psychoanalysis may have been more successful.

Model-based recovery of histological parameters from multispectral images of the colon

NASA Astrophysics Data System (ADS)

Hidovic-Rowe, Dzena; Claridge, Ela

2005-04-01

Colon cancer alters the macroarchitecture of the colon tissue. Common changes include angiogenesis and the distortion of the tissue collagen matrix. Such changes affect the colon colouration. This paper presents the principles of a novel optical imaging method capable of extracting parameters depicting histological quantities of the colon. The method is based on a computational, physics-based model of light interaction with tissue. The colon structure is represented by three layers: mucosa, submucosa and muscle layer. Optical properties of the layers are defined by molar concentration and absorption coefficients of haemoglobins; the size and density of collagen fibres; the thickness of the layer and the refractive indexes of collagen and the medium. Using the entire histologically plausible ranges for these parameters, a cross-reference is created computationally between the histological quantities and the associated spectra. The output of the model was compared to experimental data acquired in vivo from 57 histologically confirmed normal and abnormal tissue samples and histological parameters were extracted. The model produced spectra which match well the measured data, with the corresponding spectral parameters being well within histologically plausible ranges. Parameters extracted for the abnormal spectra showed the increase in blood volume fraction and changes in collagen pattern characteristic of the colon cancer. The spectra extracted from multi-spectral images of ex-vivo colon including adenocarcinoma show the characteristic features associated with normal and abnormal colon tissue. These findings suggest that it should be possible to compute histological quantities for the colon from the multi-spectral images.

Species Extrapolation of Life-Stage Physiologically-Based Pharmacokinetic (PBPK) Models to Investigate the Developmental Toxicology of Ethanol Using In vitro to In vivo (IVIVE) Methods

EPA Science Inventory

To provide useful alternatives to in vivo animal studies, in vitro assays for dose-response assessments of xenobiotic chemicals must use concentrations in media and target tissues that are within biologically-plausible limits. Determining these concentrations is a complex matter,...

Evidence of the Role of Physical Activity and Cardiorespiratory Fitness in the Prevention of Coronary Heart Disease.

ERIC Educational Resources Information Center

Leon, Arthur S.; Norstrom, Jane

1995-01-01

This paper presents epidemiologic evidence on the contributions of physical inactivity and reduced cardiorespiratory fitness to risk of coronary heart disease (CHD). The types and dose of physical activity to reduce risk of CHD and plausible biologic mechanisms for the partial protective effect are reviewed. (Author/SM)

Bridging the Gap between Physiology and Behavior: Evidence from the sSoTS Model of Human Visual Attention

ERIC Educational Resources Information Center

Mavritsaki, Eirini; Heinke, Dietmar; Allen, Harriet; Deco, Gustavo; Humphreys, Glyn W.

2011-01-01

We present the case for a role of biologically plausible neural network modeling in bridging the gap between physiology and behavior. We argue that spiking-level networks can allow "vertical" translation between physiological properties of neural systems and emergent "whole-system" performance--enabling psychological results to be simulated from…

Uncertainty Quantification and Regional Sensitivity Analysis of Snow-related Parameters in the Canadian LAnd Surface Scheme (CLASS)

NASA Astrophysics Data System (ADS)

Badawy, B.; Fletcher, C. G.

2017-12-01

The parameterization of snow processes in land surface models is an important source of uncertainty in climate simulations. Quantifying the importance of snow-related parameters, and their uncertainties, may therefore lead to better understanding and quantification of uncertainty within integrated earth system models. However, quantifying the uncertainty arising from parameterized snow processes is challenging due to the high-dimensional parameter space, poor observational constraints, and parameter interaction. In this study, we investigate the sensitivity of the land simulation to uncertainty in snow microphysical parameters in the Canadian LAnd Surface Scheme (CLASS) using an uncertainty quantification (UQ) approach. A set of training cases (n=400) from CLASS is used to sample each parameter across its full range of empirical uncertainty, as determined from available observations and expert elicitation. A statistical learning model using support vector regression (SVR) is then constructed from the training data (CLASS output variables) to efficiently emulate the dynamical CLASS simulations over a much larger (n=220) set of cases. This approach is used to constrain the plausible range for each parameter using a skill score, and to identify the parameters with largest influence on the land simulation in CLASS at global and regional scales, using a random forest (RF) permutation importance algorithm. Preliminary sensitivity tests indicate that snow albedo refreshment threshold and the limiting snow depth, below which bare patches begin to appear, have the highest impact on snow output variables. The results also show a considerable reduction of the plausible ranges of the parameters values and hence reducing their uncertainty ranges, which can lead to a significant reduction of the model uncertainty. The implementation and results of this study will be presented and discussed in details.

The adverse health effects of chronic cannabis use.

PubMed

Hall, Wayne; Degenhardt, Louisa

2014-01-01

This paper summarizes the most probable of the adverse health effects of regular cannabis use sustained over years, as indicated by epidemiological studies that have established an association between cannabis use and adverse outcomes; ruled out reverse causation; and controlled for plausible alternative explanations. We have also focused on adverse outcomes for which there is good evidence of biological plausibility. The focus is on those adverse health effects of greatest potential public health significance--those that are most likely to occur and to affect a substantial proportion of regular cannabis users. These most probable adverse effects of regular use include a dependence syndrome, impaired respiratory function, cardiovascular disease, adverse effects on adolescent psychosocial development and mental health, and residual cognitive impairment. Copyright © 2013 John Wiley & Sons, Ltd.

Small perturbations in a finger-tapping task reveal inherent nonlinearities of the underlying error correction mechanism.

PubMed

Bavassi, M Luz; Tagliazucchi, Enzo; Laje, Rodrigo

2013-02-01

Time processing in the few hundred milliseconds range is involved in the human skill of sensorimotor synchronization, like playing music in an ensemble or finger tapping to an external beat. In finger tapping, a mechanistic explanation in biologically plausible terms of how the brain achieves synchronization is still missing despite considerable research. In this work we show that nonlinear effects are important for the recovery of synchronization following a perturbation (a step change in stimulus period), even for perturbation magnitudes smaller than 10% of the period, which is well below the amount of perturbation needed to evoke other nonlinear effects like saturation. We build a nonlinear mathematical model for the error correction mechanism and test its predictions, and further propose a framework that allows us to unify the description of the three common types of perturbations. While previous authors have used two different model mechanisms for fitting different perturbation types, or have fitted different parameter value sets for different perturbation magnitudes, we propose the first unified description of the behavior following all perturbation types and magnitudes as the dynamical response of a compound model with fixed terms and a single set of parameter values. Copyright © 2012 Elsevier B.V. All rights reserved.

Compact continuum brain model for human electroencephalogram

NASA Astrophysics Data System (ADS)

Kim, J. W.; Shin, H.-B.; Robinson, P. A.

2007-12-01

A low-dimensional, compact brain model has recently been developed based on physiologically based mean-field continuum formulation of electric activity of the brain. The essential feature of the new compact model is a second order time-delayed differential equation that has physiologically plausible terms, such as rapid corticocortical feedback and delayed feedback via extracortical pathways. Due to its compact form, the model facilitates insight into complex brain dynamics via standard linear and nonlinear techniques. The model successfully reproduces many features of previous models and experiments. For example, experimentally observed typical rhythms of electroencephalogram (EEG) signals are reproduced in a physiologically plausible parameter region. In the nonlinear regime, onsets of seizures, which often develop into limit cycles, are illustrated by modulating model parameters. It is also shown that a hysteresis can occur when the system has multiple attractors. As a further illustration of this approach, power spectra of the model are fitted to those of sleep EEGs of two subjects (one with apnea, the other with narcolepsy). The model parameters obtained from the fittings show good matches with previous literature. Our results suggest that the compact model can provide a theoretical basis for analyzing complex EEG signals.

Biology of Consciousness

PubMed Central

Edelman, Gerald M.; Gally, Joseph A.; Baars, Bernard J.

2010-01-01

The Dynamic Core and Global Workspace hypotheses were independently put forward to provide mechanistic and biologically plausible accounts of how brains generate conscious mental content. The Dynamic Core proposes that reentrant neural activity in the thalamocortical system gives rise to conscious experience. Global Workspace reconciles the limited capacity of momentary conscious content with the vast repertoire of long-term memory. In this paper we show the close relationship between the two hypotheses. This relationship allows for a strictly biological account of phenomenal experience and subjectivity that is consistent with mounting experimental evidence. We examine the constraints on causal analyses of consciousness and suggest that there is now sufficient evidence to consider the design and construction of a conscious artifact. PMID:21713129

Consequentialism and the Synthetic Biology Problem.

PubMed

Heavey, Patrick

2017-04-01

This article analyzes the ethics of synthetic biology (synbio) from a consequentialist perspective, examining potential effects on food and agriculture, and on medicine, fuel, and the advancement of science. The issues of biosafety and biosecurity are also examined. A consequentialist analysis offers an essential road map to policymakers and regulators as to how to deal with synbio. Additionally, the article discusses the limitations of consequentialism as a tool for analysing synbioethics. Is it possible to predict, with any degree of plausibility, what the consequences of synthetic biology will be in 50 years, or in 100, or in 500? Synbio may take humanity to a place of radical departure from what is known or knowable.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Farrell, Kathryn, E-mail: kfarrell@ices.utexas.edu; Oden, J. Tinsley, E-mail: oden@ices.utexas.edu; Faghihi, Danial, E-mail: danial@ices.utexas.edu

A general adaptive modeling algorithm for selection and validation of coarse-grained models of atomistic systems is presented. A Bayesian framework is developed to address uncertainties in parameters, data, and model selection. Algorithms for computing output sensitivities to parameter variances, model evidence and posterior model plausibilities for given data, and for computing what are referred to as Occam Categories in reference to a rough measure of model simplicity, make up components of the overall approach. Computational results are provided for representative applications.

Synthetic Biology and the Moral Significance of Artificial Life: A Reply to Douglas, Powell and Savulescu.

PubMed

Christiansen, Andreas

2016-06-01

I discuss the moral significance of artificial life within synthetic biology via a discussion of Douglas, Powell and Savulescu's paper 'Is the creation of artificial life morally significant'. I argue that the definitions of 'artificial life' and of 'moral significance' are too narrow. Douglas, Powell and Savulescu's definition of artificial life does not capture all core projects of synthetic biology or the ethical concerns that have been voiced, and their definition of moral significance fails to take into account the possibility that creating artificial life is conditionally acceptable. Finally, I show how several important objections to synthetic biology are plausibly understood as arguing that creating artificial life in a wide sense is only conditionally acceptable. © 2016 John Wiley & Sons Ltd.

On the Biological Plausibility of Grandmother Cells: Implications for Neural Network Theories in Psychology and Neuroscience

ERIC Educational Resources Information Center

Bowers, Jeffrey S.

2009-01-01

A fundamental claim associated with parallel distributed processing (PDP) theories of cognition is that knowledge is coded in a distributed manner in mind and brain. This approach rejects the claim that knowledge is coded in a localist fashion, with words, objects, and simple concepts (e.g. "dog"), that is, coded with their own dedicated…

Are anorexia nervosa and bulimia nervosa separate disorders? Challenging the 'transdiagnostic' theory of eating disorders.

PubMed

Birmingham, C Laird; Touyz, Stephen; Harbottle, Jane

2009-01-01

Anorexia nervosa (AN) and bulimia nervosa (BN) are classified as separate and distinct clinical disorders. Recently, there has been support for a transdiagnostic theory of eating disorders, which would reclassify them as one disorder. To determine whether AN and BN are a single disorder with one cause or separate disorders with different causes. Hill's Criteria of Causation were used to test the hypothesis that AN and BN are one disorder with a single cause. Hill's Criteria of Causation demand that the minimal conditions are needed to establish a causal relationship between two items which include all of the following: strength of association, consistency, temporality, biological gradient, plausibility, coherence, experimental evidence and analogy. The hypothesis that AN and BN have a single cause did not meet all of Hill's Criteria of Causation. Strength of association, plausibility, analogy and some experimental evidence were met, but not consistency, specificity, temporality, biological gradient, coherence and most experimental evidence. The hypothesis that AN and BN are a single disorder with a common cause is not supported by Hill's Criteria of Causation. This argues against the notion of a transdiagnostic theory of eating disorders.

Observed, unknown distributions of clinical chemical quantities should be considered to be log-normal: a proposal.

PubMed

Haeckel, Rainer; Wosniok, Werner

2010-10-01

The distribution of many quantities in laboratory medicine are considered to be Gaussian if they are symmetric, although, theoretically, a Gaussian distribution is not plausible for quantities that can attain only non-negative values. If a distribution is skewed, further specification of the type is required, which may be difficult to provide. Skewed (non-Gaussian) distributions found in clinical chemistry usually show only moderately large positive skewness (e.g., log-normal- and χ(2) distribution). The degree of skewness depends on the magnitude of the empirical biological variation (CV(e)), as demonstrated using the log-normal distribution. A Gaussian distribution with a small CV(e) (e.g., for plasma sodium) is very similar to a log-normal distribution with the same CV(e). In contrast, a relatively large CV(e) (e.g., plasma aspartate aminotransferase) leads to distinct differences between a Gaussian and a log-normal distribution. If the type of an empirical distribution is unknown, it is proposed that a log-normal distribution be assumed in such cases. This avoids distributional assumptions that are not plausible and does not contradict the observation that distributions with small biological variation look very similar to a Gaussian distribution.

A preliminary and qualitative study of resource ratio theory to nitrifying lab-scale bioreactors.

PubMed

Bellucci, Micol; Ofiţeru, Irina D; Beneduce, Luciano; Graham, David W; Head, Ian M; Curtis, Thomas P

2015-05-01

The incorporation of microbial diversity in design would ideally require predictive theory that would relate operational parameters to the numbers and distribution of taxa. Resource ratio-theory (RRT) might be one such theory. Based on Monod kinetics, it explains diversity in function of resource-ratio and richness. However, to be usable in biological engineered system, the growth parameters of all the bacteria under consideration and the resource supply and diffusion parameters for all the relevant nutrients should be determined. This is challenging, but plausible, at least for low diversity groups with simple resource requirements like the ammonia oxidizing bacteria (AOB). One of the major successes of RRT was its ability to explain the 'paradox of enrichment' which states that diversity first increases and then decreases with resource richness. Here, we demonstrate that this pattern can be seen in lab-scale-activated sludge reactors and parallel simulations that incorporate the principles of RRT in a floc-based system. High and low ammonia and oxygen were supplied to continuous flow bioreactors with resource conditions correlating with the composition and diversity of resident AOB communities based on AOB 16S rDNA clone libraries. Neither the experimental work nor the simulations are definitive proof for the application of RRT in this context. However, it is sufficient evidence that such approach might work and justify a more rigorous investigation. © 2015 The Authors. Microbial Biotechnology published by John Wiley & Sons Ltd and Society for Applied Microbiology.

Modeling antibiotic treatment in hospitals: A systematic approach shows benefits of combination therapy over cycling, mixing, and mono-drug therapies.

PubMed

Tepekule, Burcu; Uecker, Hildegard; Derungs, Isabel; Frenoy, Antoine; Bonhoeffer, Sebastian

2017-09-01

Multiple treatment strategies are available for empiric antibiotic therapy in hospitals, but neither clinical studies nor theoretical investigations have yielded a clear picture when which strategy is optimal and why. Extending earlier work of others and us, we present a mathematical model capturing treatment strategies using two drugs, i.e the multi-drug therapies referred to as cycling, mixing, and combination therapy, as well as monotherapy with either drug. We randomly sample a large parameter space to determine the conditions determining success or failure of these strategies. We find that combination therapy tends to outperform the other treatment strategies. By using linear discriminant analysis and particle swarm optimization, we find that the most important parameters determining success or failure of combination therapy relative to the other treatment strategies are the de novo rate of emergence of double resistance in patients infected with sensitive bacteria and the fitness costs associated with double resistance. The rate at which double resistance is imported into the hospital via patients admitted from the outside community has little influence, as all treatment strategies are affected equally. The parameter sets for which combination therapy fails tend to fall into areas with low biological plausibility as they are characterised by very high rates of de novo emergence of resistance to both drugs compared to a single drug, and the cost of double resistance is considerably smaller than the sum of the costs of single resistance.

Does Sufficient Evidence Exist to Support a Causal Association between Vitamin D Status and Cardiovascular Disease Risk? An Assessment Using Hill’s Criteria for Causality

PubMed Central

Weyland, Patricia G.; Grant, William B.; Howie-Esquivel, Jill

2014-01-01

Serum 25-hydroxyvitamin D (25(OH)D) levels have been found to be inversely associated with both prevalent and incident cardiovascular disease (CVD) risk factors; dyslipidemia, hypertension and diabetes mellitus. This review looks for evidence of a causal association between low 25(OH)D levels and increased CVD risk. We evaluated journal articles in light of Hill’s criteria for causality in a biological system. The results of our assessment are as follows. Strength of association: many randomized controlled trials (RCTs), prospective and cross-sectional studies found statistically significant inverse associations between 25(OH)D levels and CVD risk factors. Consistency of observed association: most studies found statistically significant inverse associations between 25(OH)D levels and CVD risk factors in various populations, locations and circumstances. Temporality of association: many RCTs and prospective studies found statistically significant inverse associations between 25(OH)D levels and CVD risk factors. Biological gradient (dose-response curve): most studies assessing 25(OH)D levels and CVD risk found an inverse association exhibiting a linear biological gradient. Plausibility of biology: several plausible cellular-level causative mechanisms and biological pathways may lead from a low 25(OH)D level to increased risk for CVD with mediators, such as dyslipidemia, hypertension and diabetes mellitus. Experimental evidence: some well-designed RCTs found increased CVD risk factors with decreasing 25(OH)D levels. Analogy: the association between serum 25(OH)D levels and CVD risk is analogous to that between 25(OH)D levels and the risk of overall cancer, periodontal disease, multiple sclerosis and breast cancer. Conclusion: all relevant Hill criteria for a causal association in a biological system are satisfied to indicate a low 25(OH)D level as a CVD risk factor. PMID:25184368

A Comparison of Different Methods for Evaluating Diet, Physical Activity, and Long-Term Weight Gain in 3 Prospective Cohort Studies123

PubMed Central

Smith, Jessica D; Hou, Tao; Hu, Frank B; Rimm, Eric B; Spiegelman, Donna; Willett, Walter C; Mozaffarian, Dariush

2015-01-01

Background: The insidious pace of long-term weight gain (∼1 lb/y or 0.45 kg/y) makes it difficult to study in trials; long-term prospective cohorts provide crucial evidence on its key contributors. Most previous studies have evaluated how prevalent lifestyle habits relate to future weight gain rather than to lifestyle changes, which may be more temporally and physiologically relevant. Objective: Our objective was to evaluate and compare different methodological approaches for investigating diet, physical activity (PA), and long-term weight gain. Methods: In 3 prospective cohorts (total n = 117,992), we assessed how lifestyle relates to long-term weight change (up to 24 y of follow-up) in 4-y periods by comparing 3 analytic approaches: 1) prevalent diet and PA and 4-y weight change (prevalent analysis); 2) 4-y changes in diet and PA with a 4-y weight change (change analysis); and 3) 4-y change in diet and PA with weight change in the subsequent 4 y (lagged-change analysis). We compared these approaches and evaluated the consistency across cohorts, magnitudes of associations, and biological plausibility of findings. Results: Across the 3 methods, consistent, robust, and biologically plausible associations were seen only for the change analysis. Results for prevalent or lagged-change analyses were less consistent across cohorts, smaller in magnitude, and biologically implausible. For example, for each serving of a sugar-sweetened beverage, the observed weight gain was 0.01 lb (95% CI: −0.08, 0.10) [0.005 kg (95% CI: −0.04, 0.05)] based on prevalent analysis; 0.99 lb (95% CI: 0.83, 1.16) [0.45 kg (95% CI: 0.38, 0.53)] based on change analysis; and 0.05 lb (95% CI: −0.10, 0.21) [0.02 kg (95% CI: −0.05, 0.10)] based on lagged-change analysis. Findings were similar for other foods and PA. Conclusions: Robust, consistent, and biologically plausible relations between lifestyle and long-term weight gain are seen when evaluating lifestyle changes and weight changes in discrete periods rather than in prevalent lifestyle or lagged changes. These findings inform the optimal methods for evaluating lifestyle and long-term weight gain and the potential for bias when other methods are used. PMID:26377763

A Comparison of Different Methods for Evaluating Diet, Physical Activity, and Long-Term Weight Gain in 3 Prospective Cohort Studies.

PubMed

Smith, Jessica D; Hou, Tao; Hu, Frank B; Rimm, Eric B; Spiegelman, Donna; Willett, Walter C; Mozaffarian, Dariush

2015-11-01

The insidious pace of long-term weight gain (∼ 1 lb/y or 0.45 kg/y) makes it difficult to study in trials; long-term prospective cohorts provide crucial evidence on its key contributors. Most previous studies have evaluated how prevalent lifestyle habits relate to future weight gain rather than to lifestyle changes, which may be more temporally and physiologically relevant. Our objective was to evaluate and compare different methodological approaches for investigating diet, physical activity (PA), and long-term weight gain. In 3 prospective cohorts (total n = 117,992), we assessed how lifestyle relates to long-term weight change (up to 24 y of follow-up) in 4-y periods by comparing 3 analytic approaches: 1) prevalent diet and PA and 4-y weight change (prevalent analysis); 2) 4-y changes in diet and PA with a 4-y weight change (change analysis); and 3) 4-y change in diet and PA with weight change in the subsequent 4 y (lagged-change analysis). We compared these approaches and evaluated the consistency across cohorts, magnitudes of associations, and biological plausibility of findings. Across the 3 methods, consistent, robust, and biologically plausible associations were seen only for the change analysis. Results for prevalent or lagged-change analyses were less consistent across cohorts, smaller in magnitude, and biologically implausible. For example, for each serving of a sugar-sweetened beverage, the observed weight gain was 0.01 lb (95% CI: -0.08, 0.10) [0.005 kg (95% CI: -0.04, 0.05)] based on prevalent analysis; 0.99 lb (95% CI: 0.83, 1.16) [0.45 kg (95% CI: 0.38, 0.53)] based on change analysis; and 0.05 lb (95% CI: -0.10, 0.21) [0.02 kg (95% CI: -0.05, 0.10)] based on lagged-change analysis. Findings were similar for other foods and PA. Robust, consistent, and biologically plausible relations between lifestyle and long-term weight gain are seen when evaluating lifestyle changes and weight changes in discrete periods rather than in prevalent lifestyle or lagged changes. These findings inform the optimal methods for evaluating lifestyle and long-term weight gain and the potential for bias when other methods are used. © 2015 American Society for Nutrition.

Improving the quality of child anthropometry: Manual anthropometry in the Body Imaging for Nutritional Assessment Study (BINA).

PubMed

Conkle, Joel; Ramakrishnan, Usha; Flores-Ayala, Rafael; Suchdev, Parminder S; Martorell, Reynaldo

2017-01-01

Anthropometric data collected in clinics and surveys are often inaccurate and unreliable due to measurement error. The Body Imaging for Nutritional Assessment Study (BINA) evaluated the ability of 3D imaging to correctly measure stature, head circumference (HC) and arm circumference (MUAC) for children under five years of age. This paper describes the protocol for and the quality of manual anthropometric measurements in BINA, a study conducted in 2016-17 in Atlanta, USA. Quality was evaluated by examining digit preference, biological plausibility of z-scores, z-score standard deviations, and reliability. We calculated z-scores and analyzed plausibility based on the 2006 WHO Child Growth Standards (CGS). For reliability, we calculated intra- and inter-observer Technical Error of Measurement (TEM) and Intraclass Correlation Coefficient (ICC). We found low digit preference; 99.6% of z-scores were biologically plausible, with z-score standard deviations ranging from 0.92 to 1.07. Total TEM was 0.40 for stature, 0.28 for HC, and 0.25 for MUAC in centimeters. ICC ranged from 0.99 to 1.00. The quality of manual measurements in BINA was high and similar to that of the anthropometric data used to develop the WHO CGS. We attributed high quality to vigorous training, motivated and competent field staff, reduction of non-measurement error through the use of technology, and reduction of measurement error through adequate monitoring and supervision. Our anthropometry measurement protocol, which builds on and improves upon the protocol used for the WHO CGS, can be used to improve anthropometric data quality. The discussion illustrates the need to standardize anthropometric data quality assessment, and we conclude that BINA can provide a valuable evaluation of 3D imaging for child anthropometry because there is comparison to gold-standard, manual measurements.

Reassessing regime shifts in the North Pacific: incremental climate change and commercial fishing are necessary for explaining decadal-scale biological variability.

PubMed

Litzow, Michael A; Mueter, Franz J; Hobday, Alistair J

2014-01-01

In areas of the North Pacific that are largely free of overfishing, climate regime shifts - abrupt changes in modes of low-frequency climate variability - are seen as the dominant drivers of decadal-scale ecological variability. We assessed the ability of leading modes of climate variability [Pacific Decadal Oscillation (PDO), North Pacific Gyre Oscillation (NPGO), Arctic Oscillation (AO), Pacific-North American Pattern (PNA), North Pacific Index (NPI), El Niño-Southern Oscillation (ENSO)] to explain decadal-scale (1965-2008) patterns of climatic and biological variability across two North Pacific ecosystems (Gulf of Alaska and Bering Sea). Our response variables were the first principle component (PC1) of four regional climate parameters [sea surface temperature (SST), sea level pressure (SLP), freshwater input, ice cover], and PCs 1-2 of 36 biological time series [production or abundance for populations of salmon (Oncorhynchus spp.), groundfish, herring (Clupea pallasii), shrimp, and jellyfish]. We found that the climate modes alone could not explain ecological variability in the study region. Both linear models (for climate PC1) and generalized additive models (for biology PC1-2) invoking only the climate modes produced residuals with significant temporal trends, indicating that the models failed to capture coherent patterns of ecological variability. However, when the residual climate trend and a time series of commercial fishery catches were used as additional candidate variables, resulting models of biology PC1-2 satisfied assumptions of independent residuals and out-performed models constructed from the climate modes alone in terms of predictive power. As measured by effect size and Akaike weights, the residual climate trend was the most important variable for explaining biology PC1 variability, and commercial catch the most important variable for biology PC2. Patterns of climate sensitivity and exploitation history for taxa strongly associated with biology PC1-2 suggest plausible mechanistic explanations for these modeling results. Our findings suggest that, even in the absence of overfishing and in areas strongly influenced by internal climate variability, climate regime shift effects can only be understood in the context of other ecosystem perturbations. © 2013 John Wiley & Sons Ltd.

Mode of action in relevance of rodent liver tumors to human cancer risk.

PubMed

Holsapple, Michael P; Pitot, Henri C; Cohen, Samuel M; Cohen, Samuel H; Boobis, Alan R; Klaunig, James E; Pastoor, Timothy; Dellarco, Vicki L; Dragan, Yvonne P

2006-01-01

Hazard identification and risk assessment paradigms depend on the presumption of the similarity of rodents to humans, yet species specific responses, and the extrapolation of high-dose effects to low-dose exposures can affect the estimation of human risk from rodent data. As a consequence, a human relevance framework concept was developed by the International Programme on Chemical Safety (IPCS) and International Life Sciences Institute (ILSI) Risk Science Institute (RSI) with the central tenet being the identification of a mode of action (MOA). To perform a MOA analysis, the key biochemical, cellular, and molecular events need to first be established, and the temporal and dose-dependent concordance of each of the key events in the MOA can then be determined. The key events can be used to bridge species and dose for a given MOA. The next step in the MOA analysis is the assessment of biological plausibility for determining the relevance of the specified MOA in an animal model for human cancer risk based on kinetic and dynamic parameters. Using the framework approach, a MOA in animals could not be defined for metal overload. The MOA for phenobarbital (PB)-like P450 inducers was determined to be unlikely in humans after kinetic and dynamic factors were considered. In contrast, after these factors were considered with reference to estrogen, the conclusion was drawn that estrogen-induced tumors were plausible in humans. Finally, it was concluded that the induction of rodent liver tumors by porphyrogenic compounds followed a cytotoxic MOA, and that liver tumors formed as a result of sustained cytotoxicity and regenerative proliferation are considered relevant for evaluating human cancer risk if appropriate metabolism occurs in the animal models and in humans.

Growth rates of rainbow smelt in Lake Champlain: Effects of density and diet

USGS Publications Warehouse

Stritzel, Thomson J.L.; Parrish, D.L.; Parker-Stetter, S. L.; Rudstam, L. G.; Sullivan, P.J.

2011-01-01

Stritzel Thomson JL, Parrish DL, Parker-Stetter SL, Rudstam LG, Sullivan PJ. Growth rates of rainbow smelt in Lake Champlain: effects of density and diet. Ecology of Freshwater Fish 2010. ?? 2010 John Wiley & Sons A/S Abstract- We estimated the densities of rainbow smelt (Osmerus mordax) using hydroacoustics and obtained specimens for diet analysis and groundtruthed acoustics data from mid-water trawl sampling in four areas of Lake Champlain, USA-Canada. Densities of rainbow smelt cohorts alternated during the 2-year study; age-0 rainbow smelt were very abundant in 2001 (up to 6fish per m2) and age-1 and older were abundant (up to 1.2fish per m2) in 2002. Growth rates and densities varied among areas and years. We used model selection on eight area-year-specific variables to investigate biologically plausible predictors of rainbow smelt growth rates. The best supported model of growth rates of age-0 smelt indicated a negative relationship with age-0 density, likely associated with intraspecific competition for zooplankton. The next best-fit model had age-1 density as a predictor of age-0 growth. The best supported models (N=4) of growth rates of age-1 fish indicated a positive relationship with availability of age-0 smelt and resulting levels of cannibalism. Other plausible models were contained variants of these parameters. Cannibalistic rainbow smelt consumed younger conspecifics that were up to 53% of their length. Prediction of population dynamics for rainbow smelt requires an understanding of the relationship between density and growth as age-0 fish outgrow their main predators (adult smelt) by autumn in years with fast growth rates, but not in years with slow growth rates. ?? 2011 John Wiley & Sons A/S.

Idiopathic environmental intolerance: Part 1: A causation analysis applying Bradford Hill's criteria to the toxicogenic theory.

PubMed

Staudenmayer, Herman; Binkley, Karen E; Leznoff, Arthur; Phillips, Scott

2003-01-01

Idiopathic environmental intolerance (IEI) is a descriptor for a phenomenon that has many names including environmental illness, multiple chemical sensitivity and chemical intolerance. Toxicogenic and psychogenic theories have been proposed to explain IEI. This paper presents a causality analysis of the toxicogenic theory using Bradford Hill's nine criteria (strength, consistency, specificity, temporality, biological gradient, biological plausibility, coherence, experimental intervention and analogy) and an additional criteria (reversibility) and reviews critically the scientific literature on the topic. The results of this analysis indicate that the toxicogenic theory fails all of these criteria. There is no convincing evidence to support the fundamental postulate that IEI has a toxic aetiology; the hypothesised biological processes and mechanisms are implausible.

Biological activities and medicinal properties of Gokhru (Pedalium murex L.)

PubMed Central

Rajashekar, V; Rao, E Upender; P, Srinivas

2012-01-01

Bada Gokhru (Pedalium murex L.) is perhaps the most useful traditional medicinal plant in India. Each part of the neem tree has some medicinal property and is thus commercially exploitable. During the last five decades, apart from the chemistry of the Pedalium murex compounds, considerable progress has been achieved regarding the biological activity and medicinal applications of this plant. It is now considered as a valuable source of unique natural products for development of medicines against various diseases and also for the development of industrial products. This review gives a bird's eye view mainly on the biological activities of some of this compounds isolated, pharmacological actions of the extracts, clinical studies and plausible medicinal applications of gokharu along with their safety evaluation. PMID:23569975

Gestation-Specific Changes in the Anatomy and Physiology of Healthy Pregnant Women: An Extended Repository of Model Parameters for Physiologically Based Pharmacokinetic Modeling in Pregnancy.

PubMed

Dallmann, André; Ince, Ibrahim; Meyer, Michaela; Willmann, Stefan; Eissing, Thomas; Hempel, Georg

2017-11-01

In the past years, several repositories for anatomical and physiological parameters required for physiologically based pharmacokinetic modeling in pregnant women have been published. While providing a good basis, some important aspects can be further detailed. For example, they did not account for the variability associated with parameters or were lacking key parameters necessary for developing more detailed mechanistic pregnancy physiologically based pharmacokinetic models, such as the composition of pregnancy-specific tissues. The aim of this meta-analysis was to provide an updated and extended database of anatomical and physiological parameters in healthy pregnant women that also accounts for changes in the variability of a parameter throughout gestation and for the composition of pregnancy-specific tissues. A systematic literature search was carried out to collect study data on pregnancy-related changes of anatomical and physiological parameters. For each parameter, a set of mathematical functions was fitted to the data and to the standard deviation observed among the data. The best performing functions were selected based on numerical and visual diagnostics as well as based on physiological plausibility. The literature search yielded 473 studies, 302 of which met the criteria to be further analyzed and compiled in a database. In total, the database encompassed 7729 data. Although the availability of quantitative data for some parameters remained limited, mathematical functions could be generated for many important parameters. Gaps were filled based on qualitative knowledge and based on physiologically plausible assumptions. The presented results facilitate the integration of pregnancy-dependent changes in anatomy and physiology into mechanistic population physiologically based pharmacokinetic models. Such models can ultimately provide a valuable tool to investigate the pharmacokinetics during pregnancy in silico and support informed decision making regarding optimal dosing regimens in this vulnerable special population.

The neural optimal control hierarchy for motor control

NASA Astrophysics Data System (ADS)

DeWolf, T.; Eliasmith, C.

2011-10-01

Our empirical, neuroscientific understanding of biological motor systems has been rapidly growing in recent years. However, this understanding has not been systematically mapped to a quantitative characterization of motor control based in control theory. Here, we attempt to bridge this gap by describing the neural optimal control hierarchy (NOCH), which can serve as a foundation for biologically plausible models of neural motor control. The NOCH has been constructed by taking recent control theoretic models of motor control, analyzing the required processes, generating neurally plausible equivalent calculations and mapping them on to the neural structures that have been empirically identified to form the anatomical basis of motor control. We demonstrate the utility of the NOCH by constructing a simple model based on the identified principles and testing it in two ways. First, we perturb specific anatomical elements of the model and compare the resulting motor behavior with clinical data in which the corresponding area of the brain has been damaged. We show that damaging the assigned functions of the basal ganglia and cerebellum can cause the movement deficiencies seen in patients with Huntington's disease and cerebellar lesions. Second, we demonstrate that single spiking neuron data from our model's motor cortical areas explain major features of single-cell responses recorded from the same primate areas. We suggest that together these results show how NOCH-based models can be used to unify a broad range of data relevant to biological motor control in a quantitative, control theoretic framework.

Total Synthesis and Absolute Configuration of Laurenditerpenol: A Hypoxia Inducible Factor-1 Activation Inhibitor

PubMed Central

Chittiboyina, Amar G.; Kumar, Gundluru Mahesh; Carvalho, Paulo B.; Liu, Yang; Zhou, Yu-Dong; Nagle, Dale G.

2010-01-01

The absolute stereo structure of the natural product laurenditerpenol (1S, 6R, 7S, 10R, 11R, 14S, 15R) has been accomplished from eight plausible stereoisomers by its first asymmetric total synthesis in a highly convergent and flexible synthetic pathway. Six stereoisomers of laurenditerpenol were synthesized and evaluated for their biological activity. PMID:18004798

Constructing Precisely Computing Networks with Biophysical Spiking Neurons.

PubMed

Schwemmer, Michael A; Fairhall, Adrienne L; Denéve, Sophie; Shea-Brown, Eric T

2015-07-15

While spike timing has been shown to carry detailed stimulus information at the sensory periphery, its possible role in network computation is less clear. Most models of computation by neural networks are based on population firing rates. In equivalent spiking implementations, firing is assumed to be random such that averaging across populations of neurons recovers the rate-based approach. Recently, however, Denéve and colleagues have suggested that the spiking behavior of neurons may be fundamental to how neuronal networks compute, with precise spike timing determined by each neuron's contribution to producing the desired output (Boerlin and Denéve, 2011; Boerlin et al., 2013). By postulating that each neuron fires to reduce the error in the network's output, it was demonstrated that linear computations can be performed by networks of integrate-and-fire neurons that communicate through instantaneous synapses. This left open, however, the possibility that realistic networks, with conductance-based neurons with subthreshold nonlinearity and the slower timescales of biophysical synapses, may not fit into this framework. Here, we show how the spike-based approach can be extended to biophysically plausible networks. We then show that our network reproduces a number of key features of cortical networks including irregular and Poisson-like spike times and a tight balance between excitation and inhibition. Lastly, we discuss how the behavior of our model scales with network size or with the number of neurons "recorded" from a larger computing network. These results significantly increase the biological plausibility of the spike-based approach to network computation. We derive a network of neurons with standard spike-generating currents and synapses with realistic timescales that computes based upon the principle that the precise timing of each spike is important for the computation. We then show that our network reproduces a number of key features of cortical networks including irregular, Poisson-like spike times, and a tight balance between excitation and inhibition. These results significantly increase the biological plausibility of the spike-based approach to network computation, and uncover how several components of biological networks may work together to efficiently carry out computation. Copyright © 2015 the authors 0270-6474/15/3510112-23$15.00/0.

Evaluating and improving count-based population inference: A case study from 31 years of monitoring Sandhill Cranes

USGS Publications Warehouse

Gerber, Brian D.; Kendall, William L.

2017-01-01

Monitoring animal populations can be difficult. Limited resources often force monitoring programs to rely on unadjusted or smoothed counts as an index of abundance. Smoothing counts is commonly done using a moving-average estimator to dampen sampling variation. These indices are commonly used to inform management decisions, although their reliability is often unknown. We outline a process to evaluate the biological plausibility of annual changes in population counts and indices from a typical monitoring scenario and compare results with a hierarchical Bayesian time series (HBTS) model. We evaluated spring and fall counts, fall indices, and model-based predictions for the Rocky Mountain population (RMP) of Sandhill Cranes (Antigone canadensis) by integrating juvenile recruitment, harvest, and survival into a stochastic stage-based population model. We used simulation to evaluate population indices from the HBTS model and the commonly used 3-yr moving average estimator. We found counts of the RMP to exhibit biologically unrealistic annual change, while the fall population index was largely biologically realistic. HBTS model predictions suggested that the RMP changed little over 31 yr of monitoring, but the pattern depended on assumptions about the observational process. The HBTS model fall population predictions were biologically plausible if observed crane harvest mortality was compensatory up to natural mortality, as empirical evidence suggests. Simulations indicated that the predicted mean of the HBTS model was generally a more reliable estimate of the true population than population indices derived using a moving 3-yr average estimator. Practitioners could gain considerable advantages from modeling population counts using a hierarchical Bayesian autoregressive approach. Advantages would include: (1) obtaining measures of uncertainty; (2) incorporating direct knowledge of the observational and population processes; (3) accommodating missing years of data; and (4) forecasting population size.

Simulation-based sensitivity analysis for non-ignorably missing data.

PubMed

Yin, Peng; Shi, Jian Q

2017-01-01

Sensitivity analysis is popular in dealing with missing data problems particularly for non-ignorable missingness, where full-likelihood method cannot be adopted. It analyses how sensitively the conclusions (output) may depend on assumptions or parameters (input) about missing data, i.e. missing data mechanism. We call models with the problem of uncertainty sensitivity models. To make conventional sensitivity analysis more useful in practice we need to define some simple and interpretable statistical quantities to assess the sensitivity models and make evidence based analysis. We propose a novel approach in this paper on attempting to investigate the possibility of each missing data mechanism model assumption, by comparing the simulated datasets from various MNAR models with the observed data non-parametrically, using the K-nearest-neighbour distances. Some asymptotic theory has also been provided. A key step of this method is to plug in a plausibility evaluation system towards each sensitivity parameter, to select plausible values and reject unlikely values, instead of considering all proposed values of sensitivity parameters as in the conventional sensitivity analysis method. The method is generic and has been applied successfully to several specific models in this paper including meta-analysis model with publication bias, analysis of incomplete longitudinal data and mean estimation with non-ignorable missing data.

Path integration of head direction: updating a packet of neural activity at the correct speed using neuronal time constants.

PubMed

Walters, D M; Stringer, S M

2010-07-01

A key question in understanding the neural basis of path integration is how individual, spatially responsive, neurons may self-organize into networks that can, through learning, integrate velocity signals to update a continuous representation of location within an environment. It is of vital importance that this internal representation of position is updated at the correct speed, and in real time, to accurately reflect the motion of the animal. In this article, we present a biologically plausible model of velocity path integration of head direction that can solve this problem using neuronal time constants to effect natural time delays, over which associations can be learned through associative Hebbian learning rules. The model comprises a linked continuous attractor network and competitive network. In simulation, we show that the same model is able to learn two different speeds of rotation when implemented with two different values for the time constant, and without the need to alter any other model parameters. The proposed model could be extended to path integration of place in the environment, and path integration of spatial view.

The Impact of Deviation from Michaelis-Menten Saturation on Mathematical Model Stability Properties

NASA Technical Reports Server (NTRS)

Blackwell, Charles; Kliss, Mark (Technical Monitor)

1998-01-01

Based on purely abstract ecological theory, it has been argued that a system composed of two or more consumers competing for the same resource cannot persist. By analysis on a Monod format mathematical model, Hubble and others demonstrated that this assertion is true for all but very special cases of such competing organisms which are determined by an index formed by a grouping of. the parameters which characterize the biological processes of the competing organisms. In the laboratory, using a bioreactor, Hansen and Hubble obtained confirmatory results for several cases of two competing species, and they characterized it as "qualitative confirmation" of the assertion. This result is amazing, since the analysis required the exact equality of the hey index, and it seems certain that no pair of organism species could have exactly equal values. It is quite plausible, however, that pairs of organism species could have approximately equal indices, and the question of how different they could be and still have coexistence of the two (or more) presents itself. In this paper, the pursuit of this question and a compatible resolution is presented.

A New Insight into the Earthquake Recurrence Studies from the Three-parameter Generalized Exponential Distributions

NASA Astrophysics Data System (ADS)

Pasari, S.; Kundu, D.; Dikshit, O.

2012-12-01

Earthquake recurrence interval is one of the important ingredients towards probabilistic seismic hazard assessment (PSHA) for any location. Exponential, gamma, Weibull and lognormal distributions are quite established probability models in this recurrence interval estimation. However, they have certain shortcomings too. Thus, it is imperative to search for some alternative sophisticated distributions. In this paper, we introduce a three-parameter (location, scale and shape) exponentiated exponential distribution and investigate the scope of this distribution as an alternative of the afore-mentioned distributions in earthquake recurrence studies. This distribution is a particular member of the exponentiated Weibull distribution. Despite of its complicated form, it is widely accepted in medical and biological applications. Furthermore, it shares many physical properties with gamma and Weibull family. Unlike gamma distribution, the hazard function of generalized exponential distribution can be easily computed even if the shape parameter is not an integer. To contemplate the plausibility of this model, a complete and homogeneous earthquake catalogue of 20 events (M ≥ 7.0) spanning for the period 1846 to 1995 from North-East Himalayan region (20-32 deg N and 87-100 deg E) has been used. The model parameters are estimated using maximum likelihood estimator (MLE) and method of moment estimator (MOME). No geological or geophysical evidences have been considered in this calculation. The estimated conditional probability reaches quite high after about a decade for an elapsed time of 17 years (i.e. 2012). Moreover, this study shows that the generalized exponential distribution fits the above data events more closely compared to the conventional models and hence it is tentatively concluded that generalized exponential distribution can be effectively considered in earthquake recurrence studies.

Combining super-ensembles and statistical emulation to improve a regional climate and vegetation model

NASA Astrophysics Data System (ADS)

Hawkins, L. R.; Rupp, D. E.; Li, S.; Sarah, S.; McNeall, D. J.; Mote, P.; Betts, R. A.; Wallom, D.

2017-12-01

Changing regional patterns of surface temperature, precipitation, and humidity may cause ecosystem-scale changes in vegetation, altering the distribution of trees, shrubs, and grasses. A changing vegetation distribution, in turn, alters the albedo, latent heat flux, and carbon exchanged with the atmosphere with resulting feedbacks onto the regional climate. However, a wide range of earth-system processes that affect the carbon, energy, and hydrologic cycles occur at sub grid scales in climate models and must be parameterized. The appropriate parameter values in such parameterizations are often poorly constrained, leading to uncertainty in predictions of how the ecosystem will respond to changes in forcing. To better understand the sensitivity of regional climate to parameter selection and to improve regional climate and vegetation simulations, we used a large perturbed physics ensemble and a suite of statistical emulators. We dynamically downscaled a super-ensemble (multiple parameter sets and multiple initial conditions) of global climate simulations using a 25-km resolution regional climate model HadRM3p with the land-surface scheme MOSES2 and dynamic vegetation module TRIFFID. We simultaneously perturbed land surface parameters relating to the exchange of carbon, water, and energy between the land surface and atmosphere in a large super-ensemble of regional climate simulations over the western US. Statistical emulation was used as a computationally cost-effective tool to explore uncertainties in interactions. Regions of parameter space that did not satisfy observational constraints were eliminated and an ensemble of parameter sets that reduce regional biases and span a range of plausible interactions among earth system processes were selected. This study demonstrated that by combining super-ensemble simulations with statistical emulation, simulations of regional climate could be improved while simultaneously accounting for a range of plausible land-atmosphere feedback strengths.

AIDA - from Airborne Data Inversion to In-Depth Analysis

NASA Astrophysics Data System (ADS)

Meyer, U.; Goetze, H.; Schroeder, M.; Boerner, R.; Tezkan, B.; Winsemann, J.; Siemon, B.; Alvers, M.; Stoll, J. B.

2011-12-01

The rising competition in land use especially between water economy, agriculture, forestry, building material economy and other industries often leads to irreversible deterioration in the water and soil system (as salinization and degradation) which results in a long term damage of natural resources. A sustainable exploitation of the near subsurface by industry, economy and private households is a fundamental demand of a modern society. To fulfill this demand, a sound and comprehensive knowledge on structures and processes of the near subsurface is an important prerequisite. A spatial survey of the usable underground by aerogeophysical means and a subsequent ground geophysics survey targeted at special locations will deliver essential contributions within short time that make it possible to gain the needed additional knowledge. The complementary use of airborne and ground geophysics as well as the validation, assimilation and improvement of current findings by geological and hydrogeological investigations and plausibility tests leads to the following key questions: a) Which new and/or improved automatic algorithms (joint inversion, data assimilation and such) are useful to describe the structural setting of the usable subsurface by user specific characteristics as i.e. water volume, layer thicknesses, porosities etc.? b) What are the physical relations of the measured parameters (as electrical conductivities, magnetic susceptibilities, densities, etc.)? c) How can we deduce characteristics or parameters from the observations which describe near subsurface structures as ground water systems, their charge, discharge and recharge, vulnerabilities and other quantities? d) How plausible and realistic are the numerically obtained results in relation to user specific questions and parameters? e) Is it possible to compile material flux balances that describe spatial and time dependent impacts of environmental changes on aquifers and soils by repeated airborne surveys? In order to follow up these questions raised the project aims to achieve the following goals: a) Development of new and expansion of existent inversion strategies to improve structural parameter information on different space and time scales. b) Development, modification, and tests for a multi-parameter inversion (joint inversion). c) Development of new quantitative approaches in data assimilation and plausibility studies. d) Compilation of optimized work flows for fast employment by end users. e) Primary goal is to solve comparable society related problems (as salinization, erosion, contamination, degradation etc.) in regions within Germany and abroad by generalization of project results.

Parameter and model uncertainty in a life-table model for fine particles (PM2.5): a statistical modeling study

PubMed Central

Tainio, Marko; Tuomisto, Jouni T; Hänninen, Otto; Ruuskanen, Juhani; Jantunen, Matti J; Pekkanen, Juha

2007-01-01

Background The estimation of health impacts involves often uncertain input variables and assumptions which have to be incorporated into the model structure. These uncertainties may have significant effects on the results obtained with model, and, thus, on decision making. Fine particles (PM2.5) are believed to cause major health impacts, and, consequently, uncertainties in their health impact assessment have clear relevance to policy-making. We studied the effects of various uncertain input variables by building a life-table model for fine particles. Methods Life-expectancy of the Helsinki metropolitan area population and the change in life-expectancy due to fine particle exposures were predicted using a life-table model. A number of parameter and model uncertainties were estimated. Sensitivity analysis for input variables was performed by calculating rank-order correlations between input and output variables. The studied model uncertainties were (i) plausibility of mortality outcomes and (ii) lag, and parameter uncertainties (iii) exposure-response coefficients for different mortality outcomes, and (iv) exposure estimates for different age groups. The monetary value of the years-of-life-lost and the relative importance of the uncertainties related to monetary valuation were predicted to compare the relative importance of the monetary valuation on the health effect uncertainties. Results The magnitude of the health effects costs depended mostly on discount rate, exposure-response coefficient, and plausibility of the cardiopulmonary mortality. Other mortality outcomes (lung cancer, other non-accidental and infant mortality) and lag had only minor impact on the output. The results highlight the importance of the uncertainties associated with cardiopulmonary mortality in the fine particle impact assessment when compared with other uncertainties. Conclusion When estimating life-expectancy, the estimates used for cardiopulmonary exposure-response coefficient, discount rate, and plausibility require careful assessment, while complicated lag estimates can be omitted without this having any major effect on the results. PMID:17714598

Parameter and model uncertainty in a life-table model for fine particles (PM2.5): a statistical modeling study.

PubMed

Tainio, Marko; Tuomisto, Jouni T; Hänninen, Otto; Ruuskanen, Juhani; Jantunen, Matti J; Pekkanen, Juha

2007-08-23

The estimation of health impacts involves often uncertain input variables and assumptions which have to be incorporated into the model structure. These uncertainties may have significant effects on the results obtained with model, and, thus, on decision making. Fine particles (PM2.5) are believed to cause major health impacts, and, consequently, uncertainties in their health impact assessment have clear relevance to policy-making. We studied the effects of various uncertain input variables by building a life-table model for fine particles. Life-expectancy of the Helsinki metropolitan area population and the change in life-expectancy due to fine particle exposures were predicted using a life-table model. A number of parameter and model uncertainties were estimated. Sensitivity analysis for input variables was performed by calculating rank-order correlations between input and output variables. The studied model uncertainties were (i) plausibility of mortality outcomes and (ii) lag, and parameter uncertainties (iii) exposure-response coefficients for different mortality outcomes, and (iv) exposure estimates for different age groups. The monetary value of the years-of-life-lost and the relative importance of the uncertainties related to monetary valuation were predicted to compare the relative importance of the monetary valuation on the health effect uncertainties. The magnitude of the health effects costs depended mostly on discount rate, exposure-response coefficient, and plausibility of the cardiopulmonary mortality. Other mortality outcomes (lung cancer, other non-accidental and infant mortality) and lag had only minor impact on the output. The results highlight the importance of the uncertainties associated with cardiopulmonary mortality in the fine particle impact assessment when compared with other uncertainties. When estimating life-expectancy, the estimates used for cardiopulmonary exposure-response coefficient, discount rate, and plausibility require careful assessment, while complicated lag estimates can be omitted without this having any major effect on the results.

Proof of age required--estimating age in adults without birth records.

PubMed

Phillips, Christine; Narayanasamy, Shanti

2010-07-01

Many adults from refugee source countries do not have documents of birth, either because they have been lost in flight, or because the civil infrastructure is too fragile to support routine recording of birth. In Western countries, date of birth is used as a basic identifier, and access to services and support tends to be age regulated. Doctors are not infrequently asked to write formal reports estimating the true age of adult refugees; however, there are no existing guidelines to assist in this task. To provide an overview of methods to estimate age in living adults, and outline recommendations for best practice. Age should be estimated through physical examination; life history, matching local or national events with personal milestones; and existing nonformal documents. Accuracy of age estimation should be subject to three tests: biological plausibility, historical plausibility, and corroboration from reputable sources.

Strong systematicity through sensorimotor conceptual grounding: an unsupervised, developmental approach to connectionist sentence processing

NASA Astrophysics Data System (ADS)

Jansen, Peter A.; Watter, Scott

2012-03-01

Connectionist language modelling typically has difficulty with syntactic systematicity, or the ability to generalise language learning to untrained sentences. This work develops an unsupervised connectionist model of infant grammar learning. Following the semantic boostrapping hypothesis, the network distils word category using a developmentally plausible infant-scale database of grounded sensorimotor conceptual representations, as well as a biologically plausible semantic co-occurrence activation function. The network then uses this knowledge to acquire an early benchmark clausal grammar using correlational learning, and further acquires separate conceptual and grammatical category representations. The network displays strongly systematic behaviour indicative of the general acquisition of the combinatorial systematicity present in the grounded infant-scale language stream, outperforms previous contemporary models that contain primarily noun and verb word categories, and successfully generalises broadly to novel untrained sensorimotor grounded sentences composed of unfamiliar nouns and verbs. Limitations as well as implications to later grammar learning are discussed.

Cerebrovascular Hemodynamics in Women.

PubMed

Duque, Cristina; Feske, Steven K; Sorond, Farzaneh A

2017-12-01

Sex and gender, as biological and social factors, significantly influence health outcomes. Among the biological factors, sex differences in vascular physiology may be one specific mechanism contributing to the observed differences in clinical presentation, response to treatment, and clinical outcomes in several vascular disorders. This review focuses on the cerebrovascular bed and summarizes the existing literature on sex differences in cerebrovascular hemodynamics to highlight the knowledge deficit that exists in this domain. The available evidence is used to generate mechanistically plausible and testable hypotheses to underscore the unmet need in understanding sex-specific mechanisms as targets for more effective therapeutic and preventive strategies. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

Cure models for the analysis of time-to-event data in cancer studies.

PubMed

Jia, Xiaoyu; Sima, Camelia S; Brennan, Murray F; Panageas, Katherine S

2013-11-01

In settings when it is biologically plausible that some patients are cured after definitive treatment, cure models present an alternative to conventional survival analysis. Cure models can inform on the group of patients cured, by estimating the probability of cure, and identifying factors that influence it; while simultaneously focusing on time to recurrence and associated factors for the remaining patients. © 2013 Wiley Periodicals, Inc.

Untangling the Impacts of Climate Change on Waterborne Diseases: a Systematic Review of Relationships between Diarrheal Diseases and Temperature, Rainfall, Flooding, and Drought.

PubMed

Levy, Karen; Woster, Andrew P; Goldstein, Rebecca S; Carlton, Elizabeth J

2016-05-17

Global climate change is expected to affect waterborne enteric diseases, yet to date there has been no comprehensive, systematic review of the epidemiological literature examining the relationship between meteorological conditions and diarrheal diseases. We searched PubMed, Embase, Web of Science, and the Cochrane Collection for studies describing the relationship between diarrheal diseases and four meteorological conditions that are expected to increase with climate change: ambient temperature, heavy rainfall, drought, and flooding. We synthesized key areas of agreement and evaluated the biological plausibility of these findings, drawing from a diverse, multidisciplinary evidence base. We identified 141 articles that met our inclusion criteria. Key areas of agreement include a positive association between ambient temperature and diarrheal diseases, with the exception of viral diarrhea and an increase in diarrheal disease following heavy rainfall and flooding events. Insufficient evidence was available to evaluate the effects of drought on diarrhea. There is evidence to support the biological plausibility of these associations, but publication bias is an ongoing concern. Future research evaluating whether interventions, such as improved water and sanitation access, modify risk would further our understanding of the potential impacts of climate change on diarrheal diseases and aid in the prioritization of adaptation measures.

Neuronal networks with NMDARs and lateral inhibition implement winner-takes-all

PubMed Central

Shoemaker, Patrick A.

2015-01-01

A neural circuit that relies on the electrical properties of NMDA synaptic receptors is shown by numerical and theoretical analysis to be capable of realizing the winner-takes-all function, a powerful computational primitive that is often attributed to biological nervous systems. This biophysically-plausible model employs global lateral inhibition in a simple feedback arrangement. As its inputs increase, high-gain and then bi- or multi-stable equilibrium states may be assumed in which there is significant depolarization of a single neuron and hyperpolarization or very weak depolarization of other neurons in the network. The state of the winning neuron conveys analog information about its input. The winner-takes-all characteristic depends on the nonmonotonic current-voltage relation of NMDA receptor ion channels, as well as neural thresholding, and the gain and nature of the inhibitory feedback. Dynamical regimes vary with input strength. Fixed points may become unstable as the network enters a winner-takes-all regime, which can lead to entrained oscillations. Under some conditions, oscillatory behavior can be interpreted as winner-takes-all in nature. Stable winner-takes-all behavior is typically recovered as inputs increase further, but with still larger inputs, the winner-takes-all characteristic is ultimately lost. Network stability may be enhanced by biologically plausible mechanisms. PMID:25741276

Pesticides, chemical and industrial exposures in relation to systemic lupus erythematosus

PubMed Central

Parks, Christine G.; De Roos, Anneclaire J.

2013-01-01

Growing evidence suggests exposure to chemicals and industrial pollutants may increase risk of SLE. Here we review research on SLE associations with occupational and industrial exposures, primarily drawing on studies in human populations and summarizing epidemiologic research published in the past decade. The association of occupational silica exposure with SLE is well established, but key questions remain, including the required dose and susceptibility factors, and SLE risk due to other silicate exposures. Research on SLE and other exposures is less well developed, though several potential associations merit further consideration due to the consistency of preliminary human findings, experimental animal research, and biologic plausibility. These include pesticides and solvents, for which experimental findings also support investigation of specific agents, including organochlorines and trichloroethylene. Experimental findings and biologic plausibility suggest research on SLE and occupational exposure to hydrocarbons (i.e., mineral oils) is warranted, especially given the widespread exposures in the population. Experimental and limited human findings support further investigation of SLE related to mercury exposure, especially in dental occupations. Research on environmental risk factors in risk-enriched cohorts (family based) is recommended, as is further investigation of exposures in relation to intermediate markers of effect (e.g., antinuclear antibodies), clinical features (e.g., nephritis) and outcomes. PMID:24763537

View-tolerant face recognition and Hebbian learning imply mirror-symmetric neural tuning to head orientation

PubMed Central

Leibo, Joel Z.; Liao, Qianli; Freiwald, Winrich A.; Anselmi, Fabio; Poggio, Tomaso

2017-01-01

SUMMARY The primate brain contains a hierarchy of visual areas, dubbed the ventral stream, which rapidly computes object representations that are both specific for object identity and robust against identity-preserving transformations like depth-rotations [1, 2]. Current computational models of object recognition, including recent deep learning networks, generate these properties through a hierarchy of alternating selectivity-increasing filtering and tolerance-increasing pooling operations, similar to simple-complex cells operations [3, 4, 5, 6]. Here we prove that a class of hierarchical architectures and a broad set of biologically plausible learning rules generate approximate invariance to identity-preserving transformations at the top level of the processing hierarchy. However, all past models tested failed to reproduce the most salient property of an intermediate representation of a three-level face-processing hierarchy in the brain: mirror-symmetric tuning to head orientation [7]. Here we demonstrate that one specific biologically-plausible Hebb-type learning rule generates mirror-symmetric tuning to bilaterally symmetric stimuli like faces at intermediate levels of the architecture and show why it does so. Thus the tuning properties of individual cells inside the visual stream appear to result from group properties of the stimuli they encode and to reflect the learning rules that sculpted the information-processing system within which they reside. PMID:27916522

Biological Warfare at the 1346 Siege of Caffa

PubMed Central

2002-01-01

On the basis of a 14th-century account by the Genoese Gabriele de’ Mussi, the Black Death is widely believed to have reached Europe from the Crimea as the result of a biological warfare attack. This is not only of great historical interest but also relevant to current efforts to evaluate the threat of military or terrorist use of biological weapons. Based on published translations of the de’ Mussi manuscript, other 14th-century accounts of the Black Death, and secondary scholarly literature, I conclude that the claim that biological warfare was used at Caffa is plausible and provides the best explanation of the entry of plague into the city. This theory is consistent with the technology of the times and with contemporary notions of disease causation; however, the entry of plague into Europe from the Crimea likely occurred independent of this event. PMID:12194776

Subjectivity: A Case of Biological Individuation and an Adaptive Response to Informational Overflow

PubMed Central

Jonkisz, Jakub

2016-01-01

The article presents a perspective on the scientific explanation of the subjectivity of conscious experience. It proposes plausible answers for two empirically valid questions: the ‘how’ question concerning the developmental mechanisms of subjectivity, and the ‘why’ question concerning its function. Biological individuation, which is acquired in several different stages, serves as a provisional description of how subjective perspectives may have evolved. To the extent that an individuated informational space seems the most efficient way for a given organism to select biologically valuable information, subjectivity is deemed to constitute an adaptive response to informational overflow. One of the possible consequences of this view is that subjectivity might be (at least functionally) dissociated from consciousness, insofar as the former primarily facilitates selection, the latter action. PMID:27555835

The metaphysical lessons of synthetic biology and neuroscience.

PubMed

Baertschi, Bernard

2015-01-01

In this paper, I examine some important metaphysical lessons that are often presented as derived from two new scientific disciplines: synthetic biology and neuroscience. I analyse four of them: the nature of life, the existence of a soul (the mind-body problem), personhood, and free will. Many caveats are in order, and each 'advance' or each case should be assessed for itself. I conclude that a main lesson can nevertheless be learned: in conjunction with modern science, neuroscience and synthetic biology allow us to enrich old metaphysical debates, to deepen and even renew them. In particular, it becomes less and less plausible to consider life, mind, person, and agency as non-natural or non-physical entities. Copyright © 2015 Académie des sciences. Published by Elsevier SAS. All rights reserved.

Using Dirichlet Priors to Improve Model Parameter Plausibility

ERIC Educational Resources Information Center

Rai, Dovan; Gong, Yue; Beck, Joseph E.

2009-01-01

Student modeling is a widely used approach to make inference about a student's attributes like knowledge, learning, etc. If we wish to use these models to analyze and better understand student learning there are two problems. First, a model's ability to predict student performance is at best weakly related to the accuracy of any one of its…

Do Selective Serotonin Reuptake Inhibitors (SSRIs) Cause Fractures?

PubMed

Warden, Stuart J; Fuchs, Robyn K

2016-10-01

Recent meta-analyses report a 70 % increase in fracture risk in selective serotonin reuptake inhibitor (SSRI) users compared to non-users; however, included studies were observational and limited in their ability to establish causality. Here, we use the Bradford Hill criteria to explore causality between SSRIs and fractures. We found a strong, consistent, and temporal relationship between SSRIs and fractures, which appears to follow a biological gradient. However, specificity and biological plausibility remain concerns. In terms of specificity, the majority of available data have limitations due to either confounding by indication or channeling bias. Self-controlled case series address some of these limitations and provide relatively strong observational evidence for a causal relationship between SSRIs and fracture. In doing so, they suggest that falls contribute to fractures in SSRI users. Whether there are also underlying changes in skeletal properties remains unresolved. Initial studies provide some evidence for skeletal effects of SSRIs; however, the pathways involved need to be established before biological plausibility can be accepted. As the link between SSRIs and fractures is based on observational data and not evidence from prospective trials, there is insufficient evidence to definitively determine a causal relationship and it appears premature to label SSRIs as a secondary cause of osteoporosis. SSRIs appear to contribute to fracture-inducing falls, and addressing any fall risk associated with SSRIs may be an efficient approach to reducing SSRI-related fractures. As fractures stemming from SSRI-induced falls are more likely in individuals with compromised bone health, it is worth considering bone density testing and intervention for those presenting with risk factors for osteoporosis.

Unsupervised learning of digit recognition using spike-timing-dependent plasticity

PubMed Central

Diehl, Peter U.; Cook, Matthew

2015-01-01

In order to understand how the mammalian neocortex is performing computations, two things are necessary; we need to have a good understanding of the available neuronal processing units and mechanisms, and we need to gain a better understanding of how those mechanisms are combined to build functioning systems. Therefore, in recent years there is an increasing interest in how spiking neural networks (SNN) can be used to perform complex computations or solve pattern recognition tasks. However, it remains a challenging task to design SNNs which use biologically plausible mechanisms (especially for learning new patterns), since most such SNN architectures rely on training in a rate-based network and subsequent conversion to a SNN. We present a SNN for digit recognition which is based on mechanisms with increased biological plausibility, i.e., conductance-based instead of current-based synapses, spike-timing-dependent plasticity with time-dependent weight change, lateral inhibition, and an adaptive spiking threshold. Unlike most other systems, we do not use a teaching signal and do not present any class labels to the network. Using this unsupervised learning scheme, our architecture achieves 95% accuracy on the MNIST benchmark, which is better than previous SNN implementations without supervision. The fact that we used no domain-specific knowledge points toward the general applicability of our network design. Also, the performance of our network scales well with the number of neurons used and shows similar performance for four different learning rules, indicating robustness of the full combination of mechanisms, which suggests applicability in heterogeneous biological neural networks. PMID:26941637

Comparison of Damping Mechanisms for Transverse Waves in Solar Coronal Loops

NASA Astrophysics Data System (ADS)

Montes-Solís, María; Arregui, Iñigo

2017-09-01

We present a method to assess the plausibility of alternative mechanisms to explain the damping of magnetohydrodynamic transverse waves in solar coronal loops. The considered mechanisms are resonant absorption of kink waves in the Alfvén continuum, phase mixing of Alfvén waves, and wave leakage. Our methods make use of Bayesian inference and model comparison techniques. We first infer the values for the physical parameters that control the wave damping, under the assumption of a particular mechanism, for typically observed damping timescales. Then, the computation of marginal likelihoods and Bayes factors enable us to quantify the relative plausibility between the alternative mechanisms. We find that, in general, the evidence is not large enough to support a single particular damping mechanism as the most plausible one. Resonant absorption and wave leakage offer the most probable explanations in strong damping regimes, while phase mixing is the best candidate for weak/moderate damping. When applied to a selection of 89 observed transverse loop oscillations, with their corresponding measurements of damping timescales and taking into account data uncertainties, we find that positive evidence for a given damping mechanism is only available in a few cases.

Possibilities and limits of Internet-based registers.

PubMed

Wild, Michael; Candrian, Aron; Wenda, Klaus

2009-03-01

The Internet is an inexpensive platform for the investigation of medical questions in case of low prevalence. By accessing www.ao-nailregister.org, every interested participant may participate in the English-language survey of the complications specific to the femoral nail. The address data of the participant, the anonymised key data of the patients and the medical parameters are entered. In real time, these data are checked for plausibility, evaluated and published on the Internet where they are freely accessible immediately. Because of national differences, data acquisition caused considerable difficulties at the beginning. In addition, wrong data were entered because of linguistic or contextual misunderstandings. After having reworked the questionnaire completely, facilitating data input and implementing an automated plausibility check, these difficulties could be cleared. In a next step, the automatic evaluation of the data was implemented. Only very few data still have to be checked for plausibility manually to exclude wrong entries, which cannot be verified by the computer. The effort required for data acquisition and evaluation of the Internet-based femoral nail register was reduced distinctly. The possibility of free international participation as well as the freely accessible representation of the results offers transparency.

Comparison of Damping Mechanisms for Transverse Waves in Solar Coronal Loops

DOE Office of Scientific and Technical Information (OSTI.GOV)

Montes-Solís, María; Arregui, Iñigo, E-mail: mmsolis@iac.es

We present a method to assess the plausibility of alternative mechanisms to explain the damping of magnetohydrodynamic transverse waves in solar coronal loops. The considered mechanisms are resonant absorption of kink waves in the Alfvén continuum, phase mixing of Alfvén waves, and wave leakage. Our methods make use of Bayesian inference and model comparison techniques. We first infer the values for the physical parameters that control the wave damping, under the assumption of a particular mechanism, for typically observed damping timescales. Then, the computation of marginal likelihoods and Bayes factors enable us to quantify the relative plausibility between the alternativemore » mechanisms. We find that, in general, the evidence is not large enough to support a single particular damping mechanism as the most plausible one. Resonant absorption and wave leakage offer the most probable explanations in strong damping regimes, while phase mixing is the best candidate for weak/moderate damping. When applied to a selection of 89 observed transverse loop oscillations, with their corresponding measurements of damping timescales and taking into account data uncertainties, we find that positive evidence for a given damping mechanism is only available in a few cases.« less

A Bayesian framework for adaptive selection, calibration, and validation of coarse-grained models of atomistic systems

NASA Astrophysics Data System (ADS)

Farrell, Kathryn; Oden, J. Tinsley; Faghihi, Danial

2015-08-01

A general adaptive modeling algorithm for selection and validation of coarse-grained models of atomistic systems is presented. A Bayesian framework is developed to address uncertainties in parameters, data, and model selection. Algorithms for computing output sensitivities to parameter variances, model evidence and posterior model plausibilities for given data, and for computing what are referred to as Occam Categories in reference to a rough measure of model simplicity, make up components of the overall approach. Computational results are provided for representative applications.

Probabilistic bias analysis in pharmacoepidemiology and comparative effectiveness research: a systematic review.

PubMed

Hunnicutt, Jacob N; Ulbricht, Christine M; Chrysanthopoulou, Stavroula A; Lapane, Kate L

2016-12-01

We systematically reviewed pharmacoepidemiologic and comparative effectiveness studies that use probabilistic bias analysis to quantify the effects of systematic error including confounding, misclassification, and selection bias on study results. We found articles published between 2010 and October 2015 through a citation search using Web of Science and Google Scholar and a keyword search using PubMed and Scopus. Eligibility of studies was assessed by one reviewer. Three reviewers independently abstracted data from eligible studies. Fifteen studies used probabilistic bias analysis and were eligible for data abstraction-nine simulated an unmeasured confounder and six simulated misclassification. The majority of studies simulating an unmeasured confounder did not specify the range of plausible estimates for the bias parameters. Studies simulating misclassification were in general clearer when reporting the plausible distribution of bias parameters. Regardless of the bias simulated, the probability distributions assigned to bias parameters, number of simulated iterations, sensitivity analyses, and diagnostics were not discussed in the majority of studies. Despite the prevalence and concern of bias in pharmacoepidemiologic and comparative effectiveness studies, probabilistic bias analysis to quantitatively model the effect of bias was not widely used. The quality of reporting and use of this technique varied and was often unclear. Further discussion and dissemination of the technique are warranted. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

A Biomass-based Model to Estimate the Plausibility of Exoplanet Biosignature Gases

NASA Astrophysics Data System (ADS)

Seager, S.; Bains, W.; Hu, R.

2013-10-01

Biosignature gas detection is one of the ultimate future goals for exoplanet atmosphere studies. We have created a framework for linking biosignature gas detectability to biomass estimates, including atmospheric photochemistry and biological thermodynamics. The new framework is intended to liberate predictive atmosphere models from requiring fixed, Earth-like biosignature gas source fluxes. New biosignature gases can be considered with a check that the biomass estimate is physically plausible. We have validated the models on terrestrial production of NO, H2S, CH4, CH3Cl, and DMS. We have applied the models to propose NH3 as a biosignature gas on a "cold Haber World," a planet with a N2-H2 atmosphere, and to demonstrate why gases such as CH3Cl must have too large of a biomass to be a plausible biosignature gas on planets with Earth or early-Earth-like atmospheres orbiting a Sun-like star. To construct the biomass models, we developed a functional classification of biosignature gases, and found that gases (such as CH4, H2S, and N2O) produced from life that extracts energy from chemical potential energy gradients will always have false positives because geochemistry has the same gases to work with as life does, and gases (such as DMS and CH3Cl) produced for secondary metabolic reasons are far less likely to have false positives but because of their highly specialized origin are more likely to be produced in small quantities. The biomass model estimates are valid to one or two orders of magnitude; the goal is an independent approach to testing whether a biosignature gas is plausible rather than a precise quantification of atmospheric biosignature gases and their corresponding biomasses.

Developmental vitamin D deficiency causes abnormal brain development.

PubMed

Eyles, D W; Feron, F; Cui, X; Kesby, J P; Harms, L H; Ko, P; McGrath, J J; Burne, T H J

2009-12-01

There is now clear evidence that vitamin D is involved in brain development. Our group is interested in environmental factors that shape brain development and how this may be relevant to neuropsychiatric diseases including schizophrenia. The origins of schizophrenia are considered developmental. We hypothesised that developmental vitamin D (DVD) deficiency may be the plausible neurobiological explanation for several important epidemiological correlates of schizophrenia namely: (1) the excess winter/spring birth rate, (2) increased incidence of the disease in 2nd generation Afro-Caribbean migrants and (3) increased urban birth rate. Moreover we have published two pieces of direct epidemiological support for this hypothesis in patients. In order to establish the "Biological Plausibility" of this hypothesis we have developed an animal model to study the effect of DVD deficiency on brain development. We do this by removing vitamin D from the diet of female rats prior to breeding. At birth we return all dams to a vitamin D containing diet. Using this procedure we impose a transient, gestational vitamin D deficiency, while maintaining normal calcium levels throughout. The brains of offspring from DVD-deficient dams are characterised by (1) a mild distortion in brain shape, (2) increased lateral ventricle volumes, (3) reduced differentiation and (4) diminished expression of neurotrophic factors. As adults, the alterations in ventricular volume persist and alterations in brain gene and protein expression emerge. Adult DVD-deficient rats also display behavioural sensitivity to agents that induce psychosis (the NMDA antagonist MK-801) and have impairments in attentional processing. In this review we summarise the literature addressing the function of vitamin D on neuronal and non-neuronal cells as well as in vivo results from DVD-deficient animals. Our conclusions from these data are that vitamin D is a plausible biological risk factor for neuropsychiatric disorders and that vitamin D acts as a neurosteroid with direct effects on brain development.

Improving the quality of child anthropometry: Manual anthropometry in the Body Imaging for Nutritional Assessment Study (BINA)

PubMed Central

2017-01-01

Anthropometric data collected in clinics and surveys are often inaccurate and unreliable due to measurement error. The Body Imaging for Nutritional Assessment Study (BINA) evaluated the ability of 3D imaging to correctly measure stature, head circumference (HC) and arm circumference (MUAC) for children under five years of age. This paper describes the protocol for and the quality of manual anthropometric measurements in BINA, a study conducted in 2016–17 in Atlanta, USA. Quality was evaluated by examining digit preference, biological plausibility of z-scores, z-score standard deviations, and reliability. We calculated z-scores and analyzed plausibility based on the 2006 WHO Child Growth Standards (CGS). For reliability, we calculated intra- and inter-observer Technical Error of Measurement (TEM) and Intraclass Correlation Coefficient (ICC). We found low digit preference; 99.6% of z-scores were biologically plausible, with z-score standard deviations ranging from 0.92 to 1.07. Total TEM was 0.40 for stature, 0.28 for HC, and 0.25 for MUAC in centimeters. ICC ranged from 0.99 to 1.00. The quality of manual measurements in BINA was high and similar to that of the anthropometric data used to develop the WHO CGS. We attributed high quality to vigorous training, motivated and competent field staff, reduction of non-measurement error through the use of technology, and reduction of measurement error through adequate monitoring and supervision. Our anthropometry measurement protocol, which builds on and improves upon the protocol used for the WHO CGS, can be used to improve anthropometric data quality. The discussion illustrates the need to standardize anthropometric data quality assessment, and we conclude that BINA can provide a valuable evaluation of 3D imaging for child anthropometry because there is comparison to gold-standard, manual measurements. PMID:29240796

Synthetic constructs in/for the environment: Managing the interplay between natural and engineered Biology

PubMed Central

Schmidt, Markus; de Lorenzo, Víctor

2012-01-01

The plausible release of deeply engineered or even entirely synthetic/artificial microorganisms raises the issue of their intentional (e.g. bioremediation) or accidental interaction with the Environment. Containment systems designed in the 1980s–1990s for limiting the spread of genetically engineered bacteria and their recombinant traits are still applicable to contemporary Synthetic Biology constructs. Yet, the ease of DNA synthesis and the uncertainty on how non-natural properties and strains could interplay with the existing biological word poses yet again the challenge of designing safe and efficacious firewalls to curtail possible interactions. Such barriers may include xeno-nucleic acids (XNAs) instead of DNA as information-bearing molecules, rewriting the genetic code to make it non-understandable by the existing gene expression machineries, and/or making growth dependent on xenobiotic chemicals. PMID:22710182

E.s.r., magnetic, optical and biological (SOD and antimicrobial) studies of imidazolate bridged Cu II-Zn II and Cu II-Ni II complexes with tris(2-amino ethyl)amine as capping ligand: a plausible model for superoxide dismutase

NASA Astrophysics Data System (ADS)

Singh, Nripendra; Shukla, K. K.; Patel, R. N.; Chauhan, U. K.; Shrivastava, R.

2003-11-01

X-band e.s.r. and optical absorption spectra of the imidazolate bridged heterobimetallic complexes [(tren)Cu-E-Im-Zn-(tren)](ClO 4) 3 and [(tren)Cu-E-Im-Ni-(tren)](ClO 4) 3, where trentris(2-aminoethyl)amine, E-Im=2-ethylimidazolate ion and the related mononuclear complexes [Cu(tren)](ClO 4) 2 and [(tren)Cu-E-ImH)](ClO 4) 2 have been described. Biological activities (superoxide dismutase and antimicrobial) have also been measured and compared with reported complexes.

Application of the Hard and Soft, Acids and Bases (HSAB) theory to toxicant--target interactions.

PubMed

Lopachin, Richard M; Gavin, Terrence; Decaprio, Anthony; Barber, David S

2012-02-20

Many chemical toxicants and/or their active metabolites are electrophiles that cause cell injury by forming covalent bonds with nucleophilic targets on biological macromolecules. Covalent reactions between nucleophilic and electrophilic reagents are, however, discriminatory since there is a significant degree of selectivity associated with these interactions. Over the course of the past few decades, the theory of Hard and Soft, Acids and Bases (HSAB) has proven to be a useful tool in predicting the outcome of such reactions. This concept utilizes the inherent electronic characteristic of polarizability to define, for example, reacting electrophiles and nucleophiles as either hard or soft. These HSAB definitions have been successfully applied to chemical-induced toxicity in biological systems. Thus, according to this principle, a toxic electrophile reacts preferentially with biological targets of similar hardness or softness. The soft/hard classification of a xenobiotic electrophile has obvious utility in discerning plausible biological targets and molecular mechanisms of toxicity. The purpose of this perspective is to discuss the HSAB theory of electrophiles and nucleophiles within a toxicological framework. In principle, covalent bond formation can be described by using the properties of their outermost or frontier orbitals. Because these orbital energies for most chemicals can be calculated using quantum mechanical models, it is possible to quantify the relative softness (σ) or hardness (η) of electrophiles or nucleophiles and to subsequently convert this information into useful indices of reactivity. This atomic level information can provide insight into the design of corroborative laboratory research and thereby help investigators discern corresponding molecular sites and mechanisms of toxicant action. The use of HSAB parameters has also been instrumental in the development and identification of potential nucleophilic cytoprotectants that can scavenge toxic electrophiles. Clearly, the difficult task of delineating molecular sites and mechanisms of toxicant action can be facilitated by the application of this quantitative approach.

APPLICATION OF THE HARD AND SOFT, ACIDS AND BASES (HSAB) THEORY TO TOXICANT-TARGET INTERACTIONS

PubMed Central

LoPachin, Richard M.; Gavin, Terrence; DeCaprio, Anthony; Barber, David S.

2011-01-01

Many chemical toxicants and/or their active metabolites are electrophiles that cause cell injury by forming covalent bonds with nucleophilic targets on biological macromolecules. Covalent reactions between nucleophilic and electrophilic reagents are however discriminatory, since there is a significant degree of selectivity associated with these interactions. Over the course of the past few decades, the theory of Hard and Soft, Acid and Bases (HSAB) has proven to be a useful tool in predicting the outcome of such reactions. This concept utilizes the inherent electronic characteristic of polarizability to define, for example, reacting electrophiles and nucleophiles as either hard or soft. These HSAB definitions have been successfully applied to chemical-induced toxicity in biological systems. Thus, according to this principle, a toxic electrophile reacts preferentially with biological targets of similar hardness or softness. The soft/hard classification of a xenobiotic electrophile has obvious utility in discerning plausible biological targets and molecular mechanisms of toxicity. The purpose of this Perspective is to discuss the HSAB theory of electrophiles and nucleophiles within a toxicological framework. In principle, covalent bond formation can be described by using the properties of their outermost or frontier orbitals. Because these orbital energies for most chemicals can be calculated using quantum mechanical models, it is possible to quantify the relative softness (σ) or hardness (η) of electrophiles or nucleophiles and to subsequently convert this information into useful indices of reactivity. This atomic level information can provide insight into the design of corroborative laboratory research and thereby help investigators discern corresponding molecular sites and mechanisms of toxicant action. The use of HSAB parameters has also been instrumental in the development and identification of potential nucleophilic cytoprotectants that can scavenge toxic electrophiles. Clearly, the difficult task of delineating molecular sites and mechanisms of toxicant action can be facilitated by the application of this quantitative approach. PMID:22053936

Parametric soil water retention models: a critical evaluation of expressions for the full moisture range

NASA Astrophysics Data System (ADS)

Madi, Raneem; Huibert de Rooij, Gerrit; Mielenz, Henrike; Mai, Juliane

2018-02-01

Few parametric expressions for the soil water retention curve are suitable for dry conditions. Furthermore, expressions for the soil hydraulic conductivity curves associated with parametric retention functions can behave unrealistically near saturation. We developed a general criterion for water retention parameterizations that ensures physically plausible conductivity curves. Only 3 of the 18 tested parameterizations met this criterion without restrictions on the parameters of a popular conductivity curve parameterization. A fourth required one parameter to be fixed. We estimated parameters by shuffled complex evolution (SCE) with the objective function tailored to various observation methods used to obtain retention curve data. We fitted the four parameterizations with physically plausible conductivities as well as the most widely used parameterization. The performance of the resulting 12 combinations of retention and conductivity curves was assessed in a numerical study with 751 days of semiarid atmospheric forcing applied to unvegetated, uniform, 1 m freely draining columns for four textures. Choosing different parameterizations had a minor effect on evaporation, but cumulative bottom fluxes varied by up to an order of magnitude between them. This highlights the need for a careful selection of the soil hydraulic parameterization that ideally does not only rely on goodness of fit to static soil water retention data but also on hydraulic conductivity measurements. Parameter fits for 21 soils showed that extrapolations into the dry range of the retention curve often became physically more realistic when the parameterization had a logarithmic dry branch, particularly in fine-textured soils where high residual water contents would otherwise be fitted.

Identifying data gaps and prioritizing restoration strategies for Fremont cottonwood using linked geomorphic and population models

NASA Astrophysics Data System (ADS)

Harper, E. B.; Stella, J. C.; Fremier, A. K.

2009-12-01

Fremont cottonwood (Populus fremontii) is an important component of semi-arid riparian ecosystems throughout western North America, but its populations are in decline due to flow regulation. Achieving a balance between human resource needs and riparian ecosystem function requires a mechanistic understanding of the multiple geomorphic and biological factors affecting tree recruitment and survival, including the timing and magnitude of river flows, and the concomitant influence on suitable habitat creation and mortality from scour and sedimentation burial. Despite a great deal of empirical research on some components of the system, such as factors affecting cottonwood recruitment, other key components are less studied. Yet understanding the relative influence of the full suite of physical and life-history drivers is critical to modeling whole-population dynamics under changing environmental conditions. We addressed these issues for the Fremont cottonwood population along the Sacramento River, CA using a sensitivity analysis approach to quantify uncertainty in parameters on the outcomes of a patch-based, dynamic population model. Using a broad range of plausible values for 15 model parameters that represent key physical, biological and climatic components of the ecosystem, we ran 1,000 population simulations that consisted of a subset of 14.3 million possible combinations of parameter estimates to predict the frequency of patch colonization and total forest habitat predicted to occur under current hydrologic conditions after 175 years. Results indicate that Fremont cottonwood populations are highly sensitive to the interactions among flow regime, sedimentation rate and the depth of the capillary fringe (Fig. 1). Estimates of long-term floodplain sedimentation rate would substantially improve model accuracy. Spatial variation in sediment texture was also important to the extent that it determines the depth of the capillary fringe, which regulates the availability of water for germination and adult tree growth. Our sensitivity analyses suggest that models of future scenarios should incorporate regional climate change projections because changes in temperature and the timing and volume of precipitation affects sensitive aspects of the system, including the timing of seed release and spring snowmelt runoff. Figure 1. The relative effects on model predictions of uncertainty around each parameter included in the patch-based population model for Fremont cottonwood.

Synthetic biology and its alternatives. Descartes, Kant and the idea of engineering biological machines.

PubMed

Kogge, Werner; Richter, Michael

2013-06-01

The engineering-based approach of synthetic biology is characterized by an assumption that 'engineering by design' enables the construction of 'living machines'. These 'machines', as biological machines, are expected to display certain properties of life, such as adapting to changing environments and acting in a situated way. This paper proposes that a tension exists between the expectations placed on biological artefacts and the notion of producing such systems by means of engineering; this tension makes it seem implausible that biological systems, especially those with properties characteristic of living beings, can in fact be produced using the specific methods of engineering. We do not claim that engineering techniques have nothing to contribute to the biotechnological construction of biological artefacts. However, drawing on Descartes's and Kant's thinking on the relationship between the organism and the machine, we show that it is considerably more plausible to assume that distinctively biological artefacts emerge within a paradigm different from the paradigm of the Cartesian machine that underlies the engineering approach. We close by calling for increased attention to be paid to approaches within molecular biology and chemistry that rest on conceptions different from those of synthetic biology's engineering paradigm. Copyright © 2013 Elsevier Ltd. All rights reserved.

A computational model of visual marking using an inter-connected network of spiking neurons: the spiking search over time & space model (sSoTS).

PubMed

Mavritsaki, Eirini; Heinke, Dietmar; Humphreys, Glyn W; Deco, Gustavo

2006-01-01

In the real world, visual information is selected over time as well as space, when we prioritise new stimuli for attention. Watson and Humphreys [Watson, D., Humphreys, G.W., 1997. Visual marking: prioritizing selection for new objects by top-down attentional inhibition of old objects. Psychological Review 104, 90-122] presented evidence that new information in search tasks is prioritised by (amongst other processes) active ignoring of old items - a process they termed visual marking. In this paper we present, for the first time, an explicit computational model of visual marking using biologically plausible activation functions. The "spiking search over time and space" model (sSoTS) incorporates different synaptic components (NMDA, AMPA, GABA) and a frequency adaptation mechanism based on [Ca(2+)] sensitive K(+) current. This frequency adaptation current can act as a mechanism that suppresses the previously attended items. We show that, when coupled with a process of active inhibition applied to old items, frequency adaptation leads to old items being de-prioritised (and new items prioritised) across time in search. Furthermore, the time course of these processes mimics the time course of the preview effect in human search. The results indicate that the sSoTS model can provide a biologically plausible account of human search over time as well as space.

Why cachexia kills: examining the causality of poor outcomes in wasting conditions.

PubMed

Kalantar-Zadeh, Kamyar; Rhee, Connie; Sim, John J; Stenvinkel, Peter; Anker, Stefan D; Kovesdy, Csaba P

2013-06-01

Weight loss is the hallmark of any progressive acute or chronic disease state. In its extreme form of significant lean body mass (including skeletal muscle) and fat loss, it is referred to as cachexia. It has been known for millennia that muscle and fat wasting leads to poor outcomes including death. On one hand, conditions and risk factors that lead to cachexia and inadequate nutrition may independently lead to increased mortality. Additionaly, cachexia per se, withdrawal of nutritional support in progressive cachexia, and advanced age may lead to death via cachexia-specific pathways. Despite the strong and consistent association of cachexia with mortality, no unifying mechanism has yet been suggested as to why wasting conditions are associated with an exceptionally high mortality risk. Hence, the causality of the cachexia-death association, even though it is biologically plausible, is widely unknown. This century-long uncertainty may have played a role as to why the field of cachexia treatment development has not shown major advances over the past decades. We suggest that cachexia-associated relative thrombocytosis and platelet activation may play a causal role in cachexia-related death, while other mechanisms may also contribute including arrhythmia-associated sudden deaths, endocrine disorders such as hypothyroidism, and immune system compromise leading to infectious events and deaths. Multidimensional research including examining biologically plausible models is urgently needed to investigate the causality of the cachexia-death association.

View-Tolerant Face Recognition and Hebbian Learning Imply Mirror-Symmetric Neural Tuning to Head Orientation.

PubMed

Leibo, Joel Z; Liao, Qianli; Anselmi, Fabio; Freiwald, Winrich A; Poggio, Tomaso

2017-01-09

The primate brain contains a hierarchy of visual areas, dubbed the ventral stream, which rapidly computes object representations that are both specific for object identity and robust against identity-preserving transformations, like depth rotations [1, 2]. Current computational models of object recognition, including recent deep-learning networks, generate these properties through a hierarchy of alternating selectivity-increasing filtering and tolerance-increasing pooling operations, similar to simple-complex cells operations [3-6]. Here, we prove that a class of hierarchical architectures and a broad set of biologically plausible learning rules generate approximate invariance to identity-preserving transformations at the top level of the processing hierarchy. However, all past models tested failed to reproduce the most salient property of an intermediate representation of a three-level face-processing hierarchy in the brain: mirror-symmetric tuning to head orientation [7]. Here, we demonstrate that one specific biologically plausible Hebb-type learning rule generates mirror-symmetric tuning to bilaterally symmetric stimuli, like faces, at intermediate levels of the architecture and show why it does so. Thus, the tuning properties of individual cells inside the visual stream appear to result from group properties of the stimuli they encode and to reflect the learning rules that sculpted the information-processing system within which they reside. Copyright © 2017 Elsevier Ltd. All rights reserved.

Object recognition with hierarchical discriminant saliency networks.

PubMed

Han, Sunhyoung; Vasconcelos, Nuno

2014-01-01

The benefits of integrating attention and object recognition are investigated. While attention is frequently modeled as a pre-processor for recognition, we investigate the hypothesis that attention is an intrinsic component of recognition and vice-versa. This hypothesis is tested with a recognition model, the hierarchical discriminant saliency network (HDSN), whose layers are top-down saliency detectors, tuned for a visual class according to the principles of discriminant saliency. As a model of neural computation, the HDSN has two possible implementations. In a biologically plausible implementation, all layers comply with the standard neurophysiological model of visual cortex, with sub-layers of simple and complex units that implement a combination of filtering, divisive normalization, pooling, and non-linearities. In a convolutional neural network implementation, all layers are convolutional and implement a combination of filtering, rectification, and pooling. The rectification is performed with a parametric extension of the now popular rectified linear units (ReLUs), whose parameters can be tuned for the detection of target object classes. This enables a number of functional enhancements over neural network models that lack a connection to saliency, including optimal feature denoising mechanisms for recognition, modulation of saliency responses by the discriminant power of the underlying features, and the ability to detect both feature presence and absence. In either implementation, each layer has a precise statistical interpretation, and all parameters are tuned by statistical learning. Each saliency detection layer learns more discriminant saliency templates than its predecessors and higher layers have larger pooling fields. This enables the HDSN to simultaneously achieve high selectivity to target object classes and invariance. The performance of the network in saliency and object recognition tasks is compared to those of models from the biological and computer vision literatures. This demonstrates benefits for all the functional enhancements of the HDSN, the class tuning inherent to discriminant saliency, and saliency layers based on templates of increasing target selectivity and invariance. Altogether, these experiments suggest that there are non-trivial benefits in integrating attention and recognition.

An in silico agent-based model demonstrates Reelin function in directing lamination of neurons during cortical development.

PubMed

Caffrey, James R; Hughes, Barry D; Britto, Joanne M; Landman, Kerry A

2014-01-01

The characteristic six-layered appearance of the neocortex arises from the correct positioning of pyramidal neurons during development and alterations in this process can cause intellectual disabilities and developmental delay. Malformations in cortical development arise when neurons either fail to migrate properly from the germinal zones or fail to cease migration in the correct laminar position within the cortical plate. The Reelin signalling pathway is vital for correct neuronal positioning as loss of Reelin leads to a partially inverted cortex. The precise biological function of Reelin remains controversial and debate surrounds its role as a chemoattractant or stop signal for migrating neurons. To investigate this further we developed an in silico agent-based model of cortical layer formation. Using this model we tested four biologically plausible hypotheses for neuron motility and four biologically plausible hypotheses for the loss of neuron motility (conversion from migration). A matrix of 16 combinations of motility and conversion rules was applied against the known structure of mouse cortical layers in the wild-type cortex, the Reelin-null mutant, the Dab1-null mutant and a conditional Dab1 mutant. Using this approach, many combinations of motility and conversion mechanisms can be rejected. For example, the model does not support Reelin acting as a repelling or as a stopping signal. In contrast, the study lends very strong support to the notion that the glycoprotein Reelin acts as a chemoattractant for neurons. Furthermore, the most viable proposition for the conversion mechanism is one in which conversion is affected by a motile neuron sensing in the near vicinity neurons that have already converted. Therefore, this model helps elucidate the function of Reelin during neuronal migration and cortical development.

Applying generalized linear models as an explanatory tool of sex steroids, thyroid hormones and their relationships with environmental and physiologic factors in immature East Pacific green sea turtles (Chelonia mydas).

PubMed

Labrada-Martagón, Vanessa; Méndez-Rodríguez, Lia C; Mangel, Marc; Zenteno-Savín, Tania

2013-09-01

Generalized linear models were fitted to evaluate the relationship between 17β-estradiol (E2), testosterone (T) and thyroxine (T4) levels in immature East Pacific green sea turtles (Chelonia mydas) and their body condition, size, mass, blood biochemistry parameters, handling time, year, season and site of capture. According to external (tail size) and morphological (<77.3 straight carapace length) characteristics, 95% of the individuals were juveniles. Hormone levels, assessed on sea turtles subjected to a capture stress protocol, were <34.7nmolTL(-1), <532.3pmolE2 L(-1) and <43.8nmolT4L(-1). The statistical model explained biologically plausible metabolic relationships between hormone concentrations and blood biochemistry parameters (e.g. glucose, cholesterol) and the potential effect of environmental variables (season and study site). The variables handling time and year did not contribute significantly to explain hormone levels. Differences in sex steroids between season and study sites found by the models coincided with specific nutritional, physiological and body condition differences related to the specific habitat conditions. The models correctly predicted the median levels of the measured hormones in green sea turtles, which confirms the fitted model's utility. It is suggested that quantitative predictions could be possible when the model is tested with additional data. Copyright © 2013 Elsevier Inc. All rights reserved.

Learning Multisensory Integration and Coordinate Transformation via Density Estimation

PubMed Central

Sabes, Philip N.

2013-01-01

Sensory processing in the brain includes three key operations: multisensory integration—the task of combining cues into a single estimate of a common underlying stimulus; coordinate transformations—the change of reference frame for a stimulus (e.g., retinotopic to body-centered) effected through knowledge about an intervening variable (e.g., gaze position); and the incorporation of prior information. Statistically optimal sensory processing requires that each of these operations maintains the correct posterior distribution over the stimulus. Elements of this optimality have been demonstrated in many behavioral contexts in humans and other animals, suggesting that the neural computations are indeed optimal. That the relationships between sensory modalities are complex and plastic further suggests that these computations are learned—but how? We provide a principled answer, by treating the acquisition of these mappings as a case of density estimation, a well-studied problem in machine learning and statistics, in which the distribution of observed data is modeled in terms of a set of fixed parameters and a set of latent variables. In our case, the observed data are unisensory-population activities, the fixed parameters are synaptic connections, and the latent variables are multisensory-population activities. In particular, we train a restricted Boltzmann machine with the biologically plausible contrastive-divergence rule to learn a range of neural computations not previously demonstrated under a single approach: optimal integration; encoding of priors; hierarchical integration of cues; learning when not to integrate; and coordinate transformation. The model makes testable predictions about the nature of multisensory representations. PMID:23637588

On the use of log-transformation vs. nonlinear regression for analyzing biological power laws.

PubMed

Xiao, Xiao; White, Ethan P; Hooten, Mevin B; Durham, Susan L

2011-10-01

Power-law relationships are among the most well-studied functional relationships in biology. Recently the common practice of fitting power laws using linear regression (LR) on log-transformed data has been criticized, calling into question the conclusions of hundreds of studies. It has been suggested that nonlinear regression (NLR) is preferable, but no rigorous comparison of these two methods has been conducted. Using Monte Carlo simulations, we demonstrate that the error distribution determines which method performs better, with NLR better characterizing data with additive, homoscedastic, normal error and LR better characterizing data with multiplicative, heteroscedastic, lognormal error. Analysis of 471 biological power laws shows that both forms of error occur in nature. While previous analyses based on log-transformation appear to be generally valid, future analyses should choose methods based on a combination of biological plausibility and analysis of the error distribution. We provide detailed guidelines and associated computer code for doing so, including a model averaging approach for cases where the error structure is uncertain.

The United States and biological warfare: secrets from the early cold war and Korea.

PubMed

Bruwer, A

2001-01-01

The United States and Biological Warfare is about accusations that the United States resorted to bacteriological warfare at a time of great military stress during the Korean War. In December 1951, the then US Secretary of Defense ordered early readiness for offensive use of biological weapons. Soon afterwards, the North Korean and Chinese armies accused the United States of starting a large-scale biological warfare experiment in Korea. The US State Department denied the accusation. Both parties to the dispute maintain their positions today. The authors spent 20 years researching the accusations in North America, Europe and Japan. They were the first foreigners to be given access to Chinese classified documents. The reader is also introduced to the concept of 'plausible denial', an official US policy which allowed responsible governmental representatives to deny knowledge of certain events. The authors hope that their work will contribute to the understanding of a time when modern war expanded into a new type of violence.

The millimeter wave spectrum of silver monoxide, AgO

NASA Astrophysics Data System (ADS)

Steimle, T.; Tanimoto, M.; Namiki, K.; Saito, S.

1998-05-01

The pure rotational spectra of 107AgO and 109AgO were recorded in the 117-380 GHz spectral region using a dc-sputtering absorption cell. The 107Ag(I=1/2) and 109Ag(I=1/2) magnetic hyperfine parameters are interpreted in terms of plausible electronic configuration contributions to the X 2Πi state. It is shown that the determined unusual sign of the Λ-doubling and Fermi contact parameters implies that the X 2Πi state is dominated by a three open shell configuration. A comparison with isovalent CuO is made.

Nonlinear Bayesian filtering and learning: a neuronal dynamics for perception.

PubMed

Kutschireiter, Anna; Surace, Simone Carlo; Sprekeler, Henning; Pfister, Jean-Pascal

2017-08-18

The robust estimation of dynamical hidden features, such as the position of prey, based on sensory inputs is one of the hallmarks of perception. This dynamical estimation can be rigorously formulated by nonlinear Bayesian filtering theory. Recent experimental and behavioral studies have shown that animals' performance in many tasks is consistent with such a Bayesian statistical interpretation. However, it is presently unclear how a nonlinear Bayesian filter can be efficiently implemented in a network of neurons that satisfies some minimum constraints of biological plausibility. Here, we propose the Neural Particle Filter (NPF), a sampling-based nonlinear Bayesian filter, which does not rely on importance weights. We show that this filter can be interpreted as the neuronal dynamics of a recurrently connected rate-based neural network receiving feed-forward input from sensory neurons. Further, it captures properties of temporal and multi-sensory integration that are crucial for perception, and it allows for online parameter learning with a maximum likelihood approach. The NPF holds the promise to avoid the 'curse of dimensionality', and we demonstrate numerically its capability to outperform weighted particle filters in higher dimensions and when the number of particles is limited.

Balancing Selection in Species with Separate Sexes: Insights from Fisher’s Geometric Model

PubMed Central

Connallon, Tim; Clark, Andrew G.

2014-01-01

How common is balancing selection, and what fraction of phenotypic variance is attributable to balanced polymorphisms? Despite decades of research, answers to these questions remain elusive. Moreover, there is no clear theoretical prediction about the frequency with which balancing selection is expected to arise within a population. Here, we use an extension of Fisher’s geometric model of adaptation to predict the probability of balancing selection in a population with separate sexes, wherein polymorphism is potentially maintained by two forms of balancing selection: (1) heterozygote advantage, where heterozygous individuals at a locus have higher fitness than homozygous individuals, and (2) sexually antagonistic selection (a.k.a. intralocus sexual conflict), where the fitness of each sex is maximized by different genotypes at a locus. We show that balancing selection is common under biologically plausible conditions and that sex differences in selection or sex-by-genotype effects of mutations can each increase opportunities for balancing selection. Although heterozygote advantage and sexual antagonism represent alternative mechanisms for maintaining polymorphism, they mutually exist along a balancing selection continuum that depends on population and sex-specific parameters of selection and mutation. Sexual antagonism is the dominant mode of balancing selection across most of this continuum. PMID:24812306

Construction of Gene Regulatory Networks Using Recurrent Neural Networks and Swarm Intelligence.

PubMed

Khan, Abhinandan; Mandal, Sudip; Pal, Rajat Kumar; Saha, Goutam

2016-01-01

We have proposed a methodology for the reverse engineering of biologically plausible gene regulatory networks from temporal genetic expression data. We have used established information and the fundamental mathematical theory for this purpose. We have employed the Recurrent Neural Network formalism to extract the underlying dynamics present in the time series expression data accurately. We have introduced a new hybrid swarm intelligence framework for the accurate training of the model parameters. The proposed methodology has been first applied to a small artificial network, and the results obtained suggest that it can produce the best results available in the contemporary literature, to the best of our knowledge. Subsequently, we have implemented our proposed framework on experimental (in vivo) datasets. Finally, we have investigated two medium sized genetic networks (in silico) extracted from GeneNetWeaver, to understand how the proposed algorithm scales up with network size. Additionally, we have implemented our proposed algorithm with half the number of time points. The results indicate that a reduction of 50% in the number of time points does not have an effect on the accuracy of the proposed methodology significantly, with a maximum of just over 15% deterioration in the worst case.

Toward understanding the mechanics of hovering in insects, hummingbirds and bats

NASA Astrophysics Data System (ADS)

Vejdani, Hamid; Boerma, David; Swartz, Sharon; Breuer, Kenneth

2016-11-01

We present results on the dynamical characteristics of two different mechanisms of hovering, corresponding to the behavior of hummingbirds and bats. Using a Lagrangian formulation, we have developed a dynamical model of a body (trunk) and two rectangular wings. The trunk has 3 degrees of freedom (x, z and pitch angle) and each wing has 3 modes of actuation: flapping, pronation/supination, and wingspan extension/flexion (only present for bats). Wings can be effectively massless (hummingbird and insect wings) or relatively massive (important in the case of bats). The aerodynamic drag and lift forces are calculated using a quasi-steady blade-element model. The regions of state space in which hovering is possible are computed by over an exhaustive range of parameters. The effect of wing mass is to shrink the phase space available for viable hovering and, in general, to require higher wingbeat frequency. Moreover, by exploring hovering energy requirements, we find that the pronation angle of the wings also plays a critical role. For bats, who have relatively heavy wings, we show wing extension and flexion is critical in order to maintain a plausible hovering posture with reasonable power requirements. Comparisons with biological data show good agreement with our model predictions.

In vitro kinetics of soybean lipoxygenase with combinatorial fatty substrates and its functional significance in off flavour development.

PubMed

Mandal, Somnath; Dahuja, Anil; Kar, Abhijit; Santha, I M

2014-03-01

Lipoxygenase (Lox) mediated oxidation of polyunsaturated fatty acids (PUFA) in mature soya seeds results in objectionable flavour. In the present study, Lox isozymes were purified to near homogeneity (107-fold). Lox-2 and 3 displayed remarkable kinetic preference (1.7 and 1.5-fold, respectively) for low PUFA ratios (LA/LeA) (PRs) among the selected PUFA combinations. Lox-1 displayed no specific preference. Pure Lox-1 displayed unbiased response towards substrates with marginal preference (1.2-fold) for linoleic acid at its optimum pH. Volatile compounds profiling showed a direct relationship between PRs and hexanal to trans-2-hexenal (1.47, 2.24 and 18.90 for 2, 7 and 15 PRs, respectively) ratio. The off-flavour determining parameters like TBA value, carbonyl value and lipid hydroperoxides (LHPODs) exhibited significant negative correlation (0.76, 0.74, 0.72; p<0.0001) in selected soya genotypes displaying varied PRs and significant positive correlation (0.89, 0.81. 0.89; p<0.0001) with ratio of PI (polyene index) to PRs - suggesting the plausible significance of PUFA ratios in biological lipid peroxidation. Copyright © 2013 Elsevier Ltd. All rights reserved.

A Cross-Correlated Delay Shift Supervised Learning Method for Spiking Neurons with Application to Interictal Spike Detection in Epilepsy.

PubMed

Guo, Lilin; Wang, Zhenzhong; Cabrerizo, Mercedes; Adjouadi, Malek

2017-05-01

This study introduces a novel learning algorithm for spiking neurons, called CCDS, which is able to learn and reproduce arbitrary spike patterns in a supervised fashion allowing the processing of spatiotemporal information encoded in the precise timing of spikes. Unlike the Remote Supervised Method (ReSuMe), synapse delays and axonal delays in CCDS are variants which are modulated together with weights during learning. The CCDS rule is both biologically plausible and computationally efficient. The properties of this learning rule are investigated extensively through experimental evaluations in terms of reliability, adaptive learning performance, generality to different neuron models, learning in the presence of noise, effects of its learning parameters and classification performance. Results presented show that the CCDS learning method achieves learning accuracy and learning speed comparable with ReSuMe, but improves classification accuracy when compared to both the Spike Pattern Association Neuron (SPAN) learning rule and the Tempotron learning rule. The merit of CCDS rule is further validated on a practical example involving the automated detection of interictal spikes in EEG records of patients with epilepsy. Results again show that with proper encoding, the CCDS rule achieves good recognition performance.

Chemotherapy-induced pulmonary hypertension: role of alkylating agents.

PubMed

Ranchoux, Benoît; Günther, Sven; Quarck, Rozenn; Chaumais, Marie-Camille; Dorfmüller, Peter; Antigny, Fabrice; Dumas, Sébastien J; Raymond, Nicolas; Lau, Edmund; Savale, Laurent; Jaïs, Xavier; Sitbon, Olivier; Simonneau, Gérald; Stenmark, Kurt; Cohen-Kaminsky, Sylvia; Humbert, Marc; Montani, David; Perros, Frédéric

2015-02-01

Pulmonary veno-occlusive disease (PVOD) is an uncommon form of pulmonary hypertension (PH) characterized by progressive obstruction of small pulmonary veins and a dismal prognosis. Limited case series have reported a possible association between different chemotherapeutic agents and PVOD. We evaluated the relationship between chemotherapeutic agents and PVOD. Cases of chemotherapy-induced PVOD from the French PH network and literature were reviewed. Consequences of chemotherapy exposure on the pulmonary vasculature and hemodynamics were investigated in three different animal models (mouse, rat, and rabbit). Thirty-seven cases of chemotherapy-associated PVOD were identified in the French PH network and systematic literature analysis. Exposure to alkylating agents was observed in 83.8% of cases, mostly represented by cyclophosphamide (43.2%). In three different animal models, cyclophosphamide was able to induce PH on the basis of hemodynamic, morphological, and biological parameters. In these models, histopathological assessment confirmed significant pulmonary venous involvement highly suggestive of PVOD. Together, clinical data and animal models demonstrated a plausible cause-effect relationship between alkylating agents and PVOD. Clinicians should be aware of this uncommon, but severe, pulmonary vascular complication of alkylating agents. Copyright © 2015 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

Neural signatures of economic parameters during decision-making: a functional MRI (FMRI), electroencephalography (EEG) and autonomic monitoring study.

PubMed

Minati, Ludovico; Grisoli, Marina; Franceschetti, Silvana; Epifani, Francesca; Granvillano, Alice; Medford, Nick; Harrison, Neil A; Piacentini, Sylvie; Critchley, Hugo D

2012-01-01

Adaptive behaviour requires an ability to obtain rewards by choosing between different risky options. Financial gambles can be used to study effective decision-making experimentally, and to distinguish processes involved in choice option evaluation from outcome feedback and other contextual factors. Here, we used a paradigm where participants evaluated 'mixed' gambles, each presenting a potential gain and a potential loss and an associated variable outcome probability. We recorded neural responses using autonomic monitoring, electroencephalography (EEG) and functional neuroimaging (fMRI), and used a univariate, parametric design to test for correlations with the eleven economic parameters that varied across gambles, including expected value (EV) and amount magnitude. Consistent with behavioural economic theory, participants were risk-averse. Gamble evaluation generated detectable autonomic responses, but only weak correlations with outcome uncertainty were found, suggesting that peripheral autonomic feedback does not play a major role in this task. Long-latency stimulus-evoked EEG potentials were sensitive to expected gain and expected value, while alpha-band power reflected expected loss and amount magnitude, suggesting parallel representations of distinct economic qualities in cortical activation and central arousal. Neural correlates of expected value representation were localized using fMRI to ventromedial prefrontal cortex, while the processing of other economic parameters was associated with distinct patterns across lateral prefrontal, cingulate, insula and occipital cortices including default-mode network and early visual areas. These multimodal data provide complementary evidence for distributed substrates of choice evaluation across multiple, predominantly cortical, brain systems wherein distinct regions are preferentially attuned to specific economic features. Our findings extend biologically-plausible models of risky decision-making while providing potential biomarkers of economic representations that can be applied to the study of deficits in motivational behaviour in neurological and psychiatric patients.

Developmental engineering: a new paradigm for the design and manufacturing of cell-based products. Part II: from genes to networks: tissue engineering from the viewpoint of systems biology and network science.

PubMed

Lenas, Petros; Moos, Malcolm; Luyten, Frank P

2009-12-01

The field of tissue engineering is moving toward a new concept of "in vitro biomimetics of in vivo tissue development." In Part I of this series, we proposed a theoretical framework integrating the concepts of developmental biology with those of process design to provide the rules for the design of biomimetic processes. We named this methodology "developmental engineering" to emphasize that it is not the tissue but the process of in vitro tissue development that has to be engineered. To formulate the process design rules in a rigorous way that will allow a computational design, we should refer to mathematical methods to model the biological process taking place in vitro. Tissue functions cannot be attributed to individual molecules but rather to complex interactions between the numerous components of a cell and interactions between cells in a tissue that form a network. For tissue engineering to advance to the level of a technologically driven discipline amenable to well-established principles of process engineering, a scientifically rigorous formulation is needed of the general design rules so that the behavior of networks of genes, proteins, or cells that govern the unfolding of developmental processes could be related to the design parameters. Now that sufficient experimental data exist to construct plausible mathematical models of many biological control circuits, explicit hypotheses can be evaluated using computational approaches to facilitate process design. Recent progress in systems biology has shown that the empirical concepts of developmental biology that we used in Part I to extract the rules of biomimetic process design can be expressed in rigorous mathematical terms. This allows the accurate characterization of manufacturing processes in tissue engineering as well as the properties of the artificial tissues themselves. In addition, network science has recently shown that the behavior of biological networks strongly depends on their topology and has developed the necessary concepts and methods to describe it, allowing therefore a deeper understanding of the behavior of networks during biomimetic processes. These advances thus open the door to a transition for tissue engineering from a substantially empirical endeavor to a technology-based discipline comparable to other branches of engineering.

Macroecological analyses support an overkill scenario for late Pleistocene extinctions.

PubMed

Diniz-Filho, J A F

2004-08-01

The extinction of megafauna at the end of Pleistocene has been traditionally explained by environmental changes or overexploitation by human hunting (overkill). Despite difficulties in choosing between these alternative (and not mutually exclusive) scenarios, the plausibility of the overkill hypothesis can be established by ecological models of predator-prey interactions. In this paper, I have developed a macroecological model for the overkill hypothesis, in which prey population dynamic parameters, including abundance, geographic extent, and food supply for hunters, were derived from empirical allometric relationships with body mass. The last output correctly predicts the final destiny (survival or extinction) for 73% of the species considered, a value only slightly smaller than those obtained by more complex models based on detailed archaeological and ecological data for each species. This illustrates the high selectivity of Pleistocene extinction in relation to body mass and confers more plausibility on the overkill scenario.

[Medical and biological consequences of nuclear disasters].

PubMed

Stalpers, Lukas J A; van Dullemen, Simon; Franken, N A P Klaas

2012-01-01

Medical risks of radiation exaggerated; psychological risks underestimated. The discussion about atomic energy has become topical again following the nuclear accident in Fukushima. There is some argument about the gravity of medical and biological consequences of prolonged exposure to radiation. The risk of cancer following a low dose of radiation is usually estimated by linear extrapolation of the incidence of cancer among survivors of the atomic bombs dropped on Hiroshima and Nagasaki in 1945. The radiobiological linear-quadratic model (LQ-model) gives a more accurate description of observed data, is radiobiologically more plausible and is better supported by experimental and clinical data. On the basis of this model there is less risk of cancer being induced following radiation exposure. The gravest consequence of Chernobyl and Fukushima is not the medical and biological damage, but the psychological and economical impact on rescue workers and former inhabitants.

Getting Past the RNA World: The Initial Darwinian Ancestor

PubMed Central

Yarus, Michael

2011-01-01

SUMMARY A little-noted result of the confirmation of multiple premises of the RNA-world hypothesis is that we now know something about the dawn organisms that followed the origin of life, perhaps over 4 billion years ago. We are therefore in an improved position to reason about the biota just before RNA times, during the era of the first replicators, the first Darwinian creatures on Earth. An RNA congener still prominent in modern biology is a plausible descendent of these first replicators. PMID:20719875

The Role of an Organized Exercise and Diet Program in the Primary Prevention of Ischemic Coronary Artery Disease in the U.S. Air Force Aviators

DTIC Science & Technology

1997-05-01

33.3% in 1988 and 25.4% in 1980."° This upward trend in obesity has been attributed to Americans leading a more sedentary lifestyle (i.e. lack of...has revealed several articles which link hypercholesterolemia and sedentary lifestyle epidemiologically to ischemic coronary artery disease.’ 49...and eventually can obstruct coronary arteries. Biological plausibility is therefore demonstrated by a high TC/HDL ratio and sedentary lifestyle hastening

Computational modeling of peripheral pain: a commentary.

PubMed

Argüello, Erick J; Silva, Ricardo J; Huerta, Mónica K; Avila, René S

2015-06-11

This commentary is intended to find possible explanations for the low impact of computational modeling on pain research. We discuss the main strategies that have been used in building computational models for the study of pain. The analysis suggests that traditional models lack biological plausibility at some levels, they do not provide clinically relevant results, and they cannot capture the stochastic character of neural dynamics. On this basis, we provide some suggestions that may be useful in building computational models of pain with a wider range of applications.

Molecular bases for unity and diversity in organic evolution

NASA Technical Reports Server (NTRS)

Fox, S. W.; Ruecknagel, P.; Braunitzer, G.

1991-01-01

The origin of biological information has been ascribed at various times to DNA, RNA, or protein. The origin of nucleic acids without the action of prior informed protein has not been supported by plausible experiments, although such possibilities have been examined. The behavior of thermal proteins and of the microspheres selfassembled therefrom explain the origin of the first cells, the first membrane, the first reproduction cycle, ancient metabolism including ATP-aided synthesis of peptides and polynucleotides, growth, bioelectricity, and polybiofunctionality in general.

The Universal Plausibility Metric (UPM) & Principle (UPP).

PubMed

Abel, David L

2009-12-03

Mere possibility is not an adequate basis for asserting scientific plausibility. A precisely defined universal bound is needed beyond which the assertion of plausibility, particularly in life-origin models, can be considered operationally falsified. But can something so seemingly relative and subjective as plausibility ever be quantified? Amazingly, the answer is, "Yes." A method of objectively measuring the plausibility of any chance hypothesis (The Universal Plausibility Metric [UPM]) is presented. A numerical inequality is also provided whereby any chance hypothesis can be definitively falsified when its UPM metric of xi is < 1 (The Universal Plausibility Principle [UPP]). Both UPM and UPP pre-exist and are independent of any experimental design and data set. No low-probability hypothetical plausibility assertion should survive peer-review without subjection to the UPP inequality standard of formal falsification (xi < 1).

Testosterone and Androgen Receptor Sensitivity in Relation to Hyperactivity Symptoms in Boys with Autism Spectrum Disorders

PubMed Central

2016-01-01

Introduction Autism spectrum disorders (ASD) and hyperactivity symptoms exhibit an incidence that is male-biased. Thus androgen activity can be considered a plausible biological risk factor for these disorders. However, there is insufficient information about the association between increased androgen activity and hyperactivity symptoms in children with ASD. Methods In the present study, the relationship between parameters of androgenicity (plasmatic testosterone levels and androgen receptor sensitivity) and hyperactivity in 60 boys (age 3–15) with ASD is investigated. Given well documented differences in parent and trained examiners ratings of symptom severity, we employed a standardized parent`s questionnaire (Nisonger Child Behavior Rating Form) as well as a direct examiner`s rating (Autism diagnostic observation schedule) for assessment of hyperactivity symptoms. Results Although it was found there was no significant association between actual plasmatic testosterone levels and hyperactivity symptoms, the number of CAG triplets was significantly negatively correlated with hyperactivity symptoms (R2 = 0.118, p = 0.007) in the sample, indicating increased androgen receptor sensitivity in association with hyperactivity symptoms. Direct trained examiner´s assessment appeared to be a relevant method for evaluating of behavioral problems in the investigation of biological underpinnings of these problems in our study. Conclusions A potential ASD subtype characterized by increased rates of hyperactivity symptoms might have distinct etiopathogenesis and require a specific behavioral and pharmacological approach. We propose an increase of androgen receptor sensitivity as a biomarker for a specific ASD subtype accompanied with hyperactivity symptoms. Findings are discussed in terms of their implications for practice and future research. PMID:26910733

Retinoic Acid and Affective Disorders: The Evidence for an Association

PubMed Central

Bremner, J Douglas; Shearer, Kirsty; McCaffery, Peter

2011-01-01

Objective Isotretinoin (13-cis-retinoic acid, or 13-cis-RA) (Accutane), approved by the FDA for the treatment of acne, carries a black box warning related to the risk of depression, suicide, and psychosis. Retinoic acid (RA), the active form of vitamin A, regulates gene expression in the brain, and isotretinoin is its 13-cis isomer. Retinoids represent a group of compounds derived from vitamin A that perform a large variety of functions in many systems, in particular the CNS, and abnormal retinoid levels can have neurological effects. Although infrequent, proper recognition and treatment of psychiatric side effects in acne patients is critical given the risk of death and disability. This paper reviews the evidence for a relationship between isotretinoin, depression and suicidality. Data Sources Evidence examined includes: 1) case reports; 2) temporal association between onset of depression and exposure to the drug; 3) challenge-rechallenge cases; 4) class effect (other compounds in the same class, like vitamin A, having similar neuropsychiatric effects); 5) dose response; and 6) biologically plausible mechanisms. Study Selection All papers in the literature related to isotretinoin, depression and suicide were reviewed, as well as papers related to class effect, dose response, and biological plausibility. Data Extraction Information from individual articles in the literature was extracted. Data Synthesis The literature reviewed is consistent with an association between isotretinoin administration, depression and suicide in some individuals. Conclusions The relationship between isotretinoin and depression may have implications for a greater understanding of the neurobiology of affective disorders. PMID:21903028

Unsupervised Learning in an Ensemble of Spiking Neural Networks Mediated by ITDP.

PubMed

Shim, Yoonsik; Philippides, Andrew; Staras, Kevin; Husbands, Phil

2016-10-01

We propose a biologically plausible architecture for unsupervised ensemble learning in a population of spiking neural network classifiers. A mixture of experts type organisation is shown to be effective, with the individual classifier outputs combined via a gating network whose operation is driven by input timing dependent plasticity (ITDP). The ITDP gating mechanism is based on recent experimental findings. An abstract, analytically tractable model of the ITDP driven ensemble architecture is derived from a logical model based on the probabilities of neural firing events. A detailed analysis of this model provides insights that allow it to be extended into a full, biologically plausible, computational implementation of the architecture which is demonstrated on a visual classification task. The extended model makes use of a style of spiking network, first introduced as a model of cortical microcircuits, that is capable of Bayesian inference, effectively performing expectation maximization. The unsupervised ensemble learning mechanism, based around such spiking expectation maximization (SEM) networks whose combined outputs are mediated by ITDP, is shown to perform the visual classification task well and to generalize to unseen data. The combined ensemble performance is significantly better than that of the individual classifiers, validating the ensemble architecture and learning mechanisms. The properties of the full model are analysed in the light of extensive experiments with the classification task, including an investigation into the influence of different input feature selection schemes and a comparison with a hierarchical STDP based ensemble architecture.

Rapid Long-Range Disynaptic Inhibition Explains the Formation of Cortical Orientation Maps

PubMed Central

Antolík, Ján

2017-01-01

Competitive interactions are believed to underlie many types of cortical processing, ranging from memory formation, attention and development of cortical functional organization (e.g., development of orientation maps in primary visual cortex). In the latter case, the competitive interactions happen along the cortical surface, with local populations of neurons reinforcing each other, while competing with those displaced more distally. This specific configuration of lateral interactions is however in stark contrast with the known properties of the anatomical substrate, i.e., excitatory connections (mediating reinforcement) having longer reach than inhibitory ones (mediating competition). No satisfactory biologically plausible resolution of this conflict between anatomical measures, and assumed cortical function has been proposed. Recently a specific pattern of delays between different types of neurons in cat cortex has been discovered, where direct mono-synaptic excitation has approximately the same delay, as the combined delays of the disynaptic inhibitory interactions between excitatory neurons (i.e., the sum of delays from excitatory to inhibitory and from inhibitory to excitatory neurons). Here we show that this specific pattern of delays represents a biologically plausible explanation for how short-range inhibition can support competitive interactions that underlie the development of orientation maps in primary visual cortex. We demonstrate this statement analytically under simplifying conditions, and subsequently show using network simulations that development of orientation maps is preserved when long-range excitation, direct inhibitory to inhibitory interactions, and moderate inequality in the delays between excitatory and inhibitory pathways is added. PMID:28408869

Biologic plausibility, cellular effects, and molecular mechanisms of eicosapentaenoic acid (EPA) in atherosclerosis.

PubMed

Borow, Kenneth M; Nelson, John R; Mason, R Preston

2015-09-01

Residual cardiovascular (CV) risk remains in dyslipidemic patients despite intensive statin therapy, underscoring the need for additional intervention. Eicosapentaenoic acid (EPA), an omega-3 polyunsaturated fatty acid, is incorporated into membrane phospholipids and atherosclerotic plaques and exerts beneficial effects on the pathophysiologic cascade from onset of plaque formation through rupture. Specific salutary actions have been reported relating to endothelial function, oxidative stress, foam cell formation, inflammation, plaque formation/progression, platelet aggregation, thrombus formation, and plaque rupture. EPA also improves atherogenic dyslipidemia characterized by reduction of triglycerides without raising low-density lipoprotein cholesterol. Other beneficial effects of EPA include vasodilation, resulting in blood pressure reductions, as well as improved membrane fluidity. EPA's effects are at least additive to those of statins when given as adjunctive therapy. In this review, we present data supporting the biologic plausibility of EPA as an anti-atherosclerotic agent with potential clinical benefit for prevention of CV events, as well as its cellular effects and molecular mechanisms of action. REDUCE-IT is an ongoing, randomized, controlled study evaluating whether the high-purity ethyl ester of EPA (icosapent ethyl) at 4 g/day combined with statin therapy is superior to statin therapy alone for reducing CV events in high-risk patients with mixed dyslipidemia. The results from this study are expected to clarify the role of EPA as adjunctive therapy to a statin for reduction of residual CV risk. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

A systematic review of evidence on the association between cocaine use and seizures.

PubMed

Sordo, L; Indave, B I; Degenhardt, L; Barrio, G; Kaye, S; Ruíz-Pérez, I; Bravo, M J

2013-12-15

Institutional monographs/medical textbooks mention seizures as a neurological complication of cocaine, but no systematic reviews (SRs) have been published on this issue. We aimed to conduct a SR of the literature on the relationship between cocaine use and seizures and to summarize the biological plausibility of that relationship. The pathophysiological mechanisms that may underlie an association between cocaine and seizures were summarized; a SR was then performed using three databases (EMBASE, Medline, PsycINFO) and the Cochrane-library to search for published papers (1980-2012) aimed at quantifying the associations between cocaine use and seizures. The inclusion criteria for selection were: articles based on clinical trials, cohort, case-control (CC) or cross-sectional (CS) studies, participants ≥ 14 years old and not pregnant, and use of cocaine in the last 72 h. Information was extracted, evaluated and cross-checked independently by two researchers. Of the 1243 potentially relevant articles initially identified; one CC and 22 CS studies were finally selected. The CC study did not find cocaine use to be a risk-factor for seizures. In addition to the limitations of the CS design, these studies had important methodological weaknesses and biases. Despite its biological plausibility, no rigorous scientific evidence supports a causal relationship between cocaine use and seizures. The misinterpretation of the role of cocaine may have important implications in medical services. Well-conducted studies are urgently needed. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Unsupervised Learning in an Ensemble of Spiking Neural Networks Mediated by ITDP

PubMed Central

Staras, Kevin

2016-01-01

We propose a biologically plausible architecture for unsupervised ensemble learning in a population of spiking neural network classifiers. A mixture of experts type organisation is shown to be effective, with the individual classifier outputs combined via a gating network whose operation is driven by input timing dependent plasticity (ITDP). The ITDP gating mechanism is based on recent experimental findings. An abstract, analytically tractable model of the ITDP driven ensemble architecture is derived from a logical model based on the probabilities of neural firing events. A detailed analysis of this model provides insights that allow it to be extended into a full, biologically plausible, computational implementation of the architecture which is demonstrated on a visual classification task. The extended model makes use of a style of spiking network, first introduced as a model of cortical microcircuits, that is capable of Bayesian inference, effectively performing expectation maximization. The unsupervised ensemble learning mechanism, based around such spiking expectation maximization (SEM) networks whose combined outputs are mediated by ITDP, is shown to perform the visual classification task well and to generalize to unseen data. The combined ensemble performance is significantly better than that of the individual classifiers, validating the ensemble architecture and learning mechanisms. The properties of the full model are analysed in the light of extensive experiments with the classification task, including an investigation into the influence of different input feature selection schemes and a comparison with a hierarchical STDP based ensemble architecture. PMID:27760125

Characterizing Cancer Drug Response and Biological Correlates: A Geometric Network Approach.

PubMed

Pouryahya, Maryam; Oh, Jung Hun; Mathews, James C; Deasy, Joseph O; Tannenbaum, Allen R

2018-04-23

In the present work, we apply a geometric network approach to study common biological features of anticancer drug response. We use for this purpose the panel of 60 human cell lines (NCI-60) provided by the National Cancer Institute. Our study suggests that mathematical tools for network-based analysis can provide novel insights into drug response and cancer biology. We adopted a discrete notion of Ricci curvature to measure, via a link between Ricci curvature and network robustness established by the theory of optimal mass transport, the robustness of biological networks constructed with a pre-treatment gene expression dataset and coupled the results with the GI50 response of the cell lines to the drugs. Based on the resulting drug response ranking, we assessed the impact of genes that are likely associated with individual drug response. For genes identified as important, we performed a gene ontology enrichment analysis using a curated bioinformatics database which resulted in biological processes associated with drug response across cell lines and tissue types which are plausible from the point of view of the biological literature. These results demonstrate the potential of using the mathematical network analysis in assessing drug response and in identifying relevant genomic biomarkers and biological processes for precision medicine.

The pure rotational spectrum of CaNC

NASA Astrophysics Data System (ADS)

Scurlock, C. T.; Steimle, T. C.; Suenram, R. D.; Lovas, F. J.

1994-03-01

The pure rotational spectrum of calcium isocyanide, CaNC, in its (0,0,0) X 2Σ+ vibronic state was measured using a combination of Fourier transform microwave (FTMW) and pump/probe microwave-optical double resonance (PPMODR) spectroscopy. Gaseous CaNC was generated using a laser ablation/supersonic expansion source. The determined spectroscopic parameters are (in MHz), B=4048.754 332 (29); γ=18.055 06 (23); bF=12.481 49 (93); c=2.0735 (14); and eQq0=-2.6974 (11). The hyperfine parameters are qualitatively interpreted in terms of a plausible molecular orbital descriptions and a comparison with the alkaline earth monohalides and the alkali monocyanides is given.

The Universal Plausibility Metric (UPM) & Principle (UPP)

PubMed Central

2009-01-01

Background Mere possibility is not an adequate basis for asserting scientific plausibility. A precisely defined universal bound is needed beyond which the assertion of plausibility, particularly in life-origin models, can be considered operationally falsified. But can something so seemingly relative and subjective as plausibility ever be quantified? Amazingly, the answer is, "Yes." A method of objectively measuring the plausibility of any chance hypothesis (The Universal Plausibility Metric [UPM]) is presented. A numerical inequality is also provided whereby any chance hypothesis can be definitively falsified when its UPM metric of ξ is < 1 (The Universal Plausibility Principle [UPP]). Both UPM and UPP pre-exist and are independent of any experimental design and data set. Conclusion No low-probability hypothetical plausibility assertion should survive peer-review without subjection to the UPP inequality standard of formal falsification (ξ < 1). PMID:19958539

Exact solution for the optimal neuronal layout problem.

PubMed

Chklovskii, Dmitri B

2004-10-01

Evolution perfected brain design by maximizing its functionality while minimizing costs associated with building and maintaining it. Assumption that brain functionality is specified by neuronal connectivity, implemented by costly biological wiring, leads to the following optimal design problem. For a given neuronal connectivity, find a spatial layout of neurons that minimizes the wiring cost. Unfortunately, this problem is difficult to solve because the number of possible layouts is often astronomically large. We argue that the wiring cost may scale as wire length squared, reducing the optimal layout problem to a constrained minimization of a quadratic form. For biologically plausible constraints, this problem has exact analytical solutions, which give reasonable approximations to actual layouts in the brain. These solutions make the inverse problem of inferring neuronal connectivity from neuronal layout more tractable.

On the formation mechanisms of compact elliptical galaxies

NASA Astrophysics Data System (ADS)

Ferré-Mateu, Anna; Forbes, Duncan A.; Romanowsky, Aaron J.; Janz, Joachim; Dixon, Christopher

2018-01-01

In order to investigate the formation mechanisms of the rare compact elliptical (cE) galaxies, we have compiled a sample of 25 cEs with good SDSS spectra, covering a range of stellar masses, sizes and environments. They have been visually classified according to the interaction with their host, representing different evolutionary stages. We have included clearly disrupted galaxies, galaxies that despite not showing signs of interaction are located close to a massive neighbour (thus are good candidates for a stripping process), and cEs with no host nearby. For the latter, tidal stripping is less likely to have happened and instead they could simply represent the very low-mass, faint end of the ellipticals. We study a set of properties (structural parameters, stellar populations, star formation histories and mass ratios) that can be used to discriminate between an intrinsic or stripped origin. We find that one diagnostic tool alone is inconclusive for the majority of objects. However, if we combine all the tools a clear picture emerges. The most plausible origin, as well as the evolutionary stage and progenitor type, can be then determined. Our results favour the stripping mechanism for those galaxies in groups and clusters that have a plausible host nearby, but favours an intrinsic origin for those rare cEs without a plausible host and that are located in looser environments.

TIDAL HEATING IN A MAGMA OCEAN WITHIN JUPITER’S MOON Io

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tyler, Robert H.; Henning, Wade G.; Hamilton, Christopher W., E-mail: robert.h.tyler@nasa.gov

Active volcanism observed on Io is thought to be driven by the temporally periodic, spatially differential projection of Jupiter's gravitational field over the moon. Previous theoretical estimates of the tidal heat have all treated Io as essentially a solid, with fluids addressed only through adjustment of rheological parameters rather than through appropriate extension of the dynamics. These previous estimates of the tidal response and associated heat generation on Io are therefore incomplete and possibly erroneous because dynamical aspects of the fluid behavior are not permitted in the modeling approach. Here we address this by modeling the partial-melt asthenosphere as amore » global layer of fluid governed by the Laplace Tidal Equations. Solutions for the tidal response are then compared with solutions obtained following the traditional solid-material approach. It is found that the tidal heat in the solid can match that of the average observed heat flux (nominally 2.25 W m{sup −2}), though only over a very restricted range of plausible parameters, and that the distribution of the solid tidal heat flux cannot readily explain a longitudinal shift in the observed (inferred) low-latitude heat fluxes. The tidal heat in the fluid reaches that observed over a wider range of plausible parameters, and can also readily provide the longitudinal offset. Finally, expected feedbacks and coupling between the solid/fluid tides are discussed. Most broadly, the results suggest that both solid and fluid tidal-response estimates must be considered in exoplanet studies, particularly where orbital migration under tidal dissipation is addressed.« less

Nutrient control of phytoplankton photosynthesis in the western North Atlantic

NASA Technical Reports Server (NTRS)

Platt, Trevor; Sathyendranath, Shubha; Ulloa, Osvaldo; Harrison, William G.; Hoepffner, Nicolas; Goes, Joaquim

1992-01-01

Results from several years of oceanographic cruises are reported which show that the parameters of the photosynthesis-light curve of the flora of the North Sargasso Sea are remarkably constant in magnitude, except during the spring phytoplankton bloom when their magnitudes are noticeably higher. These results are interpreted as providing direct evidence for nutrient control of photosynthesis in the open ocean. The findings also reinforce the plausibility of using biogeochemical provinces to partition the ocean into manageable units for basin- or global-scale analysis. They show that seasonal changes in critical parameter should not be overlooked if robust carbon budgets are to be constructed, and illustrate the value of attacking the parameters that control the key fluxes, rather than the fluxes themselves, when investigating the ocean carbon cycle.

The Bradford Hill criteria and zinc-induced anosmia: a causality analysis.

PubMed

Davidson, Terence M; Smith, Wendy M

2010-07-01

To apply the Bradford Hill criteria, which are widely used to establish causality between an environmental agent and disease, to evaluate the relationship between over-the-counter intranasal zinc gluconate therapy and anosmia. Patient and literature review applying the Bradford Hill criteria on causation. University of California, San Diego, Nasal Dysfunction Clinic. The study included 25 patients who presented to the University of California, San Diego, Nasal Dysfunction Clinic complaining of acute-onset anosmia after intranasal application of homeopathic zinc gluconate gel. Each of the 9 Bradford Hill criteria--strength of association, consistency, specificity, temporality, biological gradient (dose-response), biological plausibility, biological coherence, experimental evidence, and analogy--was applied to intranasal zinc gluconate therapy and olfactory dysfunction using published, peer-reviewed medical literature and reported clinical experiences. Clinical, biological, and experimental data support the Bradford Hill criteria to demonstrate that intranasal zinc gluconate therapy causes hyposmia and anosmia. The Bradford Hill criteria represent an important tool for scientifically determining cause between environmental exposure and disease. Increased Food and Drug Administration oversight of homeopathic medications is needed to monitor the safety of these popular remedies.

GC-MS and LC-MS approaches for determination of tocopherols and tocotrienols in biological and food matrices.

PubMed

Bartosińska, E; Buszewska-Forajta, M; Siluk, D

2016-08-05

Tocopherols and tocotrienols, widely described as vitamin E derivatives, have been proven to take part in a number of important biological functions. Among them, antioxidant properties had been investigated and documented in the literature. Since tocochromanols have revealed their plausible beneficial impact on several pathological processes, such as cancerogenesis or cognitive impairment diseases, there is a growing interest in quantitative determination of these compounds in biological fluids, tissues and plant organs. However, due to vitamin E chemical features, such as lipophilic and non-polar characteristics, quantitative determination of the compounds seems to be problematic. In this paper we present current analytical approaches in tocopherols and tocotrienols determination in biological and food matrices with the use of chromatographic techniques, especially gas chromatography (GC) and high performance liquid chromatography (HPLC) coupled with mass spectrometry. Derivatization techniques applied for GC-MS analysis in the case of tocol derivatives, especially silylation and acylation, are described. Significant attention is paid to ionization process of tocopherols and tocotrienols. Copyright © 2016 Elsevier B.V. All rights reserved.

On the use of log-transformation vs. nonlinear regression for analyzing biological power laws

USGS Publications Warehouse

Xiao, X.; White, E.P.; Hooten, M.B.; Durham, S.L.

2011-01-01

Power-law relationships are among the most well-studied functional relationships in biology. Recently the common practice of fitting power laws using linear regression (LR) on log-transformed data has been criticized, calling into question the conclusions of hundreds of studies. It has been suggested that nonlinear regression (NLR) is preferable, but no rigorous comparison of these two methods has been conducted. Using Monte Carlo simulations, we demonstrate that the error distribution determines which method performs better, with NLR better characterizing data with additive, homoscedastic, normal error and LR better characterizing data with multiplicative, heteroscedastic, lognormal error. Analysis of 471 biological power laws shows that both forms of error occur in nature. While previous analyses based on log-transformation appear to be generally valid, future analyses should choose methods based on a combination of biological plausibility and analysis of the error distribution. We provide detailed guidelines and associated computer code for doing so, including a model averaging approach for cases where the error structure is uncertain. ?? 2011 by the Ecological Society of America.

The structure of the cyanobactin domain of unknown function from PatG in the patellamide gene cluster

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mann, Greg; Koehnke, Jesko; Bent, Andrew F.

The highly conserved domain of unknown function in the cyanobactin superfamily has a novel fold. The protein does not appear to bind the most plausible substrates, leaving questions as to its role. Patellamides are members of the cyanobactin family of ribosomally synthesized and post-translationally modified cyclic peptide natural products, many of which, including some patellamides, are biologically active. A detailed mechanistic understanding of the biosynthetic pathway would enable the construction of a biotechnological ‘toolkit’ to make novel analogues of patellamides that are not found in nature. All but two of the protein domains involved in patellamide biosynthesis have been characterized.more » The two domains of unknown function (DUFs) are homologous to each other and are found at the C-termini of the multi-domain proteins PatA and PatG. The domain sequence is found in all cyanobactin-biosynthetic pathways characterized to date, implying a functional role in cyanobactin biosynthesis. Here, the crystal structure of the PatG DUF domain is reported and its binding interactions with plausible substrates are investigated.« less

Plausibility and evidence: the case of homeopathy.

PubMed

Rutten, Lex; Mathie, Robert T; Fisher, Peter; Goossens, Maria; van Wassenhoven, Michel

2013-08-01

Homeopathy is controversial and hotly debated. The conclusions of systematic reviews of randomised controlled trials of homeopathy vary from 'comparable to conventional medicine' to 'no evidence of effects beyond placebo'. It is claimed that homeopathy conflicts with scientific laws and that homoeopaths reject the naturalistic outlook, but no evidence has been cited. We are homeopathic physicians and researchers who do not reject the scientific outlook; we believe that examination of the prior beliefs underlying this enduring stand-off can advance the debate. We show that interpretations of the same set of evidence--for homeopathy and for conventional medicine--can diverge. Prior disbelief in homeopathy is rooted in the perceived implausibility of any conceivable mechanism of action. Using the 'crossword analogy', we demonstrate that plausibility bias impedes assessment of the clinical evidence. Sweeping statements about the scientific impossibility of homeopathy are themselves unscientific: scientific statements must be precise and testable. There is growing evidence that homeopathic preparations can exert biological effects; due consideration of such research would reduce the influence of prior beliefs on the assessment of systematic review evidence.

Advanced biologically plausible algorithms for low-level image processing

NASA Astrophysics Data System (ADS)

Gusakova, Valentina I.; Podladchikova, Lubov N.; Shaposhnikov, Dmitry G.; Markin, Sergey N.; Golovan, Alexander V.; Lee, Seong-Whan

1999-08-01

At present, in computer vision, the approach based on modeling the biological vision mechanisms is extensively developed. However, up to now, real world image processing has no effective solution in frameworks of both biologically inspired and conventional approaches. Evidently, new algorithms and system architectures based on advanced biological motivation should be developed for solution of computational problems related to this visual task. Basic problems that should be solved for creation of effective artificial visual system to process real world imags are a search for new algorithms of low-level image processing that, in a great extent, determine system performance. In the present paper, the result of psychophysical experiments and several advanced biologically motivated algorithms for low-level processing are presented. These algorithms are based on local space-variant filter, context encoding visual information presented in the center of input window, and automatic detection of perceptually important image fragments. The core of latter algorithm are using local feature conjunctions such as noncolinear oriented segment and composite feature map formation. Developed algorithms were integrated into foveal active vision model, the MARR. It is supposed that proposed algorithms may significantly improve model performance while real world image processing during memorizing, search, and recognition.

Using novel descriptor accounting for ligand-receptor interactions to define and visually explore biologically relevant chemical space.

PubMed

Rabal, Obdulia; Oyarzabal, Julen

2012-05-25

The definition and pragmatic implementation of biologically relevant chemical space is critical in addressing navigation strategies in the overlapping regions where chemistry and therapeutically relevant targets reside and, therefore, also key to performing an efficient drug discovery project. Here, we describe the development and implementation of a simple and robust method for representing biologically relevant chemical space as a general reference according to current knowledge, independently of any reference space, and analyzing chemical structures accordingly. Underlying our method is the generation of a novel descriptor (LiRIf) that converts structural information into a one-dimensional string accounting for the plausible ligand-receptor interactions as well as for topological information. Capitalizing on ligand-receptor interactions as a descriptor enables the clustering, profiling, and comparison of libraries of compounds from a chemical biology and medicinal chemistry perspective. In addition, as a case study, R-groups analysis is performed to identify the most populated ligand-receptor interactions according to different target families (GPCR, kinases, etc.), as well as to evaluate the coverage of biologically relevant chemical space by structures annotated in different databases (ChEMBL, Glida, etc.).

Magnetotactic bacteria on Earth and on Mars.

PubMed

McKay, Christopher P; Friedmann, E Imre; Frankel, Richard B; Bazylinski, Dennis A

2003-01-01

Continued interest in the possibility of evidence for life in the ALH84001 Martian meteorite has focused on the magnetite crystals. This review is structured around three related questions: is the magnetite in ALH84001 of biological or non-biological origin, or a mixture of both? does magnetite on Earth provide insight to the plausibility of biogenic magnetite on Mars? could magnetotaxis have developed on Mars? There are credible arguments for both the biological and non-biological origin of the magnetite in ALH84001, and we suggest that more studies of ALH84001, extensive laboratory simulations of non-biological magnetite formation, as well as further studies of magnetotactic bacteria on Earth will be required to further address this question. Magnetite grains produced by bacteria could provide one of the few inorganic traces of past bacterial life on Mars that could be recovered from surface soils and sediments. If there was biogenic magnetite on Mars in sufficient abundance to leave fossil remains in the volcanic rocks of ALH84001, then it is likely that better-preserved magnetite will be found in sedimentary deposits on Mars. Deposits in ancient lakebeds could contain well-preserved chains of magnetite clearly indicating a biogenic origin.

Magnetotactic bacteria on Earth and on Mars

NASA Technical Reports Server (NTRS)

McKay, Christopher P.; Friedmann, E. Imre; Frankel, Richard B.; Bazylinski, Dennis A.

2003-01-01

Continued interest in the possibility of evidence for life in the ALH84001 Martian meteorite has focused on the magnetite crystals. This review is structured around three related questions: is the magnetite in ALH84001 of biological or non-biological origin, or a mixture of both? does magnetite on Earth provide insight to the plausibility of biogenic magnetite on Mars? could magnetotaxis have developed on Mars? There are credible arguments for both the biological and non-biological origin of the magnetite in ALH84001, and we suggest that more studies of ALH84001, extensive laboratory simulations of non-biological magnetite formation, as well as further studies of magnetotactic bacteria on Earth will be required to further address this question. Magnetite grains produced by bacteria could provide one of the few inorganic traces of past bacterial life on Mars that could be recovered from surface soils and sediments. If there was biogenic magnetite on Mars in sufficient abundance to leave fossil remains in the volcanic rocks of ALH84001, then it is likely that better-preserved magnetite will be found in sedimentary deposits on Mars. Deposits in ancient lakebeds could contain well-preserved chains of magnetite clearly indicating a biogenic origin.

Cu-catalyzed esterification reaction via aerobic oxygenation and C-C bond cleavage: an approach to α-ketoesters.

PubMed

Zhang, Chun; Feng, Peng; Jiao, Ning

2013-10-09

The Cu-catalyzed novel aerobic oxidative esterification reaction of 1,3-diones for the synthesis of α-ketoesters has been developed. This method combines C-C σ-bond cleavage, dioxygen activation and oxidative C-H bond functionalization, as well as provides a practical, neutral, and mild synthetic approach to α-ketoesters which are important units in many biologically active compounds and useful precursors in a variety of functional group transformations. A plausible radical process is proposed on the basis of mechanistic studies.

Research challange

DOE Office of Scientific and Technical Information (OSTI.GOV)

Staebler, G.R.

The technological forecast can be used as a research tool by describing the optimum forest from every plausible viewpoint and then charting a course to create it. We must make usable the things we already know, and define, plan, and execute a research attack on those we don't. The three main areas we must consider are full use of the land, maximization of production, and research management and administration. In all these considerations we must keep in mind that technology creates the need for more technology, and that it is biologically necessary to preserve the long look.

RNA catalysis and the origins of life

NASA Technical Reports Server (NTRS)

Orgel, Leslie E.

1986-01-01

The role of RNA catalysis in the origins of life is considered in connection with the discovery of riboszymes, which are RNA molecules that catalyze sequence-specific hydrolysis and transesterification reactions of RNA substrates. Due to this discovery, theories positing protein-free replication as preceding the appearance of the genetic code are more plausible. The scope of RNA catalysis in biology and chemistry is discussed, and it is noted that the development of methods to select (or predict) RNA sequences with preassigned catalytic functions would be a major contribution to the study of life's origins.

Motor neuron disease and optic neuropathy after acute exposure to a methanol-containing solvent mixture.

PubMed

Chiò, Adriano; Herrero Hernandez, Elena; Mora, Gabriele; Valentini, Consuelo; Discalzi, Gianluigi; Pira, Enrico

2004-09-01

A 34-years-old floor-layer developed optic neuropathy and motor neuron disease after being accidentally exposed to a solvent mixture containing methanol and other substances. Optic neuropathy is a complication of methanol poisoning, but the onset of a motor neuron disorder resembling amyotrophic lateral sclerosis after the exposure to these substances has not been previously described. The temporal onset of the clinical symptoms, biological plausibility, young age of the patient and absence of neurological disorders in the family history raises suspicion of a possible causative relationship.

On the applicability of STDP-based learning mechanisms to spiking neuron network models

NASA Astrophysics Data System (ADS)

Sboev, A.; Vlasov, D.; Serenko, A.; Rybka, R.; Moloshnikov, I.

2016-11-01

The ways to creating practically effective method for spiking neuron networks learning, that would be appropriate for implementing in neuromorphic hardware and at the same time based on the biologically plausible plasticity rules, namely, on STDP, are discussed. The influence of the amount of correlation between input and output spike trains on the learnability by different STDP rules is evaluated. A usability of alternative combined learning schemes, involving artificial and spiking neuron models is demonstrated on the iris benchmark task and on the practical task of gender recognition.

Computing motion using resistive networks

NASA Technical Reports Server (NTRS)

Koch, Christof; Luo, Jin; Mead, Carver; Hutchinson, James

1988-01-01

Recent developments in the theory of early vision are described which lead from the formulation of the motion problem as an ill-posed one to its solution by minimizing certain 'cost' functions. These cost or energy functions can be mapped onto simple analog and digital resistive networks. It is shown how the optical flow can be computed by injecting currents into resistive networks and recording the resulting stationary voltage distribution at each node. These networks can be implemented in cMOS VLSI circuits and represent plausible candidates for biological vision systems.

(−) Arctigenin and (+) Pinoresinol Are Antagonists of the Human Thyroid Hormone Receptor β

PubMed Central

2015-01-01

Lignans are important biologically active dietary polyphenolic compounds. Consumption of foods that are rich in lignans is associated with positive health effects. Using modeling tools to probe the ligand-binding pockets of molecular receptors, we found that lignans have high docking affinity for the human thyroid hormone receptor β. Follow-up experimental results show that lignans (−) arctigenin and (+) pinoresinol are antagonists of the human thyroid hormone receptor β. The modeled complexes show key plausible interactions between the two ligands and important amino acid residues of the receptor. PMID:25383984

Real-time physics-based 3D biped character animation using an inverted pendulum model.

PubMed

Tsai, Yao-Yang; Lin, Wen-Chieh; Cheng, Kuangyou B; Lee, Jehee; Lee, Tong-Yee

2010-01-01

We present a physics-based approach to generate 3D biped character animation that can react to dynamical environments in real time. Our approach utilizes an inverted pendulum model to online adjust the desired motion trajectory from the input motion capture data. This online adjustment produces a physically plausible motion trajectory adapted to dynamic environments, which is then used as the desired motion for the motion controllers to track in dynamics simulation. Rather than using Proportional-Derivative controllers whose parameters usually cannot be easily set, our motion tracking adopts a velocity-driven method which computes joint torques based on the desired joint angular velocities. Physically correct full-body motion of the 3D character is computed in dynamics simulation using the computed torques and dynamical model of the character. Our experiments demonstrate that tracking motion capture data with real-time response animation can be achieved easily. In addition, physically plausible motion style editing, automatic motion transition, and motion adaptation to different limb sizes can also be generated without difficulty.

Modeling protein homopolymeric repeats: possible polyglutamine structural motifs for Huntington's disease.

PubMed

Lathrop, R H; Casale, M; Tobias, D J; Marsh, J L; Thompson, L M

1998-01-01

We describe a prototype system (Poly-X) for assisting an expert user in modeling protein repeats. Poly-X reduces the large number of degrees of freedom required to specify a protein motif in complete atomic detail. The result is a small number of parameters that are easily understood by, and under the direct control of, a domain expert. The system was applied to the polyglutamine (poly-Q) repeat in the first exon of huntingtin, the gene implicated in Huntington's disease. We present four poly-Q structural motifs: two poly-Q beta-sheet motifs (parallel and antiparallel) that constitute plausible alternatives to a similar previously published poly-Q beta-sheet motif, and two novel poly-Q helix motifs (alpha-helix and pi-helix). To our knowledge, helical forms of polyglutamine have not been proposed before. The motifs suggest that there may be several plausible aggregation structures for the intranuclear inclusion bodies which have been found in diseased neurons, and may help in the effort to understand the structural basis for Huntington's disease.

Predator interference effects on biological control: The "paradox" of the generalist predator revisited

NASA Astrophysics Data System (ADS)

Parshad, Rana D.; Bhowmick, Suman; Quansah, Emmanuel; Basheer, Aladeen; Upadhyay, Ranjit Kumar

2016-10-01

An interesting conundrum in biological control questions the efficiency of generalist predators as biological control agents. Theory suggests, generalist predators are poor agents for biological control, primarily due to mutual interference. However field evidence shows they are actually quite effective in regulating pest densities. In this work we provide a plausible answer to this paradox. We analyze a three species model, where a generalist top predator is introduced into an ecosystem as a biological control, to check the population of a middle predator, that in turn is depredating on a prey species. We show that the inclusion of predator interference alone, can cause the solution of the top predator equation to blow-up in finite time, while there is global existence in the no interference case. This result shows that interference could actually cause a population explosion of the top predator, enabling it to control the target species, thus corroborating recent field evidence. Our results might also partially explain the population explosion of certain species, introduced originally for biological control purposes, such as the cane toad (Bufo marinus) in Australia, which now functions as a generalist top predator. We also show both Turing instability and spatio-temporal chaos in the model. Lastly we investigate time delay effects.

Effect of sub-pore scale morphology of biological deposits on porous media flow properties

NASA Astrophysics Data System (ADS)

Ghezzehei, T. A.

2012-12-01

Biological deposits often influence fluid flow by altering the pore space morphology and related hydrologic properties such as porosity, water retention characteristics, and permeability. In most coupled-processes models changes in porosity are inferred from biological process models using mass-balance. The corresponding evolution of permeability is estimated using (semi-) empirical porosity-permeability functions such as the Kozeny-Carman equation or power-law functions. These equations typically do not account for the heterogeneous spatial distribution and morphological irregularities of the deposits. As a result, predictions of permeability evolution are generally unsatisfactory. In this presentation, we demonstrate the significance of pore-scale deposit distribution on porosity-permeability relations using high resolution simulations of fluid flow through a single pore interspersed with deposits of varying morphologies. Based on these simulations, we present a modification to the Kozeny-Carman model that accounts for the shape of the deposits. Limited comparison with published experimental data suggests the plausibility of the proposed conceptual model.

Do US Black Women Experience Stress-Related Accelerated Biological Aging?

PubMed Central

Hicken, Margaret T.; Pearson, Jay A.; Seashols, Sarah J.; Brown, Kelly L.; Cruz, Tracey Dawson

2010-01-01

We hypothesize that black women experience accelerated biological aging in response to repeated or prolonged adaptation to subjective and objective stressors. Drawing on stress physiology and ethnographic, social science, and public health literature, we lay out the rationale for this hypothesis. We also perform a first population-based test of its plausibility, focusing on telomere length, a biomeasure of aging that may be shortened by stressors. Analyzing data from the Study of Women's Health Across the Nation (SWAN), we estimate that at ages 49–55, black women are 7.5 years biologically “older” than white women. Indicators of perceived stress and poverty account for 27% of this difference. Data limitations preclude assessing objective stressors and also result in imprecise estimates, limiting our ability to draw firm inferences. Further investigation of black-white differences in telomere length using large-population-based samples of broad age range and with detailed measures of environmental stressors is merited. PMID:20436780

Modelling malaria control by introduction of larvivorous fish.

PubMed

Lou, Yijun; Zhao, Xiao-Qiang

2011-10-01

Malaria creates serious health and economic problems which call for integrated management strategies to disrupt interactions among mosquitoes, the parasite and humans. In order to reduce the intensity of malaria transmission, malaria vector control may be implemented to protect individuals against infective mosquito bites. As a sustainable larval control method, the use of larvivorous fish is promoted in some circumstances. To evaluate the potential impacts of this biological control measure on malaria transmission, we propose and investigate a mathematical model describing the linked dynamics between the host-vector interaction and the predator-prey interaction. The model, which consists of five ordinary differential equations, is rigorously analysed via theories and methods of dynamical systems. We derive four biologically plausible and insightful quantities (reproduction numbers) that completely determine the community composition. Our results suggest that the introduction of larvivorous fish can, in principle, have important consequences for malaria dynamics, but also indicate that this would require strong predators on larval mosquitoes. Integrated strategies of malaria control are analysed to demonstrate the biological application of our developed theory.

DL-ReSuMe: A Delay Learning-Based Remote Supervised Method for Spiking Neurons.

PubMed

Taherkhani, Aboozar; Belatreche, Ammar; Li, Yuhua; Maguire, Liam P

2015-12-01

Recent research has shown the potential capability of spiking neural networks (SNNs) to model complex information processing in the brain. There is biological evidence to prove the use of the precise timing of spikes for information coding. However, the exact learning mechanism in which the neuron is trained to fire at precise times remains an open problem. The majority of the existing learning methods for SNNs are based on weight adjustment. However, there is also biological evidence that the synaptic delay is not constant. In this paper, a learning method for spiking neurons, called delay learning remote supervised method (DL-ReSuMe), is proposed to merge the delay shift approach and ReSuMe-based weight adjustment to enhance the learning performance. DL-ReSuMe uses more biologically plausible properties, such as delay learning, and needs less weight adjustment than ReSuMe. Simulation results have shown that the proposed DL-ReSuMe approach achieves learning accuracy and learning speed improvements compared with ReSuMe.

Modular rate laws for enzymatic reactions: thermodynamics, elasticities and implementation.

PubMed

Liebermeister, Wolfram; Uhlendorf, Jannis; Klipp, Edda

2010-06-15

Standard rate laws are a key requisite for systematically turning metabolic networks into kinetic models. They should provide simple, general and biochemically plausible formulae for reaction velocities and reaction elasticities. At the same time, they need to respect thermodynamic relations between the kinetic constants and the metabolic fluxes and concentrations. We present a family of reversible rate laws for reactions with arbitrary stoichiometries and various types of regulation, including mass-action, Michaelis-Menten and uni-uni reversible Hill kinetics as special cases. With a thermodynamically safe parameterization of these rate laws, parameter sets obtained by model fitting, sampling or optimization are guaranteed to lead to consistent chemical equilibrium states. A reformulation using saturation values yields simple formulae for rates and elasticities, which can be easily adjusted to the given stationary flux distributions. Furthermore, this formulation highlights the role of chemical potential differences as thermodynamic driving forces. We compare the modular rate laws to the thermodynamic-kinetic modelling formalism and discuss a simplified rate law in which the reaction rate directly depends on the reaction affinity. For automatic handling of modular rate laws, we propose a standard syntax and semantic annotations for the Systems Biology Markup Language. An online tool for inserting the rate laws into SBML models is freely available at www.semanticsbml.org. Supplementary data are available at Bioinformatics online.

Three-dimensional visualization of nanostructured surfaces and bacterial attachment using Autodesk® Maya®.

PubMed

Boshkovikj, Veselin; Fluke, Christopher J; Crawford, Russell J; Ivanova, Elena P

2014-02-28

There has been a growing interest in understanding the ways in which bacteria interact with nano-structured surfaces. As a result, there is a need for innovative approaches to enable researchers to visualize the biological processes taking place, despite the fact that it is not possible to directly observe these processes. We present a novel approach for the three-dimensional visualization of bacterial interactions with nano-structured surfaces using the software package Autodesk Maya. Our approach comprises a semi-automated stage, where actual surface topographic parameters, obtained using an atomic force microscope, are imported into Maya via a custom Python script, followed by a 'creative stage', where the bacterial cells and their interactions with the surfaces are visualized using available experimental data. The 'Dynamics' and 'nDynamics' capabilities of the Maya software allowed the construction and visualization of plausible interaction scenarios. This capability provides a practical aid to knowledge discovery, assists in the dissemination of research results, and provides an opportunity for an improved public understanding. We validated our approach by graphically depicting the interactions between the two bacteria being used for modeling purposes, Staphylococcus aureus and Pseudomonas aeruginosa, with different titanium substrate surfaces that are routinely used in the production of biomedical devices.

Three-dimensional visualization of nanostructured surfaces and bacterial attachment using Autodesk® Maya®

NASA Astrophysics Data System (ADS)

Boshkovikj, Veselin; Fluke, Christopher J.; Crawford, Russell J.; Ivanova, Elena P.

2014-02-01

There has been a growing interest in understanding the ways in which bacteria interact with nano-structured surfaces. As a result, there is a need for innovative approaches to enable researchers to visualize the biological processes taking place, despite the fact that it is not possible to directly observe these processes. We present a novel approach for the three-dimensional visualization of bacterial interactions with nano-structured surfaces using the software package Autodesk Maya. Our approach comprises a semi-automated stage, where actual surface topographic parameters, obtained using an atomic force microscope, are imported into Maya via a custom Python script, followed by a `creative stage', where the bacterial cells and their interactions with the surfaces are visualized using available experimental data. The `Dynamics' and `nDynamics' capabilities of the Maya software allowed the construction and visualization of plausible interaction scenarios. This capability provides a practical aid to knowledge discovery, assists in the dissemination of research results, and provides an opportunity for an improved public understanding. We validated our approach by graphically depicting the interactions between the two bacteria being used for modeling purposes, Staphylococcus aureus and Pseudomonas aeruginosa, with different titanium substrate surfaces that are routinely used in the production of biomedical devices.

Efficient high light acclimation involves rapid processes at multiple mechanistic levels.

PubMed

Dietz, Karl-Josef

2015-05-01

Like no other chemical or physical parameter, the natural light environment of plants changes with high speed and jumps of enormous intensity. To cope with this variability, photosynthetic organisms have evolved sensing and response mechanisms that allow efficient acclimation. Most signals originate from the chloroplast itself. In addition to very fast photochemical regulation, intensive molecular communication is realized within the photosynthesizing cell, optimizing the acclimation process. Current research has opened up new perspectives on plausible but mostly unexpected complexity in signalling events, crosstalk, and process adjustments. Within seconds and minutes, redox states, levels of reactive oxygen species, metabolites, and hormones change and transmit information to the cytosol, modifying metabolic activity, gene expression, translation activity, and alternative splicing events. Signalling pathways on an intermediate time scale of several minutes to a few hours pave the way for long-term acclimation. Thereby, a new steady state of the transcriptome, proteome, and metabolism is realized within rather short time periods irrespective of the previous acclimation history to shade or sun conditions. This review provides a time line of events during six hours in the 'stressful' life of a plant. © The Author 2015. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Inference on the Strength of Balancing Selection for Epistatically Interacting Loci

PubMed Central

Buzbas, Erkan Ozge; Joyce, Paul; Rosenberg, Noah A.

2011-01-01

Existing inference methods for estimating the strength of balancing selection in multi-locus genotypes rely on the assumption that there are no epistatic interactions between loci. Complex systems in which balancing selection is prevalent, such as sets of human immune system genes, are known to contain components that interact epistatically. Therefore, current methods may not produce reliable inference on the strength of selection at these loci. In this paper, we address this problem by presenting statistical methods that can account for epistatic interactions in making inference about balancing selection. A theoretical result due to Fearnhead (2006) is used to build a multi-locus Wright-Fisher model of balancing selection, allowing for epistatic interactions among loci. Antagonistic and synergistic types of interactions are examined. The joint posterior distribution of the selection and mutation parameters is sampled by Markov chain Monte Carlo methods, and the plausibility of models is assessed via Bayes factors. As a component of the inference process, an algorithm to generate multi-locus allele frequencies under balancing selection models with epistasis is also presented. Recent evidence on interactions among a set of human immune system genes is introduced as a motivating biological system for the epistatic model, and data on these genes are used to demonstrate the methods. PMID:21277883

Balancing selection in species with separate sexes: insights from Fisher's geometric model.

PubMed

Connallon, Tim; Clark, Andrew G

2014-07-01

How common is balancing selection, and what fraction of phenotypic variance is attributable to balanced polymorphisms? Despite decades of research, answers to these questions remain elusive. Moreover, there is no clear theoretical prediction about the frequency with which balancing selection is expected to arise within a population. Here, we use an extension of Fisher's geometric model of adaptation to predict the probability of balancing selection in a population with separate sexes, wherein polymorphism is potentially maintained by two forms of balancing selection: (1) heterozygote advantage, where heterozygous individuals at a locus have higher fitness than homozygous individuals, and (2) sexually antagonistic selection (a.k.a. intralocus sexual conflict), where the fitness of each sex is maximized by different genotypes at a locus. We show that balancing selection is common under biologically plausible conditions and that sex differences in selection or sex-by-genotype effects of mutations can each increase opportunities for balancing selection. Although heterozygote advantage and sexual antagonism represent alternative mechanisms for maintaining polymorphism, they mutually exist along a balancing selection continuum that depends on population and sex-specific parameters of selection and mutation. Sexual antagonism is the dominant mode of balancing selection across most of this continuum. Copyright © 2014 by the Genetics Society of America.

Three-dimensional visualization of nanostructured surfaces and bacterial attachment using Autodesk® Maya®

PubMed Central

Boshkovikj, Veselin; Fluke, Christopher J.; Crawford, Russell J.; Ivanova, Elena P.

2014-01-01

There has been a growing interest in understanding the ways in which bacteria interact with nano-structured surfaces. As a result, there is a need for innovative approaches to enable researchers to visualize the biological processes taking place, despite the fact that it is not possible to directly observe these processes. We present a novel approach for the three-dimensional visualization of bacterial interactions with nano-structured surfaces using the software package Autodesk Maya. Our approach comprises a semi-automated stage, where actual surface topographic parameters, obtained using an atomic force microscope, are imported into Maya via a custom Python script, followed by a ‘creative stage', where the bacterial cells and their interactions with the surfaces are visualized using available experimental data. The ‘Dynamics' and ‘nDynamics' capabilities of the Maya software allowed the construction and visualization of plausible interaction scenarios. This capability provides a practical aid to knowledge discovery, assists in the dissemination of research results, and provides an opportunity for an improved public understanding. We validated our approach by graphically depicting the interactions between the two bacteria being used for modeling purposes, Staphylococcus aureus and Pseudomonas aeruginosa, with different titanium substrate surfaces that are routinely used in the production of biomedical devices. PMID:24577105

Modeling the lowest-cost splitting of a herd of cows by optimizing a cost function

NASA Astrophysics Data System (ADS)

Gajamannage, Kelum; Bollt, Erik M.; Porter, Mason A.; Dawkins, Marian S.

2017-06-01

Animals live in groups to defend against predation and to obtain food. However, for some animals—especially ones that spend long periods of time feeding—there are costs if a group chooses to move on before their nutritional needs are satisfied. If the conflict between feeding and keeping up with a group becomes too large, it may be advantageous for some groups of animals to split into subgroups with similar nutritional needs. We model the costs and benefits of splitting in a herd of cows using a cost function that quantifies individual variation in hunger, desire to lie down, and predation risk. We model the costs associated with hunger and lying desire as the standard deviations of individuals within a group, and we model predation risk as an inverse exponential function of the group size. We minimize the cost function over all plausible groups that can arise from a given herd and study the dynamics of group splitting. We examine how the cow dynamics and cost function depend on the parameters in the model and consider two biologically-motivated examples: (1) group switching and group fission in a herd of relatively homogeneous cows, and (2) a herd with an equal number of adult males (larger animals) and adult females (smaller animals).

Response surface methodology: A non-conventional statistical tool to maximize the throughput of Streptomyces species biomass and their bioactive metabolites.

PubMed

Latha, Selvanathan; Sivaranjani, Govindhan; Dhanasekaran, Dharumadurai

2017-09-01

Among diverse actinobacteria, Streptomyces is a renowned ongoing source for the production of a large number of secondary metabolites, furnishing immeasurable pharmacological and biological activities. Hence, to meet the demand of new lead compounds for human and animal use, research is constantly targeting the bioprospecting of Streptomyces. Optimization of media components and physicochemical parameters is a plausible approach for the exploration of intensified production of novel as well as existing bioactive metabolites from various microbes, which is usually achieved by a range of classical techniques including one factor at a time (OFAT). However, the major drawbacks of conventional optimization methods have directed the use of statistical optimization approaches in fermentation process development. Response surface methodology (RSM) is one of the empirical techniques extensively used for modeling, optimization and analysis of fermentation processes. To date, several researchers have implemented RSM in different bioprocess optimization accountable for the production of assorted natural substances from Streptomyces in which the results are very promising. This review summarizes some of the recent RSM adopted studies for the enhanced production of antibiotics, enzymes and probiotics using Streptomyces with the intention to highlight the significance of Streptomyces as well as RSM to the research community and industries.

The plausibility of a role for mercury in the etiology of autism: a cellular perspective

PubMed Central

Garrecht, Matthew; Austin, David W.

2011-01-01

Autism is defined by a behavioral set of stereotypic and repetitious behavioral patterns in combination with social and communication deficits. There is emerging evidence supporting the hypothesis that autism may result from a combination of genetic susceptibility and exposure to environmental toxins at critical moments in development. Mercury (Hg) is recognized as a ubiquitous environmental neurotoxin and there is mounting evidence linking it to neurodevelopmental disorders, including autism. Of course, the evidence is not derived from experimental trials with humans but rather from methods focusing on biomarkers of Hg damage, measurements of Hg exposure, epidemiological data, and animal studies. For ethical reasons, controlled Hg exposure in humans will never be conducted. Therefore, to properly evaluate the Hg-autism etiological hypothesis, it is essential to first establish the biological plausibility of the hypothesis. This review examines the plausibility of Hg as the primary etiological agent driving the cellular mechanisms by which Hg-induced neurotoxicity may result in the physiological attributes of autism. Key areas of focus include: (1) route and cellular mechanisms of Hg exposure in autism; (2) current research and examples of possible genetic variables that are linked to both Hg sensitivity and autism; (3) the role Hg may play as an environmental toxin fueling the oxidative stress found in autism; (4) role of mitochondrial dysfunction; and (5) possible role of Hg in abnormal neuroexcitory and excitotoxity that may play a role in the immune dysregulation found in autism. Future research directions that would assist in addressing the gaps in our knowledge are proposed. PMID:22163375

A plausible neural circuit for decision making and its formation based on reinforcement learning.

PubMed

Wei, Hui; Dai, Dawei; Bu, Yijie

2017-06-01

A human's, or lower insects', behavior is dominated by its nervous system. Each stable behavior has its own inner steps and control rules, and is regulated by a neural circuit. Understanding how the brain influences perception, thought, and behavior is a central mandate of neuroscience. The phototactic flight of insects is a widely observed deterministic behavior. Since its movement is not stochastic, the behavior should be dominated by a neural circuit. Based on the basic firing characteristics of biological neurons and the neural circuit's constitution, we designed a plausible neural circuit for this phototactic behavior from logic perspective. The circuit's output layer, which generates a stable spike firing rate to encode flight commands, controls the insect's angular velocity when flying. The firing pattern and connection type of excitatory and inhibitory neurons are considered in this computational model. We simulated the circuit's information processing using a distributed PC array, and used the real-time average firing rate of output neuron clusters to drive a flying behavior simulation. In this paper, we also explored how a correct neural decision circuit is generated from network flow view through a bee's behavior experiment based on the reward and punishment feedback mechanism. The significance of this study: firstly, we designed a neural circuit to achieve the behavioral logic rules by strictly following the electrophysiological characteristics of biological neurons and anatomical facts. Secondly, our circuit's generality permits the design and implementation of behavioral logic rules based on the most general information processing and activity mode of biological neurons. Thirdly, through computer simulation, we achieved new understanding about the cooperative condition upon which multi-neurons achieve some behavioral control. Fourthly, this study aims in understanding the information encoding mechanism and how neural circuits achieve behavior control. Finally, this study also helps establish a transitional bridge between the microscopic activity of the nervous system and macroscopic animal behavior.

Understanding the neural basis of cognitive bias modification as a clinical treatment for depression.

PubMed

Eguchi, Akihiro; Walters, Daniel; Peerenboom, Nele; Dury, Hannah; Fox, Elaine; Stringer, Simon

2017-03-01

[Correction Notice: An Erratum for this article was reported in Vol 85(3) of Journal of Consulting and Clinical Psychology (see record 2017-07144-002). In the article, there was an error in the Discussion section's first paragraph for Implications and Future Work. The in-text reference citation for Penton-Voak et al. (2013) was incorrectly listed as "Blumenfeld, Preminger, Sagi, and Tsodyks (2006)". All versions of this article have been corrected.] Objective: Cognitive bias modification (CBM) eliminates cognitive biases toward negative information and is efficacious in reducing depression recurrence, but the mechanisms behind the bias elimination are not fully understood. The present study investigated, through computer simulation of neural network models, the neural dynamics underlying the use of CBM in eliminating the negative biases in the way that depressed patients evaluate facial expressions. We investigated 2 new CBM methodologies using biologically plausible synaptic learning mechanisms-continuous transformation learning and trace learning-which guide learning by exploiting either the spatial or temporal continuity between visual stimuli presented during training. We first describe simulations with a simplified 1-layer neural network, and then we describe simulations in a biologically detailed multilayer neural network model of the ventral visual pathway. After training with either the continuous transformation learning rule or the trace learning rule, the 1-layer neural network eliminated biases in interpreting neutral stimuli as sad. The multilayer neural network trained with realistic face stimuli was also shown to be able to use continuous transformation learning or trace learning to reduce biases in the interpretation of neutral stimuli. The simulation results suggest 2 biologically plausible synaptic learning mechanisms, continuous transformation learning and trace learning, that may subserve CBM. The results are highly informative for the development of experimental protocols to produce optimal CBM training methodologies with human participants. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways.

PubMed

Scott, Robert A; Lagou, Vasiliki; Welch, Ryan P; Wheeler, Eleanor; Montasser, May E; Luan, Jian'an; Mägi, Reedik; Strawbridge, Rona J; Rehnberg, Emil; Gustafsson, Stefan; Kanoni, Stavroula; Rasmussen-Torvik, Laura J; Yengo, Loïc; Lecoeur, Cecile; Shungin, Dmitry; Sanna, Serena; Sidore, Carlo; Johnson, Paul C D; Jukema, J Wouter; Johnson, Toby; Mahajan, Anubha; Verweij, Niek; Thorleifsson, Gudmar; Hottenga, Jouke-Jan; Shah, Sonia; Smith, Albert V; Sennblad, Bengt; Gieger, Christian; Salo, Perttu; Perola, Markus; Timpson, Nicholas J; Evans, David M; Pourcain, Beate St; Wu, Ying; Andrews, Jeanette S; Hui, Jennie; Bielak, Lawrence F; Zhao, Wei; Horikoshi, Momoko; Navarro, Pau; Isaacs, Aaron; O'Connell, Jeffrey R; Stirrups, Kathleen; Vitart, Veronique; Hayward, Caroline; Esko, Tõnu; Mihailov, Evelin; Fraser, Ross M; Fall, Tove; Voight, Benjamin F; Raychaudhuri, Soumya; Chen, Han; Lindgren, Cecilia M; Morris, Andrew P; Rayner, Nigel W; Robertson, Neil; Rybin, Denis; Liu, Ching-Ti; Beckmann, Jacques S; Willems, Sara M; Chines, Peter S; Jackson, Anne U; Kang, Hyun Min; Stringham, Heather M; Song, Kijoung; Tanaka, Toshiko; Peden, John F; Goel, Anuj; Hicks, Andrew A; An, Ping; Müller-Nurasyid, Martina; Franco-Cereceda, Anders; Folkersen, Lasse; Marullo, Letizia; Jansen, Hanneke; Oldehinkel, Albertine J; Bruinenberg, Marcel; Pankow, James S; North, Kari E; Forouhi, Nita G; Loos, Ruth J F; Edkins, Sarah; Varga, Tibor V; Hallmans, Göran; Oksa, Heikki; Antonella, Mulas; Nagaraja, Ramaiah; Trompet, Stella; Ford, Ian; Bakker, Stephan J L; Kong, Augustine; Kumari, Meena; Gigante, Bruna; Herder, Christian; Munroe, Patricia B; Caulfield, Mark; Antti, Jula; Mangino, Massimo; Small, Kerrin; Miljkovic, Iva; Liu, Yongmei; Atalay, Mustafa; Kiess, Wieland; James, Alan L; Rivadeneira, Fernando; Uitterlinden, Andre G; Palmer, Colin N A; Doney, Alex S F; Willemsen, Gonneke; Smit, Johannes H; Campbell, Susan; Polasek, Ozren; Bonnycastle, Lori L; Hercberg, Serge; Dimitriou, Maria; Bolton, Jennifer L; Fowkes, Gerard R; Kovacs, Peter; Lindström, Jaana; Zemunik, Tatijana; Bandinelli, Stefania; Wild, Sarah H; Basart, Hanneke V; Rathmann, Wolfgang; Grallert, Harald; Maerz, Winfried; Kleber, Marcus E; Boehm, Bernhard O; Peters, Annette; Pramstaller, Peter P; Province, Michael A; Borecki, Ingrid B; Hastie, Nicholas D; Rudan, Igor; Campbell, Harry; Watkins, Hugh; Farrall, Martin; Stumvoll, Michael; Ferrucci, Luigi; Waterworth, Dawn M; Bergman, Richard N; Collins, Francis S; Tuomilehto, Jaakko; Watanabe, Richard M; de Geus, Eco J C; Penninx, Brenda W; Hofman, Albert; Oostra, Ben A; Psaty, Bruce M; Vollenweider, Peter; Wilson, James F; Wright, Alan F; Hovingh, G Kees; Metspalu, Andres; Uusitupa, Matti; Magnusson, Patrik K E; Kyvik, Kirsten O; Kaprio, Jaakko; Price, Jackie F; Dedoussis, George V; Deloukas, Panos; Meneton, Pierre; Lind, Lars; Boehnke, Michael; Shuldiner, Alan R; van Duijn, Cornelia M; Morris, Andrew D; Toenjes, Anke; Peyser, Patricia A; Beilby, John P; Körner, Antje; Kuusisto, Johanna; Laakso, Markku; Bornstein, Stefan R; Schwarz, Peter E H; Lakka, Timo A; Rauramaa, Rainer; Adair, Linda S; Smith, George Davey; Spector, Tim D; Illig, Thomas; de Faire, Ulf; Hamsten, Anders; Gudnason, Vilmundur; Kivimaki, Mika; Hingorani, Aroon; Keinanen-Kiukaanniemi, Sirkka M; Saaristo, Timo E; Boomsma, Dorret I; Stefansson, Kari; van der Harst, Pim; Dupuis, Josée; Pedersen, Nancy L; Sattar, Naveed; Harris, Tamara B; Cucca, Francesco; Ripatti, Samuli; Salomaa, Veikko; Mohlke, Karen L; Balkau, Beverley; Froguel, Philippe; Pouta, Anneli; Jarvelin, Marjo-Riitta; Wareham, Nicholas J; Bouatia-Naji, Nabila; McCarthy, Mark I; Franks, Paul W; Meigs, James B; Teslovich, Tanya M; Florez, Jose C; Langenberg, Claudia; Ingelsson, Erik; Prokopenko, Inga; Barroso, Inês

2012-09-01

Through genome-wide association meta-analyses of up to 133,010 individuals of European ancestry without diabetes, including individuals newly genotyped using the Metabochip, we have increased the number of confirmed loci influencing glycemic traits to 53, of which 33 also increase type 2 diabetes risk (q < 0.05). Loci influencing fasting insulin concentration showed association with lipid levels and fat distribution, suggesting impact on insulin resistance. Gene-based analyses identified further biologically plausible loci, suggesting that additional loci beyond those reaching genome-wide significance are likely to represent real associations. This conclusion is supported by an excess of directionally consistent and nominally significant signals between discovery and follow-up studies. Functional analysis of these newly discovered loci will further improve our understanding of glycemic control.

Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways

PubMed Central

Scott, Robert A; Lagou, Vasiliki; Welch, Ryan P; Wheeler, Eleanor; Montasser, May E; Luan, Jian’an; Mägi, Reedik; Strawbridge, Rona J; Rehnberg, Emil; Gustafsson, Stefan; Kanoni, Stavroula; Rasmussen-Torvik, Laura J; Yengo, Loïc; Lecoeur, Cecile; Shungin, Dmitry; Sanna, Serena; Sidore, Carlo; Johnson, Paul C D; Jukema, J Wouter; Johnson, Toby; Mahajan, Anubha; Verweij, Niek; Thorleifsson, Gudmar; Hottenga, Jouke-Jan; Shah, Sonia; Smith, Albert V; Sennblad, Bengt; Gieger, Christian; Salo, Perttu; Perola, Markus; Timpson, Nicholas J; Evans, David M; Pourcain, Beate St; Wu, Ying; Andrews, Jeanette S; Hui, Jennie; Bielak, Lawrence F; Zhao, Wei; Horikoshi, Momoko; Navarro, Pau; Isaacs, Aaron; O’Connell, Jeffrey R; Stirrups, Kathleen; Vitart, Veronique; Hayward, Caroline; Esko, Tönu; Mihailov, Evelin; Fraser, Ross M; Fall, Tove; Voight, Benjamin F; Raychaudhuri, Soumya; Chen, Han; Lindgren, Cecilia M; Morris, Andrew P; Rayner, Nigel W; Robertson, Neil; Rybin, Denis; Liu, Ching-Ti; Beckmann, Jacques S; Willems, Sara M; Chines, Peter S; Jackson, Anne U; Kang, Hyun Min; Stringham, Heather M; Song, Kijoung; Tanaka, Toshiko; Peden, John F; Goel, Anuj; Hicks, Andrew A; An, Ping; Müller-Nurasyid, Martina; Franco-Cereceda, Anders; Folkersen, Lasse; Marullo, Letizia; Jansen, Hanneke; Oldehinkel, Albertine J; Bruinenberg, Marcel; Pankow, James S; North, Kari E; Forouhi, Nita G; Loos, Ruth J F; Edkins, Sarah; Varga, Tibor V; Hallmans, Göran; Oksa, Heikki; Antonella, Mulas; Nagaraja, Ramaiah; Trompet, Stella; Ford, Ian; Bakker, Stephan J L; Kong, Augustine; Kumari, Meena; Gigante, Bruna; Herder, Christian; Munroe, Patricia B; Caulfield, Mark; Antti, Jula; Mangino, Massimo; Small, Kerrin; Miljkovic, Iva; Liu, Yongmei; Atalay, Mustafa; Kiess, Wieland; James, Alan L; Rivadeneira, Fernando; Uitterlinden, Andre G; Palmer, Colin N A; Doney, Alex S F; Willemsen, Gonneke; Smit, Johannes H; Campbell, Susan; Polasek, Ozren; Bonnycastle, Lori L; Hercberg, Serge; Dimitriou, Maria; Bolton, Jennifer L; Fowkes, Gerard R; Kovacs, Peter; Lindström, Jaana; Zemunik, Tatijana; Bandinelli, Stefania; Wild, Sarah H; Basart, Hanneke V; Rathmann, Wolfgang; Grallert, Harald; Maerz, Winfried; Kleber, Marcus E; Boehm, Bernhard O; Peters, Annette; Pramstaller, Peter P; Province, Michael A; Borecki, Ingrid B; Hastie, Nicholas D; Rudan, Igor; Campbell, Harry; Watkins, Hugh; Farrall, Martin; Stumvoll, Michael; Ferrucci, Luigi; Waterworth, Dawn M; Bergman, Richard N; Collins, Francis S; Tuomilehto, Jaakko; Watanabe, Richard M; de Geus, Eco J C; Penninx, Brenda W; Hofman, Albert; Oostra, Ben A; Psaty, Bruce M; Vollenweider, Peter; Wilson, James F; Wright, Alan F; Hovingh, G Kees; Metspalu, Andres; Uusitupa, Matti; Magnusson, Patrik K E; Kyvik, Kirsten O; Kaprio, Jaakko; Price, Jackie F; Dedoussis, George V; Deloukas, Panos; Meneton, Pierre; Lind, Lars; Boehnke, Michael; Shuldiner, Alan R; van Duijn, Cornelia M; Morris, Andrew D; Toenjes, Anke; Peyser, Patricia A; Beilby, John P; Körner, Antje; Kuusisto, Johanna; Laakso, Markku; Bornstein, Stefan R; Schwarz, Peter E H; Lakka, Timo A; Rauramaa, Rainer; Adair, Linda S; Smith, George Davey; Spector, Tim D; Illig, Thomas; de Faire, Ulf; Hamsten, Anders; Gudnason, Vilmundur; Kivimaki, Mika; Hingorani, Aroon; Keinanen-Kiukaanniemi, Sirkka M; Saaristo, Timo E; Boomsma, Dorret I; Stefansson, Kari; van der Harst, Pim; Dupuis, Josée; Pedersen, Nancy L; Sattar, Naveed; Harris, Tamara B; Cucca, Francesco; Ripatti, Samuli; Salomaa, Veikko; Mohlke, Karen L; Balkau, Beverley; Froguel, Philippe; Pouta, Anneli; Jarvelin, Marjo-Riitta; Wareham, Nicholas J; Bouatia-Naji, Nabila; McCarthy, Mark I; Franks, Paul W; Meigs, James B; Teslovich, Tanya M; Florez, Jose C; Langenberg, Claudia; Ingelsson, Erik; Prokopenko, Inga; Barroso, Inês

2012-01-01

Through genome-wide association meta-analyses of up to 133,010 individuals of European ancestry without diabetes, including individuals newly genotyped using the Metabochip, we have raised the number of confirmed loci influencing glycemic traits to 53, of which 33 also increase type 2 diabetes risk (q < 0.05). Loci influencing fasting insulin showed association with lipid levels and fat distribution, suggesting impact on insulin resistance. Gene-based analyses identified further biologically plausible loci, suggesting that additional loci beyond those reaching genome-wide significance are likely to represent real associations. This conclusion is supported by an excess of directionally consistent and nominally significant signals between discovery and follow-up studies. Functional follow-up of these newly discovered loci will further improve our understanding of glycemic control. PMID:22885924

CGRP Receptor Biology: Is There More Than One Receptor?

PubMed

Hay, Debbie L

2018-05-25

Calcitonin gene-related peptide (CGRP) has many reported pharmacological actions. Can a single receptor explain all of these? This chapter outlines the molecular nature of reported CGRP binding proteins and their pharmacology. Consideration of whether CGRP has only one or has more receptors is important because of the key role that this peptide plays in migraine. It is widely thought that the calcitonin receptor-like receptor together with receptor activity-modifying protein 1 (RAMP1) is the only relevant receptor for CGRP. However, some closely related receptors also have high affinity for CGRP and it is still plausible that these play a role in CGRP biology, and in migraine. The calcitonin receptor/RAMP1 complex, which is currently called the AMY 1 receptor, seems to be the most likely candidate but more investigation is needed to determine its role.

Synthesis and biological assessment of 3,7-dihydroxytropolones.

PubMed

Hirsch, D R; Schiavone, D V; Berkowitz, A J; Morrison, L A; Masaoka, T; Wilson, J A; Lomonosova, E; Zhao, H; Patel, B S; Datla, S H; Hoft, S G; Majidi, S J; Pal, R K; Gallicchio, E; Tang, L; Tavis, J E; Le Grice, S F J; Beutler, J A; Murelli, R P

2017-12-19

3,7-Dihydroxytropolones (3,7-dHTs) are highly oxygenated troponoids that have been identified as lead compounds for several human diseases. To date, structure-function studies on these molecules have been limited due to a scarcity of synthetic methods for their preparation. New synthetic strategies towards structurally novel 3,7-dHTs would be valuable in further studying their therapeutic potential. Here we describe the successful adaptation of a [5 + 2] oxidopyrilium cycloaddition/ring-opening for 3,7-dHT synthesis, which we apply in the synthesis of a plausible biosynthetic intermediate to the natural products puberulic and puberulonic acid. We have also tested these new compounds in several biological assays related to human immunodeficiency virus (HIV), hepatitis B virus (HBV) and herpes simplex virus (HSV) in order to gain insight into structure-functional analysis related to antiviral troponoid development.

On the origin of biological chirality via natural beta-decay

NASA Technical Reports Server (NTRS)

Noyes, H. P.; Bonner, W. A.; Tomlin, J. A.

1977-01-01

An hypothesis to account for the chirality (handedness) of some biological molecules is given. Experimental evidence suggests that longitudinally polarized electrons having the chirality of terrestrial beta-decay electrons remove dextro-leucine from a racemic mixture. If, by a similar mechanism, the terrestrial environment provided more levo- than dextro-amino acids, that would account for the chirality now observed in organic molecules. An isotope of potassium has been proposed as the natural beta-emitter responsible for biomolecular chirality; however, Carbon 14 may be an even more plausible candidate. Ready availability of the carbon isotope in the terrestrial environment of 4.5 aeons ago, and the role of leucine in protein synthesis indicate that these two agents may have been chief factors in the evolution of biomolecular chirality. Suggestions for further research in this area are made.

Resolving Conflicts Between Syntax and Plausibility in Sentence Comprehension

PubMed Central

Andrews, Glenda; Ogden, Jessica E.; Halford, Graeme S.

2017-01-01

Comprehension of plausible and implausible object- and subject-relative clause sentences with and without prepositional phrases was examined. Undergraduates read each sentence then evaluated a statement as consistent or inconsistent with the sentence. Higher acceptance of consistent than inconsistent statements indicated reliance on syntactic analysis. Higher acceptance of plausible than implausible statements reflected reliance on semantic plausibility. There was greater reliance on semantic plausibility and lesser reliance on syntactic analysis for more complex object-relatives and sentences with prepositional phrases than for less complex subject-relatives and sentences without prepositional phrases. Comprehension accuracy and confidence were lower when syntactic analysis and semantic plausibility yielded conflicting interpretations. The conflict effect on comprehension was significant for complex sentences but not for less complex sentences. Working memory capacity predicted resolution of the syntax-plausibility conflict in more and less complex items only when sentences and statements were presented sequentially. Fluid intelligence predicted resolution of the conflict in more and less complex items under sequential and simultaneous presentation. Domain-general processes appear to be involved in resolving syntax-plausibility conflicts in sentence comprehension. PMID:28458748

Counterfactual Plausibility and Comparative Similarity.

PubMed

Stanley, Matthew L; Stewart, Gregory W; Brigard, Felipe De

2017-05-01

Counterfactual thinking involves imagining hypothetical alternatives to reality. Philosopher David Lewis (1973, 1979) argued that people estimate the subjective plausibility that a counterfactual event might have occurred by comparing an imagined possible world in which the counterfactual statement is true against the current, actual world in which the counterfactual statement is false. Accordingly, counterfactuals considered to be true in possible worlds comparatively more similar to ours are judged as more plausible than counterfactuals deemed true in possible worlds comparatively less similar. Although Lewis did not originally develop his notion of comparative similarity to be investigated as a psychological construct, this study builds upon his idea to empirically investigate comparative similarity as a possible psychological strategy for evaluating the perceived plausibility of counterfactual events. More specifically, we evaluate judgments of comparative similarity between episodic memories and episodic counterfactual events as a factor influencing people's judgments of plausibility in counterfactual simulations, and we also compare it against other factors thought to influence judgments of counterfactual plausibility, such as ease of simulation and prior simulation. Our results suggest that the greater the perceived similarity between the original memory and the episodic counterfactual event, the greater the perceived plausibility that the counterfactual event might have occurred. While similarity between actual and counterfactual events, ease of imagining, and prior simulation of the counterfactual event were all significantly related to counterfactual plausibility, comparative similarity best captured the variance in ratings of counterfactual plausibility. Implications for existing theories on the determinants of counterfactual plausibility are discussed. Copyright © 2016 Cognitive Science Society, Inc.

Bayesian parameter estimation for nonlinear modelling of biological pathways.

PubMed

Ghasemi, Omid; Lindsey, Merry L; Yang, Tianyi; Nguyen, Nguyen; Huang, Yufei; Jin, Yu-Fang

2011-01-01

The availability of temporal measurements on biological experiments has significantly promoted research areas in systems biology. To gain insight into the interaction and regulation of biological systems, mathematical frameworks such as ordinary differential equations have been widely applied to model biological pathways and interpret the temporal data. Hill equations are the preferred formats to represent the reaction rate in differential equation frameworks, due to their simple structures and their capabilities for easy fitting to saturated experimental measurements. However, Hill equations are highly nonlinearly parameterized functions, and parameters in these functions cannot be measured easily. Additionally, because of its high nonlinearity, adaptive parameter estimation algorithms developed for linear parameterized differential equations cannot be applied. Therefore, parameter estimation in nonlinearly parameterized differential equation models for biological pathways is both challenging and rewarding. In this study, we propose a Bayesian parameter estimation algorithm to estimate parameters in nonlinear mathematical models for biological pathways using time series data. We used the Runge-Kutta method to transform differential equations to difference equations assuming a known structure of the differential equations. This transformation allowed us to generate predictions dependent on previous states and to apply a Bayesian approach, namely, the Markov chain Monte Carlo (MCMC) method. We applied this approach to the biological pathways involved in the left ventricle (LV) response to myocardial infarction (MI) and verified our algorithm by estimating two parameters in a Hill equation embedded in the nonlinear model. We further evaluated our estimation performance with different parameter settings and signal to noise ratios. Our results demonstrated the effectiveness of the algorithm for both linearly and nonlinearly parameterized dynamic systems. Our proposed Bayesian algorithm successfully estimated parameters in nonlinear mathematical models for biological pathways. This method can be further extended to high order systems and thus provides a useful tool to analyze biological dynamics and extract information using temporal data.

Natural Variation in the Carbon Oxidation State and Oxidative Ratio of a Deciduous Forest

NASA Astrophysics Data System (ADS)

Masiello, C. A.; Calligan, L. J.; Gallagher, M. E.; Hockaday, W. C.; Robertson, G. P.

2007-12-01

Here we report natural variability in the oxidative ratio (OR) and carbon oxidation state (Cox) of a temperate, deciduous forest measured on an annual basis via elemental analysis of leaf litter. The OR of the terrestrial biosphere is a key component in O2 -based calculations of the biosphere's uptake of fossil fuel CO2 (eg [ Keeling, et al., 1996]). Ecosystem OR has been assumed to be invariant; however, small OR variations may cause significant shifts in the calculated size of the terrestrial biospheric C sink [ Randerson, et al., 2006]. Accurate measurements of OR are necessary for the accurate apportionment of fossil fuel CO2 between the atmosphere, oceans, and terrestrial biosphere. Ecosystem OR is linearly related to Cox, a parameter which can be easily measured via elemental analysis, calorimetry, or solid state nuclear magnetic resonance [ Masiello, et al., 2007]. We are measuring Cox and OR at the three deciduous forest sites within the Kellogg Biological Station NSF LTER (lter.kbs.msu.edu). We report OR from litter collected from three forest sites from 1998-2003, a time series which covers periods of both normal and low precipitation. We also report error introduced in the Cox to OR conversion via a range of plausible assumptions about ecosystem N cycling. Keeling, R. F., et al. (1996), Global and hemispheric CO2 sinks deduced from changes in atmospheric O2 concentration, Nature, 381, 218-221. Masiello, C.A. et al. (in review 2007) Two new approaches for measuring ecosystem carbon oxidation state and oxidative ratio. J.G.R. Biogeosciences. Randerson, J. T., et al. (2006), Is carbon within the global terrestrial biosphere becoming more oxidized? Implications for trends in atmospheric O2, Global Change Biology, 12, 260-271.

Can Circadian Dysregulation Exacerbate Migraines?

PubMed

Ong, Jason C; Taylor, Hannah L; Park, Margaret; Burgess, Helen J; Fox, Rina S; Snyder, Sarah; Rains, Jeanetta C; Espie, Colin A; Wyatt, James K

2018-05-04

This observational pilot study examined objective circadian phase and sleep timing in chronic migraine (CM) and healthy controls (HC) and the impact of circadian factors on migraine frequency and severity. Sleep disturbance has been identified as a risk factor in the development and maintenance of CM but the biological mechanisms linking sleep and migraine remain largely theoretical. Twenty women with CM and 20 age-matched HC completed a protocol that included a 7 day sleep assessment at home using wrist actigraphy followed by a circadian phase assessment using salivary melatonin. We compared CM vs HC on sleep parameters and circadian factors. Subsequently, we examined associations between dim-light melatonin onset (DLMO), the midpoint of the sleep episode, and the phase angle (time from DLMO to sleep midpoint) with the number of migraine days per month and the migraine disability assessment scale (MIDAS). CM and HC did not differ on measures of sleep or circadian phase. Within the CM group, more frequent migraine days per month was significantly correlated with DLMO (r = .49, P = .039) and later sleep episode (r = .47, P = .037). In addition, a greater phase angle (ie, circadian misalignment) was significantly correlated with more severe migraine-related disability (r = .48, P = .042). These relationships remained significant after adjusting for total sleep time. This pilot study revealed that circadian misalignment and delayed sleep timing are associated with higher migraine frequency and severity, which was not better accounted for by the amount of sleep. These findings support the plausibility and need for further investigation of a circadian pathway in the development and maintenance of chronic headaches. Specifically, circadian misalignment and delayed sleep timing could serve as an exacerbating factor in chronic migraines when combined with biological predispositions or environmental factors. © 2018 American Headache Society.

Modeling Collective Animal Behavior with a Cognitive Perspective: A Methodological Framework

PubMed Central

Weitz, Sebastian; Blanco, Stéphane; Fournier, Richard; Gautrais, Jacques; Jost, Christian; Theraulaz, Guy

2012-01-01

The last decades have seen an increasing interest in modeling collective animal behavior. Some studies try to reproduce as accurately as possible the collective dynamics and patterns observed in several animal groups with biologically plausible, individual behavioral rules. The objective is then essentially to demonstrate that the observed collective features may be the result of self-organizing processes involving quite simple individual behaviors. Other studies concentrate on the objective of establishing or enriching links between collective behavior researches and cognitive or physiological ones, which then requires that each individual rule be carefully validated. Here we discuss the methodological consequences of this additional requirement. Using the example of corpse clustering in ants, we first illustrate that it may be impossible to discriminate among alternative individual rules by considering only observational data collected at the group level. Six individual behavioral models are described: They are clearly distinct in terms of individual behaviors, they all reproduce satisfactorily the collective dynamics and distribution patterns observed in experiments, and we show theoretically that it is strictly impossible to discriminate two of these models even in the limit of an infinite amount of data whatever the accuracy level. A set of methodological steps are then listed and discussed as practical ways to partially overcome this problem. They involve complementary experimental protocols specifically designed to address the behavioral rules successively, conserving group-level data for the overall model validation. In this context, we highlight the importance of maintaining a sharp distinction between model enunciation, with explicit references to validated biological concepts, and formal translation of these concepts in terms of quantitative state variables and fittable functional dependences. Illustrative examples are provided of the benefits expected during the often long and difficult process of refining a behavioral model, designing adapted experimental protocols and inversing model parameters. PMID:22761685

Modeling collective animal behavior with a cognitive perspective: a methodological framework.

PubMed

Weitz, Sebastian; Blanco, Stéphane; Fournier, Richard; Gautrais, Jacques; Jost, Christian; Theraulaz, Guy

2012-01-01

The last decades have seen an increasing interest in modeling collective animal behavior. Some studies try to reproduce as accurately as possible the collective dynamics and patterns observed in several animal groups with biologically plausible, individual behavioral rules. The objective is then essentially to demonstrate that the observed collective features may be the result of self-organizing processes involving quite simple individual behaviors. Other studies concentrate on the objective of establishing or enriching links between collective behavior researches and cognitive or physiological ones, which then requires that each individual rule be carefully validated. Here we discuss the methodological consequences of this additional requirement. Using the example of corpse clustering in ants, we first illustrate that it may be impossible to discriminate among alternative individual rules by considering only observational data collected at the group level. Six individual behavioral models are described: They are clearly distinct in terms of individual behaviors, they all reproduce satisfactorily the collective dynamics and distribution patterns observed in experiments, and we show theoretically that it is strictly impossible to discriminate two of these models even in the limit of an infinite amount of data whatever the accuracy level. A set of methodological steps are then listed and discussed as practical ways to partially overcome this problem. They involve complementary experimental protocols specifically designed to address the behavioral rules successively, conserving group-level data for the overall model validation. In this context, we highlight the importance of maintaining a sharp distinction between model enunciation, with explicit references to validated biological concepts, and formal translation of these concepts in terms of quantitative state variables and fittable functional dependences. Illustrative examples are provided of the benefits expected during the often long and difficult process of refining a behavioral model, designing adapted experimental protocols and inversing model parameters.

A CRITICAL ASSESSMENT OF BIODOSIMETRY METHODS FOR LARGE-SCALE INCIDENTS

PubMed Central

Swartz, Harold M.; Flood, Ann Barry; Gougelet, Robert M.; Rea, Michael E.; Nicolalde, Roberto J.; Williams, Benjamin B.

2014-01-01

Recognition is growing regarding the possibility that terrorism or large-scale accidents could result in potential radiation exposure of hundreds of thousands of people and that the present guidelines for evaluation after such an event are seriously deficient. Therefore, there is a great and urgent need for after-the-fact biodosimetric methods to estimate radiation dose. To accomplish this goal, the dose estimates must be at the individual level, timely, accurate, and plausibly obtained in large-scale disasters. This paper evaluates current biodosimetry methods, focusing on their strengths and weaknesses in estimating human radiation exposure in large-scale disasters at three stages. First, the authors evaluate biodosimetry’s ability to determine which individuals did not receive a significant exposure so they can be removed from the acute response system. Second, biodosimetry’s capacity to classify those initially assessed as needing further evaluation into treatment-level categories is assessed. Third, we review biodosimetry’s ability to guide treatment, both short- and long-term, is reviewed. The authors compare biodosimetric methods that are based on physical vs. biological parameters and evaluate the features of current dosimeters (capacity, speed and ease of getting information, and accuracy) to determine which are most useful in meeting patients’ needs at each of the different stages. Results indicate that the biodosimetry methods differ in their applicability to the three different stages, and that combining physical and biological techniques may sometimes be most effective. In conclusion, biodosimetry techniques have different properties, and knowledge of their properties for meeting the different needs for different stages will result in their most effective use in a nuclear disaster mass-casualty event. PMID:20065671

Bayesian inferences suggest that Amazon Yunga Natives diverged from Andeans less than 5000 ybp: implications for South American prehistory.

PubMed

Scliar, Marilia O; Gouveia, Mateus H; Benazzo, Andrea; Ghirotto, Silvia; Fagundes, Nelson J R; Leal, Thiago P; Magalhães, Wagner C S; Pereira, Latife; Rodrigues, Maira R; Soares-Souza, Giordano B; Cabrera, Lilia; Berg, Douglas E; Gilman, Robert H; Bertorelle, Giorgio; Tarazona-Santos, Eduardo

2014-09-30

Archaeology reports millenary cultural contacts between Peruvian Coast-Andes and the Amazon Yunga, a rainforest transitional region between Andes and Lower Amazonia. To clarify the relationships between cultural and biological evolution of these populations, in particular between Amazon Yungas and Andeans, we used DNA-sequence data, a model-based Bayesian approach and several statistical validations to infer a set of demographic parameters. We found that the genetic diversity of the Shimaa (an Amazon Yunga population) is a subset of that of Quechuas from Central-Andes. Using the Isolation-with-Migration population genetics model, we inferred that the Shimaa ancestors were a small subgroup that split less than 5300 years ago (after the development of complex societies) from an ancestral Andean population. After the split, the most plausible scenario compatible with our results is that the ancestors of Shimaas moved toward the Peruvian Amazon Yunga and incorporated the culture and language of some of their neighbors, but not a substantial amount of their genes. We validated our results using Approximate Bayesian Computations, posterior predictive tests and the analysis of pseudo-observed datasets. We presented a case study in which model-based Bayesian approaches, combined with necessary statistical validations, shed light into the prehistoric demographic relationship between Andeans and a population from the Amazon Yunga. Our results offer a testable model for the peopling of this large transitional environmental region between the Andes and the Lower Amazonia. However, studies on larger samples and involving more populations of these regions are necessary to confirm if the predominant Andean biological origin of the Shimaas is the rule, and not the exception.

Role of local network oscillations in resting-state functional connectivity.

PubMed

Cabral, Joana; Hugues, Etienne; Sporns, Olaf; Deco, Gustavo

2011-07-01

Spatio-temporally organized low-frequency fluctuations (<0.1 Hz), observed in BOLD fMRI signal during rest, suggest the existence of underlying network dynamics that emerge spontaneously from intrinsic brain processes. Furthermore, significant correlations between distinct anatomical regions-or functional connectivity (FC)-have led to the identification of several widely distributed resting-state networks (RSNs). This slow dynamics seems to be highly structured by anatomical connectivity but the mechanism behind it and its relationship with neural activity, particularly in the gamma frequency range, remains largely unknown. Indeed, direct measurements of neuronal activity have revealed similar large-scale correlations, particularly in slow power fluctuations of local field potential gamma frequency range oscillations. To address these questions, we investigated neural dynamics in a large-scale model of the human brain's neural activity. A key ingredient of the model was a structural brain network defined by empirically derived long-range brain connectivity together with the corresponding conduction delays. A neural population, assumed to spontaneously oscillate in the gamma frequency range, was placed at each network node. When these oscillatory units are integrated in the network, they behave as weakly coupled oscillators. The time-delayed interaction between nodes is described by the Kuramoto model of phase oscillators, a biologically-based model of coupled oscillatory systems. For a realistic setting of axonal conduction speed, we show that time-delayed network interaction leads to the emergence of slow neural activity fluctuations, whose patterns correlate significantly with the empirically measured FC. The best agreement of the simulated FC with the empirically measured FC is found for a set of parameters where subsets of nodes tend to synchronize although the network is not globally synchronized. Inside such clusters, the simulated BOLD signal between nodes is found to be correlated, instantiating the empirically observed RSNs. Between clusters, patterns of positive and negative correlations are observed, as described in experimental studies. These results are found to be robust with respect to a biologically plausible range of model parameters. In conclusion, our model suggests how resting-state neural activity can originate from the interplay between the local neural dynamics and the large-scale structure of the brain. Copyright © 2011 Elsevier Inc. All rights reserved.

Mathematical Methods of Subjective Modeling in Scientific Research: I. The Mathematical and Empirical Basis

NASA Astrophysics Data System (ADS)

Pyt'ev, Yu. P.

2018-01-01

mathematical formalism for subjective modeling, based on modelling of uncertainty, reflecting unreliability of subjective information and fuzziness that is common for its content. The model of subjective judgments on values of an unknown parameter x ∈ X of the model M( x) of a research object is defined by the researcher-modeler as a space1 ( X, p( X), P{I^{\\bar x}}, Be{l^{\\bar x}}) with plausibility P{I^{\\bar x}} and believability Be{l^{\\bar x}} measures, where x is an uncertain element taking values in X that models researcher—modeler's uncertain propositions about an unknown x ∈ X, measures P{I^{\\bar x}}, Be{l^{\\bar x}} model modalities of a researcher-modeler's subjective judgments on the validity of each x ∈ X: the value of P{I^{\\bar x}}(\\tilde x = x) determines how relatively plausible, in his opinion, the equality (\\tilde x = x) is, while the value of Be{l^{\\bar x}}(\\tilde x = x) determines how the inequality (\\tilde x = x) should be relatively believed in. Versions of plausibility Pl and believability Bel measures and pl- and bel-integrals that inherit some traits of probabilities, psychophysics and take into account interests of researcher-modeler groups are considered. It is shown that the mathematical formalism of subjective modeling, unlike "standard" mathematical modeling, •enables a researcher-modeler to model both precise formalized knowledge and non-formalized unreliable knowledge, from complete ignorance to precise knowledge of the model of a research object, to calculate relative plausibilities and believabilities of any features of a research object that are specified by its subjective model M(\\tilde x), and if the data on observations of a research object is available, then it: •enables him to estimate the adequacy of subjective model to the research objective, to correct it by combining subjective ideas and the observation data after testing their consistency, and, finally, to empirically recover the model of a research object.

A novel approach for connecting temporal-ontologies with blood flow simulations.

PubMed

Weichert, F; Mertens, C; Walczak, L; Kern-Isberner, G; Wagner, M

2013-06-01

In this paper an approach for developing a temporal domain ontology for biomedical simulations is introduced. The ideas are presented in the context of simulations of blood flow in aneurysms using the Lattice Boltzmann Method. The advantages in using ontologies are manyfold: On the one hand, ontologies having been proven to be able to provide medical special knowledge e.g., key parameters for simulations. On the other hand, based on a set of rules and the usage of a reasoner, a system for checking the plausibility as well as tracking the outcome of medical simulations can be constructed. Likewise, results of simulations including data derived from them can be stored and communicated in a way that can be understood by computers. Later on, this set of results can be analyzed. At the same time, the ontologies provide a way to exchange knowledge between researchers. Lastly, this approach can be seen as a black-box abstraction of the internals of the simulation for the biomedical researcher as well. This approach is able to provide the complete parameter sets for simulations, part of the corresponding results and part of their analysis as well as e.g., geometry and boundary conditions. These inputs can be transferred to different simulation methods for comparison. Variations on the provided parameters can be automatically used to drive these simulations. Using a rule base, unphysical inputs or outputs of the simulation can be detected and communicated to the physician in a suitable and familiar way. An example for an instantiation of the blood flow simulation ontology and exemplary rules for plausibility checking are given. Copyright © 2013 Elsevier Inc. All rights reserved.

Hunting a wandering supermassive black hole in the M31 halo hermitage

DOE Office of Scientific and Technical Information (OSTI.GOV)

Miki, Yohei; Mori, Masao; Kawaguchi, Toshihiro

2014-03-10

In the hierarchical structure formation scenario, galaxies enlarge through multiple merging events with less massive galaxies. In addition, the Magorrian relation indicates that almost all galaxies are occupied by a central supermassive black hole (SMBH) of mass 10{sup –3} times the mass of its spheroidal component. Consequently, SMBHs are expected to wander in the halos of their host galaxies following a galaxy collision, although evidence of this activity is currently lacking. We investigate a current plausible location of an SMBH wandering in the halo of the Andromeda galaxy (M31). According to theoretical studies of N-body simulations, some of the manymore » substructures in the M31 halo are remnants of a minor merger occurring about 1 Gyr ago. First, to evaluate the possible parameter space of the infalling orbit of the progenitor, we perform numerous parameter studies using a graphics processing unit cluster. To reduce uncertainties in the predicted position of the expected SMBH, we then calculate the time evolution of the SMBH in the progenitor dwarf galaxy from N-body simulations using the plausible parameter sets. Our results show that the SMBH lies within the halo (∼20-50 kpc from the M31 center), closer to the Milky Way than the M31 disk. Furthermore, the predicted current positions of the SMBH were restricted to an observational field of 0.°6 × 0.°7 in the northeast region of the M31 halo. We also discuss the origin of the infalling orbit of the satellite galaxy and its relationships with the recently discovered vast thin disk plane of satellite galaxies around M31.« less

Gaining insight into the T _2^*-T2 relationship in surface NMR free-induction decay measurements

NASA Astrophysics Data System (ADS)

Grombacher, Denys; Auken, Esben

2018-05-01

One of the primary shortcomings of the surface nuclear magnetic resonance (NMR) free-induction decay (FID) measurement is the uncertainty surrounding which mechanism controls the signal's time dependence. Ideally, the FID-estimated relaxation time T_2^* that describes the signal's decay carries an intimate link to the geometry of the pore space. In this limit the parameter T_2^* is closely linked to a related parameter T2, which is more closely linked to pore-geometry. If T_2^* ˜eq {T_2} the FID can provide valuable insight into relative pore-size and can be used to make quantitative permeability estimates. However, given only FID measurements it is difficult to determine whether T_2^* is linked to pore geometry or whether it has been strongly influenced by background magnetic field inhomogeneity. If the link between an observed T_2^* and the underlying T2 could be further constrained the utility of the standard surface NMR FID measurement would be greatly improved. We hypothesize that an approach employing an updated surface NMR forward model that solves the full Bloch equations with appropriately weighted relaxation terms can be used to help constrain the T_2^*-T2 relationship. Weighting the relaxation terms requires estimating the poorly constrained parameters T2 and T1; to deal with this uncertainty we propose to conduct a parameter search involving multiple inversions that employ a suite of forward models each describing a distinct but plausible T_2^*-T2 relationship. We hypothesize that forward models given poor T2 estimates will produce poor data fits when using the complex-inversion, while forward models given reliable T2 estimates will produce satisfactory data fits. By examining the data fits produced by the suite of plausible forward models, the likely T_2^*-T2 can be constrained by identifying the range of T2 estimates that produce reliable data fits. Synthetic and field results are presented to investigate the feasibility of the proposed technique.

QCScreen: a software tool for data quality control in LC-HRMS based metabolomics.

PubMed

Simader, Alexandra Maria; Kluger, Bernhard; Neumann, Nora Katharina Nicole; Bueschl, Christoph; Lemmens, Marc; Lirk, Gerald; Krska, Rudolf; Schuhmacher, Rainer

2015-10-24

Metabolomics experiments often comprise large numbers of biological samples resulting in huge amounts of data. This data needs to be inspected for plausibility before data evaluation to detect putative sources of error e.g. retention time or mass accuracy shifts. Especially in liquid chromatography-high resolution mass spectrometry (LC-HRMS) based metabolomics research, proper quality control checks (e.g. for precision, signal drifts or offsets) are crucial prerequisites to achieve reliable and comparable results within and across experimental measurement sequences. Software tools can support this process. The software tool QCScreen was developed to offer a quick and easy data quality check of LC-HRMS derived data. It allows a flexible investigation and comparison of basic quality-related parameters within user-defined target features and the possibility to automatically evaluate multiple sample types within or across different measurement sequences in a short time. It offers a user-friendly interface that allows an easy selection of processing steps and parameter settings. The generated results include a coloured overview plot of data quality across all analysed samples and targets and, in addition, detailed illustrations of the stability and precision of the chromatographic separation, the mass accuracy and the detector sensitivity. The use of QCScreen is demonstrated with experimental data from metabolomics experiments using selected standard compounds in pure solvent. The application of the software identified problematic features, samples and analytical parameters and suggested which data files or compounds required closer manual inspection. QCScreen is an open source software tool which provides a useful basis for assessing the suitability of LC-HRMS data prior to time consuming, detailed data processing and subsequent statistical analysis. It accepts the generic mzXML format and thus can be used with many different LC-HRMS platforms to process both multiple quality control sample types as well as experimental samples in one or more measurement sequences.

An Applied Framework for Incorporating Multiple Sources of Uncertainty in Fisheries Stock Assessments.

PubMed

Scott, Finlay; Jardim, Ernesto; Millar, Colin P; Cerviño, Santiago

2016-01-01

Estimating fish stock status is very challenging given the many sources and high levels of uncertainty surrounding the biological processes (e.g. natural variability in the demographic rates), model selection (e.g. choosing growth or stock assessment models) and parameter estimation. Incorporating multiple sources of uncertainty in a stock assessment allows advice to better account for the risks associated with proposed management options, promoting decisions that are more robust to such uncertainty. However, a typical assessment only reports the model fit and variance of estimated parameters, thereby underreporting the overall uncertainty. Additionally, although multiple candidate models may be considered, only one is selected as the 'best' result, effectively rejecting the plausible assumptions behind the other models. We present an applied framework to integrate multiple sources of uncertainty in the stock assessment process. The first step is the generation and conditioning of a suite of stock assessment models that contain different assumptions about the stock and the fishery. The second step is the estimation of parameters, including fitting of the stock assessment models. The final step integrates across all of the results to reconcile the multi-model outcome. The framework is flexible enough to be tailored to particular stocks and fisheries and can draw on information from multiple sources to implement a broad variety of assumptions, making it applicable to stocks with varying levels of data availability The Iberian hake stock in International Council for the Exploration of the Sea (ICES) Divisions VIIIc and IXa is used to demonstrate the framework, starting from length-based stock and indices data. Process and model uncertainty are considered through the growth, natural mortality, fishing mortality, survey catchability and stock-recruitment relationship. Estimation uncertainty is included as part of the fitting process. Simple model averaging is used to integrate across the results and produce a single assessment that considers the multiple sources of uncertainty.

Application of Johnson et al.'s speciation threshold model to apparent colonization times of island biotas.

PubMed

Ricklefs, Robert E; Bermingham, Eldredge

2004-08-01

Understanding patterns of diversity can be furthered by analysis of the dynamics of colonization, speciation, and extinction on islands using historical information provided by molecular phylogeography. The land birds of the Lesser Antilles are one of the most thoroughly described regional faunas in this context. In an analysis of colonization times, Ricklefs and Bermingham (2001) found that the cumulative distribution of lineages with respect to increasing time since colonization exhibits a striking change in slope at a genetic distance of about 2% mitochondrial DNA sequence divergence (about one million years). They further showed how this heterogeneity could be explained by either an abrupt increase in colonization rates or a mass extinction event. Cherry et al. (2002), referring to a model developed by Johnson et al. (2000), argued instead that the pattern resulted from a speciation threshold for reproductive isolation of island populations from their continental source populations. Prior to this threshold, genetic divergence is slowed by migration from the source, and species of varying age accumulate at a low genetic distance. After the threshold is reached, source and island populations diverge more rapidly, creating heterogeneity in the distribution of apparent ages of island taxa. We simulated of Johnson et al.'s speciation-threshold model, incorporating genetic divergence at rate k and fixation at rate M of genes that have migrated between the source and the island population. Fixation resets the divergence clock to zero. The speciation-threshold model fits the distribution of divergence times of Lesser Antillean birds well with biologically plausible parameter estimates. Application of the model to the Hawaiian avifauna, which does not exhibit marked heterogeneity of genetic divergence, and the West Indian herpetofauna, which does, required unreasonably high migration-fixation rates, several orders of magnitude greater than the colonization rate. However, the plausibility of the speciation-divergence model for Lesser Antillean birds emphasizes the importance of further investigation of historical biogeography on a regional scale for whole biotas, as well as the migration of genes between populations on long time scales and the achievement of reproductive isolation.

Efficient digital implementation of a conductance-based globus pallidus neuron and the dynamics analysis

NASA Astrophysics Data System (ADS)

Yang, Shuangming; Wei, Xile; Deng, Bin; Liu, Chen; Li, Huiyan; Wang, Jiang

2018-03-01

Balance between biological plausibility of dynamical activities and computational efficiency is one of challenging problems in computational neuroscience and neural system engineering. This paper proposes a set of efficient methods for the hardware realization of the conductance-based neuron model with relevant dynamics, targeting reproducing the biological behaviors with low-cost implementation on digital programmable platform, which can be applied in wide range of conductance-based neuron models. Modified GP neuron models for efficient hardware implementation are presented to reproduce reliable pallidal dynamics, which decode the information of basal ganglia and regulate the movement disorder related voluntary activities. Implementation results on a field-programmable gate array (FPGA) demonstrate that the proposed techniques and models can reduce the resource cost significantly and reproduce the biological dynamics accurately. Besides, the biological behaviors with weak network coupling are explored on the proposed platform, and theoretical analysis is also made for the investigation of biological characteristics of the structured pallidal oscillator and network. The implementation techniques provide an essential step towards the large-scale neural network to explore the dynamical mechanisms in real time. Furthermore, the proposed methodology enables the FPGA-based system a powerful platform for the investigation on neurodegenerative diseases and real-time control of bio-inspired neuro-robotics.

Increased electrical conductivity of peptides through annealing process

NASA Astrophysics Data System (ADS)

Namgung, Seok Daniel; Lee, Jaehun; Choe, Ik Rang; Sung, Taehoon; Kim, Young-O.; Lee, Yoon-Sik; Nam, Ki Tae; Kwon, Jang-Yeon

2017-08-01

Biocompatible biologically occurring polymer is suggested as a component of human implantable devices since conventional inorganic materials are apt to trigger inflammation and toxicity problem within human body. Peptides consisting of aromatic amino acid, tyrosine, are chosen, and enhancement on electrical conductivity is studied. Annealing process gives rise to the decrease on resistivity of the peptide films and the growth of the carrier concentration is a plausible reason for such a decrease on resistivity. The annealed peptides are further applied to an active layer of field effect transistor, in which low on/off current ratio (˜10) is obtained.

The scanning electron microscope as a tool in space biology

NASA Technical Reports Server (NTRS)

Barrett, R. A.

1983-01-01

Normal erythrocytes are disc-shaped and are referred to here descriptively as discocytes. Several morphologically variant forms occur nomally but in rather small amounts, usually less than one percent of total. It has been shown though, that spiculed variant forms referred to as echinocytes are generated in significant amounts at zero g. Normal red cells have been stressed in vitro in an effort to duplicate the observed discocyte-echinocyte transformation at zero g. The significance of this transformation to extended stay in space and some of the plausible reasons for this transformation are discussed.

Intention, emotion, and action: a neural theory based on semantic pointers.

PubMed

Schröder, Tobias; Stewart, Terrence C; Thagard, Paul

2014-06-01

We propose a unified theory of intentions as neural processes that integrate representations of states of affairs, actions, and emotional evaluation. We show how this theory provides answers to philosophical questions about the concept of intention, psychological questions about human behavior, computational questions about the relations between belief and action, and neuroscientific questions about how the brain produces actions. Our theory of intention ties together biologically plausible mechanisms for belief, planning, and motor control. The computational feasibility of these mechanisms is shown by a model that simulates psychologically important cases of intention. © 2013 Cognitive Science Society, Inc.

Racemic alkaloids from the fungus Ganoderma cochlear.

PubMed

Wang, Xin-Long; Dou, Man; Luo, Qi; Cheng, Li-Zhi; Yan, Yong-Ming; Li, Rong-Tao; Cheng, Yong-Xian

2017-01-01

Seven pairs of new alkaloid enantiomers, ganocochlearines C-I (1, 3-8), and three pairs of known alkaloids were isolated from the fruiting bodies of Ganoderma cochlear. The chemical structures of new compounds were elucidated on the basis of 1D and 2D NMR data. The absolute configurations of compounds 1, 3-10 were assigned by ECD calculations. Biological activities of these isolates against renal fibrosis were accessed in rat normal or diseased renal interstitial fibroblast cells. Importantly, the plausible biosynthetic pathway for this class of alkaloids was originally proposed. Copyright © 2016 Elsevier B.V. All rights reserved.

When plausibility manipulations work: an examination of their role in the development of false beliefs and memories.

PubMed

Bays, Rebecca B; Zabrucky, Karen M; Gagne, Phill

2012-01-01

In the current study we examined whether prevalence information and imagery encoding influence participants' general plausibility, personal plausibility, belief, and memory ratings for suggested childhood events. Results showed decreases in general and personal plausibility ratings for low prevalence events when encoding instructions were not elaborate; however, instructions to repeatedly imagine suggested events elicited personal plausibility increases for low-prevalence events, evidence that elaborate imagery negated the effect of our prevalence manipulation. We found no evidence of imagination inflation or false memory construction. We discuss critical differences in researchers' manipulations of plausibility and imagery that may influence results of false memory studies in the literature. In future research investigators should focus on the specific nature of encoding instructions when examining the development of false memories.

Biological parameters used in setting captive-breeding quotas for Indonesia's breeding facilities.

PubMed

Janssen, Jordi; Chng, Serene C L

2018-02-01

The commercial captive breeding of wildlife is often seen as a potential conservation tool to relieve pressure on wild populations, but laundering of wild-sourced specimens as captive bred can seriously undermine conservation efforts and provide a false sense of sustainability. Indonesia is at the center of such controversy; therefore, we examined Indonesia's captive-breeding production plan (CBPP) for 2016. We compared the biological parameters used in the CBPP with parameters in the literature and with parameters suggested by experts on each species and identified shortcomings of the CBPP. Production quotas for 99 out of 129 species were based on inaccurate or unrealistic biological parameters and production quotas deviated more than 10% from what parameters in the literature allow for. For 38 species, the quota exceeded the number of animals that can be bred based on the biological parameters (range 100-540%) calculated with equations in the CBPP. We calculated a lower reproductive output for 88 species based on published biological parameters compared with the parameters used in the CBPP. The equations used in the production plan did not appear to account for other factors (e.g., different survival rate for juveniles compared to adult animals) involved in breeding the proposed large numbers of specimens. We recommend the CBPP be adjusted so that realistic published biological parameters are applied and captive-breeding quotas are not allocated to species if their captive breeding is unlikely to be successful or no breeding stock is available. The shortcomings in the current CBPP create loopholes that mean mammals, reptiles, and amphibians from Indonesia declared captive bred may have been sourced from the wild. © 2017 Society for Conservation Biology.

Thermodynamic modeling of transcription: sensitivity analysis differentiates biological mechanism from mathematical model-induced effects.

PubMed

Dresch, Jacqueline M; Liu, Xiaozhou; Arnosti, David N; Ay, Ahmet

2010-10-24

Quantitative models of gene expression generate parameter values that can shed light on biological features such as transcription factor activity, cooperativity, and local effects of repressors. An important element in such investigations is sensitivity analysis, which determines how strongly a model's output reacts to variations in parameter values. Parameters of low sensitivity may not be accurately estimated, leading to unwarranted conclusions. Low sensitivity may reflect the nature of the biological data, or it may be a result of the model structure. Here, we focus on the analysis of thermodynamic models, which have been used extensively to analyze gene transcription. Extracted parameter values have been interpreted biologically, but until now little attention has been given to parameter sensitivity in this context. We apply local and global sensitivity analyses to two recent transcriptional models to determine the sensitivity of individual parameters. We show that in one case, values for repressor efficiencies are very sensitive, while values for protein cooperativities are not, and provide insights on why these differential sensitivities stem from both biological effects and the structure of the applied models. In a second case, we demonstrate that parameters that were thought to prove the system's dependence on activator-activator cooperativity are relatively insensitive. We show that there are numerous parameter sets that do not satisfy the relationships proferred as the optimal solutions, indicating that structural differences between the two types of transcriptional enhancers analyzed may not be as simple as altered activator cooperativity. Our results emphasize the need for sensitivity analysis to examine model construction and forms of biological data used for modeling transcriptional processes, in order to determine the significance of estimated parameter values for thermodynamic models. Knowledge of parameter sensitivities can provide the necessary context to determine how modeling results should be interpreted in biological systems.

Fuzzy Stochastic Petri Nets for Modeling Biological Systems with Uncertain Kinetic Parameters

PubMed Central

Liu, Fei; Heiner, Monika; Yang, Ming

2016-01-01

Stochastic Petri nets (SPNs) have been widely used to model randomness which is an inherent feature of biological systems. However, for many biological systems, some kinetic parameters may be uncertain due to incomplete, vague or missing kinetic data (often called fuzzy uncertainty), or naturally vary, e.g., between different individuals, experimental conditions, etc. (often called variability), which has prevented a wider application of SPNs that require accurate parameters. Considering the strength of fuzzy sets to deal with uncertain information, we apply a specific type of stochastic Petri nets, fuzzy stochastic Petri nets (FSPNs), to model and analyze biological systems with uncertain kinetic parameters. FSPNs combine SPNs and fuzzy sets, thereby taking into account both randomness and fuzziness of biological systems. For a biological system, SPNs model the randomness, while fuzzy sets model kinetic parameters with fuzzy uncertainty or variability by associating each parameter with a fuzzy number instead of a crisp real value. We introduce a simulation-based analysis method for FSPNs to explore the uncertainties of outputs resulting from the uncertainties associated with input parameters, which works equally well for bounded and unbounded models. We illustrate our approach using a yeast polarization model having an infinite state space, which shows the appropriateness of FSPNs in combination with simulation-based analysis for modeling and analyzing biological systems with uncertain information. PMID:26910830

Cannabis and psychosis: an update on course and biological plausible mechanisms.

PubMed

Linszen, Don; van Amelsvoort, Therese

2007-03-01

Cannabis use is the most commonly abused illicit substance. Its relation with psychosis remains a topic of debate. Epidemiological studies suggest that cannabis is a component cause accounting for approximately 10% of cases. An increasing number of studies have been published on neurobiological effects of cannabis and vulnerability of psychosis. Acute cannabis administration can induce memory impairments, sometimes persisting months following abstinence. There is no evidence that residual effects on cognition remain after years of abstinence. The scarce literature on neuro-imaging mainly done in nonpsychotic populations, show little evidence that cannabis has effects on brain anatomy. Acute effects of cannabis include increases of cerebral blood flow, whereas long-term effects of cannabis include attenuation of cerebral blood flow. In animals Delta9-tetrahydrocannabinol enhances dopaminergic neurotransmission in brain regions known to be implicated in psychosis. Studies in humans show that genetic vulnerability may add to increased risk of developing psychosis and cognitive impairments following cannabis consumption. Delta9-tetrahydrocannabinol induces psychotic like states and memory impairments in healthy volunteers. Simultaneously with increasing understanding of neurobiological cannabis effects, there is a lack of studies in people with psychosis. There are plausible mechanisms that might explain the psychotogenic effects of cannabis.

Explicit B-spline regularization in diffeomorphic image registration

PubMed Central

Tustison, Nicholas J.; Avants, Brian B.

2013-01-01

Diffeomorphic mappings are central to image registration due largely to their topological properties and success in providing biologically plausible solutions to deformation and morphological estimation problems. Popular diffeomorphic image registration algorithms include those characterized by time-varying and constant velocity fields, and symmetrical considerations. Prior information in the form of regularization is used to enforce transform plausibility taking the form of physics-based constraints or through some approximation thereof, e.g., Gaussian smoothing of the vector fields [a la Thirion's Demons (Thirion, 1998)]. In the context of the original Demons' framework, the so-called directly manipulated free-form deformation (DMFFD) (Tustison et al., 2009) can be viewed as a smoothing alternative in which explicit regularization is achieved through fast B-spline approximation. This characterization can be used to provide B-spline “flavored” diffeomorphic image registration solutions with several advantages. Implementation is open source and available through the Insight Toolkit and our Advanced Normalization Tools (ANTs) repository. A thorough comparative evaluation with the well-known SyN algorithm (Avants et al., 2008), implemented within the same framework, and its B-spline analog is performed using open labeled brain data and open source evaluation tools. PMID:24409140

Commentary: Fundamental problems with candidate gene-by-environment interaction studies - reflections on Moore and Thoemmes (2016).

PubMed

Border, Richard; Keller, Matthew C

2017-03-01

Moore and Thoemmes elaborate on one particular source of difficulty in the study of candidate gene-by-environment interactions (cG × E): how different biologically plausible configurations of gene-environment covariation can bias estimates of cG × E when not explicitly modeled. However, even if cG × E investigators were able to account for the sources of bias Moore and Thoemmes elaborate, it is unlikely that conventional approaches would yield reliable results. Published cG × E findings to date have generally employed inadequate analytic procedures, have relied on samples orders of magnitude too small to detect plausible effects, and have relied on a particular candidate gene approach that has been unfruitful and largely jettisoned in mainstream genetic analyses of complex traits. Analytic procedures for the study of gene-environment interplay must evolve to meet the challenges that the genetic architecture of complex traits presents, and investigators must collaborate on grander scales if we hope to begin to understand how specific genes and environments combine to affect behavior. © 2017 Association for Child and Adolescent Mental Health.

Cardiovascular Reactivity in Patients With Major Depressive Disorder With High- or Low-Level Depressive Symptoms: A Cross-Sectional Comparison of Cardiovascular Reactivity to Laboratory-Induced Mental Stress.

PubMed

Wang, Mei-Yeh; Chiu, Chen-Huan; Lee, Hsin-Chien; Su, Chien-Tien; Tsai, Pei-Shan

2016-03-01

Depression increases the risk of adverse cardiac events. Cardiovascular reactivity is defined as the pattern of cardiovascular responses to mental stress. An altered pattern of cardiovascular reactivity is an indicator of subsequent cardiovascular disease. Because depression and adverse cardiac events may have a dose-dependent association, this study examined the differences in cardiovascular reactivity to mental stress between patients with major depressive disorder (MDD) with high depression levels and those with low depression levels. Moreover, autonomic nervous system regulation is a highly plausible biological mechanism for the pattern of cardiovascular reactivity to mental stress. The association between cardiovascular reactivity and parameters of heart rate variability (HRV), an index for quantifying autonomic nervous system activity modulation, was thus examined. This study included 88 patients with MDD. HRV was measured before stress induction. The Stroop Color and Word Test and mirror star-tracing task were used to induce mental stress. We observed no significant association between depressive symptom level and any of the cardiovascular reactivity parameters. Cardiovascular reactivity to mental stress was comparable between patients with MDD with high-level depressive symptoms and those with low-level depressive symptoms. After adjusting for confounding variables, the high-frequency domain of HRV was found to be an independent predictor of the magnitude of heart rate reactivity (β = -.33, p = .002). In conclusion, the magnitude of cardiovascular reactivity may be independent of depression severity in patients with MDD. The autonomic regulation of cardiovascular responses to mental stress primarily influences heart rate reactivity in patients with MDD. © The Author(s) 2015.

Development of an in silico stochastic 4D model of tumor growth with angiogenesis.

PubMed

Forster, Jake C; Douglass, Michael J J; Harriss-Phillips, Wendy M; Bezak, Eva

2017-04-01

A stochastic computer model of tumour growth with spatial and temporal components that includes tumour angiogenesis was developed. In the current work it was used to simulate head and neck tumour growth. The model also provides the foundation for a 4D cellular radiotherapy simulation tool. The model, developed in Matlab, contains cell positions randomised in 3D space without overlap. Blood vessels are represented by strings of blood vessel units which branch outwards to achieve the desired tumour relative vascular volume. Hypoxic cells have an increased cell cycle time and become quiescent at oxygen tensions less than 1 mmHg. Necrotic cells are resorbed. A hierarchy of stem cells, transit cells and differentiated cells is considered along with differentiated cell loss. Model parameters include the relative vascular volume (2-10%), blood oxygenation (20-100 mmHg), distance from vessels to the onset of necrosis (80-300 μm) and probability for stem cells to undergo symmetric division (2%). Simulations were performed to observe the effects of hypoxia on tumour growth rate for head and neck cancers. Simulations were run on a supercomputer with eligible parts running in parallel on 12 cores. Using biologically plausible model parameters for head and neck cancers, the tumour volume doubling time varied from 45 ± 5 days (n = 3) for well oxygenated tumours to 87 ± 5 days (n = 3) for severely hypoxic tumours. The main achievements of the current model were randomised cell positions and the connected vasculature structure between the cells. These developments will also be beneficial when irradiating the simulated tumours using Monte Carlo track structure methods. © 2017 American Association of Physicists in Medicine.

Modeling pN2 through Geological Time: Implications for Planetary Climates and Atmospheric Biosignatures.

PubMed

Stüeken, E E; Kipp, M A; Koehler, M C; Schwieterman, E W; Johnson, B; Buick, R

2016-12-01

Nitrogen is a major nutrient for all life on Earth and could plausibly play a similar role in extraterrestrial biospheres. The major reservoir of nitrogen at Earth's surface is atmospheric N 2 , but recent studies have proposed that the size of this reservoir may have fluctuated significantly over the course of Earth's history with particularly low levels in the Neoarchean-presumably as a result of biological activity. We used a biogeochemical box model to test which conditions are necessary to cause large swings in atmospheric N 2 pressure. Parameters for our model are constrained by observations of modern Earth and reconstructions of biomass burial and oxidative weathering in deep time. A 1-D climate model was used to model potential effects on atmospheric climate. In a second set of tests, we perturbed our box model to investigate which parameters have the greatest impact on the evolution of atmospheric pN 2 and consider possible implications for nitrogen cycling on other planets. Our results suggest that (a) a high rate of biomass burial would have been needed in the Archean to draw down atmospheric pN 2 to less than half modern levels, (b) the resulting effect on temperature could probably have been compensated by increasing solar luminosity and a mild increase in pCO 2 , and (c) atmospheric oxygenation could have initiated a stepwise pN 2 rebound through oxidative weathering. In general, life appears to be necessary for significant atmospheric pN 2 swings on Earth-like planets. Our results further support the idea that an exoplanetary atmosphere rich in both N 2 and O 2 is a signature of an oxygen-producing biosphere. Key Words: Biosignatures-Early Earth-Planetary atmospheres. Astrobiology 16, 949-963.

Finding optimal vaccination strategies under parameter uncertainty using stochastic programming.

PubMed

Tanner, Matthew W; Sattenspiel, Lisa; Ntaimo, Lewis

2008-10-01

We present a stochastic programming framework for finding the optimal vaccination policy for controlling infectious disease epidemics under parameter uncertainty. Stochastic programming is a popular framework for including the effects of parameter uncertainty in a mathematical optimization model. The problem is initially formulated to find the minimum cost vaccination policy under a chance-constraint. The chance-constraint requires that the probability that R(*)

An engineer's view on genetic information and biological evolution.

PubMed

Battail, Gérard

2004-01-01

We develop ideas on genome replication introduced in Battail [Europhys. Lett. 40 (1997) 343]. Starting with the hypothesis that the genome replication process uses error-correcting means, and the auxiliary one that nested codes are used to this end, we first review the concepts of redundancy and error-correcting codes. Then we show that these hypotheses imply that: distinct species exist with a hierarchical taxonomy, there is a trend of evolution towards complexity, and evolution proceeds by discrete jumps. At least the first two features above may be considered as biological facts so, in the absence of direct evidence, they provide an indirect proof in favour of the hypothesized error-correction system. The very high redundancy of genomes makes it possible. In order to explain how it is implemented, we suggest that soft codes and replication decoding, to be briefly described, are plausible candidates. Experimentally proven properties of long-range correlation of the DNA message substantiate this claim.

Minireview: The Roles of Small RNA Pathways in Reproductive Medicine

PubMed Central

Buchold, Gregory M.

2011-01-01

The discovery of small noncoding RNA, including P-element-induced wimpy testis-interacting RNA, small interfering RNA, and microRNA, has energized research in reproductive medicine. In the two decades since the identification of small RNA, first in Caenorhabditis elegans and then in other animals, scientists in many disciplines have made significant progress in elucidating their biology. A powerful battery of tools, including knockout mice and small RNA mimics and antagonists, has facilitated investigation into the functional roles and therapeutic potential of these small RNA pathways. Current data indicate that small RNA play significant roles in normal development and physiology and pathological conditions of the reproductive tracts of females and males. Biologically plausible mRNA targets for these microRNA are aggressively being discovered. The next phase of research will focus on elucidating the clinical utility of small RNA-selective agonists and antagonists. PMID:21546411

Update on zinc biology.

PubMed

Solomons, Noel W

2013-01-01

Zinc has become a prominent nutrient of clinical and public health interest in the new millennium. Functions and actions for zinc emerge as increasingly ubiquitous in mammalian anatomy, physiology and metabolism. There is undoubtedly an underpinning in fundamental biology for all of the aspects of zinc in human health (clinical and epidemiological) in pediatric and public health practice. Unfortunately, basic science research may not have achieved a full understanding as yet. As a complement to the applied themes in the companion articles, a selection of recent advances in the domains homeostatic regulation and transport of zinc is presented; they are integrated, in turn, with findings on genetic expression, intracellular signaling, immunity and host defense, and bone growth. The elements include ionic zinc, zinc transporters, metallothioneins, zinc metalloenzymes and zinc finger proteins. In emerging basic research, we find some plausible mechanistic explanations for delayed linear growth with zinc deficiency and increased infectious disease resistance with zinc supplementation. Copyright © 2013 S. Karger AG, Basel.

Male circumcision and HIV infection risk.

PubMed

Krieger, John N

2012-02-01

Male circumcision is being promoted to reduce human immunodeficiency virus type 1 (HIV) infection rates. This review evaluates the scientific evidence suggesting that male circumcision reduces HIV infection risk in high-risk heterosexual populations. We followed the updated International Consultation on Urological Diseases evidence-based medicine recommendations to critically review the scientific evidence on male circumcision and HIV infection risk. Level 1 evidence supports the concept that male circumcision substantially reduces the risk of HIV infection. Three major lines of evidence support this conclusion: biological data suggesting that this concept is plausible, data from observational studies supported by high-quality meta-analyses, and three randomized clinical trials supported by high-quality meta-analyses. The evidence from these biological studies, observational studies, randomized controlled clinical trials, meta-analyses, and cost-effectiveness studies is conclusive. The challenges to implementation of male circumcision as a public health measure in high-risk populations must now be faced.

Harmonic Training and the Formation of Pitch Representation in a Neural Network Model of the Auditory Brain

PubMed Central

Ahmad, Nasir; Higgins, Irina; Walker, Kerry M. M.; Stringer, Simon M.

2016-01-01

Attempting to explain the perceptual qualities of pitch has proven to be, and remains, a difficult problem. The wide range of sounds which elicit pitch and a lack of agreement across neurophysiological studies on how pitch is encoded by the brain have made this attempt more difficult. In describing the potential neural mechanisms by which pitch may be processed, a number of neural networks have been proposed and implemented. However, no unsupervised neural networks with biologically accurate cochlear inputs have yet been demonstrated. This paper proposes a simple system in which pitch representing neurons are produced in a biologically plausible setting. Purely unsupervised regimes of neural network learning are implemented and these prove to be sufficient in identifying the pitch of sounds with a variety of spectral profiles, including sounds with missing fundamental frequencies and iterated rippled noises. PMID:27047368

A new modulated Hebbian learning rule--biologically plausible method for local computation of a principal subspace.

PubMed

Jankovic, Marko; Ogawa, Hidemitsu

2003-08-01

This paper presents one possible implementation of a transformation that performs linear mapping to a lower-dimensional subspace. Principal component subspace will be the one that will be analyzed. Idea implemented in this paper represents generalization of the recently proposed infinity OH neural method for principal component extraction. The calculations in the newly proposed method are performed locally--a feature which is usually considered as desirable from the biological point of view. Comparing to some other wellknown methods, proposed synaptic efficacy learning rule requires less information about the value of the other efficacies to make single efficacy modification. Synaptic efficacies are modified by implementation of Modulated Hebb-type (MH) learning rule. Slightly modified MH algorithm named Modulated Hebb Oja (MHO) algorithm, will be also introduced. Structural similarity of the proposed network with part of the retinal circuit will be presented, too.

Beyond the PhD: Putting the Right Tools in Your Research Toolbox

PubMed Central

Downs, Charles A.; Morrison, Helena W.

2013-01-01

Postdoctoral training is vital to a successful career for nurse researchers with a biological or biobehavioral focus. Such training provides structured time to devote to gaining substantive knowledge, expanding one’s biological-methods repertoire, and writing grants. However, for unknown reasons, relatively few nurses pursue postdoctoral training. A few plausible explanations include a near critical shortage of nursing faculty coupled with an aging population in need of health care, a lack of available mentoring for predoctoral students to pursue postdoctoral training, and the difficulty of navigating the process of finding and choosing the right match for a postdoctoral experience. The purposes of this article are to provide a rationale for choosing postdoctoral training, review common fellowship opportunities, and discuss the process of finding and choosing the right match for postdoctoral training. The authors provide two prospective plans for postdoctoral training and include a plan for staying on track during the postdoctoral experience. PMID:20026452

Beyond the PhD: putting the right tools in your research toolbox.

PubMed

Downs, Charles A; Morrison, Helena W

2011-01-01

Postdoctoral training is vital to a successful career for nurse researchers with a biological or biobehavioral focus. Such training provides structured time to devote to gaining substantive knowledge, expanding one's biological-methods repertoire, and writing grants. However, for unknown reasons, relatively few nurses pursue postdoctoral training. A few plausible explanations include a near critical shortage of nursing faculty coupled with an aging population in need of health care, a lack of available mentoring for predoctoral students to pursue postdoctoral training, and the difficulty of navigating the process of finding and choosing the right match for a postdoctoral experience. The purposes of this article are to provide a rationale for choosing postdoctoral training, review common fellowship opportunities, and discuss the process of finding and choosing the right match for postdoctoral training. The authors provide two prospective plans for postdoctoral training and include a plan for staying on track during the postdoctoral experience.

Bioprecipitation: a feedback cycle linking earth history, ecosystem dynamics and land use through biological ice nucleators in the atmosphere.

PubMed

Morris, Cindy E; Conen, Franz; Alex Huffman, J; Phillips, Vaughan; Pöschl, Ulrich; Sands, David C

2014-02-01

Landscapes influence precipitation via the water vapor and energy fluxes they generate. Biologically active landscapes also generate aerosols containing microorganisms, some being capable of catalyzing ice formation and crystal growth in clouds at temperatures near 0 °C. The resulting precipitation is beneficial for the growth of plants and microorganisms. Mounting evidence from observations and numerical simulations support the plausibility of a bioprecipitation feedback cycle involving vegetated landscapes and the microorganisms they host. Furthermore, the evolutionary history of ice nucleation-active bacteria such as Pseudomonas syringae supports that they have been part of this process on geological time scales since the emergence of land plants. Elucidation of bioprecipitation feedbacks involving landscapes and their microflora could contribute to appraising the impact that modified landscapes have on regional weather and biodiversity, and to avoiding inadvertent, negative consequences of landscape management. © 2013 John Wiley & Sons Ltd.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Seager, S.; Bains, W.; Hu, R.

Biosignature gas detection is one of the ultimate future goals for exoplanet atmosphere studies. We have created a framework for linking biosignature gas detectability to biomass estimates, including atmospheric photochemistry and biological thermodynamics. The new framework is intended to liberate predictive atmosphere models from requiring fixed, Earth-like biosignature gas source fluxes. New biosignature gases can be considered with a check that the biomass estimate is physically plausible. We have validated the models on terrestrial production of NO, H{sub 2}S, CH{sub 4}, CH{sub 3}Cl, and DMS. We have applied the models to propose NH{sub 3} as a biosignature gas on amore » 'cold Haber World', a planet with a N{sub 2}-H{sub 2} atmosphere, and to demonstrate why gases such as CH{sub 3}Cl must have too large of a biomass to be a plausible biosignature gas on planets with Earth or early-Earth-like atmospheres orbiting a Sun-like star. To construct the biomass models, we developed a functional classification of biosignature gases, and found that gases (such as CH{sub 4}, H{sub 2}S, and N{sub 2}O) produced from life that extracts energy from chemical potential energy gradients will always have false positives because geochemistry has the same gases to work with as life does, and gases (such as DMS and CH{sub 3}Cl) produced for secondary metabolic reasons are far less likely to have false positives but because of their highly specialized origin are more likely to be produced in small quantities. The biomass model estimates are valid to one or two orders of magnitude; the goal is an independent approach to testing whether a biosignature gas is plausible rather than a precise quantification of atmospheric biosignature gases and their corresponding biomasses.« less

Reduced graphene oxide as an effective adsorbent for removal of malachite green dye: Plausible adsorption pathways.

PubMed

Gupta, Kanika; Khatri, Om P

2017-09-01

Efficient removal of malachite green (MG) dye from simulated wastewater is demonstrated using high surface area reduced graphene oxide (rGO). The plausible interaction pathways between MG dye and rGO are deduced from nanostructural features (HRTEM) of rGO and spectroscopic analyses (FTIR and Raman). The high surface area (931m 2 ⋅gm -1 ) of rGO, π-π interaction between the aromatic rings of MG dye and graphitic skeleton, and electrostatic interaction of cationic centre of MG dye with π-electron clouds and negatively charged residual oxygen functionalities of rGO collectively facilitate the adsorption of MG dye on the rGO. The rGO displays adsorption capacity as high as 476.2mg⋅g -1 for MG dye. The thermodynamic parameters calculated from the temperature dependent isotherms suggested that the adsorption was a spontaneous and endothermic process. These results promise the potential of high surface area rGO for efficient removal of cationic dyes for wastewater treatment. Copyright © 2017 Elsevier Inc. All rights reserved.

Dynamic causal modelling: a critical review of the biophysical and statistical foundations.

PubMed

Daunizeau, J; David, O; Stephan, K E

2011-09-15

The goal of dynamic causal modelling (DCM) of neuroimaging data is to study experimentally induced changes in functional integration among brain regions. This requires (i) biophysically plausible and physiologically interpretable models of neuronal network dynamics that can predict distributed brain responses to experimental stimuli and (ii) efficient statistical methods for parameter estimation and model comparison. These two key components of DCM have been the focus of more than thirty methodological articles since the seminal work of Friston and colleagues published in 2003. In this paper, we provide a critical review of the current state-of-the-art of DCM. We inspect the properties of DCM in relation to the most common neuroimaging modalities (fMRI and EEG/MEG) and the specificity of inference on neural systems that can be made from these data. We then discuss both the plausibility of the underlying biophysical models and the robustness of the statistical inversion techniques. Finally, we discuss potential extensions of the current DCM framework, such as stochastic DCMs, plastic DCMs and field DCMs. Copyright © 2009 Elsevier Inc. All rights reserved.

The Line-drawing Problem in Disease Definition.

PubMed

Rogers, Wendy A; Walker, Mary Jean

2017-08-01

Biological dysfunction is regarded, in many accounts, as necessary and perhaps sufficient for disease. But although disease is conceptualized as all-or-nothing, biological functions often differ by degree. A tension is created by attempting to use a continuous variable as the basis for a categorical definition, raising questions about how we are to pinpoint the boundary between health and disease. This is the line-drawing problem. In this paper, we show how the line-drawing problem arises within "dysfunction-requiring" accounts of disease, such as those of Christopher Boorse and Jerome Wakefield. We then provide several detailed examples to establish that biological dysfunction cannot provide a boundary. We examine potential ways of resolving the line-drawing problem, either by dropping one of the claims that generates it, or by appealing to additional criteria. We argue that two of these options are plausible, and that each of these can be applied with regard to different diseases. © The Author 2017. Published by Oxford University Press, on behalf of the Journal of Medicine and Philosophy Inc. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Morphology-Controlled Synthesis of Rhodium Nanoparticles for Cancer Phototherapy.

PubMed

Kang, Seounghun; Shin, Woojun; Choi, Myung-Ho; Ahn, Minchul; Kim, Young-Kwan; Kim, Seongchan; Min, Dal-Hee; Jang, Hongje

2018-06-22

Rhodium nanoparticles are promising transition metal nanocatalysts for electrochemical and synthetic organic chemistry applications. However, notwithstanding their potential, to date, Rh nanoparticles have not been utilized for biological applications; there has been no cytotoxicity study of Rh reported in the literature. In this regard, the absence of a facile and controllable synthetic strategy of Rh nanostructures with various sizes and morphologies might be responsible for the lack of progress in this field. Herein, we have developed a synthetic strategy for Rh nanostructures with controllable morphology through an inverse-directional galvanic replacement reaction. Three types of Rh-based nanostructures-nanoshells, nanoframes, and porous nanoplates-were successfully synthesized. A plausible synthetic mechanism based on thermodynamic considerations has also been proposed. The cytotoxicity, surface functionalization, and photothermal therapeutic effect of manufactured Rh nanostructures were systematically investigated to reveal their potential for in vitro and in vivo biological applications. Considering the comparable behavior of porous Rh nanoplates to that of gold nanostructures that are widely used in nanomedicine, the present study introduces Rh-based nanostructures into the field of biological research.

Learning may need only a few bits of synaptic precision

NASA Astrophysics Data System (ADS)

Baldassi, Carlo; Gerace, Federica; Lucibello, Carlo; Saglietti, Luca; Zecchina, Riccardo

2016-05-01

Learning in neural networks poses peculiar challenges when using discretized rather then continuous synaptic states. The choice of discrete synapses is motivated by biological reasoning and experiments, and possibly by hardware implementation considerations as well. In this paper we extend a previous large deviations analysis which unveiled the existence of peculiar dense regions in the space of synaptic states which accounts for the possibility of learning efficiently in networks with binary synapses. We extend the analysis to synapses with multiple states and generally more plausible biological features. The results clearly indicate that the overall qualitative picture is unchanged with respect to the binary case, and very robust to variation of the details of the model. We also provide quantitative results which suggest that the advantages of increasing the synaptic precision (i.e., the number of internal synaptic states) rapidly vanish after the first few bits, and therefore that, for practical applications, only few bits may be needed for near-optimal performance, consistent with recent biological findings. Finally, we demonstrate how the theoretical analysis can be exploited to design efficient algorithmic search strategies.

Parturition dysfunction in obesity: time to target the pathobiology.

PubMed

Carlson, Nicole S; Hernandez, Teri L; Hurt, K Joseph

2015-12-18

Over a third of women of childbearing age in the United States are obese, and during pregnancy they are at increased risk for delayed labor onset and slow labor progress that often results in unplanned cesarean delivery. The biology behind this dysfunctional parturition is not well understood. Studies of obesity-induced changes in parturition physiology may facilitate approaches to optimize labor in obese women. In this review, we summarize known and proposed biologic effects of obesity on labor preparation, contraction/synchronization, and endurance, drawing on both clinical observation and experimental data. We present evidence from human and animal studies of interactions between obesity and parturition signaling in all elements of the birth process, including: delayed cervical ripening, prostaglandin insensitivity, amniotic membrane strengthening, decreased myometrial oxytocin receptor expression, decreased myocyte action potential initiation and contractility, decreased myocyte gap junction formation, and impaired myocyte neutralization of reactive oxygen species. We found convincing clinical data on the effect of obesity on labor initiation and successful delivery, but few studies on the underlying pathobiology. We suggest research opportunities and therapeutic interventions based on plausible biologic mechanisms.

A systematic approach to designing reliable VV optimization methodology: assessment of internal validity of echocardiographic, electrocardiographic and haemodynamic optimization of cardiac resynchronization therapy.

PubMed

Kyriacou, Andreas; Li Kam Wa, Matthew E; Pabari, Punam A; Unsworth, Beth; Baruah, Resham; Willson, Keith; Peters, Nicholas S; Kanagaratnam, Prapa; Hughes, Alun D; Mayet, Jamil; Whinnett, Zachary I; Francis, Darrel P

2013-08-10

In atrial fibrillation (AF), VV optimization of biventricular pacemakers can be examined in isolation. We used this approach to evaluate internal validity of three VV optimization methods by three criteria. Twenty patients (16 men, age 75 ± 7) in AF were optimized, at two paced heart rates, by LVOT VTI (flow), non-invasive arterial pressure, and ECG (minimizing QRS duration). Each optimization method was evaluated for: singularity (unique peak of function), reproducibility of optimum, and biological plausibility of the distribution of optima. The reproducibility (standard deviation of the difference, SDD) of the optimal VV delay was 10 ms for pressure, versus 8 ms (p=ns) for QRS and 34 ms (p<0.01) for flow. Singularity of optimum was 85% for pressure, 63% for ECG and 45% for flow (Chi(2)=10.9, p<0.005). The distribution of pressure optima was biologically plausible, with 80% LV pre-excited (p=0.007). The distributions of ECG (55% LV pre-excitation) and flow (45% LV pre-excitation) optima were no different to random (p=ns). The pressure-derived optimal VV delay is unaffected by the paced rate: SDD between slow and fast heart rate is 9 ms, no different from the reproducibility SDD at both heart rates. Using non-invasive arterial pressure, VV delay optimization by parabolic fitting is achievable with good precision, satisfying all 3 criteria of internal validity. VV optimum is unaffected by heart rate. Neither QRS minimization nor LVOT VTI satisfy all validity criteria, and therefore seem weaker candidate modalities for VV optimization. AF, unlinking interventricular from atrioventricular delay, uniquely exposes resynchronization concepts to experimental scrutiny. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Soy intake and breast cancer risk: an evaluation based on a systematic review of epidemiologic evidence among the Japanese population.

PubMed

Nagata, Chisato; Mizoue, Tetsuya; Tanaka, Keitaro; Tsuji, Ichiro; Tamakoshi, Akiko; Matsuo, Keitaro; Wakai, Kenji; Inoue, Manami; Tsugane, Shoichiro; Sasazuki, Shizuka

2014-03-01

We reviewed epidemiological studies of soy intake and breast cancer among Japanese women. This report is one among a series of articles by our research group, which is evaluating the existing evidence concerning the association between health-related lifestyles and cancer. Original data were obtained from MEDLINE searches using PubMed or from searches of the Ichushi database, complemented with manual searches. Evaluation of associations was based on the strength of evidence and the magnitude of association, together with biological plausibility. Five cohort studies and six case-control studies were identified. Among the cohort studies, two studies observed that total soy intake (in terms of total amounts of soy foods or soy isoflavones) was associated with a moderate (0.5 ≤ relative risk ≤ 0.67 with statistical significance) or strong (relative risk ≤ 0.5 with statistical significance) risk reduction of breast cancer in postmenopausal women. Among the case-control studies, two studies reported a weak (0.67 ≤ odds ratio ≤ 1.5 with statistical significance or 0.5 ≤ odds ratio ≤ 0.67 without statistical significance) inverse association between total soy intake and the risk of breast cancer. In the former, this association was observed in all women combined-premenopausal and postmenopausal women-but in the latter, the association was confined to postmenopausal women. The associations of intakes of individual soy foods with the risk of breast cancer were generally null. There is some evidence that supports the biological plausibility of a protective effect of isoflavones on breast cancer risk. We conclude that soy intake possibly decreases the risk of breast cancer among Japanese women.

Cause of Cambrian Explosion - Terrestrial or Cosmic?

PubMed

Steele, Edward J; Al-Mufti, Shirwan; Augustyn, Kenneth A; Chandrajith, Rohana; Coghlan, John P; Coulson, S G; Ghosh, Sudipto; Gillman, Mark; Gorczynski, Reginald M; Klyce, Brig; Louis, Godfrey; Mahanama, Kithsiri; Oliver, Keith R; Padron, Julio; Qu, Jiangwen; Schuster, John A; Smith, W E; Snyder, Duane P; Steele, Julian A; Stewart, Brent J; Temple, Robert; Tokoro, Gensuke; Tout, Christopher A; Unzicker, Alexander; Wainwright, Milton; Wallis, Jamie; Wallis, Daryl H; Wallis, Max K; Wetherall, John; Wickramasinghe, D T; Wickramasinghe, J T; Wickramasinghe, N Chandra; Liu, Yongsheng

2018-08-01

We review the salient evidence consistent with or predicted by the Hoyle-Wickramasinghe (H-W) thesis of Cometary (Cosmic) Biology. Much of this physical and biological evidence is multifactorial. One particular focus are the recent studies which date the emergence of the complex retroviruses of vertebrate lines at or just before the Cambrian Explosion of ∼500 Ma. Such viruses are known to be plausibly associated with major evolutionary genomic processes. We believe this coincidence is not fortuitous but is consistent with a key prediction of H-W theory whereby major extinction-diversification evolutionary boundaries coincide with virus-bearing cometary-bolide bombardment events. A second focus is the remarkable evolution of intelligent complexity (Cephalopods) culminating in the emergence of the Octopus. A third focus concerns the micro-organism fossil evidence contained within meteorites as well as the detection in the upper atmosphere of apparent incoming life-bearing particles from space. In our view the totality of the multifactorial data and critical analyses assembled by Fred Hoyle, Chandra Wickramasinghe and their many colleagues since the 1960s leads to a very plausible conclusion - life may have been seeded here on Earth by life-bearing comets as soon as conditions on Earth allowed it to flourish (about or just before 4.1 Billion years ago); and living organisms such as space-resistant and space-hardy bacteria, viruses, more complex eukaryotic cells, fertilised ova and seeds have been continuously delivered ever since to Earth so being one important driver of further terrestrial evolution which has resulted in considerable genetic diversity and which has led to the emergence of mankind. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Context-Dependent Modulation of Functional Connectivity: Secondary Somatosensory Cortex to Prefrontal Cortex Connections in Two-Stimulus-Interval Discrimination Tasks

PubMed Central

Chow, Stephanie S.; Romo, Ranulfo; Brody, Carlos D.

2010-01-01

In a complex world, a sensory cue may prompt different actions in different contexts. A laboratory example of context-dependent sensory processing is the two-stimulus-interval discrimination task. In each trial, a first stimulus (f1) must be stored in short-term memory and later compared with a second stimulus (f2), for the animal to come to a binary decision. Prefrontal cortex (PFC) neurons need to interpret the f1 information in one way (perhaps with a positive weight) and the f2 information in an opposite way (perhaps with a negative weight), although they come from the very same secondary somatosensory cortex (S2) neurons; therefore, a functional sign inversion is required. This task thus provides a clear example of context-dependent processing. Here we develop a biologically plausible model of a context-dependent signal transformation of the stimulus encoding from S2 to PFC. To ground our model in experimental neurophysiology, we use neurophysiological data recorded by R. Romo’s laboratory from both cortical area S2 and PFC in monkeys performing the task. Our main goal is to use experimentally observed context-dependent modulations of firing rates in cortical area S2 as the basis for a model that achieves a context-dependent inversion of the sign of S2 to PFC connections. This is done without requiring any changes in connectivity (Salinas, 2004b). We (1) characterize the experimentally observed context-dependent firing rate modulation in area S2, (2) construct a model that results in the sign transformation, and (3) characterize the robustness and consequent biological plausibility of the model. PMID:19494146

Occupational exposure to trichloroethylene is associated with a decline in lymphocyte subsets and soluble CD27 and CD30 markers

PubMed Central

Lan, Qing; Zhang, Luoping; Tang, Xiaojiang; Shen, Min; Smith, Martyn T.; Qiu, Chuangyi; Ge, Yichen; Ji, Zhiying; Xiong, Jun; He, Jian; Reiss, Boris; Hao, Zhenyue; Liu, Songwang; Xie, Yuxuan; Guo, Weihong; Purdue, Mark P.; Galvan, Noe; Xin, Kerry X.; Hu, Wei; Beane Freeman, Laura E.; Blair, Aaron E.; Li, Laiyu; Rothman, Nathaniel; Vermeulen, Roel; Huang, Hanlin

2010-01-01

Occupational cohort and case–control studies suggest that trichloroethylene (TCE) exposure may be associated with non-Hodgkin lymphoma (NHL) but findings are not consistent. There is a need for mechanistic studies to evaluate the biologic plausibility of this association. We carried out a cross-sectional molecular epidemiology study of 80 healthy workers that used TCE and 96 comparable unexposed controls in Guangdong, China. Personal exposure measurements were taken over a three-week period before blood collection. Ninety-six percent of workers were exposed to TCE below the current US Occupational Safety and Health Administration Permissible Exposure Limit (100 p.p.m. 8 h time-weighted average), with a mean (SD) of 22.2 (36.0) p.p.m. The total lymphocyte count and each of the major lymphocyte subsets including CD4+ T cells, CD8+ T cells, natural killer (NK) cells and B cells were significantly decreased among the TCE-exposed workers compared with controls (P < 0.05), with evidence of a dose-dependent decline. Further, there was a striking 61% decline in sCD27 plasma level and a 34% decline in sCD30 plasma level among TCE-exposed workers compared with controls. This is the first report that TCE exposure under the current Occupational Safety and Health Administration workplace standard is associated with a decline in all major lymphocyte subsets and sCD27 and sCD30, which play an important role in regulating cellular activity in subsets of T, B and NK cells and are associated with lymphocyte activation. Given that altered immunity is an established risk factor for NHL, these results add to the biologic plausibility that TCE is a possible lymphomagen. PMID:20530238

A consistent framework to predict mass fluxes and depletion times for DNAPL contaminations in heterogeneous aquifers under uncertainty

NASA Astrophysics Data System (ADS)

Koch, Jonas; Nowak, Wolfgang

2013-04-01

At many hazardous waste sites and accidental spills, dense non-aqueous phase liquids (DNAPLs) such as TCE, PCE, or TCA have been released into the subsurface. Once a DNAPL is released into the subsurface, it serves as persistent source of dissolved-phase contamination. In chronological order, the DNAPL migrates through the porous medium and penetrates the aquifer, it forms a complex pattern of immobile DNAPL saturation, it dissolves into the groundwater and forms a contaminant plume, and it slowly depletes and bio-degrades in the long-term. In industrial countries the number of such contaminated sites is tremendously high to the point that a ranking from most risky to least risky is advisable. Such a ranking helps to decide whether a site needs to be remediated or may be left to natural attenuation. Both the ranking and the designing of proper remediation or monitoring strategies require a good understanding of the relevant physical processes and their inherent uncertainty. To this end, we conceptualize a probabilistic simulation framework that estimates probability density functions of mass discharge, source depletion time, and critical concentration values at crucial target locations. Furthermore, it supports the inference of contaminant source architectures from arbitrary site data. As an essential novelty, the mutual dependencies of the key parameters and interacting physical processes are taken into account throughout the whole simulation. In an uncertain and heterogeneous subsurface setting, we identify three key parameter fields: the local velocities, the hydraulic permeabilities and the DNAPL phase saturations. Obviously, these parameters depend on each other during DNAPL infiltration, dissolution and depletion. In order to highlight the importance of these mutual dependencies and interactions, we present results of several model set ups where we vary the physical and stochastic dependencies of the input parameters and simulated processes. Under these changes, the probability density functions demonstrate strong statistical shifts in their expected values and in their uncertainty. Considering the uncertainties of all key parameters but neglecting their interactions overestimates the output uncertainty. However, consistently using all available physical knowledge when assigning input parameters and simulating all relevant interactions of the involved processes reduces the output uncertainty significantly back down to useful and plausible ranges. When using our framework in an inverse setting, omitting a parameter dependency within a crucial physical process would lead to physical meaningless identified parameters. Thus, we conclude that the additional complexity we propose is both necessary and adequate. Overall, our framework provides a tool for reliable and plausible prediction, risk assessment, and model based decision support for DNAPL contaminated sites.

Perception of Biological Motion in Schizophrenia and Healthy Individuals: A Behavioral and fMRI Study

PubMed Central

Kim, Jejoong; Park, Sohee; Blake, Randolph

2011-01-01

Background Anomalous visual perception is a common feature of schizophrenia plausibly associated with impaired social cognition that, in turn, could affect social behavior. Past research suggests impairment in biological motion perception in schizophrenia. Behavioral and functional magnetic resonance imaging (fMRI) experiments were conducted to verify the existence of this impairment, to clarify its perceptual basis, and to identify accompanying neural concomitants of those deficits. Methodology/Findings In Experiment 1, we measured ability to detect biological motion portrayed by point-light animations embedded within masking noise. Experiment 2 measured discrimination accuracy for pairs of point-light biological motion sequences differing in the degree of perturbation of the kinematics portrayed in those sequences. Experiment 3 measured BOLD signals using event-related fMRI during a biological motion categorization task. Compared to healthy individuals, schizophrenia patients performed significantly worse on both the detection (Experiment 1) and discrimination (Experiment 2) tasks. Consistent with the behavioral results, the fMRI study revealed that healthy individuals exhibited strong activation to biological motion, but not to scrambled motion in the posterior portion of the superior temporal sulcus (STSp). Interestingly, strong STSp activation was also observed for scrambled or partially scrambled motion when the healthy participants perceived it as normal biological motion. On the other hand, STSp activation in schizophrenia patients was not selective to biological or scrambled motion. Conclusion Schizophrenia is accompanied by difficulties discriminating biological from non-biological motion, and associated with those difficulties are altered patterns of neural responses within brain area STSp. The perceptual deficits exhibited by schizophrenia patients may be an exaggerated manifestation of neural events within STSp associated with perceptual errors made by healthy observers on these same tasks. The present findings fit within the context of theories of delusion involving perceptual and cognitive processes. PMID:21625492

SBML-PET: a Systems Biology Markup Language-based parameter estimation tool.

PubMed

Zi, Zhike; Klipp, Edda

2006-11-01

The estimation of model parameters from experimental data remains a bottleneck for a major breakthrough in systems biology. We present a Systems Biology Markup Language (SBML) based Parameter Estimation Tool (SBML-PET). The tool is designed to enable parameter estimation for biological models including signaling pathways, gene regulation networks and metabolic pathways. SBML-PET supports import and export of the models in the SBML format. It can estimate the parameters by fitting a variety of experimental data from different experimental conditions. SBML-PET has a unique feature of supporting event definition in the SMBL model. SBML models can also be simulated in SBML-PET. Stochastic Ranking Evolution Strategy (SRES) is incorporated in SBML-PET for parameter estimation jobs. A classic ODE Solver called ODEPACK is used to solve the Ordinary Differential Equation (ODE) system. http://sysbio.molgen.mpg.de/SBML-PET/. The website also contains detailed documentation for SBML-PET.

Precise-spike-driven synaptic plasticity: learning hetero-association of spatiotemporal spike patterns.

PubMed

Yu, Qiang; Tang, Huajin; Tan, Kay Chen; Li, Haizhou

2013-01-01

A new learning rule (Precise-Spike-Driven (PSD) Synaptic Plasticity) is proposed for processing and memorizing spatiotemporal patterns. PSD is a supervised learning rule that is analytically derived from the traditional Widrow-Hoff rule and can be used to train neurons to associate an input spatiotemporal spike pattern with a desired spike train. Synaptic adaptation is driven by the error between the desired and the actual output spikes, with positive errors causing long-term potentiation and negative errors causing long-term depression. The amount of modification is proportional to an eligibility trace that is triggered by afferent spikes. The PSD rule is both computationally efficient and biologically plausible. The properties of this learning rule are investigated extensively through experimental simulations, including its learning performance, its generality to different neuron models, its robustness against noisy conditions, its memory capacity, and the effects of its learning parameters. Experimental results show that the PSD rule is capable of spatiotemporal pattern classification, and can even outperform a well studied benchmark algorithm with the proposed relative confidence criterion. The PSD rule is further validated on a practical example of an optical character recognition problem. The results again show that it can achieve a good recognition performance with a proper encoding. Finally, a detailed discussion is provided about the PSD rule and several related algorithms including tempotron, SPAN, Chronotron and ReSuMe.

Precise-Spike-Driven Synaptic Plasticity: Learning Hetero-Association of Spatiotemporal Spike Patterns

PubMed Central

Yu, Qiang; Tang, Huajin; Tan, Kay Chen; Li, Haizhou

2013-01-01

A new learning rule (Precise-Spike-Driven (PSD) Synaptic Plasticity) is proposed for processing and memorizing spatiotemporal patterns. PSD is a supervised learning rule that is analytically derived from the traditional Widrow-Hoff rule and can be used to train neurons to associate an input spatiotemporal spike pattern with a desired spike train. Synaptic adaptation is driven by the error between the desired and the actual output spikes, with positive errors causing long-term potentiation and negative errors causing long-term depression. The amount of modification is proportional to an eligibility trace that is triggered by afferent spikes. The PSD rule is both computationally efficient and biologically plausible. The properties of this learning rule are investigated extensively through experimental simulations, including its learning performance, its generality to different neuron models, its robustness against noisy conditions, its memory capacity, and the effects of its learning parameters. Experimental results show that the PSD rule is capable of spatiotemporal pattern classification, and can even outperform a well studied benchmark algorithm with the proposed relative confidence criterion. The PSD rule is further validated on a practical example of an optical character recognition problem. The results again show that it can achieve a good recognition performance with a proper encoding. Finally, a detailed discussion is provided about the PSD rule and several related algorithms including tempotron, SPAN, Chronotron and ReSuMe. PMID:24223789

Do Daughters Really Cause Divorce? Stress, Pregnancy, and Family Composition

PubMed Central

Hamoudi, Amar; Nobles, Jenna

2014-01-01

Provocative studies have reported that in the United States, marriages producing firstborn daughters are more likely to divorce than those producing firstborn sons. The findings have been interpreted as contemporary evidence of fathers' son preference. Our study explores the potential role of another set of dynamics that may drive these patterns: namely, selection into live birth. Epidemiological evidence indicates that the characteristic female survival advantage may begin before birth. If stress accompanying unstable marriages has biological effects on fecundity, a female survival advantage could generate an association between stability and the sex composition of offspring. Combining regression and simulation techniques to analyze real-world data, we ask, How much of the observed association between sex of the firstborn child and risk of divorce could plausibly be accounted for by the joint effects of female survival advantage and reduced fecundity associated with unstable marriage? Using data from the National Longitudinal Survey of Youth (NLSY79), we find that relationship conflict predicts the sex of children born after conflict was measured; conflict also predicts subsequent divorce. Conservative specification of parameters linking pregnancy characteristics, selection into live birth, and divorce are sufficient to generate a selection-driven association between offspring sex and divorce, which is consequential in magnitude. Our findings illustrate the value of demographic accounting of processes which occur before birth—a period when many outcomes of central interest in the population sciences begin to take shape. PMID:25024115

Do daughters really cause divorce? Stress, pregnancy, and family composition.

PubMed

Hamoudi, Amar; Nobles, Jenna

2014-08-01

Provocative studies have reported that in the United States, marriages producing firstborn daughters are more likely to divorce than those producing firstborn sons. The findings have been interpreted as contemporary evidence of fathers' son preference. Our study explores the potential role of another set of dynamics that may drive these patterns: namely, selection into live birth. Epidemiological evidence indicates that the characteristic female survival advantage may begin before birth. If stress accompanying unstable marriages has biological effects on fecundity, a female survival advantage could generate an association between stability and the sex composition of offspring. Combining regression and simulation techniques to analyze real-world data, we ask, How much of the observed association between sex of the firstborn child and risk of divorce could plausibly be accounted for by the joint effects of female survival advantage and reduced fecundity associated with unstable marriage? Using data from the National Longitudinal Survey of Youth (NLSY79), we find that relationship conflict predicts the sex of children born after conflict was measured; conflict also predicts subsequent divorce. Conservative specification of parameters linking pregnancy characteristics, selection into live birth, and divorce are sufficient to generate a selection-driven association between offspring sex and divorce, which is consequential in magnitude. Our findings illustrate the value of demographic accounting of processes which occur before birth-a period when many outcomes of central interest in the population sciences begin to take shape.

Pilgrims sailing the Titanic: plausibility effects on memory for misinformation.

PubMed

Hinze, Scott R; Slaten, Daniel G; Horton, William S; Jenkins, Ryan; Rapp, David N

2014-02-01

People rely on information they read even when it is inaccurate (Marsh, Meade, & Roediger, Journal of Memory and Language 49:519-536, 2003), but how ubiquitous is this phenomenon? In two experiments, we investigated whether this tendency to encode and rely on inaccuracies from text might be influenced by the plausibility of misinformation. In Experiment 1, we presented stories containing inaccurate plausible statements (e.g., "The Pilgrims' ship was the Godspeed"), inaccurate implausible statements (e.g., . . . the Titanic), or accurate statements (e.g., . . . the Mayflower). On a subsequent test of general knowledge, participants relied significantly less on implausible than on plausible inaccuracies from the texts but continued to rely on accurate information. In Experiment 2, we replicated these results with the addition of a think-aloud procedure to elicit information about readers' noticing and evaluative processes for plausible and implausible misinformation. Participants indicated more skepticism and less acceptance of implausible than of plausible inaccuracies. In contrast, they often failed to notice, completely ignored, and at times even explicitly accepted the misinformation provided by plausible lures. These results offer insight into the conditions under which reliance on inaccurate information occurs and suggest potential mechanisms that may underlie reported misinformation effects.

The Utility of Cognitive Plausibility in Language Acquisition Modeling: Evidence From Word Segmentation.

PubMed

Phillips, Lawrence; Pearl, Lisa

2015-11-01

The informativity of a computational model of language acquisition is directly related to how closely it approximates the actual acquisition task, sometimes referred to as the model's cognitive plausibility. We suggest that though every computational model necessarily idealizes the modeled task, an informative language acquisition model can aim to be cognitively plausible in multiple ways. We discuss these cognitive plausibility checkpoints generally and then apply them to a case study in word segmentation, investigating a promising Bayesian segmentation strategy. We incorporate cognitive plausibility by using an age-appropriate unit of perceptual representation, evaluating the model output in terms of its utility, and incorporating cognitive constraints into the inference process. Our more cognitively plausible model shows a beneficial effect of cognitive constraints on segmentation performance. One interpretation of this effect is as a synergy between the naive theories of language structure that infants may have and the cognitive constraints that limit the fidelity of their inference processes, where less accurate inference approximations are better when the underlying assumptions about how words are generated are less accurate. More generally, these results highlight the utility of incorporating cognitive plausibility more fully into computational models of language acquisition. Copyright © 2015 Cognitive Science Society, Inc.

Exploring the dynamics of balance data — movement variability in terms of drift and diffusion

NASA Astrophysics Data System (ADS)

Gottschall, Julia; Peinke, Joachim; Lippens, Volker; Nagel, Volker

2009-02-01

We introduce a method to analyze postural control on a balance board by reconstructing the underlying dynamics in terms of a Langevin model. Drift and diffusion coefficients are directly estimated from the data and fitted by a suitable parametrization. The governing parameters are utilized to evaluate balance performance and the impact of supra-postural tasks on it. We show that the proposed method of analysis gives not only self-consistent results but also provides a plausible model for the reconstruction of balance dynamics.

Defining time crystals via representation theory

NASA Astrophysics Data System (ADS)

Khemani, Vedika; von Keyserlingk, C. W.; Sondhi, S. L.

2017-09-01

Time crystals are proposed states of matter which spontaneously break time translation symmetry. There is no settled definition of such states. We offer a new definition which follows the traditional recipe for Wigner symmetries and order parameters. Supplementing our definition with a few plausible assumptions we find that a) systems with time-independent Hamiltonians should not exhibit time translation symmetry breaking while b) the recently studied π spin glass/Floquet time crystal can be viewed as breaking a global internal symmetry and as breaking time translation symmetry, as befits its two names.

Gaussian Mixture Model of Heart Rate Variability

PubMed Central

Costa, Tommaso; Boccignone, Giuseppe; Ferraro, Mario

2012-01-01

Heart rate variability (HRV) is an important measure of sympathetic and parasympathetic functions of the autonomic nervous system and a key indicator of cardiovascular condition. This paper proposes a novel method to investigate HRV, namely by modelling it as a linear combination of Gaussians. Results show that three Gaussians are enough to describe the stationary statistics of heart variability and to provide a straightforward interpretation of the HRV power spectrum. Comparisons have been made also with synthetic data generated from different physiologically based models showing the plausibility of the Gaussian mixture parameters. PMID:22666386

On the costs of self-interested economic behavior: how does stinginess get under the skin?

PubMed

Dunn, Elizabeth W; Ashton-James, Claire E; Hanson, Margaret D; Aknin, Lara B

2010-05-01

The present study examined how financial decisions 'get under the skin'. Participants played an economic game in which they could donate some of their payment to another student. Affect was measured afterward and salivary cortisol was measured before and afterward. Participants who kept more money for themselves reported less positive affect, more negative affect, and more shame. Shame predicted higher levels of post-game cortisol, controlling for pre-game cortisol; stingy economic behavior therefore produced a significant indirect effect on cortisol via shame. Thus, shame and cortisol represent plausible emotional and biological pathways linking everyday decisions with downstream consequences for health.

Essential and Nonessential Micronutrients and Sport

NASA Astrophysics Data System (ADS)

Beavers, Kristen M.; Serra, Monica C.

The purpose of this chapter is to review the role of micronutrients in sport. Attention is given to the function of micronutrients in the body, examples of quality dietary sources of each micronutrient, and an assessment of the literature examining how the recommended daily intake of a micronutrient may or may not change with exercise. The discussion includes plausible biological mechanisms of proposed performance enhancement and current research to support or negate these claims. Water-soluble vitamins, fat-soluble vitamins, macrominerals, and select microminerals are discussed in detail, and a comprehensive table reviewing all micronutrients recommendations for the athlete is provided. Practical applications for professionals working with athletes conclude the chapter.

Commentary: Plastic ocean and the cancer connection: 7 questions and answers.

PubMed

Benno Meyer-Rochow, V; Valérie Gross, J; Steffany, Frank; Zeuss, Dominique; Erren, Thomas C

2015-10-01

A plethora of recent scientific reports testifies to challenges the world is facing from an ever-increasing marine plastic pollution. Toxicological concerns have been put forward, but possible links between the now ubiquitous synthetic polymers and human as well as wildlife cancers remain to be investigated. Hence, this commentary which addresses seven questions. Given numerous uncertainties on the factual impacts of plastics, we should embark on empirical studies into the validity of biologically plausible links between plastic residues and cancers and concomitantly consider ways to reduce plastics in the world within and around us. Copyright © 2015 Elsevier Inc. All rights reserved.

Exogenous hormone use, reproductive history and risk of adult myeloid leukaemia.

PubMed

Poynter, J N; Fonstad, R; Blair, C K; Roesler, M; Cerhan, J R; Hirsch, B; Nguyen, P; Ross, J A

2013-10-01

A hormonal aetiology is one explanation for the lower incidence of myeloid leukaemia in women compared with men. In this population-based case-control study, we evaluated associations between exogenous hormone use and reproductive history and myeloid leukaemia, overall and by disease subtype. We observed a suggestive association between oral contraceptive use and acute myeloid leukaemia (odds ratio=0.55, 95% confidence interval=0.32-0.96). Hormone replacement therapy and reproductive factors were not associated with risk. Despite the biological plausibility for a role of oestrogen in leukaemogenesis, other aetiologic factors are likely to explain the differing incidence rates in males and females.

Genetic changes associated with testicular cancer susceptibility.

PubMed

Pyle, Louise C; Nathanson, Katherine L

2016-10-01

Testicular germ cell tumor (TGCT) is a highly heritable cancer primarily affecting young white men. Genome-wide association studies (GWAS) have been particularly effective in identifying multiple common variants with strong contribution to TGCT risk. These loci identified through association studies have implicated multiple genes as associated with TGCT predisposition, many of which are unique among cancer types, and regulate processes such as pluripotency, sex specification, and microtubule assembly. Together these biologically plausible genes converge on pathways involved in male germ cell development and maturation, and suggest that perturbation of them confers susceptibility to TGCT, as a developmental defect of germ cell differentiation. Copyright © 2016 Elsevier Inc. All rights reserved.

Down syndrome, RASopathies, and other rare syndromes.

PubMed

Kratz, Christian P; Izraeli, Shai

2017-04-01

In this article we discuss the occurrence of myeloid neoplasms in patients with a range of syndromes that are due to germline defects of the RAS signaling pathway and in patients with trisomy 21. Both RAS mutations and trisomy 21 are common somatic events contributing to leukemogenis. Thus, the increased leukemia risk observed in children affected by these conditions is biologically highly plausible. Children with myeloid neoplasms in the context of these syndromes require different treatments than children with sporadic myeloid neoplasms and provide an opportunity to study the role of trisomy 21 and RAS signaling during leukemogenesis and development. Copyright © 2017 Elsevier Inc. All rights reserved.

EBV and Autoimmunity.

PubMed

Ascherio, Alberto; Munger, Kassandra L

2015-01-01

Although a role of EBV in autoimmunity is biologically plausible and evidence of altered immune responses to EBV is abundant in several autoimmune diseases, inference on causality requires the determination that disease risk is higher in individuals infected with EBV than in those uninfected and that in the latter it increases following EBV infection. This determination has so far been possible only for multiple sclerosis (MS) and, to some extent, for systemic lupus erythematosus (SLE), whereas evidence is either lacking or not supportive for other autoimmune conditions. In this chapter, we present the main epidemiological findings that justify the conclusion that EBV is a component cause of MS and SLE and possible mechanisms underlying these effects.

Photosynthetic approaches to chemical biotechnology.

PubMed

Desai, Shuchi H; Atsumi, Shota

2013-12-01

National interest and environmental advocates encourage alternatives to petroleum-based products. Besides biofuels, many other valuable chemicals used in every-day life are petroleum derivatives or require petroleum for their production. A plausible alternative to production using petroleum for chemical production is to harvest the abundant carbon dioxide resources in the environment to produce valuable hydrocarbons. Currently, efforts are being made to utilize a natural biological system, photosynthetic microorganisms, to perform this task. Photosynthetic microorganisms are attractive to use for biochemical production because they utilize economical resources for survival: sunlight and carbon dioxide. This review examines the various compounds produced by photosynthetic microorganisms. Copyright © 2013 Elsevier Ltd. All rights reserved.

Evolutionary and preservational constraints on origins of biologic groups: divergence times of eutherian mammals

NASA Technical Reports Server (NTRS)

Foote, M.; Hunter, J. P.; Janis, C. M.; Sepkoski, J. J. Jr

1999-01-01

Some molecular clock estimates of divergence times of taxonomic groups undergoing evolutionary radiation are much older than the groups' first observed fossil record. Mathematical models of branching evolution are used to estimate the maximal rate of fossil preservation consistent with a postulated missing history, given the sum of species durations implied by early origins under a range of species origination and extinction rates. The plausibility of postulated divergence times depends on origination, extinction, and preservation rates estimated from the fossil record. For eutherian mammals, this approach suggests that it is unlikely that many modern orders arose much earlier than their oldest fossil records.

Pathological documentation of complete elimination of Barrett's metaplasia following endoscopic multipolar electrocoagulation therapy

PubMed Central

Fennerty, M; Corless, C; Sheppard, B; Faigel, D; Lieberman, D; Sampliner, R

2001-01-01

The previous paradigm that Barrett's is an irreversible premalignant lesion has recently been challenged by a proliferation of reports documenting elimination of Barrett's by a variety of endoscopic techniques. Whether Barrett's is entirely eliminated is unknown as endoscopic biopsy samples the surface of the epithelium only. Numerous reports document underlying specialised columnar epithelium in many of these trials. Until now there have been no reports of pathological examination of the entire oesophagus as a specimen. This case documents complete elimination of intestinal metaplasia from the oesophagus and supports the biological plausibility of these research techniques.


Keywords: Barrett's oesophagus; endoscopy; multipolar electrocoagulation PMID:11413122

The KUPNetViz: a biological network viewer for multiple -omics datasets in kidney diseases.

PubMed

Moulos, Panagiotis; Klein, Julie; Jupp, Simon; Stevens, Robert; Bascands, Jean-Loup; Schanstra, Joost P

2013-07-24

Constant technological advances have allowed scientists in biology to migrate from conventional single-omics to multi-omics experimental approaches, challenging bioinformatics to bridge this multi-tiered information. Ongoing research in renal biology is no exception. The results of large-scale and/or high throughput experiments, presenting a wealth of information on kidney disease are scattered across the web. To tackle this problem, we recently presented the KUPKB, a multi-omics data repository for renal diseases. In this article, we describe KUPNetViz, a biological graph exploration tool allowing the exploration of KUPKB data through the visualization of biomolecule interactions. KUPNetViz enables the integration of multi-layered experimental data over different species, renal locations and renal diseases to protein-protein interaction networks and allows association with biological functions, biochemical pathways and other functional elements such as miRNAs. KUPNetViz focuses on the simplicity of its usage and the clarity of resulting networks by reducing and/or automating advanced functionalities present in other biological network visualization packages. In addition, it allows the extrapolation of biomolecule interactions across different species, leading to the formulations of new plausible hypotheses, adequate experiment design and to the suggestion of novel biological mechanisms. We demonstrate the value of KUPNetViz by two usage examples: the integration of calreticulin as a key player in a larger interaction network in renal graft rejection and the novel observation of the strong association of interleukin-6 with polycystic kidney disease. The KUPNetViz is an interactive and flexible biological network visualization and exploration tool. It provides renal biologists with biological network snapshots of the complex integrated data of the KUPKB allowing the formulation of new hypotheses in a user friendly manner.

The KUPNetViz: a biological network viewer for multiple -omics datasets in kidney diseases

PubMed Central

2013-01-01

Background Constant technological advances have allowed scientists in biology to migrate from conventional single-omics to multi-omics experimental approaches, challenging bioinformatics to bridge this multi-tiered information. Ongoing research in renal biology is no exception. The results of large-scale and/or high throughput experiments, presenting a wealth of information on kidney disease are scattered across the web. To tackle this problem, we recently presented the KUPKB, a multi-omics data repository for renal diseases. Results In this article, we describe KUPNetViz, a biological graph exploration tool allowing the exploration of KUPKB data through the visualization of biomolecule interactions. KUPNetViz enables the integration of multi-layered experimental data over different species, renal locations and renal diseases to protein-protein interaction networks and allows association with biological functions, biochemical pathways and other functional elements such as miRNAs. KUPNetViz focuses on the simplicity of its usage and the clarity of resulting networks by reducing and/or automating advanced functionalities present in other biological network visualization packages. In addition, it allows the extrapolation of biomolecule interactions across different species, leading to the formulations of new plausible hypotheses, adequate experiment design and to the suggestion of novel biological mechanisms. We demonstrate the value of KUPNetViz by two usage examples: the integration of calreticulin as a key player in a larger interaction network in renal graft rejection and the novel observation of the strong association of interleukin-6 with polycystic kidney disease. Conclusions The KUPNetViz is an interactive and flexible biological network visualization and exploration tool. It provides renal biologists with biological network snapshots of the complex integrated data of the KUPKB allowing the formulation of new hypotheses in a user friendly manner. PMID:23883183

Plausibility Judgments in Conceptual Change and Epistemic Cognition

ERIC Educational Resources Information Center

Lombardi, Doug; Nussbaum, E. Michael; Sinatra, Gale M.

2016-01-01

Plausibility judgments rarely have been addressed empirically in conceptual change research. Recent research, however, suggests that these judgments may be pivotal to conceptual change about certain topics where a gap exists between what scientists and laypersons find plausible. Based on a philosophical and empirical foundation, this article…

Supporting cognition in systems biology analysis: findings on users' processes and design implications.

PubMed

Mirel, Barbara

2009-02-13

Current usability studies of bioinformatics tools suggest that tools for exploratory analysis support some tasks related to finding relationships of interest but not the deep causal insights necessary for formulating plausible and credible hypotheses. To better understand design requirements for gaining these causal insights in systems biology analyses a longitudinal field study of 15 biomedical researchers was conducted. Researchers interacted with the same protein-protein interaction tools to discover possible disease mechanisms for further experimentation. Findings reveal patterns in scientists' exploratory and explanatory analysis and reveal that tools positively supported a number of well-structured query and analysis tasks. But for several of scientists' more complex, higher order ways of knowing and reasoning the tools did not offer adequate support. Results show that for a better fit with scientists' cognition for exploratory analysis systems biology tools need to better match scientists' processes for validating, for making a transition from classification to model-based reasoning, and for engaging in causal mental modelling. As the next great frontier in bioinformatics usability, tool designs for exploratory systems biology analysis need to move beyond the successes already achieved in supporting formulaic query and analysis tasks and now reduce current mismatches with several of scientists' higher order analytical practices. The implications of results for tool designs are discussed.

Hormonal contraceptive use and women's risk of HIV acquisition: priorities emerging from recent data.

PubMed

Ralph, Lauren J; Gollub, Erica L; Jones, Heidi E

2015-12-01

Understanding whether hormonal contraception increases women's risk of HIV acquisition is a public health priority. This review summarizes recent epidemiologic and biologic data, and considers the implications of new evidence on research and programmatic efforts. Two secondary analyses of HIV prevention trials demonstrated increased HIV risk among depot medroxyprogesterone acetate (DMPA) users compared with nonhormonal/no method users and norethisterone enanthate (NET-EN) users. A study of women in serodiscordant partnerships found no significant association for DMPA or implants. Two meta-analyses found elevated risks of HIV among DMPA users compared with nonhormonal/no method users, with no association for NET-EN or combined oral contraceptive pills. In-vitro and animal model studies identified plausible biological mechanisms by which progestin exposure could increase risk of HIV, depending on the type and dose of progestin, but such mechanisms have not been definitively observed in humans. Recent epidemiologic and biologic evidence on hormonal contraception and HIV suggests a harmful profile for DMPA but not combined oral contraceptives. In limited data, NET-EN appears safer than DMPA. More research is needed on other progestin-based methods, especially implants and Sayana Press. Future priorities include updating modeling studies with new pooled estimates, continued basic science to understand biological mechanisms, expanding contraceptive choice, and identifying effective ways to promote dual method use.

Comparative Study on Interaction of Form and Motion Processing Streams by Applying Two Different Classifiers in Mechanism for Recognition of Biological Movement

PubMed Central

2014-01-01

Research on psychophysics, neurophysiology, and functional imaging shows particular representation of biological movements which contains two pathways. The visual perception of biological movements formed through the visual system called dorsal and ventral processing streams. Ventral processing stream is associated with the form information extraction; on the other hand, dorsal processing stream provides motion information. Active basic model (ABM) as hierarchical representation of the human object had revealed novelty in form pathway due to applying Gabor based supervised object recognition method. It creates more biological plausibility along with similarity with original model. Fuzzy inference system is used for motion pattern information in motion pathway creating more robustness in recognition process. Besides, interaction of these paths is intriguing and many studies in various fields considered it. Here, the interaction of the pathways to get more appropriated results has been investigated. Extreme learning machine (ELM) has been implied for classification unit of this model, due to having the main properties of artificial neural networks, but crosses from the difficulty of training time substantially diminished in it. Here, there will be a comparison between two different configurations, interactions using synergetic neural network and ELM, in terms of accuracy and compatibility. PMID:25276860

Applying Aggregate Exposure Pathway and Adverse Outcome ...

EPA Pesticide Factsheets

Hazard assessment for nanomaterials often involves applying in vitro dose-response data to estimate potential health risks that arise from exposure to products that contain nanomaterials. However, much uncertainty is inherent in relating bioactivities observed in an in vitro system to the perturbations of biological mechanisms that lead to apical adverse health outcomes in living organisms. The Adverse Outcome Pathway (AOP) framework addresses this uncertainty by acting as a scaffold onto which in vitro toxicity testing and other data can be arranged to aid in the interpretation of these results in terms of biologically-relevant responses, as an AOP connects an upstream molecular initiating event (MIE) to a downstream adverse outcome. In addition to hazard assessment, risk estimation also requires reconciling in vitro concentrations sufficient to produce bioactivity with in vivo concentrations that can trigger a MIE at the relevant biological target. Such target site exposures (TSEs) can be estimated by integrating pharmacokinetic considerations with environmental and exposure factors. Environmental and exposure data have been historically scattered in various resources, such as monitoring data for air pollutants or exposure models for specific chemicals. The Aggregate Exposure Pathway (AEP) framework is introduced to organize existing knowledge concerning biologically, chemically, and physically plausible, as well as empirically supported, links between the i

Computational methods using genome-wide association studies to predict radiotherapy complications and to identify correlative molecular processes

NASA Astrophysics Data System (ADS)

Oh, Jung Hun; Kerns, Sarah; Ostrer, Harry; Powell, Simon N.; Rosenstein, Barry; Deasy, Joseph O.

2017-02-01

The biological cause of clinically observed variability of normal tissue damage following radiotherapy is poorly understood. We hypothesized that machine/statistical learning methods using single nucleotide polymorphism (SNP)-based genome-wide association studies (GWAS) would identify groups of patients of differing complication risk, and furthermore could be used to identify key biological sources of variability. We developed a novel learning algorithm, called pre-conditioned random forest regression (PRFR), to construct polygenic risk models using hundreds of SNPs, thereby capturing genomic features that confer small differential risk. Predictive models were trained and validated on a cohort of 368 prostate cancer patients for two post-radiotherapy clinical endpoints: late rectal bleeding and erectile dysfunction. The proposed method results in better predictive performance compared with existing computational methods. Gene ontology enrichment analysis and protein-protein interaction network analysis are used to identify key biological processes and proteins that were plausible based on other published studies. In conclusion, we confirm that novel machine learning methods can produce large predictive models (hundreds of SNPs), yielding clinically useful risk stratification models, as well as identifying important underlying biological processes in the radiation damage and tissue repair process. The methods are generally applicable to GWAS data and are not specific to radiotherapy endpoints.

Exosomes in HIV infection: A review and critical look.

PubMed

Ellwanger, Joel Henrique; Veit, Tiago Degani; Chies, José Artur Bogo

2017-09-01

Exosomes are nanovesicles released into the extracellular medium by different cell types. These vesicles carry a variety of protein and RNA cargos, and have a central role in cellular signaling and regulation. A PubMed search using the term "exosomes" finds 67 articles published in 2006. Ten years later, the same search returns approximately 1200 results for 2016 alone. The growing interest in exosomes within the scientific community reflects the different roles exerted by extracellular vesicles in biological systems and diseases. However, the increase in academic production addressing the biological function of exosomes causes much confusion, especially where the focus is on the role of exosomes in pathological situations. In this review, we critically interpret the current state of the research on exosomes and HIV infection. It is plausible to assume that exosomes influence the pathogenesis of HIV infection through their biological cargo (primarily membrane proteins and microRNAs). On the other hand, evidence for a usurpation of the exosomal budding and trafficking machinery by HIV during infection is limited, although such a mechanism cannot be ruled out. This review also discusses several biological aspects of exosomal function in the immune system. Finally, the limitations of current exosome research are pointed out. Copyright © 2017 Elsevier B.V. All rights reserved.

SBML-PET-MPI: a parallel parameter estimation tool for Systems Biology Markup Language based models.

PubMed

Zi, Zhike

2011-04-01

Parameter estimation is crucial for the modeling and dynamic analysis of biological systems. However, implementing parameter estimation is time consuming and computationally demanding. Here, we introduced a parallel parameter estimation tool for Systems Biology Markup Language (SBML)-based models (SBML-PET-MPI). SBML-PET-MPI allows the user to perform parameter estimation and parameter uncertainty analysis by collectively fitting multiple experimental datasets. The tool is developed and parallelized using the message passing interface (MPI) protocol, which provides good scalability with the number of processors. SBML-PET-MPI is freely available for non-commercial use at http://www.bioss.uni-freiburg.de/cms/sbml-pet-mpi.html or http://sites.google.com/site/sbmlpetmpi/.

Parameter estimation using meta-heuristics in systems biology: a comprehensive review.

PubMed

Sun, Jianyong; Garibaldi, Jonathan M; Hodgman, Charlie

2012-01-01

This paper gives a comprehensive review of the application of meta-heuristics to optimization problems in systems biology, mainly focussing on the parameter estimation problem (also called the inverse problem or model calibration). It is intended for either the system biologist who wishes to learn more about the various optimization techniques available and/or the meta-heuristic optimizer who is interested in applying such techniques to problems in systems biology. First, the parameter estimation problems emerging from different areas of systems biology are described from the point of view of machine learning. Brief descriptions of various meta-heuristics developed for these problems follow, along with outlines of their advantages and disadvantages. Several important issues in applying meta-heuristics to the systems biology modelling problem are addressed, including the reliability and identifiability of model parameters, optimal design of experiments, and so on. Finally, we highlight some possible future research directions in this field.

Source Effects and Plausibility Judgments When Reading about Climate Change

ERIC Educational Resources Information Center

Lombardi, Doug; Seyranian, Viviane; Sinatra, Gale M.

2014-01-01

Gaps between what scientists and laypeople find plausible may act as a barrier to learning complex and/or controversial socioscientific concepts. For example, individuals may consider scientific explanations that human activities are causing current climate change as implausible. This plausibility judgment may be due-in part-to individuals'…

Plausibility and Perspective Influence the Processing of Counterfactual Narratives

ERIC Educational Resources Information Center

Ferguson, Heather J.; Jayes, Lewis T.

2018-01-01

Previous research has established that readers' eye movements are sensitive to the difficulty with which a word is processed. One important factor that influences processing is the fit of a word within the wider context, including its plausibility. Here we explore the influence of plausibility in counterfactual language processing. Counterfactuals…

Association of parameter, software, and hardware variation with large-scale behavior across 57,000 climate models

PubMed Central

Knight, Christopher G.; Knight, Sylvia H. E.; Massey, Neil; Aina, Tolu; Christensen, Carl; Frame, Dave J.; Kettleborough, Jamie A.; Martin, Andrew; Pascoe, Stephen; Sanderson, Ben; Stainforth, David A.; Allen, Myles R.

2007-01-01

In complex spatial models, as used to predict the climate response to greenhouse gas emissions, parameter variation within plausible bounds has major effects on model behavior of interest. Here, we present an unprecedentedly large ensemble of >57,000 climate model runs in which 10 parameters, initial conditions, hardware, and software used to run the model all have been varied. We relate information about the model runs to large-scale model behavior (equilibrium sensitivity of global mean temperature to a doubling of carbon dioxide). We demonstrate that effects of parameter, hardware, and software variation are detectable, complex, and interacting. However, we find most of the effects of parameter variation are caused by a small subset of parameters. Notably, the entrainment coefficient in clouds is associated with 30% of the variation seen in climate sensitivity, although both low and high values can give high climate sensitivity. We demonstrate that the effect of hardware and software is small relative to the effect of parameter variation and, over the wide range of systems tested, may be treated as equivalent to that caused by changes in initial conditions. We discuss the significance of these results in relation to the design and interpretation of climate modeling experiments and large-scale modeling more generally. PMID:17640921

Model fit versus biological relevance: Evaluating photosynthesis-temperature models for three tropical seagrass species

NASA Astrophysics Data System (ADS)

Adams, Matthew P.; Collier, Catherine J.; Uthicke, Sven; Ow, Yan X.; Langlois, Lucas; O'Brien, Katherine R.

2017-01-01

When several models can describe a biological process, the equation that best fits the data is typically considered the best. However, models are most useful when they also possess biologically-meaningful parameters. In particular, model parameters should be stable, physically interpretable, and transferable to other contexts, e.g. for direct indication of system state, or usage in other model types. As an example of implementing these recommended requirements for model parameters, we evaluated twelve published empirical models for temperature-dependent tropical seagrass photosynthesis, based on two criteria: (1) goodness of fit, and (2) how easily biologically-meaningful parameters can be obtained. All models were formulated in terms of parameters characterising the thermal optimum (Topt) for maximum photosynthetic rate (Pmax). These parameters indicate the upper thermal limits of seagrass photosynthetic capacity, and hence can be used to assess the vulnerability of seagrass to temperature change. Our study exemplifies an approach to model selection which optimises the usefulness of empirical models for both modellers and ecologists alike.

Model fit versus biological relevance: Evaluating photosynthesis-temperature models for three tropical seagrass species.

PubMed

Adams, Matthew P; Collier, Catherine J; Uthicke, Sven; Ow, Yan X; Langlois, Lucas; O'Brien, Katherine R

2017-01-04

When several models can describe a biological process, the equation that best fits the data is typically considered the best. However, models are most useful when they also possess biologically-meaningful parameters. In particular, model parameters should be stable, physically interpretable, and transferable to other contexts, e.g. for direct indication of system state, or usage in other model types. As an example of implementing these recommended requirements for model parameters, we evaluated twelve published empirical models for temperature-dependent tropical seagrass photosynthesis, based on two criteria: (1) goodness of fit, and (2) how easily biologically-meaningful parameters can be obtained. All models were formulated in terms of parameters characterising the thermal optimum (T opt ) for maximum photosynthetic rate (P max ). These parameters indicate the upper thermal limits of seagrass photosynthetic capacity, and hence can be used to assess the vulnerability of seagrass to temperature change. Our study exemplifies an approach to model selection which optimises the usefulness of empirical models for both modellers and ecologists alike.

Model fit versus biological relevance: Evaluating photosynthesis-temperature models for three tropical seagrass species

PubMed Central

Adams, Matthew P.; Collier, Catherine J.; Uthicke, Sven; Ow, Yan X.; Langlois, Lucas; O’Brien, Katherine R.

2017-01-01

When several models can describe a biological process, the equation that best fits the data is typically considered the best. However, models are most useful when they also possess biologically-meaningful parameters. In particular, model parameters should be stable, physically interpretable, and transferable to other contexts, e.g. for direct indication of system state, or usage in other model types. As an example of implementing these recommended requirements for model parameters, we evaluated twelve published empirical models for temperature-dependent tropical seagrass photosynthesis, based on two criteria: (1) goodness of fit, and (2) how easily biologically-meaningful parameters can be obtained. All models were formulated in terms of parameters characterising the thermal optimum (Topt) for maximum photosynthetic rate (Pmax). These parameters indicate the upper thermal limits of seagrass photosynthetic capacity, and hence can be used to assess the vulnerability of seagrass to temperature change. Our study exemplifies an approach to model selection which optimises the usefulness of empirical models for both modellers and ecologists alike. PMID:28051123

Retrieving the optical parameters of biological tissues using diffuse reflectance spectroscopy and Fourier series expansions. I. theory and application.

PubMed

Muñoz Morales, Aarón A; Vázquez Y Montiel, Sergio

2012-10-01

The determination of optical parameters of biological tissues is essential for the application of optical techniques in the diagnosis and treatment of diseases. Diffuse Reflection Spectroscopy is a widely used technique to analyze the optical characteristics of biological tissues. In this paper we show that by using diffuse reflectance spectra and a new mathematical model we can retrieve the optical parameters by applying an adjustment of the data with nonlinear least squares. In our model we represent the spectra using a Fourier series expansion finding mathematical relations between the polynomial coefficients and the optical parameters. In this first paper we use spectra generated by the Monte Carlo Multilayered Technique to simulate the propagation of photons in turbid media. Using these spectra we determine the behavior of Fourier series coefficients when varying the optical parameters of the medium under study. With this procedure we find mathematical relations between Fourier series coefficients and optical parameters. Finally, the results show that our method can retrieve the optical parameters of biological tissues with accuracy that is adequate for medical applications.

On the distinguishability of HRF models in fMRI.

PubMed

Rosa, Paulo N; Figueiredo, Patricia; Silvestre, Carlos J

2015-01-01

Modeling the Hemodynamic Response Function (HRF) is a critical step in fMRI studies of brain activity, and it is often desirable to estimate HRF parameters with physiological interpretability. A biophysically informed model of the HRF can be described by a non-linear time-invariant dynamic system. However, the identification of this dynamic system may leave much uncertainty on the exact values of the parameters. Moreover, the high noise levels in the data may hinder the model estimation task. In this context, the estimation of the HRF may be seen as a problem of model falsification or invalidation, where we are interested in distinguishing among a set of eligible models of dynamic systems. Here, we propose a systematic tool to determine the distinguishability among a set of physiologically plausible HRF models. The concept of absolutely input-distinguishable systems is introduced and applied to a biophysically informed HRF model, by exploiting the structure of the underlying non-linear dynamic system. A strategy to model uncertainty in the input time-delay and magnitude is developed and its impact on the distinguishability of two physiologically plausible HRF models is assessed, in terms of the maximum noise amplitude above which it is not possible to guarantee the falsification of one model in relation to another. Finally, a methodology is proposed for the choice of the input sequence, or experimental paradigm, that maximizes the distinguishability of the HRF models under investigation. The proposed approach may be used to evaluate the performance of HRF model estimation techniques from fMRI data.

Assessing Integrated Pest Management Adoption: Measurement Problems and Policy Implications

NASA Astrophysics Data System (ADS)

Puente, Molly; Darnall, Nicole; Forkner, Rebecca E.

2011-11-01

For more than a decade, the U.S. government has promoted integrated pest management (IPM) to advance sustainable agriculture. However, the usefulness of this practice has been questioned because of lagging implementation. There are at least two plausible rationales for the slow implementation: (1) growers are not adopting IPM—for whatever reason—and (2) current assessment methods are inadequate at assessing IPM implementation. Our research addresses the second plausibility. We suggest that the traditional approach to measuring IPM implementation on its own fails to assess the distinct, biologically hierarchical components of IPM, and instead aggregates growers' management practices into an overall adoption score. Knowledge of these distinct components and the extent to which they are implemented can inform government officials as to how they should develop targeted assistance programs to encourage broader IPM use. We address these concerns by assessing the components of IPM adoption and comparing our method to the traditional approach alone. Our results indicate that there are four distinct components of adoption—weed, insect, general, and ecosystem management—and that growers implement the first two components significantly more often than the latter two. These findings suggest that using a more nuanced measure to assess IPM adoption that expands on the traditional approach, allows for a better understanding of the degree of IPM implementation.

From Snow to Hill to ALS: An epidemiological odyssey in search of ALS causation.

PubMed

Armon, Carmel

2018-05-21

Establishing mechanisms of disease causation in neurodegenerative diseases has long seemed to be beyond the pale of traditional epidemiological tools. Establishing a plausible mechanism for initiation of amyotrophic lateral sclerosis (ALS) has appeared a particularly elusive goal. This review shows that a likely mechanism for ALS initiation may be inferred by applying classical methods of epidemiological inference. Advances in characterizing the biology of ALS suggest that most cases of ALS are cortically-generated, part of the ALS-FTD spectrum, with focal onset and spread by contiguity within the motor super-network. Evidence-based methods identified the most credible exogenous risk factor - smoking. AB Hill's nine viewpoints to inferring causation from association were invoked. The most likely mechanism consistent with smoking being a risk factor for ALS was inferred: cumulative DNA damage, akin to cumulative somatic mutations in carcinogenesis. Focal onset supports the concept that these changes, occurring in a single cell, may trigger the cascade leading to clinical ALS. The plausibility of this mechanism was affirmed by its coherence/consistency with other observations in sporadic, familial and western Pacific ALS. Application of traditional epidemiological reasoning suggests that cumulative DNA damage may contribute to disease onset in ALS. Copyright © 2018 Elsevier B.V. All rights reserved.

Compact stars

NASA Astrophysics Data System (ADS)

Estevez-Delgado, Gabino; Estevez-Delgado, Joaquin

2018-05-01

An analysis and construction is presented for a stellar model characterized by two parameters (w, n) associated with the compactness ratio and anisotropy, respectively. The reliability range for the parameter w ≤ 1.97981225149 corresponds with a compactness ratio u ≤ 0.2644959374, the density and pressures are positive, regular and monotonic decrescent functions, the radial and tangential speed of sound are lower than the light speed, moreover, than the plausible stability. The behavior of the speeds of sound are determinate for the anisotropy parameter n, admitting a subinterval where the speeds are monotonic crescent functions and other where we have monotonic decrescent functions for the same speeds, both cases describing a compact object that is also potentially stable. In the bigger value for the observational mass M = 2.05 M⊙ and radii R = 12.957 Km for the star PSR J0348+0432, the model indicates that the maximum central density ρc = 1.283820319 × 1018 Kg/m3 corresponds to the maximum value of the anisotropy parameter and the radial and tangential speed of the sound are monotonic decrescent functions.

Hidden symmetries of the extended Kitaev-Heisenberg model: Implications for the honeycomb-lattice iridates A2IrO3

NASA Astrophysics Data System (ADS)

Chaloupka, Jiří; Khaliullin, Giniyat

2015-07-01

We have explored the hidden symmetries of a generic four-parameter nearest-neighbor spin model, allowed in honeycomb-lattice compounds under trigonal compression. Our method utilizes a systematic algorithm to identify all dual transformations of the model that map the Hamiltonian on itself, changing the parameters and providing exact links between different points in its parameter space. We have found the complete set of points of hidden SU(2) symmetry at which a seemingly highly anisotropic model can be mapped back on the Heisenberg model and inherits therefore its properties such as the presence of gapless Goldstone modes. The procedure used to search for the hidden symmetries is quite general and may be extended to other bond-anisotropic spin models and other lattices, such as the triangular, kagome, hyperhoneycomb, or harmonic-honeycomb lattices. We apply our findings to the honeycomb-lattice iridates Na2IrO3 and Li2IrO3 , and illustrate how they help to identify plausible values of the model parameters that are compatible with the available experimental data.

Semantic and Plausibility Preview Benefit Effects in English: Evidence from Eye Movements

PubMed Central

Schotter, Elizabeth R.; Jia, Annie

2016-01-01

Theories of preview benefit in reading hinge on integration across saccades and the idea that preview benefit is greater the more similar the preview and target are. Schotter (2013) reported preview benefit from a synonymous preview, but it is unclear whether this effect occurs because of similarity between the preview and target (integration), or because of contextual fit of the preview—synonyms satisfy both accounts. Studies in Chinese have found evidence for preview benefit for words that are unrelated to the target, but are contextually plausible (Yang, Li, Wang, Slattery, & Rayner, 2014; Yang, Wang, Tong, & Rayner, 2012), which is incompatible with an integration account but supports a contextual fit account. Here, we used plausible and implausible unrelated previews in addition to plausible synonym, antonym, and identical previews to further investigate these accounts for readers of English. Early reading measures were shorter for all plausible preview conditions compared to the implausible preview condition. In later reading measures, a benefit for the plausible unrelated preview condition was not observed. In a second experiment, we asked questions that probed whether the reader encoded the preview or target. Readers were more likely to report the preview when they had skipped the word and not regressed to it, and when the preview was plausible. Thus, under certain circumstances, the preview word is processed to a high level of representation (i.e., semantic plausibility) regardless of its relationship to the target, but its influence on reading is relatively short-lived, being replaced by the target word, when fixated. PMID:27123754

Understanding Karma Police: The Perceived Plausibility of Noun Compounds as Predicted by Distributional Models of Semantic Representation

PubMed Central

Günther, Fritz; Marelli, Marco

2016-01-01

Noun compounds, consisting of two nouns (the head and the modifier) that are combined into a single concept, differ in terms of their plausibility: school bus is a more plausible compound than saddle olive. The present study investigates which factors influence the plausibility of attested and novel noun compounds. Distributional Semantic Models (DSMs) are used to obtain formal (vector) representations of word meanings, and compositional methods in DSMs are employed to obtain such representations for noun compounds. From these representations, different plausibility measures are computed. Three of those measures contribute in predicting the plausibility of noun compounds: The relatedness between the meaning of the head noun and the compound (Head Proximity), the relatedness between the meaning of modifier noun and the compound (Modifier Proximity), and the similarity between the head noun and the modifier noun (Constituent Similarity). We find non-linear interactions between Head Proximity and Modifier Proximity, as well as between Modifier Proximity and Constituent Similarity. Furthermore, Constituent Similarity interacts non-linearly with the familiarity with the compound. These results suggest that a compound is perceived as more plausible if it can be categorized as an instance of the category denoted by the head noun, if the contribution of the modifier to the compound meaning is clear but not redundant, and if the constituents are sufficiently similar in cases where this contribution is not clear. Furthermore, compounds are perceived to be more plausible if they are more familiar, but mostly for cases where the relation between the constituents is less clear. PMID:27732599

Making More Plausible What is Hard To Believe: Historical Justifications and Illustrations of Newton's Third Law.

ERIC Educational Resources Information Center

Gauld, Colin

1998-01-01

Reports that many students do not believe Newton's law of action and reaction and suggests ways in which its plausibility might be enhanced. Reviews how this law has been made more plausible over time by Newton and those who succeeded him. Contains 25 references. (DDR)

Plausibility Reappraisals and Shifts in Middle School Students' Climate Change Conceptions

ERIC Educational Resources Information Center

Lombardi, Doug; Sinatra, Gale M.; Nussbaum, E. Michael

2013-01-01

Plausibility is a central but under-examined topic in conceptual change research. Climate change is an important socio-scientific topic; however, many view human-induced climate change as implausible. When learning about climate change, students need to make plausibility judgments but they may not be sufficiently critical or reflective. The…

A Method of Q-Matrix Validation for the Linear Logistic Test Model

PubMed Central

Baghaei, Purya; Hohensinn, Christine

2017-01-01

The linear logistic test model (LLTM) is a well-recognized psychometric model for examining the components of difficulty in cognitive tests and validating construct theories. The plausibility of the construct model, summarized in a matrix of weights, known as the Q-matrix or weight matrix, is tested by (1) comparing the fit of LLTM with the fit of the Rasch model (RM) using the likelihood ratio (LR) test and (2) by examining the correlation between the Rasch model item parameters and LLTM reconstructed item parameters. The problem with the LR test is that it is almost always significant and, consequently, LLTM is rejected. The drawback of examining the correlation coefficient is that there is no cut-off value or lower bound for the magnitude of the correlation coefficient. In this article we suggest a simulation method to set a minimum benchmark for the correlation between item parameters from the Rasch model and those reconstructed by the LLTM. If the cognitive model is valid then the correlation coefficient between the RM-based item parameters and the LLTM-reconstructed item parameters derived from the theoretical weight matrix should be greater than those derived from the simulated matrices. PMID:28611721

Scale-dependent CMB power asymmetry from primordial speed of sound and a generalized δ N formalism

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Dong-Gang; Cai, Yi-Fu; Zhao, Wen

2016-02-01

We explore a plausible mechanism that the hemispherical power asymmetry in the CMB is produced by the spatial variation of the primordial sound speed parameter. We suggest that in a generalized approach of the δ N formalism the local e-folding number may depend on some other primordial parameters besides the initial values of inflaton. Here the δ N formalism is extended by considering the effects of a spatially varying sound speed parameter caused by a super-Hubble perturbation of a light field. Using this generalized δ N formalism, we systematically calculate the asymmetric primordial spectrum in the model of multi-speed inflation by taking intomore » account the constraints of primordial non-Gaussianities. We further discuss specific model constraints, and the corresponding asymmetry amplitudes are found to be scale-dependent, which can accommodate current observations of the power asymmetry at different length scales.« less

Fast pyrolysis kinetics of alkali lignin: Evaluation of apparent rate parameters and product time evolution.

PubMed

Ojha, Deepak Kumar; Viju, Daniel; Vinu, R

2017-10-01

In this study, the apparent kinetics of fast pyrolysis of alkali lignin was evaluated by obtaining isothermal mass loss data in the timescale of 2-30s at 400-700°C in an analytical pyrolyzer. The data were analyzed using different reaction models to determine the rate constants and apparent rate parameters. First order and one dimensional diffusion models resulted in good fits with experimental data with apparent activation energy of 23kJmol -1 . Kinetic compensation effect was established using a large number of kinetic parameters reported in the literature for pyrolysis of different lignins. The time evolution of the major functional groups in the pyrolysate was analyzed using in situ Fourier transform infrared spectroscopy. Maximum production of the volatiles occurred around 10-12s. A clear transformation of guaiacols to phenol, catechol and their derivatives, and aromatic hydrocarbons was observed with increasing temperature. The plausible reaction steps involved in various transformations are discussed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Electrochemical impedance spectroscopy of lithium-titanium disulfide rechargeable cells

NASA Technical Reports Server (NTRS)

Narayanan, S. R.; Shen, D. H.; Surampudi, S.; Attia, A. I.; Halpert, G.

1993-01-01

The two-terminal alternating current impedance of Li/TiS2 rechargeable cells was studied as a function of frequency, state-of-charge, and extended cycling. Analysis based on a plausible equivalent circuit model for the Li/TiS2 cell leads to evaluation of kinetic parameters for the various physicochemical processes occurring at the electrode/electrolyte interfaces. To investigate the causes of cell degradation during extended cycling, the parameters evaluated for cells cycled 5 times were compared with the parameters of cells cycled over 600 times. The findings are that the combined ohmic resistance of the electrolyte and electrodes suffers a tenfold increase after extended cycling, while the charge-transfer resistance and diffusional impedance at the TiS2/electrolyte interface are not significantIy affected. The results reflect the morphological change and increase in area of the anode due to cycling. The study also shows that overdischarge of a cathode-limited cell causes a decrease in the diffusion coefficient of the lithium ion in the cathode.

Bayesian analysis of caustic-crossing microlensing events

NASA Astrophysics Data System (ADS)

Cassan, A.; Horne, K.; Kains, N.; Tsapras, Y.; Browne, P.

2010-06-01

Aims: Caustic-crossing binary-lens microlensing events are important anomalous events because they are capable of detecting an extrasolar planet companion orbiting the lens star. Fast and robust modelling methods are thus of prime interest in helping to decide whether a planet is detected by an event. Cassan introduced a new set of parameters to model binary-lens events, which are closely related to properties of the light curve. In this work, we explain how Bayesian priors can be added to this framework, and investigate on interesting options. Methods: We develop a mathematical formulation that allows us to compute analytically the priors on the new parameters, given some previous knowledge about other physical quantities. We explicitly compute the priors for a number of interesting cases, and show how this can be implemented in a fully Bayesian, Markov chain Monte Carlo algorithm. Results: Using Bayesian priors can accelerate microlens fitting codes by reducing the time spent considering physically implausible models, and helps us to discriminate between alternative models based on the physical plausibility of their parameters.

Calculating background levels for ecological risk parameters in toxic harbor sediment

USGS Publications Warehouse

Leadon, C.J.; McDonnell, T.R.; Lear, J.; Barclift, D.

2007-01-01

Establishing background levels for biological parameters is necessary in assessing the ecological risks from harbor sediment contaminated with toxic chemicals. For chemicals in sediment, the term contaminated is defined as having concentrations above background and significant human health or ecological risk levels. For biological parameters, a site could be considered contaminated if levels of the parameter are either more or less than the background level, depending on the specific parameter. Biological parameters can include tissue chemical concentrations in ecological receptors, bioassay responses, bioaccumulation levels, and benthic community metrics. Chemical parameters can include sediment concentrations of a variety of potentially toxic chemicals. Indirectly, contaminated harbor sediment can impact shellfish, fish, birds, and marine mammals, and human populations. This paper summarizes the methods used to define background levels for chemical and biological parameters from a survey of ecological risk investigations of marine harbor sediment at California Navy bases. Background levels for regional biological indices used to quantify ecological risks for benthic communities are also described. Generally, background stations are positioned in relatively clean areas exhibiting the same physical and general chemical characteristics as nearby areas with contaminated harbor sediment. The number of background stations and the number of sample replicates per background station depend on the statistical design of the sediment ecological risk investigation, developed through the data quality objective (DQO) process. Biological data from the background stations can be compared to data from a contaminated site by using minimum or maximum background levels or comparative statistics. In Navy ecological risk assessments (ERA's), calculated background levels and appropriate ecological risk screening criteria are used to identify sampling stations and sites with contaminated sediments.

Parameter Estimation and Model Selection in Computational Biology

PubMed Central

Lillacci, Gabriele; Khammash, Mustafa

2010-01-01

A central challenge in computational modeling of biological systems is the determination of the model parameters. Typically, only a fraction of the parameters (such as kinetic rate constants) are experimentally measured, while the rest are often fitted. The fitting process is usually based on experimental time course measurements of observables, which are used to assign parameter values that minimize some measure of the error between these measurements and the corresponding model prediction. The measurements, which can come from immunoblotting assays, fluorescent markers, etc., tend to be very noisy and taken at a limited number of time points. In this work we present a new approach to the problem of parameter selection of biological models. We show how one can use a dynamic recursive estimator, known as extended Kalman filter, to arrive at estimates of the model parameters. The proposed method follows. First, we use a variation of the Kalman filter that is particularly well suited to biological applications to obtain a first guess for the unknown parameters. Secondly, we employ an a posteriori identifiability test to check the reliability of the estimates. Finally, we solve an optimization problem to refine the first guess in case it should not be accurate enough. The final estimates are guaranteed to be statistically consistent with the measurements. Furthermore, we show how the same tools can be used to discriminate among alternate models of the same biological process. We demonstrate these ideas by applying our methods to two examples, namely a model of the heat shock response in E. coli, and a model of a synthetic gene regulation system. The methods presented are quite general and may be applied to a wide class of biological systems where noisy measurements are used for parameter estimation or model selection. PMID:20221262

Bayesian uncertainty analysis for complex systems biology models: emulation, global parameter searches and evaluation of gene functions.

PubMed

Vernon, Ian; Liu, Junli; Goldstein, Michael; Rowe, James; Topping, Jen; Lindsey, Keith

2018-01-02

Many mathematical models have now been employed across every area of systems biology. These models increasingly involve large numbers of unknown parameters, have complex structure which can result in substantial evaluation time relative to the needs of the analysis, and need to be compared to observed data of various forms. The correct analysis of such models usually requires a global parameter search, over a high dimensional parameter space, that incorporates and respects the most important sources of uncertainty. This can be an extremely difficult task, but it is essential for any meaningful inference or prediction to be made about any biological system. It hence represents a fundamental challenge for the whole of systems biology. Bayesian statistical methodology for the uncertainty analysis of complex models is introduced, which is designed to address the high dimensional global parameter search problem. Bayesian emulators that mimic the systems biology model but which are extremely fast to evaluate are embeded within an iterative history match: an efficient method to search high dimensional spaces within a more formal statistical setting, while incorporating major sources of uncertainty. The approach is demonstrated via application to a model of hormonal crosstalk in Arabidopsis root development, which has 32 rate parameters, for which we identify the sets of rate parameter values that lead to acceptable matches between model output and observed trend data. The multiple insights into the model's structure that this analysis provides are discussed. The methodology is applied to a second related model, and the biological consequences of the resulting comparison, including the evaluation of gene functions, are described. Bayesian uncertainty analysis for complex models using both emulators and history matching is shown to be a powerful technique that can greatly aid the study of a large class of systems biology models. It both provides insight into model behaviour and identifies the sets of rate parameters of interest.

Depressive symptoms predict head and neck cancer survival: Examining plausible behavioral and biological pathways.

PubMed

Zimmaro, Lauren A; Sephton, Sandra E; Siwik, Chelsea J; Phillips, Kala M; Rebholz, Whitney N; Kraemer, Helena C; Giese-Davis, Janine; Wilson, Liz; Bumpous, Jeffrey M; Cash, Elizabeth D

2018-03-01

Head and neck cancers are associated with high rates of depression, which may increase the risk for poorer immediate and long-term outcomes. Here it was hypothesized that greater depressive symptoms would predict earlier mortality, and behavioral (treatment interruption) and biological (treatment response) mediators were examined. Patients (n = 134) reported depressive symptomatology at treatment planning. Clinical data were reviewed at the 2-year follow-up. Greater depressive symptoms were associated with significantly shorter survival (hazard ratio, 0.868; 95% confidence interval [CI], 0.819-0.921; P < .001), higher rates of chemoradiation interruption (odds ratio, 0.865; 95% CI, 0.774-0.966; P = .010), and poorer treatment response (odds ratio, 0.879; 95% CI, 0.803-0.963; P = .005). The poorer treatment response partially explained the depression-survival relation. Other known prognostic indicators did not challenge these results. Depressive symptoms at the time of treatment planning predict overall 2-year mortality. Effects are partly influenced by the treatment response. Depression screening and intervention may be beneficial. Future studies should examine parallel biological pathways linking depression to cancer survival, including endocrine disruption and inflammation. Cancer 2018;124:1053-60. © 2018 American Cancer Society. © 2018 American Cancer Society.

Developing Research Capabilities in Energy Biosciences: Design principles of photosynthetic biofuel production.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Donald D. Brown; David Savage

2012-06-30

The current fossil fuel-based energy infrastructure is not sustainable. Solar radiation is a plausible alternative, but realizing it as such will require significant technological advances in the ability to harvest light energy and convert it into suitable fuels. The biological system of photosynthesis can carry out these reactions, and in principle could be engineered using the tools of synthetic biology. One desirable implementation would be to rewire the reactions of a photosynthetic bacterium to direct the energy harvested from solar radiation into the synthesis of the biofuel H2. Proposed here is a series of experiments to lay the basic sciencemore » groundwork for such an attempt. The goal is to elucidate the transcriptional network of photosynthesis using a novel driver-reporter screen, evolve more robust hydrogenases for improved catalysis, and to test the ability of the photosynthetic machinery to directly produce H2 in vivo. The results of these experiments will have broad implications for the understanding of photosynthesis, enzyme function, and the engineering of biological systems for sustainable energy production. The ultimate impact could be a fundamental transformation of the world's energy economy.« less

Physical plausibility of cold star models satisfying Karmarkar conditions

NASA Astrophysics Data System (ADS)

Fuloria, Pratibha; Pant, Neeraj

2017-11-01

In the present article, we have obtained a new well behaved solution to Einstein's field equations in the background of Karmarkar spacetime. The solution has been used for stellar modelling within the demand of current observational evidences. All the physical parameters are well behaved inside the stellar interior and our model satisfies all the required conditions to be physically realizable. The obtained compactness parameter is within the Buchdahl limit, i.e. 2M/R ≤ 8/9 . The TOV equation is well maintained inside the fluid spheres. The stability of the models has been further confirmed by using Herrera's cracking method. The models proposed in the present work are compatible with observational data of compact objects 4U1608-52 and PSRJ1903+327. The necessary graphs have been shown to authenticate the physical viability of our models.

Biologically inspired design of feedback control systems implemented using DNA strand displacement reactions.

PubMed

Foo, Mathias; Sawlekar, Rucha; Kulkarni, Vishwesh V; Bates, Declan G

2016-08-01

The use of abstract chemical reaction networks (CRNs) as a modelling and design framework for the implementation of computing and control circuits using enzyme-free, entropy driven DNA strand displacement (DSD) reactions is starting to garner widespread attention in the area of synthetic biology. Previous work in this area has demonstrated the theoretical plausibility of using this approach to design biomolecular feedback control systems based on classical proportional-integral (PI) controllers, which may be constructed from CRNs implementing gain, summation and integrator operators. Here, we propose an alternative design approach that utilises the abstract chemical reactions involved in cellular signalling cycles to implement a biomolecular controller - termed a signalling-cycle (SC) controller. We compare the performance of the PI and SC controllers in closed-loop with a nonlinear second-order chemical process. Our results show that the SC controller outperforms the PI controller in terms of both performance and robustness, and also requires fewer abstract chemical reactions to implement, highlighting its potential usefulness in the construction of biomolecular control circuits.

The role of the oncogenic Rab35 in cancer invasion, metastasis, and immune evasion, especially in leukemia.

PubMed

Villagomez, Fabian R; Medina-Contreras, Oscar; Cerna-Cortes, Jorge Francisco; Patino-Lopez, Genaro

2018-05-28

The study of cancer has allowed researchers to describe some biological characteristics that tumor cells acquire during their development, known as the "hallmarks of cancer" but more research is needed to expand our knowledge about cancer biology and to generate new strategies of treatment. The role that RabGTPases might play in some hallmarks of cancer represents interesting areas of study since these proteins are frequently altered in cancer. However, their participation is not well known. Recently, Rab35was recognized as an oncogenic RabGTPase and and because of its association with different cellular functions, distinctly important in immune cells, a possible role of Rab35 in leukemia can be suggested. Nevertheless, the involvement of Rab35 in cancer remains poorly understood and its possible specific role in leukemia remains unknown. In this review, we analyze general aspects of the participation of RabGTPases in cancer, and especially, the plausible role of Rab35 in leukemia.

Effects of model structural uncertainty on carbon cycle projections: biological nitrogen fixation as a case study

NASA Astrophysics Data System (ADS)

Wieder, William R.; Cleveland, Cory C.; Lawrence, David M.; Bonan, Gordon B.

2015-04-01

Uncertainties in terrestrial carbon (C) cycle projections increase uncertainty of potential climate feedbacks. Efforts to improve model performance often include increased representation of biogeochemical processes, such as coupled carbon-nitrogen (N) cycles. In doing so, models are becoming more complex, generating structural uncertainties in model form that reflect incomplete knowledge of how to represent underlying processes. Here, we explore structural uncertainties associated with biological nitrogen fixation (BNF) and quantify their effects on C cycle projections. We find that alternative plausible structures to represent BNF result in nearly equivalent terrestrial C fluxes and pools through the twentieth century, but the strength of the terrestrial C sink varies by nearly a third (50 Pg C) by the end of the twenty-first century under a business-as-usual climate change scenario representative concentration pathway 8.5. These results indicate that actual uncertainty in future C cycle projections may be larger than previously estimated, and this uncertainty will limit C cycle projections until model structures can be evaluated and refined.

Effects of radiobiological uncertainty on vehicle and habitat shield design for missions to the moon and Mars

NASA Technical Reports Server (NTRS)

Wilson, John W.; Nealy, John E.; Schimmerling, Walter; Cucinotta, Francis A.; Wood, James S.

1993-01-01

Some consequences of uncertainties in radiobiological risk due to galactic cosmic ray (GCR) exposure are analyzed for their effect on engineering designs for the first lunar outpost and a mission to explore Mars. This report presents the plausible effect of biological uncertainties, the design changes necessary to reduce the uncertainties to acceptable levels for a safe mission, and an evaluation of the mission redesign cost. Estimates of the amount of shield mass required to compensate for radiobiological uncertainty are given for a simplified vehicle and habitat. The additional amount of shield mass required to provide a safety factor for uncertainty compensation is calculated from the expected response to GCR exposure. The amount of shield mass greatly increases in the estimated range of biological uncertainty, thus, escalating the estimated cost of the mission. The estimates are used as a quantitative example for the cost-effectiveness of research in radiation biophysics and radiation physics.

Developing PFC representations using reinforcement learning

PubMed Central

Reynolds, Jeremy R.; O'Reilly, Randall C.

2009-01-01

From both functional and biological considerations, it is widely believed that action production, planning, and goal-oriented behaviors supported by the frontal cortex are organized hierarchically (Fuster, 1990, Koechlin, Ody, & Kouneiher, 2003, & Miller, Galanter, & Pribram, 1960) However, the nature of the different levels of the hierarchy remains unclear, and little attention has been paid to the origins of such a hierarchy. We address these issues through biologically-inspired computational models that develop representations through reinforcement learning. We explore several different factors in these models that might plausibly give rise to a hierarchical organization of representations within the PFC, including an initial connectivity hierarchy within PFC, a hierarchical set of connections between PFC and subcortical structures controlling it, and differential synaptic plasticity schedules. Simulation results indicate that architectural constraints contribute to the segregation of different types of representations, and that this segregation facilitates learning. These findings are consistent with the idea that there is a functional hierarchy in PFC, as captured in our earlier computational models of PFC function and a growing body of empirical data. PMID:19591977

The natural selection of altruistic traits.

PubMed

Boehm, C

1999-09-01

Proponents of the standard evolutionary biology paradigm explain human "altruism" in terms of either nepotism or strict reciprocity. On that basis our underlying nature is reduced to a function of inclusive fitness: human nature has to be totally selfish or nepotistic. Proposed here are three possible paths to giving costly aid to nonrelatives, paths that are controversial because they involve assumed pleiotropic effects or group selection. One path is pleiotropic subsidies that help to extend nepotistic helping behavior from close family to nonrelatives. Another is "warfare"-if and only if warfare recurred in the Paleolithic. The third and most plausible hypothesis is based on the morally based egalitarian syndrome of prehistoric hunter-gatherers, which reduced phenotypic variation at the within-group level, increased it at the between-group level, and drastically curtailed the advantages of free riders. In an analysis consistent with the fundamental tenets of evolutionary biology, these three paths are evaluated as explanations for the evolutionary development of a rather complicated human social nature.

Development of biological and nonbiological explanations for the Viking label release data. [hydrogen peroxide theory

NASA Technical Reports Server (NTRS)

1980-01-01

The plausibility that hydrogen peroxide, widely distributed within the Mars surface material, was responsible for the evocative response obtained by the Viking Labeled Release (LR) experiment on Mars was investigated. Although a mixture of gamma Fe2O3 and silica sand stimulated the LR nutrient reaction with hydrogen peroxide and reduced the rate of hydrogen decomposition under various storage conditions, the Mars analog soil prepared by the Viking Inorganic Analysis Team to match the Mars analytical data does not cause such effects. Nor is adequate resistance to UV irradiation shown. On the basis of the results and consideration presented while the hydrogen peroxide theory remains the most, if not only, attractive chemical explanation of the LR data, it remains unconvincing on critical points. Until problems concerning the formation and stabilization of hydrogen peroxide on the surface of Mars can be overcome, adhere to the scientific evidence requires serious consideration of the biological theory.

Biological Insights From 108 Schizophrenia-Associated Genetic Loci

PubMed Central

Ripke, Stephan; Neale, Benjamin M; Corvin, Aiden; Walters, James TR; Farh, Kai-How; Holmans, Peter A; Lee, Phil; Bulik-Sullivan, Brendan; Collier, David A; Huang, Hailiang; Pers, Tune H; Agartz, Ingrid; Agerbo, Esben; Albus, Margot; Alexander, Madeline; Amin, Farooq; Bacanu, Silviu A; Begemann, Martin; Belliveau, Richard A; Bene, Judit; Bergen, Sarah E; Bevilacqua, Elizabeth; Bigdeli, Tim B; Black, Donald W; Bruggeman, Richard; Buccola, Nancy G; Buckner, Randy L; Byerley, William; Cahn, Wiepke; Cai, Guiqing; Campion, Dominique; Cantor, Rita M; Carr, Vaughan J; Carrera, Noa; Catts, Stanley V; Chambert, Kimberley D; Chan, Raymond CK; Chan, Ronald YL; Chen, Eric YH; Cheng, Wei; Cheung, Eric FC; Chong, Siow Ann; Cloninger, C Robert; Cohen, David; Cohen, Nadine; Cormican, Paul; Craddock, Nick; Crowley, James J; Curtis, David; Davidson, Michael; Davis, Kenneth L; Degenhardt, Franziska; Del Favero, Jurgen; Demontis, Ditte; Dikeos, Dimitris; Dinan, Timothy; Djurovic, Srdjan; Donohoe, Gary; Drapeau, Elodie; Duan, Jubao; Dudbridge, Frank; Durmishi, Naser; Eichhammer, Peter; Eriksson, Johan; Escott-Price, Valentina; Essioux, Laurent; Fanous, Ayman H; Farrell, Martilias S; Frank, Josef; Franke, Lude; Freedman, Robert; Freimer, Nelson B; Friedl, Marion; Friedman, Joseph I; Fromer, Menachem; Genovese, Giulio; Georgieva, Lyudmila; Giegling, Ina; Giusti-Rodríguez, Paola; Godard, Stephanie; Goldstein, Jacqueline I; Golimbet, Vera; Gopal, Srihari; Gratten, Jacob; de Haan, Lieuwe; Hammer, Christian; Hamshere, Marian L; Hansen, Mark; Hansen, Thomas; Haroutunian, Vahram; Hartmann, Annette M; Henskens, Frans A; Herms, Stefan; Hirschhorn, Joel N; Hoffmann, Per; Hofman, Andrea; Hollegaard, Mads V; Hougaard, David M; Ikeda, Masashi; Joa, Inge; Julià, Antonio; Kahn, René S; Kalaydjieva, Luba; Karachanak-Yankova, Sena; Karjalainen, Juha; Kavanagh, David; Keller, Matthew C; Kennedy, James L; Khrunin, Andrey; Kim, Yunjung; Klovins, Janis; Knowles, James A; Konte, Bettina; Kucinskas, Vaidutis; Kucinskiene, Zita Ausrele; Kuzelova-Ptackova, Hana; Kähler, Anna K; Laurent, Claudine; Lee, Jimmy; Lee, S Hong; Legge, Sophie E; Lerer, Bernard; Li, Miaoxin; Li, Tao; Liang, Kung-Yee; Lieberman, Jeffrey; Limborska, Svetlana; Loughland, Carmel M; Lubinski, Jan; Lönnqvist, Jouko; Macek, Milan; Magnusson, Patrik KE; Maher, Brion S; Maier, Wolfgang; Mallet, Jacques; Marsal, Sara; Mattheisen, Manuel; Mattingsdal, Morten; McCarley, Robert W; McDonald, Colm; McIntosh, Andrew M; Meier, Sandra; Meijer, Carin J; Melegh, Bela; Melle, Ingrid; Mesholam-Gately, Raquelle I; Metspalu, Andres; Michie, Patricia T; Milani, Lili; Milanova, Vihra; Mokrab, Younes; Morris, Derek W; Mors, Ole; Murphy, Kieran C; Murray, Robin M; Myin-Germeys, Inez; Müller-Myhsok, Bertram; Nelis, Mari; Nenadic, Igor; Nertney, Deborah A; Nestadt, Gerald; Nicodemus, Kristin K; Nikitina-Zake, Liene; Nisenbaum, Laura; Nordin, Annelie; O’Callaghan, Eadbhard; O’Dushlaine, Colm; O’Neill, F Anthony; Oh, Sang-Yun; Olincy, Ann; Olsen, Line; Van Os, Jim; Pantelis, Christos; Papadimitriou, George N; Papiol, Sergi; Parkhomenko, Elena; Pato, Michele T; Paunio, Tiina; Pejovic-Milovancevic, Milica; Perkins, Diana O; Pietiläinen, Olli; Pimm, Jonathan; Pocklington, Andrew J; Powell, John; Price, Alkes; Pulver, Ann E; Purcell, Shaun M; Quested, Digby; Rasmussen, Henrik B; Reichenberg, Abraham; Reimers, Mark A; Richards, Alexander L; Roffman, Joshua L; Roussos, Panos; Ruderfer, Douglas M; Salomaa, Veikko; Sanders, Alan R; Schall, Ulrich; Schubert, Christian R; Schulze, Thomas G; Schwab, Sibylle G; Scolnick, Edward M; Scott, Rodney J; Seidman, Larry J; Shi, Jianxin; Sigurdsson, Engilbert; Silagadze, Teimuraz; Silverman, Jeremy M; Sim, Kang; Slominsky, Petr; Smoller, Jordan W; So, Hon-Cheong; Spencer, Chris C A; Stahl, Eli A; Stefansson, Hreinn; Steinberg, Stacy; Stogmann, Elisabeth; Straub, Richard E; Strengman, Eric; Strohmaier, Jana; Stroup, T Scott; Subramaniam, Mythily; Suvisaari, Jaana; Svrakic, Dragan M; Szatkiewicz, Jin P; Söderman, Erik; Thirumalai, Srinivas; Toncheva, Draga; Tosato, Sarah; Veijola, Juha; Waddington, John; Walsh, Dermot; Wang, Dai; Wang, Qiang; Webb, Bradley T; Weiser, Mark; Wildenauer, Dieter B; Williams, Nigel M; Williams, Stephanie; Witt, Stephanie H; Wolen, Aaron R; Wong, Emily HM; Wormley, Brandon K; Xi, Hualin Simon; Zai, Clement C; Zheng, Xuebin; Zimprich, Fritz; Wray, Naomi R; Stefansson, Kari; Visscher, Peter M; Adolfsson, Rolf; Andreassen, Ole A; Blackwood, Douglas HR; Bramon, Elvira; Buxbaum, Joseph D; Børglum, Anders D; Cichon, Sven; Darvasi, Ariel; Domenici, Enrico; Ehrenreich, Hannelore; Esko, Tõnu; Gejman, Pablo V; Gill, Michael; Gurling, Hugh; Hultman, Christina M; Iwata, Nakao; Jablensky, Assen V; Jönsson, Erik G; Kendler, Kenneth S; Kirov, George; Knight, Jo; Lencz, Todd; Levinson, Douglas F; Li, Qingqin S; Liu, Jianjun; Malhotra, Anil K; McCarroll, Steven A; McQuillin, Andrew; Moran, Jennifer L; Mortensen, Preben B; Mowry, Bryan J; Nöthen, Markus M; Ophoff, Roel A; Owen, Michael J; Palotie, Aarno; Pato, Carlos N; Petryshen, Tracey L; Posthuma, Danielle; Rietschel, Marcella; Riley, Brien P; Rujescu, Dan; Sham, Pak C; Sklar, Pamela; St Clair, David; Weinberger, Daniel R; Wendland, Jens R; Werge, Thomas; Daly, Mark J; Sullivan, Patrick F; O’Donovan, Michael C

2014-01-01

Summary Schizophrenia is a highly heritable disorder. Genetic risk is conferred by a large number of alleles, including common alleles of small effect that might be detected by genome-wide association studies. Here, we report a multi-stage schizophrenia genome-wide association study of up to 36,989 cases and 113,075 controls. We identify 128 independent associations spanning 108 conservatively defined loci that meet genome-wide significance, 83 of which have not been previously reported. Associations were enriched among genes expressed in brain providing biological plausibility for the findings. Many findings have the potential to provide entirely novel insights into aetiology, but associations at DRD2 and multiple genes involved in glutamatergic neurotransmission highlight molecules of known and potential therapeutic relevance to schizophrenia, and are consistent with leading pathophysiological hypotheses. Independent of genes expressed in brain, associations were enriched among genes expressed in tissues that play important roles in immunity, providing support for the hypothesized link between the immune system and schizophrenia. PMID:25056061

Resveratrol and Ophthalmic Diseases

PubMed Central

Abu-Amero, Khaled K.; Kondkar, Altaf A.; Chalam, Kakarla V.

2016-01-01

Resveratrol, a naturally occurring plant polyphenol found in grapes, is the principal biologically active component in red wine. Clinical studies have shown that resveratrol due to its potent anti-oxidant and anti-inflammatory properties are cardio-protective, chemotherapeutic, neuroprotective, and display anti-aging effects. Oxidative stress and inflammation play a critical role in the initiation and progression of age-related ocular diseases (glaucoma, cataract, diabetic retinopathy and macular degeneration) that lead to progressive loss of vision and blindness. In vitro and in vivo (animal model) experimental studies performed so far have provided evidence for the biological effects of resveratrol on numerous pathways including oxidative stress, inflammation, mitochondrial dysfunction, apoptosis, pro-survival or angiogenesis that are implicated in the pathogenesis of these age-related ocular disorders. In this review, we provide a brief overview of current scientific literature on resveratrol, its plausible mechanism(s) of action, its potential use and current limitations as a nutritional therapeutic intervention in the eye and its related disorders. PMID:27058553

Trimethylamine-N-oxide switches from stabilizing nature: A mechanistic outlook through experimental techniques and molecular dynamics simulation

NASA Astrophysics Data System (ADS)

Rani, Anjeeta; Jayaraj, Abhilash; Jayaram, B.; Pannuru, Venkatesu

2016-03-01

In adaptation biology of the discovery of the intracellular osmolytes, the osmolytes are found to play a central role in cellular homeostasis and stress response. A number of models using these molecules are now poised to address a wide range of problems in biology. Here, a combination of biophysical measurements and molecular dynamics (MD) simulation method is used to examine the effect of trimethylamine-N-oxide (TMAO) on stem bromelain (BM) structure, stability and function. From the analysis of our results, we found that TMAO destabilizes BM hydrophobic pockets and active site as a result of concerted polar and non-polar interactions which is strongly evidenced by MD simulation carried out for 250 ns. This destabilization is enthalpically favourable at higher concentrations of TMAO while entropically unfavourable. However, to the best of our knowledge, the results constitute first detailed unambiguous proof of destabilizing effect of most commonly addressed TMAO on the interactions governing stability of BM and present plausible mechanism of protein unfolding by TMAO.

Using critical evaluation to reappraise plausibility judgments: A critical cognitive component of conceptual change

NASA Astrophysics Data System (ADS)

Lombardi, D.

2011-12-01

Plausibility judgments-although well represented in conceptual change theories (see, for example, Chi, 2005; diSessa, 1993; Dole & Sinatra, 1998; Posner et al., 1982)-have received little empirical attention until our recent work investigating teachers' and students' understanding of and perceptions about human-induced climate change (Lombardi & Sinatra, 2010, 2011). In our first study with undergraduate students, we found that greater plausibility perceptions of human-induced climate accounted for significantly greater understanding of weather and climate distinctions after instruction, even after accounting for students' prior knowledge (Lombardi & Sinatra, 2010). In a follow-up study with inservice science and preservice elementary teachers, we showed that anger about the topic of climate change and teaching about climate change was significantly related to implausible perceptions about human-induced climate change (Lombardi & Sinatra, 2011). Results from our recent studies helped to inform our development of a model of the role of plausibility judgments in conceptual change situations. The model applies to situations involving cognitive dissonance, where background knowledge conflicts with an incoming message. In such situations, we define plausibility as a judgment on the relative potential truthfulness of incoming information compared to one's existing mental representations (Rescher, 1976). Students may not consciously think when making plausibility judgments, expending only minimal mental effort in what is referred to as an automatic cognitive process (Stanovich, 2009). However, well-designed instruction could facilitate students' reappraisal of plausibility judgments in more effortful and conscious cognitive processing. Critical evaluation specifically may be one effective method to promote plausibility reappraisal in a classroom setting (Lombardi & Sinatra, in progress). In science education, critical evaluation involves the analysis of how evidentiary data support a hypothesis and its alternatives. The presentation will focus on how instruction promoting critical evaluation can encourage individuals to reappraise their plausibility judgments and initiate knowledge reconstruction. In a recent pilot study, teachers experienced an instructional scaffold promoting critical evaluation of two competing climate change theories (i.e., human-induced and increasing solar irradiance) and significantly changed both their plausibility judgments and perceptions of correctness toward the scientifically-accepted model of human-induced climate change. A comparison group of teachers who did not experience the critical evaluation activity showed no significant change. The implications of these studies for future research and instruction will be discussed in the presentation, including effective ways to increase students' and teachers' ability to be critically evaluative and reappraise their plausibility judgments. With controversial science issues, such as climate change, such abilities may be necessary to facilitate conceptual change.

Understanding system dynamics of an adaptive enzyme network from globally profiled kinetic parameters.

PubMed

Chiang, Austin W T; Liu, Wei-Chung; Charusanti, Pep; Hwang, Ming-Jing

2014-01-15

A major challenge in mathematical modeling of biological systems is to determine how model parameters contribute to systems dynamics. As biological processes are often complex in nature, it is desirable to address this issue using a systematic approach. Here, we propose a simple methodology that first performs an enrichment test to find patterns in the values of globally profiled kinetic parameters with which a model can produce the required system dynamics; this is then followed by a statistical test to elucidate the association between individual parameters and different parts of the system's dynamics. We demonstrate our methodology on a prototype biological system of perfect adaptation dynamics, namely the chemotaxis model for Escherichia coli. Our results agreed well with those derived from experimental data and theoretical studies in the literature. Using this model system, we showed that there are motifs in kinetic parameters and that these motifs are governed by constraints of the specified system dynamics. A systematic approach based on enrichment statistical tests has been developed to elucidate the relationships between model parameters and the roles they play in affecting system dynamics of a prototype biological network. The proposed approach is generally applicable and therefore can find wide use in systems biology modeling research.

The cost-effectiveness of dulaglutide versus liraglutide for the treatment of type 2 diabetes mellitus in Spain in patients with BMI ≥30 kg/m2.

PubMed

Dilla, Tatiana; Alexiou, Dimitra; Chatzitheofilou, Ismini; Ayyub, Ruba; Lowin, Julia; Norrbacka, Kirsi

2017-05-01

Dulaglutide 1.5 mg once weekly is a novel glucagon-like peptide 1 (GLP-1) receptor agonist, for the treatment of type two diabetes mellitus (T2DM). The objective was to estimate the cost-effectiveness of dulaglutide once weekly vs liraglutide 1.8 mg once daily for the treatment of T2DM in Spain in patients with a BMI ≥30 kg/m 2 . The IMS CORE Diabetes Model (CDM) was used to estimate costs and outcomes from the perspective of Spanish National Health System, capturing relevant direct medical costs over a lifetime time horizon. Comparative safety and efficacy data were derived from direct comparison of dulaglutide 1.5 mg vs liraglutide 1.8 mg from the AWARD-6 trial in patients with a body mass index (BMI) ≥30 kg/m 2 . All patients were assumed to remain on treatment for 2 years before switching treatment to basal insulin at a daily dose of 40 IU. One-way sensitivity analyses (OWSA) and probabilistic sensitivity analyses (PSA) were conducted to explore the sensitivity of the model to plausible variations in key parameters and uncertainty of model inputs. Under base case assumptions, dulaglutide 1.5 mg was less costly and more effective vs liraglutide 1.8 mg (total lifetime costs €108,489 vs €109,653; total QALYS 10.281 vs 10.259). OWSA demonstrated that dulaglutide 1.5 mg remained dominant given plausible variations in key input parameters. Results of the PSA were consistent with base case results. Primary limitations of the analysis are common to other cost-effectiveness analyses of chronic diseases like T2DM and include the extrapolation of short-term clinical data to the lifetime time horizon and uncertainty around optimum treatment durations. The model found that dulaglutide 1.5 mg was more effective and less costly than liraglutide 1.8 mg for the treatment of T2DM in Spain. Findings were robust to plausible variations in inputs. Based on these results, dulaglutide may result in cost savings to the Spanish National Health System.

Calibration and validation of coarse-grained models of atomic systems: application to semiconductor manufacturing

NASA Astrophysics Data System (ADS)

Farrell, Kathryn; Oden, J. Tinsley

2014-07-01

Coarse-grained models of atomic systems, created by aggregating groups of atoms into molecules to reduce the number of degrees of freedom, have been used for decades in important scientific and technological applications. In recent years, interest in developing a more rigorous theory for coarse graining and in assessing the predictivity of coarse-grained models has arisen. In this work, Bayesian methods for the calibration and validation of coarse-grained models of atomistic systems in thermodynamic equilibrium are developed. For specificity, only configurational models of systems in canonical ensembles are considered. Among major challenges in validating coarse-grained models are (1) the development of validation processes that lead to information essential in establishing confidence in the model's ability predict key quantities of interest and (2), above all, the determination of the coarse-grained model itself; that is, the characterization of the molecular architecture, the choice of interaction potentials and thus parameters, which best fit available data. The all-atom model is treated as the "ground truth," and it provides the basis with respect to which properties of the coarse-grained model are compared. This base all-atom model is characterized by an appropriate statistical mechanics framework in this work by canonical ensembles involving only configurational energies. The all-atom model thus supplies data for Bayesian calibration and validation methods for the molecular model. To address the first challenge, we develop priors based on the maximum entropy principle and likelihood functions based on Gaussian approximations of the uncertainties in the parameter-to-observation error. To address challenge (2), we introduce the notion of model plausibilities as a means for model selection. This methodology provides a powerful approach toward constructing coarse-grained models which are most plausible for given all-atom data. We demonstrate the theory and methods through applications to representative atomic structures and we discuss extensions to the validation process for molecular models of polymer structures encountered in certain semiconductor nanomanufacturing processes. The powerful method of model plausibility as a means for selecting interaction potentials for coarse-grained models is discussed in connection with a coarse-grained hexane molecule. Discussions of how all-atom information is used to construct priors are contained in an appendix.

Radiation signatures from a locally energized flaring loop

NASA Technical Reports Server (NTRS)

Emslie, A. G.; Vlahos, L.

1980-01-01

The radiation signatures from a locally energized solar flare loop based on the physical properties of the energy release mechanisms were consistent with hard X-ray, microwave, and EUV observations for plausible source parameters. It was found that a suprathermal tail of high energy electrons is produced by the primary energy release, and that the number of energetic charged particles ejected into the interplanetary medium in the model is consistent with observations. The radiation signature model predicts that the intrinsic polarization of the hard X-ray burst should increase over the photon energy range of 20 to 100 keV.

Non-linear wave interaction in a plasma column

NASA Technical Reports Server (NTRS)

Larsen, J.-M.; Crawford, F. W.

1979-01-01

Non-linear three-wave interaction is analysed for propagation along a cylindrical plasma column surrounded by an infinite dielectric, in the absence of a static magnetic field. An averaged-Lagrangian method is used, and the results are specialized to parametric interaction and mode conversion, assuming an undepleted pump wave. The theory for these two types of interactions is extended to include imperfect synchronism, and the effects of loss. Computations are presented indicating that parametric growth rates of the order of a fraction of a decibel per centimeter should be obtainable for plausible laboratory plasma column parameters.

A methodology for global-sensitivity analysis of time-dependent outputs in systems biology modelling.

PubMed

Sumner, T; Shephard, E; Bogle, I D L

2012-09-07

One of the main challenges in the development of mathematical and computational models of biological systems is the precise estimation of parameter values. Understanding the effects of uncertainties in parameter values on model behaviour is crucial to the successful use of these models. Global sensitivity analysis (SA) can be used to quantify the variability in model predictions resulting from the uncertainty in multiple parameters and to shed light on the biological mechanisms driving system behaviour. We present a new methodology for global SA in systems biology which is computationally efficient and can be used to identify the key parameters and their interactions which drive the dynamic behaviour of a complex biological model. The approach combines functional principal component analysis with established global SA techniques. The methodology is applied to a model of the insulin signalling pathway, defects of which are a major cause of type 2 diabetes and a number of key features of the system are identified.

Extended Kalman Filter for Estimation of Parameters in Nonlinear State-Space Models of Biochemical Networks

PubMed Central

Sun, Xiaodian; Jin, Li; Xiong, Momiao

2008-01-01

It is system dynamics that determines the function of cells, tissues and organisms. To develop mathematical models and estimate their parameters are an essential issue for studying dynamic behaviors of biological systems which include metabolic networks, genetic regulatory networks and signal transduction pathways, under perturbation of external stimuli. In general, biological dynamic systems are partially observed. Therefore, a natural way to model dynamic biological systems is to employ nonlinear state-space equations. Although statistical methods for parameter estimation of linear models in biological dynamic systems have been developed intensively in the recent years, the estimation of both states and parameters of nonlinear dynamic systems remains a challenging task. In this report, we apply extended Kalman Filter (EKF) to the estimation of both states and parameters of nonlinear state-space models. To evaluate the performance of the EKF for parameter estimation, we apply the EKF to a simulation dataset and two real datasets: JAK-STAT signal transduction pathway and Ras/Raf/MEK/ERK signaling transduction pathways datasets. The preliminary results show that EKF can accurately estimate the parameters and predict states in nonlinear state-space equations for modeling dynamic biochemical networks. PMID:19018286

A feedback model of visual attention.

PubMed

Spratling, M W; Johnson, M H

2004-03-01

Feedback connections are a prominent feature of cortical anatomy and are likely to have a significant functional role in neural information processing. We present a neural network model of cortical feedback that successfully simulates neurophysiological data associated with attention. In this domain, our model can be considered a more detailed, and biologically plausible, implementation of the biased competition model of attention. However, our model is more general as it can also explain a variety of other top-down processes in vision, such as figure/ground segmentation and contextual cueing. This model thus suggests that a common mechanism, involving cortical feedback pathways, is responsible for a range of phenomena and provides a unified account of currently disparate areas of research.

Possible prebiotic significance of polyamines in the condensation, protection, encapsulation, and biological properties of DNA

NASA Technical Reports Server (NTRS)

Baeza, Isabel; Ibanez, Miguel; Wong, Carlos; Chavez, Pedro; Gariglio, Patricio; Oro, J.

1992-01-01

While DNA which has undergone ionic condensation with Co(3+)(NH3)6 is resistant to the action of the endonuclase DNAse I, in much the same way as DNA condensed with spermidine, it was significantly less active in transcription with the E. coli RNA polymerase than DNA-spermidine condensed forms. Although both compacted forms of DNA were more efficiently encapsulated into neutral liposomes, negatively charged liposomes were seldom formed in the presence of the present, positive ion-condensed DNA; spermidine is accordingly proposed as a plausible prebiotic DNA-condensing agent. Attention is given to the relevance of the polyimide-nucleic acids complexes in the evolution of life.

Digital hardware implementation of a stochastic two-dimensional neuron model.

PubMed

Grassia, F; Kohno, T; Levi, T

2016-11-01

This study explores the feasibility of stochastic neuron simulation in digital systems (FPGA), which realizes an implementation of a two-dimensional neuron model. The stochasticity is added by a source of current noise in the silicon neuron using an Ornstein-Uhlenbeck process. This approach uses digital computation to emulate individual neuron behavior using fixed point arithmetic operation. The neuron model's computations are performed in arithmetic pipelines. It was designed in VHDL language and simulated prior to mapping in the FPGA. The experimental results confirmed the validity of the developed stochastic FPGA implementation, which makes the implementation of the silicon neuron more biologically plausible for future hybrid experiments. Copyright © 2017 Elsevier Ltd. All rights reserved.

Neural associative memories for the integration of language, vision and action in an autonomous agent.

PubMed

Markert, H; Kaufmann, U; Kara Kayikci, Z; Palm, G

2009-03-01

Language understanding is a long-standing problem in computer science. However, the human brain is capable of processing complex languages with seemingly no difficulties. This paper shows a model for language understanding using biologically plausible neural networks composed of associative memories. The model is able to deal with ambiguities on the single word and grammatical level. The language system is embedded into a robot in order to demonstrate the correct semantical understanding of the input sentences by letting the robot perform corresponding actions. For that purpose, a simple neural action planning system has been combined with neural networks for visual object recognition and visual attention control mechanisms.

Spike train generation and current-to-frequency conversion in silicon diodes

NASA Technical Reports Server (NTRS)

Coon, D. D.; Perera, A. G. U.

1989-01-01

A device physics model is developed to analyze spontaneous neuron-like spike train generation in current driven silicon p(+)-n-n(+) devices in cryogenic environments. The model is shown to explain the very high dynamic range (0 to the 7th) current-to-frequency conversion and experimental features of the spike train frequency as a function of input current. The devices are interesting components for implementation of parallel asynchronous processing adjacent to cryogenically cooled focal planes because of their extremely low current and power requirements, their electronic simplicity, and their pulse coding capability, and could be used to form the hardware basis for neural networks which employ biologically plausible means of information coding.

Tunnel junction based memristors as artificial synapses

PubMed Central

Thomas, Andy; Niehörster, Stefan; Fabretti, Savio; Shepheard, Norman; Kuschel, Olga; Küpper, Karsten; Wollschläger, Joachim; Krzysteczko, Patryk; Chicca, Elisabetta

2015-01-01

We prepared magnesia, tantalum oxide, and barium titanate based tunnel junction structures and investigated their memristive properties. The low amplitudes of the resistance change in these types of junctions are the major obstacle for their use. Here, we increased the amplitude of the resistance change from 10% up to 100%. Utilizing the memristive properties, we looked into the use of the junction structures as artificial synapses. We observed analogs of long-term potentiation, long-term depression and spike-time dependent plasticity in these simple two terminal devices. Finally, we suggest a possible pathway of these devices toward their integration in neuromorphic systems for storing analog synaptic weights and supporting the implementation of biologically plausible learning mechanisms. PMID:26217173

Modelling the spread of innovation in wild birds.

PubMed

Shultz, Thomas R; Montrey, Marcel; Aplin, Lucy M

2017-06-01

We apply three plausible algorithms in agent-based computer simulations to recent experiments on social learning in wild birds. Although some of the phenomena are simulated by all three learning algorithms, several manifestations of social conformity bias are simulated by only the approximate majority (AM) algorithm, which has roots in chemistry, molecular biology and theoretical computer science. The simulations generate testable predictions and provide several explanatory insights into the diffusion of innovation through a population. The AM algorithm's success raises the possibility of its usefulness in studying group dynamics more generally, in several different scientific domains. Our differential-equation model matches simulation results and provides mathematical insights into the dynamics of these algorithms. © 2017 The Author(s).

A role for neurotransmission and neurodevelopment in attention-deficit/hyperactivity disorder

PubMed Central

2009-01-01

Attention-deficit/hyperactivity disorder (ADHD) has a moderate to high genetic component, probably due to many genes with small effects. Several susceptibility genes have been suggested on the basis of hypotheses that catecholaminergic pathways in the brain are responsible for ADHD. However, many negative association findings have been reported, indicating a limited success for investigations using this approach. The results from genome-wide association studies have suggested that genes related to general brain functions rather than specific aspects of the disorder may contribute to its development. Plausible biological hypotheses linked to neurotransmission and neurodevelopment in general and common to different psychiatric conditions need to be considered when defining candidate genes for ADHD association studies. PMID:19930624

Complex role of HIF in cancer: the known, the unknown, and the unexpected

PubMed Central

Tiburcio, Patricia Denise; Choi, Hyunsung; Huang, L Eric

2014-01-01

Tumor hypoxia has long been recognized as a driving force of malignant progression and therapeutic resistance. The discovery of hypoxia-inducible transcription factors (HIFs) has greatly advanced our understanding of how cancer cells cope with hypoxic stress by maintaining bioenergetics through the stimulation of glycolysis. Until recently, however, it remained perplexing why proliferative cancer cells opt for aerobic glycolysis, an energy-inefficient process of glucose metabolism. Furthermore, the role of HIF in cancer has also become complex. In this review, we highlight recent groundbreaking findings in cancer metabolism, put forward plausible explanations to the complex role of HIF, and underscore remaining issues in cancer biology. PMID:27774467

Potential role of coenzyme Q10 in facilitating recovery from statin-induced rhabdomyolysis.

PubMed

Wang, L W; Jabbour, A; Hayward, C S; Furlong, T J; Girgis, L; Macdonald, P S; Keogh, A M

2015-04-01

Rhabdomyolysis is a rare, but serious complication of statin therapy, and represents the most severe end of the spectrum of statin-induced myotoxicity. We report a case where coenzyme Q10 facilitated recovery from statin-induced rhabdomyolysis and acute renal failure, which had initially persisted despite statin cessation and haemodialysis. This observation is biologically plausible due to the recognised importance of coenzyme Q10 in mitochondrial bioenergetics within myocytes, and the fact that statins inhibit farnesyl pyrophosphate production, a biochemical step crucial for coenzyme Q10 synthesis. Coenzyme Q10 is generally well tolerated, and may potentially benefit patients with statin-induced rhabdomyolysis. © 2015 Royal Australasian College of Physicians.

Melanoma detection using smartphone and multimode hyperspectral imaging

NASA Astrophysics Data System (ADS)

MacKinnon, Nicholas; Vasefi, Fartash; Booth, Nicholas; Farkas, Daniel L.

2016-04-01

This project's goal is to determine how to effectively implement a technology continuum from a low cost, remotely deployable imaging device to a more sophisticated multimode imaging system within a standard clinical practice. In this work a smartphone is used in conjunction with an optical attachment to capture cross-polarized and collinear color images of a nevus that are analyzed to quantify chromophore distribution. The nevus is also imaged by a multimode hyperspectral system, our proprietary SkinSpect™ device. Relative accuracy and biological plausibility of the two systems algorithms are compared to assess aspects of feasibility of in-home or primary care practitioner smartphone screening prior to rigorous clinical analysis via the SkinSpect.

Multimode optical dermoscopy (SkinSpect) analysis for skin with melanocytic nevus

NASA Astrophysics Data System (ADS)

Vasefi, Fartash; MacKinnon, Nicholas; Saager, Rolf; Kelly, Kristen M.; Maly, Tyler; Chave, Robert; Booth, Nicholas; Durkin, Anthony J.; Farkas, Daniel L.

2016-04-01

We have developed a multimode dermoscope (SkinSpect™) capable of illuminating human skin samples in-vivo with spectrally-programmable linearly-polarized light at 33 wavelengths between 468nm and 857 nm. Diffusely reflected photons are separated into collinear and cross-polarized image paths and images captured for each illumination wavelength. In vivo human skin nevi (N = 20) were evaluated with the multimode dermoscope and melanin and hemoglobin concentrations were compared with Spatially Modulated Quantitative Spectroscopy (SMoQS) measurements. Both systems show low correlation between their melanin and hemoglobin concentrations, demonstrating the ability of the SkinSpect™ to separate these molecular signatures and thus act as a biologically plausible device capable of early onset melanoma detection.

A neural model of rule generation in inductive reasoning.

PubMed

Rasmussen, Daniel; Eliasmith, Chris

2011-01-01

Inductive reasoning is a fundamental and complex aspect of human intelligence. In particular, how do subjects, given a set of particular examples, generate general descriptions of the rules governing that set? We present a biologically plausible method for accomplishing this task and implement it in a spiking neuron model. We demonstrate the success of this model by applying it to the problem domain of Raven's Progressive Matrices, a widely used tool in the field of intelligence testing. The model is able to generate the rules necessary to correctly solve Raven's items, as well as recreate many of the experimental effects observed in human subjects. Copyright © 2011 Cognitive Science Society, Inc.

Negotiating plausibility: intervening in the future of nanotechnology.

PubMed

Selin, Cynthia

2011-12-01

The national-level scenarios project NanoFutures focuses on the social, political, economic, and ethical implications of nanotechnology, and is initiated by the Center for Nanotechnology in Society at Arizona State University (CNS-ASU). The project involves novel methods for the development of plausible visions of nanotechnology-enabled futures, elucidates public preferences for various alternatives, and, using such preferences, helps refine future visions for research and outreach. In doing so, the NanoFutures project aims to address a central question: how to deliberate the social implications of an emergent technology whose outcomes are not known. The solution pursued by the NanoFutures project is twofold. First, NanoFutures limits speculation about the technology to plausible visions. This ambition introduces a host of concerns about the limits of prediction, the nature of plausibility, and how to establish plausibility. Second, it subjects these visions to democratic assessment by a range of stakeholders, thus raising methodological questions as to who are relevant stakeholders and how to activate different communities so as to engage the far future. This article makes the dilemmas posed by decisions about such methodological issues transparent and therefore articulates the role of plausibility in anticipatory governance.

The relative importance of physicochemical factors to stream biological condition in urbanizing basins: Evidence from multimodel inference

USGS Publications Warehouse

Carlisle, Daren M.; Bryant, Wade L.

2011-01-01

Many physicochemical factors potentially impair stream ecosystems in urbanizing basins, but few studies have evaluated their relative importance simultaneously, especially in different environmental settings. We used data collected in 25 to 30 streams along a gradient of urbanization in each of 6 metropolitan areas (MAs) to evaluate the relative importance of 11 physicochemical factors on the condition of algal, macroinvertebrate, and fish assemblages. For each assemblage, biological condition was quantified using 2 separate metrics, nonmetric multidimensional scaling ordination site scores and the ratio of observed/expected taxa, both derived in previous studies. Separate linear regression models with 1 or 2 factors as predictors were developed for each MA and assemblage metric. Model parsimony was evaluated based on Akaike’s Information Criterion for small sample size (AICc) and Akaike weights, and variable importance was estimated by summing the Akaike weights across models containing each stressor variable. Few of the factors were strongly correlated (Pearson |r| > 0.7) within MAs. Physicochemical factors explained 17 to 81% of variance in biological condition. Most (92 of 118) of the most plausible models contained 2 predictors, and generally more variance could be explained by the additive effects of 2 factors than by any single factor alone. None of the factors evaluated was universally important for all MAs or biological assemblages. The relative importance of factors varied for different measures of biological condition, biological assemblages, and MA. Our results suggest that the suite of physicochemical factors affecting urban stream ecosystems varies across broad geographic areas, along gradients of urban intensity, and among basins within single MAs.

A Systems Biology Analysis Unfolds the Molecular Pathways and Networks of Two Proteobacteria in Spaceflight and Simulated Microgravity Conditions.

PubMed

Roy, Raktim; Shilpa, P Phani; Bagh, Sangram

2016-09-01

Bacteria are important organisms for space missions due to their increased pathogenesis in microgravity that poses risks to the health of astronauts and for projected synthetic biology applications at the space station. We understand little about the effect, at the molecular systems level, of microgravity on bacteria, despite their significant incidence. In this study, we proposed a systems biology pipeline and performed an analysis on published gene expression data sets from multiple seminal studies on Pseudomonas aeruginosa and Salmonella enterica serovar Typhimurium under spaceflight and simulated microgravity conditions. By applying gene set enrichment analysis on the global gene expression data, we directly identified a large number of new, statistically significant cellular and metabolic pathways involved in response to microgravity. Alteration of metabolic pathways in microgravity has rarely been reported before, whereas in this analysis metabolic pathways are prevalent. Several of those pathways were found to be common across studies and species, indicating a common cellular response in microgravity. We clustered genes based on their expression patterns using consensus non-negative matrix factorization. The genes from different mathematically stable clusters showed protein-protein association networks with distinct biological functions, suggesting the plausible functional or regulatory network motifs in response to microgravity. The newly identified pathways and networks showed connection with increased survival of pathogens within macrophages, virulence, and antibiotic resistance in microgravity. Our work establishes a systems biology pipeline and provides an integrated insight into the effect of microgravity at the molecular systems level. Systems biology-Microgravity-Pathways and networks-Bacteria. Astrobiology 16, 677-689.

A Systems Biology Analysis Unfolds the Molecular Pathways and Networks of Two Proteobacteria in Spaceflight and Simulated Microgravity Conditions

NASA Astrophysics Data System (ADS)

Roy, Raktim; Phani Shilpa, P.; Bagh, Sangram

2016-09-01

Bacteria are important organisms for space missions due to their increased pathogenesis in microgravity that poses risks to the health of astronauts and for projected synthetic biology applications at the space station. We understand little about the effect, at the molecular systems level, of microgravity on bacteria, despite their significant incidence. In this study, we proposed a systems biology pipeline and performed an analysis on published gene expression data sets from multiple seminal studies on Pseudomonas aeruginosa and Salmonella enterica serovar Typhimurium under spaceflight and simulated microgravity conditions. By applying gene set enrichment analysis on the global gene expression data, we directly identified a large number of new, statistically significant cellular and metabolic pathways involved in response to microgravity. Alteration of metabolic pathways in microgravity has rarely been reported before, whereas in this analysis metabolic pathways are prevalent. Several of those pathways were found to be common across studies and species, indicating a common cellular response in microgravity. We clustered genes based on their expression patterns using consensus non-negative matrix factorization. The genes from different mathematically stable clusters showed protein-protein association networks with distinct biological functions, suggesting the plausible functional or regulatory network motifs in response to microgravity. The newly identified pathways and networks showed connection with increased survival of pathogens within macrophages, virulence, and antibiotic resistance in microgravity. Our work establishes a systems biology pipeline and provides an integrated insight into the effect of microgravity at the molecular systems level.

THE ADVERSE OUTCOME PATHWAY (AOP) FRAMEWORK ...

EPA Pesticide Factsheets

An Adverse Outcome Pathway (AOP) represents the organization of current and newly acquired knowledge of biological pathways. These pathways contain a series of nodes (Key Events, KEs) that when sufficiently altered influence the next node on the pathway, beginning from an Molecular Initiating Event (MIE), through intermediate KEs, ending in an Adverse Outcome (AO) which may be used as a basis for decision making. A KE is a measurable biological change, and is linked with other KEs via Key Event Relationships (KERs). A given KE may be involved in several AOPs, leading to a plausible network of biological changes that are involved in an organism’s response to an external stressor. When describing an AOP, five guiding principles have been proposed [1]: 1) an AOP is not specific to a single external stressor, 2) AOPs are modular, with KEs and KERs that can be used in several AOPs, 3) a single AOP is the unit of development, 4) most biological responses will be the result of networks of AOPs, and 5) AOPs will be modified as more biological knowledge becomes available. The collaborative development of AOPs is recommended to be performed using the AOP-Wiki (https://aopwiki.org), which is an effort between the European Commission – DG Joint Research Centre (JRC) and U.S. Environmental Protection Agency (EPA). The Wiki is one part of a larger OECD-sponsored AOP Knowledgebase effort, which is a repository for all AOPs developed as part of the Organization for Economic

Pattern cladistics and the 'realism-antirealism debate' in the philosophy of biology.

PubMed

Vergara-Silva, Francisco

2009-06-01

Despite the amount of work that has been produced on the subject over the years, the 'transformation of cladistics' is still a misunderstood episode in the history of comparative biology. Here, I analyze two outstanding, highly contrasting historiographic accounts on the matter, under the perspective of an influential dichotomy in the philosophy of science: the opposition between Scientific Realism and Empiricism. Placing special emphasis on the notion of 'causal grounding' of morphological characters (sensu Olivier Rieppel) in modern developmental biology's (mechanistic) theories, I arrive at the conclusion that a 'new transformation of cladistics' is philosophically plausible. This 'reformed' understanding of 'pattern cladistics' entails retaining the interpretation of cladograms as 'schemes of synapomorphies', but in association to construing cladogram nodes as 'developmental-genetic taxic homologies', instead of 'standard Darwinian ancestors'. The reinterpretation of pattern cladistics presented here additionally proposes to take Bas Van Fraassen's 'constructive empiricism' as a philosophical stance that could properly support such analysis of developmental-genetic data for systematic purposes. The latter suggestion is justified through a reappraisal of previous ideas developed by prominent pattern cladists (mainly, Colin Patterson), which concerned a scientifically efficient 'observable/non-observable distinction' linked to the conceptual pair 'ontogeny and phylogeny'. Finally, I argue that a robust articulation of Antirealist alternatives in systematics may provide a rational basis for its disciplinary separation from evolutionary biology, as well as for a critical reconsideration of the proper role of certain Scientific Realist positions, currently popular in comparative biology.

Invariance of visual operations at the level of receptive fields

PubMed Central

Lindeberg, Tony

2013-01-01

The brain is able to maintain a stable perception although the visual stimuli vary substantially on the retina due to geometric transformations and lighting variations in the environment. This paper presents a theory for achieving basic invariance properties already at the level of receptive fields. Specifically, the presented framework comprises (i) local scaling transformations caused by objects of different size and at different distances to the observer, (ii) locally linearized image deformations caused by variations in the viewing direction in relation to the object, (iii) locally linearized relative motions between the object and the observer and (iv) local multiplicative intensity transformations caused by illumination variations. The receptive field model can be derived by necessity from symmetry properties of the environment and leads to predictions about receptive field profiles in good agreement with receptive field profiles measured by cell recordings in mammalian vision. Indeed, the receptive field profiles in the retina, LGN and V1 are close to ideal to what is motivated by the idealized requirements. By complementing receptive field measurements with selection mechanisms over the parameters in the receptive field families, it is shown how true invariance of receptive field responses can be obtained under scaling transformations, affine transformations and Galilean transformations. Thereby, the framework provides a mathematically well-founded and biologically plausible model for how basic invariance properties can be achieved already at the level of receptive fields and support invariant recognition of objects and events under variations in viewpoint, retinal size, object motion and illumination. The theory can explain the different shapes of receptive field profiles found in biological vision, which are tuned to different sizes and orientations in the image domain as well as to different image velocities in space-time, from a requirement that the visual system should be invariant to the natural types of image transformations that occur in its environment. PMID:23894283

Genomic Instability and Radiation Risk in Molecular Pathways to Colon Cancer

PubMed Central

Kaiser, Jan Christian; Meckbach, Reinhard; Jacob, Peter

2014-01-01

Colon cancer is caused by multiple genomic alterations which lead to genomic instability (GI). GI appears in molecular pathways of microsatellite instability (MSI) and chromosomal instability (CIN) with clinically observed case shares of about 15–20% and 80–85%. Radiation enhances the colon cancer risk by inducing GI, but little is known about different outcomes for MSI and CIN. Computer-based modelling can facilitate the understanding of the phenomena named above. Comprehensive biological models, which combine the two main molecular pathways to colon cancer, are fitted to incidence data of Japanese a-bomb survivors. The preferred model is selected according to statistical criteria and biological plausibility. Imprints of cell-based processes in the succession from adenoma to carcinoma are identified by the model from age dependences and secular trends of the incidence data. Model parameters show remarkable compliance with mutation rates and growth rates for adenoma, which has been reported over the last fifteen years. Model results suggest that CIN begins during fission of intestinal crypts. Chromosomal aberrations are generated at a markedly elevated rate which favors the accelerated growth of premalignant adenoma. Possibly driven by a trend of Westernization in the Japanese diet, incidence rates for the CIN pathway increased notably in subsequent birth cohorts, whereas rates pertaining to MSI remained constant. An imbalance between number of CIN and MSI cases began to emerge in the 1980s, whereas in previous decades the number of cases was almost equal. The CIN pathway exhibits a strong radio-sensitivity, probably more intensive in men. Among young birth cohorts of both sexes the excess absolute radiation risk related to CIN is larger by an order of magnitude compared to the MSI-related risk. Observance of pathway-specific risks improves the determination of the probability of causation for radiation-induced colon cancer in individual patients, if their exposure histories are known. PMID:25356998

Cooperation of Deterministic Dynamics and Random Noise in Production of Complex Syntactical Avian Song Sequences: A Neural Network Model

PubMed Central

Yamashita, Yuichi; Okumura, Tetsu; Okanoya, Kazuo; Tani, Jun

2011-01-01

How the brain learns and generates temporal sequences is a fundamental issue in neuroscience. The production of birdsongs, a process which involves complex learned sequences, provides researchers with an excellent biological model for this topic. The Bengalese finch in particular learns a highly complex song with syntactical structure. The nucleus HVC (HVC), a premotor nucleus within the avian song system, plays a key role in generating the temporal structures of their songs. From lesion studies, the nucleus interfacialis (NIf) projecting to the HVC is considered one of the essential regions that contribute to the complexity of their songs. However, the types of interaction between the HVC and the NIf that can produce complex syntactical songs remain unclear. In order to investigate the function of interactions between the HVC and NIf, we have proposed a neural network model based on previous biological evidence. The HVC is modeled by a recurrent neural network (RNN) that learns to generate temporal patterns of songs. The NIf is modeled as a mechanism that provides auditory feedback to the HVC and generates random noise that feeds into the HVC. The model showed that complex syntactical songs can be replicated by simple interactions between deterministic dynamics of the RNN and random noise. In the current study, the plausibility of the model is tested by the comparison between the changes in the songs of actual birds induced by pharmacological inhibition of the NIf and the changes in the songs produced by the model resulting from modification of parameters representing NIf functions. The efficacy of the model demonstrates that the changes of songs induced by pharmacological inhibition of the NIf can be interpreted as a trade-off between the effects of noise and the effects of feedback on the dynamics of the RNN of the HVC. These facts suggest that the current model provides a convincing hypothesis for the functional role of NIf–HVC interaction. PMID:21559065

Uncertainty analysis of least-cost modeling for designing wildlife linkages.

PubMed

Beier, Paul; Majka, Daniel R; Newell, Shawn L

2009-12-01

Least-cost models for focal species are widely used to design wildlife corridors. To evaluate the least-cost modeling approach used to develop 15 linkage designs in southern California, USA, we assessed robustness of the largest and least constrained linkage. Species experts parameterized models for eight species with weights for four habitat factors (land cover, topographic position, elevation, road density) and resistance values for each class within a factor (e.g., each class of land cover). Each model produced a proposed corridor for that species. We examined the extent to which uncertainty in factor weights and class resistance values affected two key conservation-relevant outputs, namely, the location and modeled resistance to movement of each proposed corridor. To do so, we compared the proposed corridor to 13 alternative corridors created with parameter sets that spanned the plausible ranges of biological uncertainty in these parameters. Models for five species were highly robust (mean overlap 88%, little or no increase in resistance). Although the proposed corridors for the other three focal species overlapped as little as 0% (mean 58%) of the alternative corridors, resistance in the proposed corridors for these three species was rarely higher than resistance in the alternative corridors (mean difference was 0.025 on a scale of 1 10; worst difference was 0.39). As long as the model had the correct rank order of resistance values and factor weights, our results suggest that the predicted corridor is robust to uncertainty. The three carnivore focal species, alone or in combination, were not effective umbrellas for the other focal species. The carnivore corridors failed to overlap the predicted corridors of most other focal species and provided relatively high resistance for the other focal species (mean increase of 2.7 resistance units). Least-cost modelers should conduct uncertainty analysis so that decision-makers can appreciate the potential impact of model uncertainty on conservation decisions. Our approach to uncertainty analysis (which can be called a worst-case scenario approach) is appropriate for complex models in which distribution of the input parameters cannot be specified.

Prediction of radiation-induced normal tissue complications in radiotherapy using functional image data

NASA Astrophysics Data System (ADS)

Nioutsikou, Elena; Partridge, Mike; Bedford, James L.; Webb, Steve

2005-03-01

The aim of this study has been to explicitly include the functional heterogeneity of an organ as a factor that contributes to the probability of complication of normal tissues following radiotherapy. Situations for which the inclusion of this information can be advantageous to the design of treatment plans are then investigated. A Java program has been implemented for this purpose. This makes use of a voxelated model of a patient, which is based on registered anatomical and functional data in order to enable functional voxel weighting. Using this model, the functional dose-volume histogram (fDVH) and the functional normal tissue complication probability (fNTCP) are then introduced as extensions to the conventional dose-volume histogram (DVH) and normal tissue complication probability (NTCP). In the presence of functional heterogeneity, these tools are physically more meaningful for plan evaluation than the traditional indices, as they incorporate additional information and are anticipated to show a better correlation with outcome. New parameters mf, nf and TD50f are required to replace the m, n and TD50 parameters. A range of plausible values was investigated, awaiting fitting of these new parameters to patient outcomes where functional data have been measured. As an example, the model is applied to two lung datasets utilizing accurately registered computed tomography (CT) and single photon emission computed tomography (SPECT) perfusion scans. Assuming a linear perfusion-function relationship, the biological index mean perfusion weighted lung dose (MPWLD) has been extracted from integration over outlined regions of interest. In agreement with the MPWLD ranking, the fNTCP predictions reveal that incorporation of functional imaging in radiotherapy treatment planning is most beneficial for organs with a large volume effect and large focal areas of dysfunction. There is, however, no additional advantage in cases presenting with homogeneous function. Although presented for lung radiotherapy, this model is general. It can also be applied to positron emission tomography (PET)-CT or functional magnetic resonance imaging (fMRI)-CT registered data and extended to the functional description of tumour control probability.

Membrane tension: A challenging but universal physical parameter in cell biology.

PubMed

Pontes, Bruno; Monzo, Pascale; Gauthier, Nils C

2017-11-01

The plasma membrane separates the interior of cells from the outside environment. The membrane tension, defined as the force per unit length acting on a cross-section of membrane, regulates many vital biological processes. In this review, we summarize the first historical findings and the latest advances, showing membrane tension as an important physical parameter in cell biology. We also discuss how this parameter must be better integrated and we propose experimental approaches for key unanswered questions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Propagation of kinetic uncertainties through a canonical topology of the TLR4 signaling network in different regions of biochemical reaction space

PubMed Central

2010-01-01

Background Signal transduction networks represent the information processing systems that dictate which dynamical regimes of biochemical activity can be accessible to a cell under certain circumstances. One of the major concerns in molecular systems biology is centered on the elucidation of the robustness properties and information processing capabilities of signal transduction networks. Achieving this goal requires the establishment of causal relations between the design principle of biochemical reaction systems and their emergent dynamical behaviors. Methods In this study, efforts were focused in the construction of a relatively well informed, deterministic, non-linear dynamic model, accounting for reaction mechanisms grounded on standard mass action and Hill saturation kinetics, of the canonical reaction topology underlying Toll-like receptor 4 (TLR4)-mediated signaling events. This signaling mechanism has been shown to be deployed in macrophages during a relatively short time window in response to lypopolysaccharyde (LPS) stimulation, which leads to a rapidly mounted innate immune response. An extensive computational exploration of the biochemical reaction space inhabited by this signal transduction network was performed via local and global perturbation strategies. Importantly, a broad spectrum of biologically plausible dynamical regimes accessible to the network in widely scattered regions of parameter space was reconstructed computationally. Additionally, experimentally reported transcriptional readouts of target pro-inflammatory genes, which are actively modulated by the network in response to LPS stimulation, were also simulated. This was done with the main goal of carrying out an unbiased statistical assessment of the intrinsic robustness properties of this canonical reaction topology. Results Our simulation results provide convincing numerical evidence supporting the idea that a canonical reaction mechanism of the TLR4 signaling network is capable of performing information processing in a robust manner, a functional property that is independent of the signaling task required to be executed. Nevertheless, it was found that the robust performance of the network is not solely determined by its design principle (topology), but this may be heavily dependent on the network's current position in biochemical reaction space. Ultimately, our results enabled us the identification of key rate limiting steps which most effectively control the performance of the system under diverse dynamical regimes. Conclusions Overall, our in silico study suggests that biologically relevant and non-intuitive aspects on the general behavior of a complex biomolecular network can be elucidated only when taking into account a wide spectrum of dynamical regimes attainable by the system. Most importantly, this strategy provides the means for a suitable assessment of the inherent variational constraints imposed by the structure of the system when systematically probing its parameter space. PMID:20230643

From Mouth-level to Tooth-level DMFS: Conceptualizing a Theoretical Framework

PubMed Central

Bandyopadhyay, Dipankar

2015-01-01

Objective There is no dearth of correlated count data in any biological or clinical settings, and the ability to accurately analyze and interpret such data remains an exciting area of research. In oral health epidemiology, the Decayed, Missing, Filled (DMF) index has been continuously used for over 70 years as the key measure to quantify caries experience. The DMF index projects a subject’s caries status using either the DMF(T), the total number of DMF teeth, or the DMF(S), counting the total DMF teeth surfaces, for that subject. However, surfaces within a particular tooth or a subject constitute clustered data, and the DMFS mostly overlook this clustering effect to attain an over-simplified summary index, ignoring the true tooth-level caries status. Besides, the DMFT/DMFS might exhibit excess of some specific counts (say, zeroes representing the set of relatively disease-free carious state), or can exhibit overdispersion, and accounting for the excess responses or overdispersion remains a key component is selecting the appropriate modeling strategy. Methods & Results This concept paper presents the rationale and the theoretical framework which a dental researcher might consider at the onset in order to choose a plausible statistical model for tooth-level DMFS. Various nuances related to model fitting, selection and parameter interpretation are also explained. Conclusion The author recommends conceptualizing the correct stochastic framework should serve as the guiding force to the dental researcher’s never-ending goal of assessing complex covariate-response relationships efficiently. PMID:26618183

Information Flow in Interaction Networks II: Channels, Path Lengths, and Potentials

PubMed Central

Stojmirović, Aleksandar

2012-01-01

Abstract In our previous publication, a framework for information flow in interaction networks based on random walks with damping was formulated with two fundamental modes: emitting and absorbing. While many other network analysis methods based on random walks or equivalent notions have been developed before and after our earlier work, one can show that they can all be mapped to one of the two modes. In addition to these two fundamental modes, a major strength of our earlier formalism was its accommodation of context-specific directed information flow that yielded plausible and meaningful biological interpretation of protein functions and pathways. However, the directed flow from origins to destinations was induced via a potential function that was heuristic. Here, with a theoretically sound approach called the channel mode, we extend our earlier work for directed information flow. This is achieved by constructing a potential function facilitating a purely probabilistic interpretation of the channel mode. For each network node, the channel mode combines the solutions of emitting and absorbing modes in the same context, producing what we call a channel tensor. The entries of the channel tensor at each node can be interpreted as the amount of flow passing through that node from an origin to a destination. Similarly to our earlier model, the channel mode encompasses damping as a free parameter that controls the locality of information flow. Through examples involving the yeast pheromone response pathway, we illustrate the versatility and stability of our new framework. PMID:22409812

The Time Course of Plausibility Effects on Eye Movements in Reading: Evidence from Noun-Noun Compounds

ERIC Educational Resources Information Center

Staub, Adrian; Rayner, Keith; Pollatsek, Alexander; Hyona, Jukka; Majewski, Helen

2007-01-01

Readers' eye movements were monitored as they read sentences containing noun-noun compounds that varied in frequency (e.g., elevator mechanic, mountain lion). The left constituent of the compound was either plausible or implausible as a head noun at the point at which it appeared, whereas the compound as a whole was always plausible. When the head…

Environmental parameters of the Tennessee River in Alabama. 2: Physical, chemical, and biological parameters. [biological and chemical effects of thermal pollution from nuclear power plants on water quality

NASA Technical Reports Server (NTRS)

Rosing, L. M.

1976-01-01

Physical, chemical and biological water quality data from five sites in the Tennessee River, two in Guntersville Reservoir and three in Wheeler Reservoir were correlated with climatological data for three annual cycles. Two of the annual cycles are for the years prior to the Browns Ferry Nuclear Power Plant operations and one is for the first 14 months of Plant operations. A comparison of the results of the annual cycles indicates that two distinct physical conditions in the reservoirs occur, one during the warm months when the reservoirs are at capacity and one during the colder winter months when the reservoirs have been drawn-down for water storage during the rainy months and for weed control. The wide variations of physical and chemical parameters to which the biological organisms are subjected on an annual basis control the biological organisms and their population levels. A comparison of the parameters of the site below the Power plant indicates that the heated effluent from the plant operating with two of the three reactors has not had any effect on the organisms at this site. Recommendations given include the development of prediction mathematical models (statistical analysis) for the physical and chemical parameters under specific climatological conditions which affect biological organisms. Tabulated data of chemical analysis of water and organism populations studied is given.

Dynamical compensation and structural identifiability of biological models: Analysis, implications, and reconciliation.

PubMed

Villaverde, Alejandro F; Banga, Julio R

2017-11-01

The concept of dynamical compensation has been recently introduced to describe the ability of a biological system to keep its output dynamics unchanged in the face of varying parameters. However, the original definition of dynamical compensation amounts to lack of structural identifiability. This is relevant if model parameters need to be estimated, as is often the case in biological modelling. Care should we taken when using an unidentifiable model to extract biological insight: the estimated values of structurally unidentifiable parameters are meaningless, and model predictions about unmeasured state variables can be wrong. Taking this into account, we explore alternative definitions of dynamical compensation that do not necessarily imply structural unidentifiability. Accordingly, we show different ways in which a model can be made identifiable while exhibiting dynamical compensation. Our analyses enable the use of the new concept of dynamical compensation in the context of parameter identification, and reconcile it with the desirable property of structural identifiability.

Understanding Schizophrenia as a Disorder of Consciousness: Biological Correlates and Translational Implications from Quantum Theory Perspectives

PubMed Central

Venkatasubramanian, Ganesan

2015-01-01

From neurophenomenological perspectives, schizophrenia has been conceptualized as “a disorder with heterogeneous manifestations that can be integrally understood to involve fundamental perturbations in consciousness”. While these theoretical constructs based on consciousness facilitate understanding the ‘gestalt’ of schizophrenia, systematic research to unravel translational implications of these models is warranted. To address this, one needs to begin with exploration of plausible biological underpinnings of “perturbed consciousness” in schizophrenia. In this context, an attractive proposition to understand the biology of consciousness is “the orchestrated object reduction (Orch-OR) theory” which invokes quantum processes in the microtubules of neurons. The Orch-OR model is particularly important for understanding schizophrenia especially due to the shared ‘scaffold’ of microtubules. The initial sections of this review focus on the compelling evidence to support the view that “schizophrenia is a disorder of consciousness” through critical summary of the studies that have demonstrated self-abnormalities, aberrant time perception as well as dysfunctional intentional binding in this disorder. Subsequently, these findings are linked with ‘Orch-OR theory’ through the research evidence for aberrant neural oscillations as well as microtubule abnormalities observed in schizophrenia. Further sections emphasize the applicability and translational implications of Orch-OR theory in the context of schizophrenia and elucidate the relevance of quantum biology to understand the origins of this puzzling disorder as “fundamental disturbances in consciousness”. PMID:25912536

Understanding schizophrenia as a disorder of consciousness: biological correlates and translational implications from quantum theory perspectives.

PubMed

Venkatasubramanian, Ganesan

2015-04-30

From neurophenomenological perspectives, schizophrenia has been conceptualized as "a disorder with heterogeneous manifestations that can be integrally understood to involve fundamental perturbations in consciousness". While these theoretical constructs based on consciousness facilitate understanding the 'gestalt' of schizophrenia, systematic research to unravel translational implications of these models is warranted. To address this, one needs to begin with exploration of plausible biological underpinnings of "perturbed consciousness" in schizophrenia. In this context, an attractive proposition to understand the biology of consciousness is "the orchestrated object reduction (Orch-OR) theory" which invokes quantum processes in the microtubules of neurons. The Orch-OR model is particularly important for understanding schizophrenia especially due to the shared 'scaffold' of microtubules. The initial sections of this review focus on the compelling evidence to support the view that "schizophrenia is a disorder of consciousness" through critical summary of the studies that have demonstrated self-abnormalities, aberrant time perception as well as dysfunctional intentional binding in this disorder. Subsequently, these findings are linked with 'Orch-OR theory' through the research evidence for aberrant neural oscillations as well as microtubule abnormalities observed in schizophrenia. Further sections emphasize the applicability and translational implications of Orch-OR theory in the context of schizophrenia and elucidate the relevance of quantum biology to understand the origins of this puzzling disorder as "fundamental disturbances in consciousness".

Rocky Worlds Limited to ∼1.8 Earth Radii by Atmospheric Escape during a Star’s Extreme UV Saturation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lehmer, Owen R.; Catling, David C., E-mail: info@lehmer.us

Recent observations and analysis of low-mass (<10 M {sub ⊕}) exoplanets have found that rocky planets only have radii up to 1.5–2 R {sub ⊕}. Two general hypotheses exist for the cause of the dichotomy between rocky and gas-enveloped planets (or possible water worlds): either low-mass planets do not necessarily form thick atmospheres of a few wt.%, or the thick atmospheres on these planets easily escape, driven by X-ray and extreme ultraviolet (XUV) emissions from young parent stars. Here, we show that a cutoff between rocky and gas-enveloped planets due to hydrodynamic escape is most likely to occur at amore » mean radius of 1.76 ± 0.38 (2 σ ) R {sub ⊕} around Sun-like stars. We examine the limit in rocky planet radii predicted by hydrodynamic escape across a wide range of possible model inputs, using 10,000 parameter combinations drawn randomly from plausible parameter ranges. We find a cutoff between rocky and gas-enveloped planets that agrees with the observed cutoff. The large cross-section available for XUV absorption in the extremely distended primitive atmospheres of low-mass planets results in complete loss of atmospheres during the ∼100 Myr phase of stellar XUV saturation. In contrast, more-massive planets have less-distended atmospheres and less escape, and so retain thick atmospheres through XUV saturation—and then indefinitely as the XUV and escape fluxes drop over time. The agreement between our model and exoplanet data leads us to conclude that hydrodynamic escape plausibly explains the observed upper limit on rocky planet size and few planets (a “valley”, or “radius gap”) in the 1.5–2 R {sub ⊕} range.« less

Applying Multimodel Ensemble from Regional Climate Models for Improving Runoff Projections on Semiarid Regions of Spain

NASA Astrophysics Data System (ADS)

Garcia Galiano, S. G.; Olmos, P.; Giraldo Osorio, J. D.

2015-12-01

In the Mediterranean area, significant changes on temperature and precipitation are expected throughout the century. These trends could exacerbate the existing conditions in regions already vulnerable to climatic variability, reducing the water availability. Improving knowledge about plausible impacts of climate change on water cycle processes at basin scale, is an important step for building adaptive capacity to the impacts in this region, where severe water shortages are expected for the next decades. RCMs ensemble in combination with distributed hydrological models with few parameters, constitutes a valid and robust methodology to increase the reliability of climate and hydrological projections. For reaching this objective, a novel methodology for building Regional Climate Models (RCMs) ensembles of meteorological variables (rainfall an temperatures), was applied. RCMs ensembles are justified for increasing the reliability of climate and hydrological projections. The evaluation of RCMs goodness-of-fit to build the ensemble is based on empirical probability density functions (PDF) extracted from both RCMs dataset and a highly resolution gridded observational dataset, for the time period 1961-1990. The applied method is considering the seasonal and annual variability of the rainfall and temperatures. The RCMs ensembles constitute the input to a distributed hydrological model at basin scale, for assessing the runoff projections. The selected hydrological model is presenting few parameters in order to reduce the uncertainties involved. The study basin corresponds to a head basin of Segura River Basin, located in the South East of Spain. The impacts on runoff and its trend from observational dataset and climate projections, were assessed. Considering the control period 1961-1990, plausible significant decreases in runoff for the time period 2021-2050, were identified.

Resilience of Key Biological Parameters of the Senegalese Flat Sardinella to Overfishing and Climate Change.

PubMed

Ba, Kamarel; Thiaw, Modou; Lazar, Najih; Sarr, Alassane; Brochier, Timothée; Ndiaye, Ismaïla; Faye, Alioune; Sadio, Oumar; Panfili, Jacques; Thiaw, Omar Thiom; Brehmer, Patrice

2016-01-01

The stock of the Senegalese flat sardinella, Sardinella maderensis, is highly exploited in Senegal, West Africa. Its growth and reproduction parameters are key biological indicators for improving fisheries management. This study reviewed these parameters using landing data from small-scale fisheries in Senegal and literature information dated back more than 25 years. Age was estimated using length-frequency data to calculate growth parameters and assess the growth performance index. With global climate change there has been an increase in the average sea surface temperature along the Senegalese coast but the length-weight parameters, sex ratio, size at first sexual maturity, period of reproduction and condition factor of S. maderensis have not changed significantly. The above parameters of S. maderensis have hardly changed, despite high exploitation and fluctuations in environmental conditions that affect the early development phases of small pelagic fish in West Africa. This lack of plasticity of the species regarding of the biological parameters studied should be considered when planning relevant fishery management plans.

High-dose intravenous vitamin C combined with cytotoxic chemotherapy in patients with advanced cancer: a phase I-II clinical trial.

PubMed

Hoffer, L John; Robitaille, Line; Zakarian, Robert; Melnychuk, David; Kavan, Petr; Agulnik, Jason; Cohen, Victor; Small, David; Miller, Wilson H

2015-01-01

Biological and some clinical evidence suggest that high-dose intravenous vitamin C (IVC) could increase the effectiveness of cancer chemotherapy. IVC is widely used by integrative and complementary cancer therapists, but rigorous data are lacking as to its safety and which cancers and chemotherapy regimens would be the most promising to investigate in detail. We carried out a phase I-II safety, tolerability, pharmacokinetic and efficacy trial of IVC combined with chemotherapy in patients whose treating oncologist judged that standard-of-care or off-label chemotherapy offered less than a 33% likelihood of a meaningful response. We documented adverse events and toxicity associated with IVC infusions, determined pre- and post-chemotherapy vitamin C and oxalic acid pharmacokinetic profiles, and monitored objective clinical responses, mood and quality of life. Fourteen patients were enrolled. IVC was safe and generally well tolerated, although some patients experienced transient adverse events during or after IVC infusions. The pre- and post-chemotherapy pharmacokinetic profiles suggested that tissue uptake of vitamin C increases after chemotherapy, with no increase in urinary oxalic acid excretion. Three patients with different types of cancer experienced unexpected transient stable disease, increased energy and functional improvement. Despite IVC's biological and clinical plausibility, career cancer investigators currently ignore it while integrative cancer therapists use it widely but without reporting the kind of clinical data that is normally gathered in cancer drug development. The present study neither proves nor disproves IVC's value in cancer therapy, but it provides practical information, and indicates a feasible way to evaluate this plausible but unproven therapy in an academic environment that is currently uninterested in it. If carried out in sufficient numbers, simple studies like this one could identify specific clusters of cancer type, chemotherapy regimen and IVC in which exceptional responses occur frequently enough to justify appropriately focused clinical trials. ClinicalTrials.gov NCT01050621.

Trial-by-Trial Modulation of Associative Memory Formation by Reward Prediction Error and Reward Anticipation as Revealed by a Biologically Plausible Computational Model.

PubMed

Aberg, Kristoffer C; Müller, Julia; Schwartz, Sophie

2017-01-01

Anticipation and delivery of rewards improves memory formation, but little effort has been made to disentangle their respective contributions to memory enhancement. Moreover, it has been suggested that the effects of reward on memory are mediated by dopaminergic influences on hippocampal plasticity. Yet, evidence linking memory improvements to actual reward computations reflected in the activity of the dopaminergic system, i.e., prediction errors and expected values, is scarce and inconclusive. For example, different previous studies reported that the magnitude of prediction errors during a reinforcement learning task was a positive, negative, or non-significant predictor of successfully encoding simultaneously presented images. Individual sensitivities to reward and punishment have been found to influence the activation of the dopaminergic reward system and could therefore help explain these seemingly discrepant results. Here, we used a novel associative memory task combined with computational modeling and showed independent effects of reward-delivery and reward-anticipation on memory. Strikingly, the computational approach revealed positive influences from both reward delivery, as mediated by prediction error magnitude, and reward anticipation, as mediated by magnitude of expected value, even in the absence of behavioral effects when analyzed using standard methods, i.e., by collapsing memory performance across trials within conditions. We additionally measured trait estimates of reward and punishment sensitivity and found that individuals with increased reward (vs. punishment) sensitivity had better memory for associations encoded during positive (vs. negative) prediction errors when tested after 20 min, but a negative trend when tested after 24 h. In conclusion, modeling trial-by-trial fluctuations in the magnitude of reward, as we did here for prediction errors and expected value computations, provides a comprehensive and biologically plausible description of the dynamic interplay between reward, dopamine, and associative memory formation. Our results also underline the importance of considering individual traits when assessing reward-related influences on memory.

High-Dose Intravenous Vitamin C Combined with Cytotoxic Chemotherapy in Patients with Advanced Cancer: A Phase I-II Clinical Trial

PubMed Central

Hoffer, L. John; Robitaille, Line; Zakarian, Robert; Melnychuk, David; Kavan, Petr; Agulnik, Jason; Cohen, Victor; Small, David; Miller, Wilson H.

2015-01-01

Background Biological and some clinical evidence suggest that high-dose intravenous vitamin C (IVC) could increase the effectiveness of cancer chemotherapy. IVC is widely used by integrative and complementary cancer therapists, but rigorous data are lacking as to its safety and which cancers and chemotherapy regimens would be the most promising to investigate in detail. Methods and Findings We carried out a phase I-II safety, tolerability, pharmacokinetic and efficacy trial of IVC combined with chemotherapy in patients whose treating oncologist judged that standard-of-care or off-label chemotherapy offered less than a 33% likelihood of a meaningful response. We documented adverse events and toxicity associated with IVC infusions, determined pre- and post-chemotherapy vitamin C and oxalic acid pharmacokinetic profiles, and monitored objective clinical responses, mood and quality of life. Fourteen patients were enrolled. IVC was safe and generally well tolerated, although some patients experienced transient adverse events during or after IVC infusions. The pre- and post-chemotherapy pharmacokinetic profiles suggested that tissue uptake of vitamin C increases after chemotherapy, with no increase in urinary oxalic acid excretion. Three patients with different types of cancer experienced unexpected transient stable disease, increased energy and functional improvement. Conclusions Despite IVC’s biological and clinical plausibility, career cancer investigators currently ignore it while integrative cancer therapists use it widely but without reporting the kind of clinical data that is normally gathered in cancer drug development. The present study neither proves nor disproves IVC’s value in cancer therapy, but it provides practical information, and indicates a feasible way to evaluate this plausible but unproven therapy in an academic environment that is currently uninterested in it. If carried out in sufficient numbers, simple studies like this one could identify specific clusters of cancer type, chemotherapy regimen and IVC in which exceptional responses occur frequently enough to justify appropriately focused clinical trials. Trial Registration ClinicalTrials.gov NCT01050621 PMID:25848948

Effects of plausibility on structural priming.

PubMed

Christianson, Kiel; Luke, Steven G; Ferreira, Fernanda

2010-03-01

We report a replication and extension of Ferreira (2003), in which it was observed that native adult English speakers misinterpret passive sentences that relate implausible but not impossible semantic relationships (e.g., The angler was caught by the fish) significantly more often than they do plausible passives or plausible or implausible active sentences. In the experiment reported here, participants listened to the same plausible and implausible passive and active sentences as in Ferreira (2003), answered comprehension questions, and then orally described line drawings of simple transitive actions. The descriptions were analyzed as a measure of structural priming (Bock, 1986). Question accuracy data replicated Ferreira (2003). Production data yielded an interaction: Passive descriptions were produced more often after plausible passives and implausible actives. We interpret these results as indicative of a language processor that proceeds along differentiated morphosyntactic and semantic routes. The processor may end up adjudicating between conflicting outputs from these routes by settling on a "good enough" representation that is not completely faithful to the input.

The Plausibility of a String Quartet Performance in Virtual Reality.

PubMed

Bergstrom, Ilias; Azevedo, Sergio; Papiotis, Panos; Saldanha, Nuno; Slater, Mel

2017-04-01

We describe an experiment that explores the contribution of auditory and other features to the illusion of plausibility in a virtual environment that depicts the performance of a string quartet. 'Plausibility' refers to the component of presence that is the illusion that the perceived events in the virtual environment are really happening. The features studied were: Gaze (the musicians ignored the participant, the musicians sometimes looked towards and followed the participant's movements), Sound Spatialization (Mono, Stereo, Spatial), Auralization (no sound reflections, reflections corresponding to a room larger than the one perceived, reflections that exactly matched the virtual room), and Environment (no sound from outside of the room, birdsong and wind corresponding to the outside scene). We adopted the methodology based on color matching theory, where 20 participants were first able to assess their feeling of plausibility in the environment with each of the four features at their highest setting. Then five times participants started from a low setting on all features and were able to make transitions from one system configuration to another until they matched their original feeling of plausibility. From these transitions a Markov transition matrix was constructed, and also probabilities of a match conditional on feature configuration. The results show that Environment and Gaze were individually the most important factors influencing the level of plausibility. The highest probability transitions were to improve Environment and Gaze, and then Auralization and Spatialization. We present this work as both a contribution to the methodology of assessing presence without questionnaires, and showing how various aspects of a musical performance can influence plausibility.

What if? Neural activity underlying semantic and episodic counterfactual thinking.

PubMed

Parikh, Natasha; Ruzic, Luka; Stewart, Gregory W; Spreng, R Nathan; De Brigard, Felipe

2018-05-25

Counterfactual thinking (CFT) is the process of mentally simulating alternative versions of known facts. In the past decade, cognitive neuroscientists have begun to uncover the neural underpinnings of CFT, particularly episodic CFT (eCFT), which activates regions in the default network (DN) also activated by episodic memory (eM) recall. However, the engagement of DN regions is different for distinct kinds of eCFT. More plausible counterfactuals and counterfactuals about oneself show stronger activity in DN regions compared to implausible and other- or object-focused counterfactuals. The current study sought to identify a source for this difference in DN activity. Specifically, self-focused counterfactuals may also be more plausible, suggesting that DN core regions are sensitive to the plausibility of a simulation. On the other hand, plausible and self-focused counterfactuals may involve more episodic information than implausible and other-focused counterfactuals, which would imply DN sensitivity to episodic information. In the current study, we compared episodic and semantic counterfactuals generated to be plausible or implausible against episodic and semantic memory reactivation using fMRI. Taking multivariate and univariate approaches, we found that the DN is engaged more during episodic simulations, including eM and all eCFT, than during semantic simulations. Semantic simulations engaged more inferior temporal and lateral occipital regions. The only region that showed strong plausibility effects was the hippocampus, which was significantly engaged for implausible CFT but not for plausible CFT, suggestive of binding more disparate information. Consequences of these findings for the cognitive neuroscience of mental simulation are discussed. Published by Elsevier Inc.

The double crush syndrome revisited--a Delphi study to reveal current expert views on mechanisms underlying dual nerve disorders.

PubMed

Schmid, Annina B; Coppieters, Michel W

2011-12-01

A high prevalence of dual nerve disorders is frequently reported. How a secondary nerve disorder may develop following a primary nerve disorder remains largely unknown. Although still frequently cited, most explanatory theories were formulated many years ago. Considering recent advances in neuroscience, it is uncertain whether these theories still reflect current expert opinion. A Delphi study was conducted to update views on potential mechanisms underlying dual nerve disorders. In three rounds, seventeen international experts in the field of peripheral nerve disorders were asked to list possible mechanisms and rate their plausibility. Mechanisms with a median plausibility rating of ≥7 out of 10 were considered highly plausible. The experts identified fourteen mechanisms associated with a first nerve disorder that may predispose to the development of another nerve disorder. Of these fourteen mechanisms, nine have not previously been linked to double crush. Four mechanisms were considered highly plausible (impaired axonal transport, ion channel up or downregulation, inflammation in the dorsal root ganglia and neuroma-in-continuity). Eight additional mechanisms were listed which are not triggered by a primary nerve disorder, but may render the nervous system more vulnerable to multiple nerve disorders, such as systemic diseases and neurotoxic medication. Even though many mechanisms were classified as plausible or highly plausible, overall plausibility ratings varied widely. Experts indicated that a wide range of mechanisms has to be considered to better understand dual nerve disorders. Previously listed theories cannot be discarded, but may be insufficient to explain the high prevalence of dual nerve disorders. Copyright © 2011 Elsevier Ltd. All rights reserved.

Understanding asteroid collisional history through experimental and numerical studies

NASA Technical Reports Server (NTRS)

Davis, Donald R.; Ryan, Eileen V.; Weidenschilling, S. J.

1991-01-01

Asteroids can lose angular momentum due to so called splash effect, the analog to the drain effect for cratering impacts. Numerical code with the splash effect incorporated was applied to study the simultaneous evolution of asteroid sized and spins. Results are presented on the spin changes of asteroids due to various physical effects that are incorporated in the described model. The goal was to understand the interplay between the evolution of sizes and spins over a wide and plausible range of model parameters. A single starting population was used both for size distribution and the spin distribution of asteroids and the changes in the spins were calculated over solar system history for different model parameters. It is shown that there is a strong coupling between the size and spin evolution, that the observed relative spindown of asteroids approximately 100 km diameter is likely to be the result of the angular momentum splash effect.

Understanding asteroid collisional history through experimental and numerical studies

NASA Astrophysics Data System (ADS)

Davis, Donald R.; Ryan, Eileen V.; Weidenschilling, S. J.

1991-06-01

Asteroids can lose angular momentum due to so called splash effect, the analog to the drain effect for cratering impacts. Numerical code with the splash effect incorporated was applied to study the simultaneous evolution of asteroid sized and spins. Results are presented on the spin changes of asteroids due to various physical effects that are incorporated in the described model. The goal was to understand the interplay between the evolution of sizes and spins over a wide and plausible range of model parameters. A single starting population was used both for size distribution and the spin distribution of asteroids and the changes in the spins were calculated over solar system history for different model parameters. It is shown that there is a strong coupling between the size and spin evolution, that the observed relative spindown of asteroids approximately 100 km diameter is likely to be the result of the angular momentum splash effect.

Magnetic anisotropy in the Kitaev model systems Na2IrO3 and RuCl3

NASA Astrophysics Data System (ADS)

Chaloupka, Jiří; Khaliullin, Giniyat

2016-08-01

We study the ordered moment direction in the extended Kitaev-Heisenberg model relevant to honeycomb lattice magnets with strong spin-orbit coupling. We utilize numerical diagonalization and analyze the exact cluster ground states using a particular set of spin-coherent states, obtaining thereby quantum corrections to the magnetic anisotropy beyond conventional perturbative methods. It is found that the quantum fluctuations strongly modify the moment direction obtained at a classical level and are thus crucial for a precise quantification of the interactions. The results show that the moment direction is a sensitive probe of the model parameters in real materials. Focusing on the experimentally relevant zigzag phases of the model, we analyze the currently available neutron-diffraction and resonant x-ray-diffraction data on Na2IrO3 and RuCl3 and discuss the parameter regimes plausible in these Kitaev-Heisenberg model systems.

An interacting O + O supergiant close binary system: Cygnus OB2-5 (V729 Cyg)

NASA Astrophysics Data System (ADS)

Yaşarsoy, B.; Yakut, K.

2014-08-01

The massive interacting close binary system V729 Cyg (OIa + O/WN9), plausibly progenitor of a Wolf-Rayet system, is studied using new observations gathered over 65 nights and earlier published data. Radial velocity and five color light curves are analysed simultaneously. Estimated physical parameters of the components are M1=36±3 M, M2=10±1 M, R1=27±1 R, R2=15±0.6 R, log(L1/L⊙)=5.59±0.06, and log(L2/L⊙)=4.65±0.07. We give only the formal 1σ scatter, but we believe systematic errors in the luminosities, of uncertain origin as discussed in the text, are likely to be much bigger. The distance of the Cygnus OB2 association is estimated as 967±48 pc by using our newly obtained parameters.

Constraints on the synchronization of entorhinal cortex stellate cells

NASA Astrophysics Data System (ADS)

Crotty, Patrick; Lasker, Eric; Cheng, Sen

2012-07-01

Synchronized oscillations of large numbers of central neurons are believed to be important for a wide variety of cognitive functions, including long-term memory recall and spatial navigation. It is therefore plausible that evolution has optimized the biophysical properties of central neurons in some way for synchronized oscillations to occur. Here, we use computational models to investigate the relationships between the presumably genetically determined parameters of stellate cells in layer II of the entorhinal cortex and the ability of coupled populations of these cells to synchronize their intrinsic oscillations: in particular, we calculate the time it takes circuits of two or three cells with initially randomly distributed phases to synchronize their oscillations to within one action potential width, and the metabolic energy they consume in doing so. For recurrent circuit topologies, we find that parameters giving low intrinsic firing frequencies close to those actually observed are strongly advantageous for both synchronization time and metabolic energy consumption.

Bidirectional reflectance distribution function based surface modeling of non-Lambertian using intensity data of light detection and ranging.

PubMed

Li, Xiaolu; Liang, Yu; Xu, Lijun

2014-09-01

To provide a credible model for light detection and ranging (LiDAR) target classification, the focus of this study is on the relationship between intensity data of LiDAR and the bidirectional reflectance distribution function (BRDF). An integration method based on the built-in-lab coaxial laser detection system was advanced. A kind of intermediary BRDF model advanced by Schlick was introduced into the integration method, considering diffuse and specular backscattering characteristics of the surface. A group of measurement campaigns were carried out to investigate the influence of the incident angle and detection range on the measured intensity data. Two extracted parameters r and S(λ) are influenced by different surface features, which illustrate the surface features of the distribution and magnitude of reflected energy, respectively. The combination of two parameters can be used to describe the surface characteristics for target classification in a more plausible way.

Enriching plausible new hypothesis generation in PubMed.

PubMed

Baek, Seung Han; Lee, Dahee; Kim, Minjoo; Lee, Jong Ho; Song, Min

2017-01-01

Most of earlier studies in the field of literature-based discovery have adopted Swanson's ABC model that links pieces of knowledge entailed in disjoint literatures. However, the issue concerning their practicability remains to be solved since most of them did not deal with the context surrounding the discovered associations and usually not accompanied with clinical confirmation. In this study, we aim to propose a method that expands and elaborates the existing hypothesis by advanced text mining techniques for capturing contexts. We extend ABC model to allow for multiple B terms with various biological types. We were able to concretize a specific, metabolite-related hypothesis with abundant contextual information by using the proposed method. Starting from explaining the relationship between lactosylceramide and arterial stiffness, the hypothesis was extended to suggest a potential pathway consisting of lactosylceramide, nitric oxide, malondialdehyde, and arterial stiffness. The experiment by domain experts showed that it is clinically valid. The proposed method is designed to provide plausible candidates of the concretized hypothesis, which are based on extracted heterogeneous entities and detailed relation information, along with a reliable ranking criterion. Statistical tests collaboratively conducted with biomedical experts provide the validity and practical usefulness of the method unlike previous studies. Applying the proposed method to other cases, it would be helpful for biologists to support the existing hypothesis and easily expect the logical process within it.

Contrast normalization contributes to a biologically-plausible model of receptive-field development in primary visual cortex (V1)

PubMed Central

Willmore, Ben D.B.; Bulstrode, Harry; Tolhurst, David J.

2012-01-01

Neuronal populations in the primary visual cortex (V1) of mammals exhibit contrast normalization. Neurons that respond strongly to simple visual stimuli – such as sinusoidal gratings – respond less well to the same stimuli when they are presented as part of a more complex stimulus which also excites other, neighboring neurons. This phenomenon is generally attributed to generalized patterns of inhibitory connections between nearby V1 neurons. The Bienenstock, Cooper and Munro (BCM) rule is a neural network learning rule that, when trained on natural images, produces model neurons which, individually, have many tuning properties in common with real V1 neurons. However, when viewed as a population, a BCM network is very different from V1 – each member of the BCM population tends to respond to the same dominant features of visual input, producing an incomplete, highly redundant code for visual information. Here, we demonstrate that, by adding contrast normalization into the BCM rule, we arrive at a neurally-plausible Hebbian learning rule that can learn an efficient sparse, overcomplete representation that is a better model for stimulus selectivity in V1. This suggests that one role of contrast normalization in V1 is to guide the neonatal development of receptive fields, so that neurons respond to different features of visual input. PMID:22230381

Single neuron modeling and data assimilation in BNST neurons

NASA Astrophysics Data System (ADS)

Farsian, Reza

Neurons, although tiny in size, are vastly complicated systems, which are responsible for the most basic yet essential functions of any nervous system. Even the most simple models of single neurons are usually high dimensional, nonlinear, and contain many parameters and states which are unobservable in a typical neurophysiological experiment. One of the most fundamental problems in experimental neurophysiology is the estimation of these parameters and states, since knowing their values is essential in identification, model construction, and forward prediction of biological neurons. Common methods of parameter and state estimation do not perform well for neural models due to their high dimensionality and nonlinearity. In this dissertation, two alternative approaches for parameters and state estimation of biological neurons have been demonstrated: dynamical parameter estimation (DPE) and a Markov Chain Monte Carlo (MCMC) method. The first method uses elements of chaos control and synchronization theory for parameter and state estimation. MCMC is a statistical approach which uses a path integral formulation to evaluate a mean and an error bound for these unobserved parameters and states. These methods have been applied to biological system of neurons in Bed Nucleus of Stria Termialis neurons (BNST) of rats. State and parameters of neurons in both systems were estimated, and their value were used for recreating a realistic model and predicting the behavior of the neurons successfully. The knowledge of biological parameters can ultimately provide a better understanding of the internal dynamics of a neuron in order to build robust models of neuron networks.

Scoping the parameter space for demo and the engineering test facility (ETF)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Meier, Wayne R.

1999-01-19

In our IFE development plan, we have set a goal of building an Engineering Test Facility (ETF) for a total cost of $2B and a Demo for $3B. In Mike Campbell' s presentation at Madison, we included a viewgraph with an example Demo that had 80 to 250 MWe of net power and showed a plausible argument that it could cost less than $3B. In this memo, I examine the design space for the Demo and then briefly for the ETF. Instead of attempting to estimate the costs of the drivers, I pose the question in a way to definemore » R&D goals: As a function of key design and performance parameters, how much can the driver cost if the total facility cost is limited to the specified goal? The design parameters examined for the Demo included target gain, driver energy, driver efficiency, and net power output. For the ETF; the design parameters are target gain, driver energy, and target yield. The resulting graphs of allowable driver cost determine the goals that the driver R&D programs must seek to meet.« less

Cellular signaling identifiability analysis: a case study.

PubMed

Roper, Ryan T; Pia Saccomani, Maria; Vicini, Paolo

2010-05-21

Two primary purposes for mathematical modeling in cell biology are (1) simulation for making predictions of experimental outcomes and (2) parameter estimation for drawing inferences from experimental data about unobserved aspects of biological systems. While the former purpose has become common in the biological sciences, the latter is less common, particularly when studying cellular and subcellular phenomena such as signaling-the focus of the current study. Data are difficult to obtain at this level. Therefore, even models of only modest complexity can contain parameters for which the available data are insufficient for estimation. In the present study, we use a set of published cellular signaling models to address issues related to global parameter identifiability. That is, we address the following question: assuming known time courses for some model variables, which parameters is it theoretically impossible to estimate, even with continuous, noise-free data? Following an introduction to this problem and its relevance, we perform a full identifiability analysis on a set of cellular signaling models using DAISY (Differential Algebra for the Identifiability of SYstems). We use our analysis to bring to light important issues related to parameter identifiability in ordinary differential equation (ODE) models. We contend that this is, as of yet, an under-appreciated issue in biological modeling and, more particularly, cell biology. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

An evolutionary firefly algorithm for the estimation of nonlinear biological model parameters.

PubMed

Abdullah, Afnizanfaizal; Deris, Safaai; Anwar, Sohail; Arjunan, Satya N V

2013-01-01

The development of accurate computational models of biological processes is fundamental to computational systems biology. These models are usually represented by mathematical expressions that rely heavily on the system parameters. The measurement of these parameters is often difficult. Therefore, they are commonly estimated by fitting the predicted model to the experimental data using optimization methods. The complexity and nonlinearity of the biological processes pose a significant challenge, however, to the development of accurate and fast optimization methods. We introduce a new hybrid optimization method incorporating the Firefly Algorithm and the evolutionary operation of the Differential Evolution method. The proposed method improves solutions by neighbourhood search using evolutionary procedures. Testing our method on models for the arginine catabolism and the negative feedback loop of the p53 signalling pathway, we found that it estimated the parameters with high accuracy and within a reasonable computation time compared to well-known approaches, including Particle Swarm Optimization, Nelder-Mead, and Firefly Algorithm. We have also verified the reliability of the parameters estimated by the method using an a posteriori practical identifiability test.

An Evolutionary Firefly Algorithm for the Estimation of Nonlinear Biological Model Parameters

PubMed Central

Abdullah, Afnizanfaizal; Deris, Safaai; Anwar, Sohail; Arjunan, Satya N. V.

2013-01-01

The development of accurate computational models of biological processes is fundamental to computational systems biology. These models are usually represented by mathematical expressions that rely heavily on the system parameters. The measurement of these parameters is often difficult. Therefore, they are commonly estimated by fitting the predicted model to the experimental data using optimization methods. The complexity and nonlinearity of the biological processes pose a significant challenge, however, to the development of accurate and fast optimization methods. We introduce a new hybrid optimization method incorporating the Firefly Algorithm and the evolutionary operation of the Differential Evolution method. The proposed method improves solutions by neighbourhood search using evolutionary procedures. Testing our method on models for the arginine catabolism and the negative feedback loop of the p53 signalling pathway, we found that it estimated the parameters with high accuracy and within a reasonable computation time compared to well-known approaches, including Particle Swarm Optimization, Nelder-Mead, and Firefly Algorithm. We have also verified the reliability of the parameters estimated by the method using an a posteriori practical identifiability test. PMID:23469172

Crop-model assisted phenomics and genome-wide association study for climate adaptation of indica rice. 2. Thermal stress and spikelet sterility.

PubMed

Dingkuhn, Michael; Pasco, Richard; Pasuquin, Julie Mae; Damo, Jean; Soulié, Jean-Christophe; Raboin, Louis-Marie; Dusserre, Julie; Sow, Abdoulaye; Manneh, Baboucarr; Shrestha, Suchit; Kretzschmar, Tobias

2017-07-10

Low night and high day temperatures during sensitive reproductive stages cause spikelet sterility in rice. Phenotyping of tolerance traits in the field is difficult because of temporal interactions with phenology and organ temperature differing from ambient. Physiological models can be used to separate these effects. A 203-accession indica rice diversity panel was phenotyped for sterility in ten environments in Senegal and Madagascar and climate data were recorded. Here we report on sterility responses while a companion study reported on phenology. The objectives were to improve the RIDEV model of rice thermal sterility, to estimate response traits by fitting model parameters, and to link the response traits to genomic regions through genome-wide association studies (GWAS). RIDEV captured 64% of variation of sterility when cold acclimation during vegetative stage was simulated, but only 38% when it was not. The RIDEV parameters gave more and stronger quantitative trait loci (QTLs) than index variables derived more directly from observation. The 15 QTLs identified at P<1 × 10-5 (33 at P<1 × 10-4) were related to sterility effects of heat, cold, cold acclimation, or unexplained causes (baseline sterility). Nine annotated genes were found on average within the 50% linkage disequilibrium (LD) region. Among them, one to five plausible candidate genes per QTL were identified based on known expression profiles (organ, stage, stress factors) and function. Meiosis-, development- and flowering-related genes were frequent, as well a stress signaling kinases and transcription factors. Putative epigenetic factors such as DNA methylases or histone-related genes were frequent in cold-acclimation QTLs, and positive-effect alleles were frequent in cold-tolerant highland rice from Madagascar. The results indicate that epigenetic control of acclimation may be important in indica rice genotypes adapted to cool environments. © The Author 2017. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

A direct method for computing extreme value (Gumbel) parameters for gapped biological sequence alignments.

PubMed

Quinn, Terrance; Sinkala, Zachariah

2014-01-01

We develop a general method for computing extreme value distribution (Gumbel, 1958) parameters for gapped alignments. Our approach uses mixture distribution theory to obtain associated BLOSUM matrices for gapped alignments, which in turn are used for determining significance of gapped alignment scores for pairs of biological sequences. We compare our results with parameters already obtained in the literature.

Western municipal water conservation policy: The case of disaggregated demand

NASA Astrophysics Data System (ADS)

Burness, Stuart; Chermak, Janie; Krause, Kate

2005-03-01

We investigate aspects of the felicity of both incentive-based and command and control policies in effecting municipal water conservation goals. When demand can be disaggregated according to uses or users, our results suggest that policy efforts be focused on the submarket wherein demand is more elastic. Under plausible consumer parameters, a household production function approach to water utilization prescribes the nature of demand elasticities in alternative uses and squares nicely with empirical results from the literature. An empirical example illustrates. Overall, given data and other informational limitations, extant institutional structures, and in situ technology, our analysis suggests a predisposition for command and control policies over incentive-based tools.

Filter Strategies for Mars Science Laboratory Orbit Determination

NASA Technical Reports Server (NTRS)

Thompson, Paul F.; Gustafson, Eric D.; Kruizinga, Gerhard L.; Martin-Mur, Tomas J.

2013-01-01

The Mars Science Laboratory (MSL) spacecraft had ambitious navigation delivery and knowledge accuracy requirements for landing inside Gale Crater. Confidence in the orbit determination (OD) solutions was increased by investigating numerous filter strategies for solving the orbit determination problem. We will discuss the strategy for the different types of variations: for example, data types, data weights, solar pressure model covariance, and estimating versus considering model parameters. This process generated a set of plausible OD solutions that were compared to the baseline OD strategy. Even implausible or unrealistic results were helpful in isolating sensitivities in the OD solutions to certain model parameterizations or data types.

On the RNG theory of turbulence

NASA Technical Reports Server (NTRS)

Lam, S. H.

1992-01-01

The Yakhot and Orszag (1986) renormalization group (RNG) theory of turbulence has generated a number of scaling law constants in reasonable quantitative agreement with experiments. The theory itself is highly mathematical, and its assumptions and approximations are not easily appreciated. The present paper reviews the RNG theory and recasts it in more conventional terms using a distinctly different viewpoint. A new formulation based on an alternative interpretation of the origin of the random force is presented, showing that the artificially introduced epsilon in the original theory is an adjustable parameter, thus offering a plausible explanation for the remarkable record of quantitative success of the so-called epsilon-expansion procedure.

Perspectives on the Use of Algae as Biological Indicators for Monitoring and Protecting Aquatic Environments, with Special Reference to Malaysian Freshwater Ecosystems

PubMed Central

Omar, Wan Maznah Wan

2010-01-01

Algal communities possess many attributes as biological indicators of spatial and temporal environmental changes. Algal parameters, especially the community structural and functional variables that have been used in biological monitoring programs, are highlighted in this document. Biological indicators like algae have only recently been included in water quality assessments in some areas of Malaysia. The use of algal parameters in identifying various types of water degradation is essential and complementary to other environmental indicators. PMID:24575199

Assessing compatibility of direct detection data: halo-independent global likelihood analyses

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gelmini, Graciela B.; Huh, Ji-Haeng; Witte, Samuel J.

2016-10-18

We present two different halo-independent methods to assess the compatibility of several direct dark matter detection data sets for a given dark matter model using a global likelihood consisting of at least one extended likelihood and an arbitrary number of Gaussian or Poisson likelihoods. In the first method we find the global best fit halo function (we prove that it is a unique piecewise constant function with a number of down steps smaller than or equal to a maximum number that we compute) and construct a two-sided pointwise confidence band at any desired confidence level, which can then be comparedmore » with those derived from the extended likelihood alone to assess the joint compatibility of the data. In the second method we define a “constrained parameter goodness-of-fit” test statistic, whose p-value we then use to define a “plausibility region” (e.g. where p≥10%). For any halo function not entirely contained within the plausibility region, the level of compatibility of the data is very low (e.g. p<10%). We illustrate these methods by applying them to CDMS-II-Si and SuperCDMS data, assuming dark matter particles with elastic spin-independent isospin-conserving interactions or exothermic spin-independent isospin-violating interactions.« less

Yoga for Depression and Anxiety: A Review of Published Research and Implications for Healthcare Providers.

PubMed

Uebelacker, Lisa A; Broughton, Monica K

2016-03-01

There is increasing interest in the use of yoga as way to manage or treat depression and anxiety. Yoga is afford- able, appealing, and accessible for many people, and there are plausible cognitive/affective and biologic mechanisms by which yoga could have a positive impact on depression and anxiety. There is indeed preliminary evidence that yoga may be helpful for these problems, and there are several ongoing larger-scale randomized clinical trials. The current evidence base is strongest for yoga as efficacious in reducing symptoms of unipolar depression. However, there may be risks to engaging in yoga as well. Healthcare providers can help patients evaluate whether a particular community-based yoga class is helpful and safe for them.

The Role of Omega-3 Fatty Acids in Developmental Psychopathology: A Systematic Review on Early Psychosis, Autism, and ADHD

PubMed Central

Nobile, Maria; Ciappolino, Valentina; Delvecchio, Giuseppe; Tesei, Alessandra; Turolo, Stefano; Crippa, Alessandro; Mazzocchi, Alessandra; Altamura, Carlo A.; Brambilla, Paolo

2017-01-01

In this systematic review, we will consider and debate studies that have explored the effects of ω-3 polyunsaturated fatty acids (PUFAs) in three major, and somehow related, developmental psychiatric disorders: Autism, Attention Deficit and Hyperactivity disorder and Psychosis. The impact of ω-3 PUFAs on clinical symptoms and, if possible, brain trajectory in children and adolescents suffering from these illnesses will be reviewed and discussed, considering the biological plausibility of the effects of omega-3 fatty acids, together with their potential perspectives in the field. Heterogeneity in study designs will be discussed in the light of differences in results and interpretation of studies carried out so far. PMID:29207548

Evidence-based cancer prevention recommendations for Japanese.

PubMed

Sasazuki, S; Inoue, M; Shimazu, T; Wakai, K; Naito, M; Nagata, C; Tanaka, K; Tsuji, I; Sugawara, Y; Mizoue, T; Matsuo, K; Ito, H; Tamakoshi, A; Sawada, N; Nakayama, T; Kitamura, Y; Sadakane, A; Tsugane, S

2018-06-01

A comprehensive evidence-based cancer prevention recommendation for Japanese was developed. We evaluated the magnitude of the associations of lifestyle factors and infection with cancer through a systematic review of the literature, meta-analysis of published data, and pooled analysis of cohort studies in Japan. Then, we judged the strength of evidence based on the consistency of the associations between exposure and cancer and biological plausibility. Important factors were extracted and summarized as an evidence-based, current cancer prevention recommendation: 'Cancer Prevention Recommendation for Japanese'. The recommendation addresses six important domains related to exposure and cancer, including smoking, alcohol drinking, diet, physical activity, body weight and infection. The next step should focus on the development of effective behavior modification programs and their implementation and dissemination.

Human expunction

NASA Astrophysics Data System (ADS)

Klee, Robert

2017-10-01

Thomas Nagel in `The Absurd' (Nagel 1971) mentions the future expunction of the human species as a `metaphor' for our ability to see our lives from the outside, which he claims is one source of our sense of life's absurdity. I argue that the future expunction (not to be confused with extinction) of everything human - indeed of everything biological in a terran sense - is not a mere metaphor but a physical certainty under the laws of nature. The causal processes by which human expunction will take place are presented in some empirical detail, so that philosophers cannot dismiss it as merely speculative. I also argue that appeals to anthropic principles or to forms of mystical cosmology are of no plausible avail in the face of human expunction under the laws of physics.

Semantics-based plausible reasoning to extend the knowledge coverage of medical knowledge bases for improved clinical decision support.

PubMed

Mohammadhassanzadeh, Hossein; Van Woensel, William; Abidi, Samina Raza; Abidi, Syed Sibte Raza

2017-01-01

Capturing complete medical knowledge is challenging-often due to incomplete patient Electronic Health Records (EHR), but also because of valuable, tacit medical knowledge hidden away in physicians' experiences. To extend the coverage of incomplete medical knowledge-based systems beyond their deductive closure, and thus enhance their decision-support capabilities, we argue that innovative, multi-strategy reasoning approaches should be applied. In particular, plausible reasoning mechanisms apply patterns from human thought processes, such as generalization, similarity and interpolation, based on attributional, hierarchical, and relational knowledge. Plausible reasoning mechanisms include inductive reasoning , which generalizes the commonalities among the data to induce new rules, and analogical reasoning , which is guided by data similarities to infer new facts. By further leveraging rich, biomedical Semantic Web ontologies to represent medical knowledge, both known and tentative, we increase the accuracy and expressivity of plausible reasoning, and cope with issues such as data heterogeneity, inconsistency and interoperability. In this paper, we present a Semantic Web-based, multi-strategy reasoning approach, which integrates deductive and plausible reasoning and exploits Semantic Web technology to solve complex clinical decision support queries. We evaluated our system using a real-world medical dataset of patients with hepatitis, from which we randomly removed different percentages of data (5%, 10%, 15%, and 20%) to reflect scenarios with increasing amounts of incomplete medical knowledge. To increase the reliability of the results, we generated 5 independent datasets for each percentage of missing values, which resulted in 20 experimental datasets (in addition to the original dataset). The results show that plausibly inferred knowledge extends the coverage of the knowledge base by, on average, 2%, 7%, 12%, and 16% for datasets with, respectively, 5%, 10%, 15%, and 20% of missing values. This expansion in the KB coverage allowed solving complex disease diagnostic queries that were previously unresolvable, without losing the correctness of the answers. However, compared to deductive reasoning, data-intensive plausible reasoning mechanisms yield a significant performance overhead. We observed that plausible reasoning approaches, by generating tentative inferences and leveraging domain knowledge of experts, allow us to extend the coverage of medical knowledge bases, resulting in improved clinical decision support. Second, by leveraging OWL ontological knowledge, we are able to increase the expressivity and accuracy of plausible reasoning methods. Third, our approach is applicable to clinical decision support systems for a range of chronic diseases.

Trans-dimensional matched-field geoacoustic inversion with hierarchical error models and interacting Markov chains.

PubMed

Dettmer, Jan; Dosso, Stan E

2012-10-01

This paper develops a trans-dimensional approach to matched-field geoacoustic inversion, including interacting Markov chains to improve efficiency and an autoregressive model to account for correlated errors. The trans-dimensional approach and hierarchical seabed model allows inversion without assuming any particular parametrization by relaxing model specification to a range of plausible seabed models (e.g., in this case, the number of sediment layers is an unknown parameter). Data errors are addressed by sampling statistical error-distribution parameters, including correlated errors (covariance), by applying a hierarchical autoregressive error model. The well-known difficulty of low acceptance rates for trans-dimensional jumps is addressed with interacting Markov chains, resulting in a substantial increase in efficiency. The trans-dimensional seabed model and the hierarchical error model relax the degree of prior assumptions required in the inversion, resulting in substantially improved (more realistic) uncertainty estimates and a more automated algorithm. In particular, the approach gives seabed parameter uncertainty estimates that account for uncertainty due to prior model choice (layering and data error statistics). The approach is applied to data measured on a vertical array in the Mediterranean Sea.

Speed of CMEs and the Magnetic Non-Potentiality of their Source Active Regions

NASA Technical Reports Server (NTRS)

Tiwari, Sanjiv Kumar; Falconer, David Allen; Moore, Ronald L.; Venkatakrishnan, P.; Winebarger, Amy R.; Khazanov, Igor G.

2014-01-01

Most fast coronal mass ejections (CMEs) originate from solar active regions (ARs). Non-potentiality of ARs plausibly determines the speed of CMEs in the outer corona. Several other unexplored parameters might be important as well. To find out the relation between the intial speed of CMEs and the non-potentiality of source ARs, we identified over a hundred of CMEs with source ARs via their co-produced flares. The speed of the CMEs are collected from the SOHO LASCO CME catalog. We have used vector magnetograms obtained with HMI/SDO, to evaluate various magnetic non-potentiality parameters, e.g. magnetic free-energy proxies, twist, shear angle, signed shear angle, net current etc. We have also included several other parameters e.g. total unsigned flux, magnetic area of ARs, area of sunspots, to investigate their correlation, if any, with the initial speeds of CMEs. Our preliminary results show that the ARs with larger non-potentiality and area produce faster CMEs but they can also produce slow ones. The ARs with lesser non-potentiality and area generally produce only slower CMEs.

The Evolution of Globular Cluster Systems In Early-Type Galaxies

NASA Astrophysics Data System (ADS)

Grillmair, Carl

1999-07-01

We will measure structural parameters {core radii and concentrations} of globular clusters in three early-type galaxies using deep, four-point dithered observations. We have chosen globular cluster systems which have young, medium-age and old cluster populations, as indicated by cluster colors and luminosities. Our primary goal is to test the hypothesis that globular cluster luminosity functions evolve towards a ``universal'' form. Previous observations have shown that young cluster systems have exponential luminosity functions rather than the characteristic log-normal luminosity function of old cluster systems. We will test to see whether such young system exhibits a wider range of structural parameters than an old systems, and whether and at what rate plausible disruption mechanisms will cause the luminosity function to evolve towards a log-normal form. A simple observational comparison of structural parameters between different age cluster populations and between diff er ent sub-populations within the same galaxy will also provide clues concerning both the formation and destruction mechanisms of star clusters, the distinction between open and globular clusters, and the advisability of using globular cluster luminosity functions as distance indicators.

Cerebellar-inspired algorithm for adaptive control of nonlinear dielectric elastomer-based artificial muscle

PubMed Central

Assaf, Tareq; Rossiter, Jonathan M.; Porrill, John

2016-01-01

Electroactive polymer actuators are important for soft robotics, but can be difficult to control because of compliance, creep and nonlinearities. Because biological control mechanisms have evolved to deal with such problems, we investigated whether a control scheme based on the cerebellum would be useful for controlling a nonlinear dielectric elastomer actuator, a class of artificial muscle. The cerebellum was represented by the adaptive filter model, and acted in parallel with a brainstem, an approximate inverse plant model. The recurrent connections between the two allowed for direct use of sensory error to adjust motor commands. Accurate tracking of a displacement command in the actuator's nonlinear range was achieved by either semi-linear basis functions in the cerebellar model or semi-linear functions in the brainstem corresponding to recruitment in biological muscle. In addition, allowing transfer of training between cerebellum and brainstem as has been observed in the vestibulo-ocular reflex prevented the steady increase in cerebellar output otherwise required to deal with creep. The extensibility and relative simplicity of the cerebellar-based adaptive-inverse control scheme suggests that it is a plausible candidate for controlling this type of actuator. Moreover, its performance highlights important features of biological control, particularly nonlinear basis functions, recruitment and transfer of training. PMID:27655667

Phytochemical and biological studies of Atriplex inflata f. Muell.: isolation of secondary bioactive metabolites.

PubMed

Ben Nejma, Aymen; Znati, Mansour; Nguir, Asma; Daich, Adam; Othman, Mohamed; Lawson, Ata Martin; Ben Jannet, Hichem

2017-08-01

This work describes the phytochemical and biological investigation of the Tunisian Atriplex inflata F. Muell (Chenopodiaceae). Their chemical structures were elucidated on the basis of extensive spectroscopic methods, including 1D NMR and 2D NMR, ESI-HRMS and comparison with available literature data. The isolates were evaluated for their antioxidant activity by the DPPH • , ABTS +• , Fe 3+ and catalase assays and also for their antibacterial and anticholinesterase activity. The chemical study of Atriplex inflata F. Muell led to the isolation of two fatty acids (9E)-methyl-8,11,12-trihydroxyoctadec-9-enoate 1 and (9E)-8,11,12-trihydroxyoctadecenoic acid 2 together with (Z)-litchiol B 3 and 20-hydroxyecdysone 4. Three of which are reported here for the first time in Atriplex genus. Based on the biosynthesis of hydroxylated arachidonic acid and derivatives, a plausible biogenesis pathway of the two fatty acids (1 and 2) was proposed. (Z)-litchiol B (3) was found to be the most active against Staphylococcus aureus. According to the literature, this is the first time that compounds 1, 2 and 3 were tested for their eventual biological activity. In the results of the present work, we have proposed the biogenesis pathway of unsaturated fatty acid and described the structure-activity relationship. © 2017 Royal Pharmaceutical Society.

Application of plausible reasoning to AI-based control systems

NASA Technical Reports Server (NTRS)

Berenji, Hamid; Lum, Henry, Jr.

1987-01-01

Some current approaches to plausible reasoning in artificial intelligence are reviewed and discussed. Some of the most significant recent advances in plausible and approximate reasoning are examined. A synergism among the techniques of uncertainty management is advocated, and brief discussions on the certainty factor approach, probabilistic approach, Dempster-Shafer theory of evidence, possibility theory, linguistic variables, and fuzzy control are presented. Some extensions to these methods are described, and the applications of the methods are considered.

Dynamical compensation and structural identifiability of biological models: Analysis, implications, and reconciliation

PubMed Central

2017-01-01

The concept of dynamical compensation has been recently introduced to describe the ability of a biological system to keep its output dynamics unchanged in the face of varying parameters. However, the original definition of dynamical compensation amounts to lack of structural identifiability. This is relevant if model parameters need to be estimated, as is often the case in biological modelling. Care should we taken when using an unidentifiable model to extract biological insight: the estimated values of structurally unidentifiable parameters are meaningless, and model predictions about unmeasured state variables can be wrong. Taking this into account, we explore alternative definitions of dynamical compensation that do not necessarily imply structural unidentifiability. Accordingly, we show different ways in which a model can be made identifiable while exhibiting dynamical compensation. Our analyses enable the use of the new concept of dynamical compensation in the context of parameter identification, and reconcile it with the desirable property of structural identifiability. PMID:29186132

Quantitative evaluations of mechanisms of radiofrequency interactions with biological molecules and processes.

PubMed

Sheppard, Asher R; Swicord, Mays L; Balzano, Quirino

2008-10-01

The complexity of interactions of electromagnetic fields up to 10(12) Hz with the ions, atoms, and molecules of biological systems has given rise to a large number of established and proposed biophysical mechanisms applicable over a wide range of time and distance scales, field amplitudes, frequencies, and waveforms. This review focuses on the physical principles that guide quantitative assessment of mechanisms applicable for exposures at or below the level of endogenous electric fields associated with development, wound healing, and excitation of muscles and the nervous system (generally, 1 to 10(2) V m(-1)), with emphasis on conditions where temperature increases are insignificant (<1 K). Experiment and theory demonstrate possible demodulation at membrane barriers for frequencies < or =10 MHz, but not at higher frequencies. Although signal levels somewhat below system noise can be detected, signal-to-noise ratios substantially less than 0.1 cannot be overcome by cooperativity, signal averaging, coherent detection, or by nonlinear dynamical systems. Sensory systems and possible effects on biological magnetite suggest paradigms for extreme sensitivity at lower frequencies, but there are no known radiofrequency (RF) analogues. At the molecular level, vibrational modes are so overdamped by water molecules that excitation of molecular modes below the far infrared cannot occur. Two RF mechanisms plausibly may affect biological matter under common exposure conditions. For frequencies below approximately 150 MHz, shifts in the rate of chemical reactions can be mediated by radical pairs and, at all frequencies, dielectric and resistive heating can raise temperature and increase the entropy of the affected biological system.

Integrated Bio-Entity Network: A System for Biological Knowledge Discovery

PubMed Central

Bell, Lindsey; Chowdhary, Rajesh; Liu, Jun S.; Niu, Xufeng; Zhang, Jinfeng

2011-01-01

A significant part of our biological knowledge is centered on relationships between biological entities (bio-entities) such as proteins, genes, small molecules, pathways, gene ontology (GO) terms and diseases. Accumulated at an increasing speed, the information on bio-entity relationships is archived in different forms at scattered places. Most of such information is buried in scientific literature as unstructured text. Organizing heterogeneous information in a structured form not only facilitates study of biological systems using integrative approaches, but also allows discovery of new knowledge in an automatic and systematic way. In this study, we performed a large scale integration of bio-entity relationship information from both databases containing manually annotated, structured information and automatic information extraction of unstructured text in scientific literature. The relationship information we integrated in this study includes protein–protein interactions, protein/gene regulations, protein–small molecule interactions, protein–GO relationships, protein–pathway relationships, and pathway–disease relationships. The relationship information is organized in a graph data structure, named integrated bio-entity network (IBN), where the vertices are the bio-entities and edges represent their relationships. Under this framework, graph theoretic algorithms can be designed to perform various knowledge discovery tasks. We designed breadth-first search with pruning (BFSP) and most probable path (MPP) algorithms to automatically generate hypotheses—the indirect relationships with high probabilities in the network. We show that IBN can be used to generate plausible hypotheses, which not only help to better understand the complex interactions in biological systems, but also provide guidance for experimental designs. PMID:21738677

Stress and reproductive failure: past notions, present insights and future directions

PubMed Central

Sheps, Sam; Clara Arck, Petra

2008-01-01

Problem Maternal stress perception is frequently alleged as a cause of infertility, miscarriages, late pregnancy complications or impaired fetal development. The purpose of the present review is to critically assess the biological and epidemiological evidence that considers the plausibility of a stress link to human reproductive failure. Methods All epidemiological studies published between 1980 and 2007 that tested the link between stress exposure and impaired reproductive success in humans were identified. Study outcomes were evaluated on the basis of how associations were predicted, tested and integrated with theories of etiology arising from recent scientific developments in the basic sciences. Further, published evidence arising from basic science research has been assessed in order to provide a mechanistic concept and biological evidence for the link between stress perception and reproductive success. Results Biological evidence points to an immune–endocrine disequilibrium in response to stress and describes a hierarchy of biological mediators involved in a stress trigger to reproductive failure. Epidemiological evidence presents positive correlations between various pregnancy failure outcomes with pre-conception negative life events and elevated daily urinary cortisol. Strikingly, a relatively new conceptual approach integrating the two strands of evidence suggests the programming of stress susceptibility in mother and fetus via a so-called pregnancy stress syndrome. Conclusions An increasing specificity of knowledge is available about the types and impact of biological and social pathways involved in maternal stress responses. The present evidence is sufficient to warrant a reconsideration of conventional views on the etiology of reproductive failure. Physicians and patients will benefit from the adaptation of this integrated evidence to daily clinical practice. PMID:18274890

Universally Sloppy Parameter Sensitivities in Systems Biology Models

PubMed Central

Gutenkunst, Ryan N; Waterfall, Joshua J; Casey, Fergal P; Brown, Kevin S; Myers, Christopher R; Sethna, James P

2007-01-01

Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring in vivo biochemical parameters is difficult, and collectively fitting them to other experimental data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling model that collective fitting could yield well-constrained predictions, even when it left individual parameters very poorly constrained. We also showed that the model had a “sloppy” spectrum of parameter sensitivities, with eigenvalues roughly evenly distributed over many decades. Here we use a collection of models from the literature to test whether such sloppy spectra are common in systems biology. Strikingly, we find that every model we examine has a sloppy spectrum of sensitivities. We also test several consequences of this sloppiness for building predictive models. In particular, sloppiness suggests that collective fits to even large amounts of ideal time-series data will often leave many parameters poorly constrained. Tests over our model collection are consistent with this suggestion. This difficulty with collective fits may seem to argue for direct parameter measurements, but sloppiness also implies that such measurements must be formidably precise and complete to usefully constrain many model predictions. We confirm this implication in our growth-factor-signaling model. Our results suggest that sloppy sensitivity spectra are universal in systems biology models. The prevalence of sloppiness highlights the power of collective fits and suggests that modelers should focus on predictions rather than on parameters. PMID:17922568

Universally sloppy parameter sensitivities in systems biology models.

PubMed

Gutenkunst, Ryan N; Waterfall, Joshua J; Casey, Fergal P; Brown, Kevin S; Myers, Christopher R; Sethna, James P

2007-10-01

Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring in vivo biochemical parameters is difficult, and collectively fitting them to other experimental data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling model that collective fitting could yield well-constrained predictions, even when it left individual parameters very poorly constrained. We also showed that the model had a "sloppy" spectrum of parameter sensitivities, with eigenvalues roughly evenly distributed over many decades. Here we use a collection of models from the literature to test whether such sloppy spectra are common in systems biology. Strikingly, we find that every model we examine has a sloppy spectrum of sensitivities. We also test several consequences of this sloppiness for building predictive models. In particular, sloppiness suggests that collective fits to even large amounts of ideal time-series data will often leave many parameters poorly constrained. Tests over our model collection are consistent with this suggestion. This difficulty with collective fits may seem to argue for direct parameter measurements, but sloppiness also implies that such measurements must be formidably precise and complete to usefully constrain many model predictions. We confirm this implication in our growth-factor-signaling model. Our results suggest that sloppy sensitivity spectra are universal in systems biology models. The prevalence of sloppiness highlights the power of collective fits and suggests that modelers should focus on predictions rather than on parameters.

[Effects of biologically active pectin-containing dietary supplement on gastroduodenal motility in patients with a functional dyspepsia].

PubMed

Loranskaia, T I; Kabanova, I N; Klykova, E V

2002-01-01

For 21 patients with a functional dyspepsia the influencing biologically active additives to nutrition "Pekcecom" on dynamics of clinical symptoms and parameters gastroduodenal motility under the data gastroduodenoscintigraphy was studied. The usage of biologically active additives during 4 weeks was accompanied by deboosting of accelerated gastric emptying for want of statistically significant influencing on a normal and delayed gastric emptying and parameters of duodenal transit.

Automated numerical simulation of biological pattern formation based on visual feedback simulation framework

PubMed Central

Sun, Mingzhu; Xu, Hui; Zeng, Xingjuan; Zhao, Xin

2017-01-01

There are various fantastic biological phenomena in biological pattern formation. Mathematical modeling using reaction-diffusion partial differential equation systems is employed to study the mechanism of pattern formation. However, model parameter selection is both difficult and time consuming. In this paper, a visual feedback simulation framework is proposed to calculate the parameters of a mathematical model automatically based on the basic principle of feedback control. In the simulation framework, the simulation results are visualized, and the image features are extracted as the system feedback. Then, the unknown model parameters are obtained by comparing the image features of the simulation image and the target biological pattern. Considering two typical applications, the visual feedback simulation framework is applied to fulfill pattern formation simulations for vascular mesenchymal cells and lung development. In the simulation framework, the spot, stripe, labyrinthine patterns of vascular mesenchymal cells, the normal branching pattern and the branching pattern lacking side branching for lung branching are obtained in a finite number of iterations. The simulation results indicate that it is easy to achieve the simulation targets, especially when the simulation patterns are sensitive to the model parameters. Moreover, this simulation framework can expand to other types of biological pattern formation. PMID:28225811

Automated numerical simulation of biological pattern formation based on visual feedback simulation framework.

PubMed

Sun, Mingzhu; Xu, Hui; Zeng, Xingjuan; Zhao, Xin

2017-01-01

There are various fantastic biological phenomena in biological pattern formation. Mathematical modeling using reaction-diffusion partial differential equation systems is employed to study the mechanism of pattern formation. However, model parameter selection is both difficult and time consuming. In this paper, a visual feedback simulation framework is proposed to calculate the parameters of a mathematical model automatically based on the basic principle of feedback control. In the simulation framework, the simulation results are visualized, and the image features are extracted as the system feedback. Then, the unknown model parameters are obtained by comparing the image features of the simulation image and the target biological pattern. Considering two typical applications, the visual feedback simulation framework is applied to fulfill pattern formation simulations for vascular mesenchymal cells and lung development. In the simulation framework, the spot, stripe, labyrinthine patterns of vascular mesenchymal cells, the normal branching pattern and the branching pattern lacking side branching for lung branching are obtained in a finite number of iterations. The simulation results indicate that it is easy to achieve the simulation targets, especially when the simulation patterns are sensitive to the model parameters. Moreover, this simulation framework can expand to other types of biological pattern formation.

Online model checking approach based parameter estimation to a neuronal fate decision simulation model in Caenorhabditis elegans with hybrid functional Petri net with extension.

PubMed

Li, Chen; Nagasaki, Masao; Koh, Chuan Hock; Miyano, Satoru

2011-05-01

Mathematical modeling and simulation studies are playing an increasingly important role in helping researchers elucidate how living organisms function in cells. In systems biology, researchers typically tune many parameters manually to achieve simulation results that are consistent with biological knowledge. This severely limits the size and complexity of simulation models built. In order to break this limitation, we propose a computational framework to automatically estimate kinetic parameters for a given network structure. We utilized an online (on-the-fly) model checking technique (which saves resources compared to the offline approach), with a quantitative modeling and simulation architecture named hybrid functional Petri net with extension (HFPNe). We demonstrate the applicability of this framework by the analysis of the underlying model for the neuronal cell fate decision model (ASE fate model) in Caenorhabditis elegans. First, we built a quantitative ASE fate model containing 3327 components emulating nine genetic conditions. Then, using our developed efficient online model checker, MIRACH 1.0, together with parameter estimation, we ran 20-million simulation runs, and were able to locate 57 parameter sets for 23 parameters in the model that are consistent with 45 biological rules extracted from published biological articles without much manual intervention. To evaluate the robustness of these 57 parameter sets, we run another 20 million simulation runs using different magnitudes of noise. Our simulation results concluded that among these models, one model is the most reasonable and robust simulation model owing to the high stability against these stochastic noises. Our simulation results provide interesting biological findings which could be used for future wet-lab experiments.

Biological data assimilation for parameter estimation of a phytoplankton functional type model for the western North Pacific

NASA Astrophysics Data System (ADS)

Hoshiba, Yasuhiro; Hirata, Takafumi; Shigemitsu, Masahito; Nakano, Hideyuki; Hashioka, Taketo; Masuda, Yoshio; Yamanaka, Yasuhiro

2018-06-01

Ecosystem models are used to understand ecosystem dynamics and ocean biogeochemical cycles and require optimum physiological parameters to best represent biological behaviours. These physiological parameters are often tuned up empirically, while ecosystem models have evolved to increase the number of physiological parameters. We developed a three-dimensional (3-D) lower-trophic-level marine ecosystem model known as the Nitrogen, Silicon and Iron regulated Marine Ecosystem Model (NSI-MEM) and employed biological data assimilation using a micro-genetic algorithm to estimate 23 physiological parameters for two phytoplankton functional types in the western North Pacific. The estimation of the parameters was based on a one-dimensional simulation that referenced satellite data for constraining the physiological parameters. The 3-D NSI-MEM optimized by the data assimilation improved the timing of a modelled plankton bloom in the subarctic and subtropical regions compared to the model without data assimilation. Furthermore, the model was able to improve not only surface concentrations of phytoplankton but also their subsurface maximum concentrations. Our results showed that surface data assimilation of physiological parameters from two contrasting observatory stations benefits the representation of vertical plankton distribution in the western North Pacific.

Beyond terrestrial biology: charting the chemical universe of α-amino acid structures.

PubMed

Meringer, Markus; Cleaves, H James; Freeland, Stephen J

2013-11-25

α-Amino acids are fundamental to biochemistry as the monomeric building blocks with which cells construct proteins according to genetic instructions. However, the 20 amino acids of the standard genetic code represent a tiny fraction of the number of α-amino acid chemical structures that could plausibly play such a role, both from the perspective of natural processes by which life emerged and evolved, and from the perspective of human-engineered genetically coded proteins. Until now, efforts to describe the structures comprising this broader set, or even estimate their number, have been hampered by the complex combinatorial properties of organic molecules. Here, we use computer software based on graph theory and constructive combinatorics in order to conduct an efficient and exhaustive search of the chemical structures implied by two careful and precise definitions of the α-amino acids relevant to coded biological proteins. Our results include two virtual libraries of α-amino acid structures corresponding to these different approaches, comprising 121 044 and 3 846 structures, respectively, and suggest a simple approach to exploring much larger, as yet uncomputed, libraries of interest.

Obesity and Natriuretic Peptides, BNP and NT-proBNP: Mechanisms and Diagnostic Implications for Heart Failure

PubMed Central

Madamanchi, Chaitanya; Alhosaini, Hassan; Sumida, Arihiro; Runge, Marschall S.

2014-01-01

Many advances have been made in the diagnosis and management of heart failure (HF) in recent years. Cardiac biomarkers are an essential tool for clinicians: point of care B-Type Natriuretic Peptide (BNP) and its N-terminal counterpart (NT-proBNP) levels help distinguish cardiac from non-cardiac causes of dyspnea and are also useful in the prognosis and monitoring of the efficacy of therapy. One of the major limitations of HF biomarkers is in obese patients where the relationship between BNP and NT-proBNP levels and myocardial stiffness is complex. Recent data suggest an inverse relationship between BNP and NT-proBNP levels and body mass index. Given the ever-increasing prevalence of obesity world-wide, it is important to understand the benefits and limitations of HF biomarkers in this population. This review will explore the biology, physiology, and pathophysiology of these peptides and the cardiac endocrine paradox in HF. We also examine the clinical evidence, mechanisms, and plausible biological explanations for the discord between BNP levels and HF in obese patients. PMID:25156856

Energy Drinks and Myocardial Ischemia: A Review of Case Reports.

PubMed

Lippi, Giuseppe; Cervellin, Gianfranco; Sanchis-Gomar, Fabian

2016-07-01

The use and abuse of energy drinks (EDs) is constantly increasing worldwide. We performed a systematic search in Medline, Scopus and Web of Science to identify evidence about the potential link between these beverages and myocardial ischemia. Overall, 8 case reports could be detected, all of which described a realistic association between large intake of EDs and episodes of myocardial ischemia. Interestingly, no additional triggers of myocardial ischemia other than energy drinks could be identified in the vast majority of cases. Some plausible explanations can be brought in support of this association. Most of the biological effects of EDs are seemingly mediated by a positive inotropic effect on cardiac function, which entails increase in heart rate, cardiac output and contractility, stroke volume and arterial blood pressure. Additional biological abnormalities reported after EDs intake include increased platelet aggregation, endothelial dysfunction, hyperglycemia as well as an increase in total cholesterol, triglycerides and low-density lipoprotein cholesterol. Although a causal relationship between large consumption of EDs and myocardial ischemia cannot be definitely established so far, concerns about the cardiovascular risk of excessive consumption of these beverages are seemingly justified.

Activation and Resolution of Periodontal Inflammation and Its Systemic Impact

PubMed Central

Hasturk, Hatice; Kantarci, Alpdogan

2015-01-01

Inflammation is a highly organized event impacting upon organs, tissues and biological systems. Periodontal diseases are characterized by dysregulation or dysfunction of resolution pathways of inflammation resulting in a failure of healing and a dominant chronic, progressive, destructive and predominantly unresolved inflammation. The biological consequences of inflammatory processes may be independent of the etiological agents such as trauma, microbial organisms and stress. The impact of the inflammatory pathological process depends upon the affected tissues or organ system. Whilst mediators are similar, there is a tissue specificity for the inflammatory events. It is plausible that inflammatory processes in one organ could directly lead to pathologies in another organ or tissue. Communication between distant parts of the body and their inflammatory status is also mediated by common signaling mechanisms mediated via cells and soluble mediators. This review focuses on periodontal inflammation, its systemic associations and advances in therapeutic approaches based on mediators acting through orchestration of natural pathway to resolution of inflammation. We also discuss a new treatment concept where natural pathways of resolution of periodontal inflammation can be used to limit systemic inflammation and promote healing and regeneration. PMID:26252412

Optoelectronic analogs of self-programming neural nets - Architecture and methodologies for implementing fast stochastic learning by simulated annealing

NASA Technical Reports Server (NTRS)

Farhat, Nabil H.

1987-01-01

Self-organization and learning is a distinctive feature of neural nets and processors that sets them apart from conventional approaches to signal processing. It leads to self-programmability which alleviates the problem of programming complexity in artificial neural nets. In this paper architectures for partitioning an optoelectronic analog of a neural net into distinct layers with prescribed interconnectivity pattern to enable stochastic learning by simulated annealing in the context of a Boltzmann machine are presented. Stochastic learning is of interest because of its relevance to the role of noise in biological neural nets. Practical considerations and methodologies for appreciably accelerating stochastic learning in such a multilayered net are described. These include the use of parallel optical computing of the global energy of the net, the use of fast nonvolatile programmable spatial light modulators to realize fast plasticity, optical generation of random number arrays, and an adaptive noisy thresholding scheme that also makes stochastic learning more biologically plausible. The findings reported predict optoelectronic chips that can be used in the realization of optical learning machines.

RNAfbinv: an interactive Java application for fragment-based design of RNA sequences.

PubMed

Weinbrand, Lina; Avihoo, Assaf; Barash, Danny

2013-11-15

In RNA design problems, it is plausible to assume that the user would be interested in preserving a particular RNA secondary structure motif, or fragment, for biological reasons. The preservation could be in structure or sequence, or both. Thus, the inverse RNA folding problem could benefit from considering fragment constraints. We have developed a new interactive Java application called RNA fragment-based inverse that allows users to insert an RNA secondary structure in dot-bracket notation. It then performs sequence design that conforms to the shape of the input secondary structure, the specified thermodynamic stability, the specified mutational robustness and the user-selected fragment after shape decomposition. In this shape-based design approach, specific RNA structural motifs with known biological functions are strictly enforced, while others can possess more flexibility in their structure in favor of preserving physical attributes and additional constraints. RNAfbinv is freely available for download on the web at http://www.cs.bgu.ac.il/~RNAexinv/RNAfbinv. The site contains a help file with an explanation regarding the exact use.

Simulating Flying Insects Using Dynamics and Data-Driven Noise Modeling to Generate Diverse Collective Behaviors

PubMed Central

Ren, Jiaping; Wang, Xinjie; Manocha, Dinesh

2016-01-01

We present a biologically plausible dynamics model to simulate swarms of flying insects. Our formulation, which is based on biological conclusions and experimental observations, is designed to simulate large insect swarms of varying densities. We use a force-based model that captures different interactions between the insects and the environment and computes collision-free trajectories for each individual insect. Furthermore, we model the noise as a constructive force at the collective level and present a technique to generate noise-induced insect movements in a large swarm that are similar to those observed in real-world trajectories. We use a data-driven formulation that is based on pre-recorded insect trajectories. We also present a novel evaluation metric and a statistical validation approach that takes into account various characteristics of insect motions. In practice, the combination of Curl noise function with our dynamics model is used to generate realistic swarm simulations and emergent behaviors. We highlight its performance for simulating large flying swarms of midges, fruit fly, locusts and moths and demonstrate many collective behaviors, including aggregation, migration, phase transition, and escape responses. PMID:27187068

Hot Spots in a Network of Functional Sites

PubMed Central

Ozbek, Pemra; Soner, Seren; Haliloglu, Turkan

2013-01-01

It is of significant interest to understand how proteins interact, which holds the key phenomenon in biological functions. Using dynamic fluctuations in high frequency modes, we show that the Gaussian Network Model (GNM) predicts hot spot residues with success rates ranging between S 8–58%, C 84–95%, P 5–19% and A 81–92% on unbound structures and S 8–51%, C 97–99%, P 14–50%, A 94–97% on complex structures for sensitivity, specificity, precision and accuracy, respectively. High specificity and accuracy rates with a single property on unbound protein structures suggest that hot spots are predefined in the dynamics of unbound structures and forming the binding core of interfaces, whereas the prediction of other functional residues with similar dynamic behavior explains the lower precision values. The latter is demonstrated with the case studies; ubiquitin, hen egg-white lysozyme and M2 proton channel. The dynamic fluctuations suggest a pseudo network of residues with high frequency fluctuations, which could be plausible for the mechanism of biological interactions and allosteric regulation. PMID:24023934

Flood risk assessment and robust management under deep uncertainty: Application to Dhaka City

NASA Astrophysics Data System (ADS)

Mojtahed, Vahid; Gain, Animesh Kumar; Giupponi, Carlo

2014-05-01

The socio-economic changes as well as climatic changes have been the main drivers of uncertainty in environmental risk assessment and in particular flood. The level of future uncertainty that researchers face when dealing with problems in a future perspective with focus on climate change is known as Deep Uncertainty (also known as Knightian uncertainty), since nobody has already experienced and undergone those changes before and our knowledge is limited to the extent that we have no notion of probabilities, and therefore consolidated risk management approaches have limited potential.. Deep uncertainty is referred to circumstances that analysts and experts do not know or parties to decision making cannot agree on: i) the appropriate models describing the interaction among system variables, ii) probability distributions to represent uncertainty about key parameters in the model 3) how to value the desirability of alternative outcomes. The need thus emerges to assist policy-makers by providing them with not a single and optimal solution to the problem at hand, such as crisp estimates for the costs of damages of natural hazards considered, but instead ranges of possible future costs, based on the outcomes of ensembles of assessment models and sets of plausible scenarios. Accordingly, we need to substitute optimality as a decision criterion with robustness. Under conditions of deep uncertainty, the decision-makers do not have statistical and mathematical bases to identify optimal solutions, while instead they should prefer to implement "robust" decisions that perform relatively well over all conceivable outcomes out of all future unknown scenarios. Under deep uncertainty, analysts cannot employ probability theory or other statistics that usually can be derived from observed historical data and therefore, we turn to non-statistical measures such as scenario analysis. We construct several plausible scenarios with each scenario being a full description of what may happen in future and based on a meaningful synthesis of parameters' values with control of their correlations for maintaining internal consistencies. This paper aims at incorporating a set of data mining and sampling tools to assess uncertainty of model outputs under future climatic and socio-economic changes for Dhaka city and providing a decision support system for robust flood management and mitigation policies. After constructing an uncertainty matrix to identify the main sources of uncertainty for Dhaka City, we identify several hazard and vulnerability maps based on future climatic and socio-economic scenarios. The vulnerability of each flood management alternative under different set of scenarios is determined and finally the robustness of each plausible solution considered is defined based on the above assessment.

Biological indicators in response to radiofrequency/microwave exposure.

PubMed

Marjanović, Ana Marija; Pavičić, Ivan; Trošić, Ivančica

2012-09-01

Over the years, due to rapid technological progress, radiation from man-made sources exceeded that of natural origin. There is a general concern regarding a growing number of appliances that use radiofrequency/ microwave (RF/MW) radiation with particular emphasis on mobile communication systems. Since nonthermal biological effects and mechanisms of RF/MW radiation are still uncertain, laboratory studies on animal models, tissues, cells, and cell free system are of extraordinary importance in bioelectromagnetic research. We believe that such investigations play a supporting role in public risk assessment. Cellular systems with the potential for a clear response to RF/MW exposures should be used in those studies. It is known that organism is a complex electrochemical system where processes of oxidation and reduction regularly occur. One of the plausible mechanisms is connected with generation of reactive oxygen species (ROS). Depending on concentration, ROS can have both beneficial and deleterious effects. Positive effects are connected with cell signalling, defence against infectious agents, and proliferative cell ability. On the other hand, excessive production, which overloads antioxidant defence mechanism, leads to cellular damage with serious potential for disease development. ROS concentration increase within the cell caused by RF/MW radiation seems to be a biologically relevant hypothesis to give clear insight into the RF/MW action at non-thermal level of radiation. In order to better understand the exact mechanism of action and its consequences, further research is needed in the field. We would like to present current knowledge on possible biological mechanisms of RF/MW actions.

Adaptive force produced by stress-induced regulation of random variation intensity.

PubMed

Shimansky, Yury P

2010-08-01

The Darwinian theory of life evolution is capable of explaining the majority of related phenomena. At the same time, the mechanisms of optimizing traits beneficial to a population as a whole but not directly to an individual remain largely unclear. There are also significant problems with explaining the phenomenon of punctuated equilibrium. From another perspective, multiple mechanisms for the regulation of the rate of genetic mutations according to the environmental stress have been discovered, but their precise functional role is not well understood yet. Here a novel mathematical paradigm called a Kinetic-Force Principle (KFP), which can serve as a general basis for biologically plausible optimization methods, is introduced and its rigorous derivation is provided. Based on this principle, it is shown that, if the rate of random changes in a biological system is proportional, even only roughly, to the amount of environmental stress, a virtual force is created, acting in the direction of stress relief. It is demonstrated that KFP can provide important insights into solving the above problems. Evidence is presented in support of a hypothesis that the nature employs KFP for accelerating adaptation in biological systems. A detailed comparison between KFP and the principle of variation and natural selection is presented and their complementarity is revealed. It is concluded that KFP is not a competing alternative, but a powerful addition to the principle of variation and natural selection. It is also shown KFP can be used in multiple ways for adaptation of individual biological organisms.

Would a madman have been so wise as this?" The effects of source credibility and message credibility on validation.

PubMed

Foy, Jeffrey E; LoCasto, Paul C; Briner, Stephen W; Dyar, Samantha

2017-02-01

Readers rapidly check new information against prior knowledge during validation, but research is inconsistent as to whether source credibility affects validation. We argue that readers are likely to accept highly plausible assertions regardless of source, but that high source credibility may boost acceptance of claims that are less plausible based on general world knowledge. In Experiment 1, participants read narratives with assertions for which the plausibility varied depending on the source. For high credibility sources, we found that readers were faster to read information confirming these assertions relative to contradictory information. We found the opposite patterns for low credibility characters. In Experiment 2, readers read claims from the same high or low credibility sources, but the claims were always plausible based on general world knowledge. Readers consistently took longer to read contradictory information, regardless of source. In Experiment 3, participants read modified versions of "The Tell-Tale Heart," which was narrated entirely by an unreliable source. We manipulated the plausibility of a target event, as well as whether high credibility characters within the story provided confirmatory or contradictory information about the narrator's description of the target event. Though readers rated the narrator as being insane, they were more likely to believe the narrator's assertions about the target event when it was plausible and corroborated by other characters. We argue that sourcing research would benefit from focusing on the relationship between source credibility, message credibility, and multiple sources within a text.

Practical limits for reverse engineering of dynamical systems: a statistical analysis of sensitivity and parameter inferability in systems biology models.

PubMed

Erguler, Kamil; Stumpf, Michael P H

2011-05-01

The size and complexity of cellular systems make building predictive models an extremely difficult task. In principle dynamical time-course data can be used to elucidate the structure of the underlying molecular mechanisms, but a central and recurring problem is that many and very different models can be fitted to experimental data, especially when the latter are limited and subject to noise. Even given a model, estimating its parameters remains challenging in real-world systems. Here we present a comprehensive analysis of 180 systems biology models, which allows us to classify the parameters with respect to their contribution to the overall dynamical behaviour of the different systems. Our results reveal candidate elements of control in biochemical pathways that differentially contribute to dynamics. We introduce sensitivity profiles that concisely characterize parameter sensitivity and demonstrate how this can be connected to variability in data. Systematically linking data and model sloppiness allows us to extract features of dynamical systems that determine how well parameters can be estimated from time-course measurements, and associates the extent of data required for parameter inference with the model structure, and also with the global dynamical state of the system. The comprehensive analysis of so many systems biology models reaffirms the inability to estimate precisely most model or kinetic parameters as a generic feature of dynamical systems, and provides safe guidelines for performing better inferences and model predictions in the context of reverse engineering of mathematical models for biological systems.

Mini-review of the geotechnical parameters of municipal solid waste: Mechanical and biological pre-treated versus raw untreated waste.

PubMed

Petrovic, Igor

2016-09-01

The most viable option for biostabilisation of old sanitary landfills, filled with raw municipal solid waste, is the so-called bioreactor landfill. Even today, bioreactor landfills are viable options in many economically developing countries. However, in order to reduce the biodegradable component of landfilled waste, mechanical and biological treatment has become a widely accepted waste treatment technology, especially in more prosperous countries. Given that mechanical and biological treatment alters the geotechnical properties of raw waste material, the design of sanitary landfills which accepts mechanically and biologically treated waste, should be carried out with a distinct set of geotechnical parameters. However, under the assumption that 'waste is waste', some design engineers might be tempted to use geotechnical parameters of untreated raw municipal solid waste and mechanical and biological pre-treated municipal solid waste interchangeably. Therefore, to provide guidelines for use and to provide an aggregated source of this information, this mini-review provides comparisons of geotechnical parameters of mechanical and biological pre-treated waste and raw untreated waste at various decomposition stages. This comparison reveals reasonable correlations between the hydraulic conductivity values of untreated and mechanical and biological pre-treated municipal solid waste. It is recognised that particle size might have a significant influence on the hydraulic conductivity of both municipal solid waste types. However, the compression ratios and shear strengths of untreated and pre-treated municipal solid waste do not show such strong correlations. Furthermore, another emerging topic that requires appropriate attention is the recovery of resources that are embedded in old landfills. Therefore, the presented results provide a valuable tool for engineers designing landfills for mechanical and biological pre-treated waste or bioreactor landfills for untreated raw waste as well as planning landfill mining projects. © The Author(s) 2016.

Study of Carrying Capacity Assesment for Natural Fisheries in Jatibarang Reservoir In Semarang City

NASA Astrophysics Data System (ADS)

Sujono, Bambang; Anggoro, Sutrisno

2018-02-01

Jatibarang reservoir serves as water supply in dry season and controlling flood in Semarang City. This reservoir is stem Kreo River which cathment areas of 54 km2, pool of area 110 ha and volume is 20 billion m3. This reservoir is potential to develop as natural fisheries area. The goals of this research were to explore existing condition of physical, biological as well as chemical parameter; carrying capacity assessment for natural fisheries; determining appropriate fish species to be developed in Jatibarang reservoir. This research was done in descriptive explorative scheme. Field survey and laboratory analyses were conducted to identify physical, chemical and biological parameters of the water. Physical parameters measured were temperature and water brightness. Chemical parameters measured were pH, DO, phosphate, Ammonia, nitrites and nitrate, while biological parameter measured were chlorophyll-a concentration. Carrying capacity analyses was done referred to the Government Regulation Number 82, 2001 that regulate the management of water quality and water pollution control. Based on the research, it showed that the existing condition of physical, chemical and biological parameters were still good to be used for natural fisheries. Based on TSI index, it classified as eutrofic water. Furthermore, tilapia fish (Oreochromis mossambicus), nile tilapia (Oreochromis niloticus) tawes (Barbonymus gonionotus) and carper fish (Cyprinus carpio) were considered as best species for natural fisheries in Jatibarang Reservoir.

PyDREAM: high-dimensional parameter inference for biological models in python.

PubMed

Shockley, Erin M; Vrugt, Jasper A; Lopez, Carlos F; Valencia, Alfonso

2018-02-15

Biological models contain many parameters whose values are difficult to measure directly via experimentation and therefore require calibration against experimental data. Markov chain Monte Carlo (MCMC) methods are suitable to estimate multivariate posterior model parameter distributions, but these methods may exhibit slow or premature convergence in high-dimensional search spaces. Here, we present PyDREAM, a Python implementation of the (Multiple-Try) Differential Evolution Adaptive Metropolis [DREAM(ZS)] algorithm developed by Vrugt and ter Braak (2008) and Laloy and Vrugt (2012). PyDREAM achieves excellent performance for complex, parameter-rich models and takes full advantage of distributed computing resources, facilitating parameter inference and uncertainty estimation of CPU-intensive biological models. PyDREAM is freely available under the GNU GPLv3 license from the Lopez lab GitHub repository at http://github.com/LoLab-VU/PyDREAM. c.lopez@vanderbilt.edu. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Chromogranin A: Novel biomarker between periodontal disease and psychosocial stress

PubMed Central

Reshma, Arunima Padmakumar; Arunachalam, Rajeev; Pillai, Jayakumar Kochu; Kurra, Sarath Babu; Varkey, Vini K.; Prince, Mohanraj J.

2013-01-01

Context: The psychosocial stress has long been regarded as a significant pre-disposing factor for periodontal disease. The association between the periodontal disease and the neuroendocrine hormones has been observed. Chromogranin A (CgA) is supposed to link the activity of the neuroendocrine system to local and systemic immune functions and to be related to periodontitis. Aims: The aim of this study was to determine the CgA levels in saliva and plasma in periodontal health and disease and to assess their potential relationship to periodontitis. Settings and Designs: In this case-control study, the association between periodontal disease and stress marker has been assessed. Materials and Methods: Sixty subjects were chosen for this study: With case group comprising of 30 subjects with chronic periodontitis and control group comprising of 30 healthy subjects. Salivary and plasma CgA levels were determined by ELISA technique. Clinical parameters included were plaque index, papillary bleeding index and clinical attachment loss and probing depth. Correlation analysis was calculated by independent sample t-test. Results: Significantly higher CgA levels were found in saliva and plasma of patients with chronic periodontitis compared with healthy individuals (P < 0.05). No significant difference were observed between salivary and plasma CgA levels. Conclusions: The elevated level CgA in the plasma and saliva of subjects with stress induced chronic periodontitis has yielded insights into biological plausible association between the psychosocial stress and chronic periodontitis. Thus, our results suggest that CgA is a useful biomarker for evaluating at least in part the etiopathogenesis of periodontitis. PMID:23869129

Virtual Neurorobotics (VNR) to Accelerate Development of Plausible Neuromorphic Brain Architectures.

PubMed

Goodman, Philip H; Buntha, Sermsak; Zou, Quan; Dascalu, Sergiu-Mihai

2007-01-01

Traditional research in artificial intelligence and machine learning has viewed the brain as a specially adapted information-processing system. More recently the field of social robotics has been advanced to capture the important dynamics of human cognition and interaction. An overarching societal goal of this research is to incorporate the resultant knowledge about intelligence into technology for prosthetic, assistive, security, and decision support applications. However, despite many decades of investment in learning and classification systems, this paradigm has yet to yield truly "intelligent" systems. For this reason, many investigators are now attempting to incorporate more realistic neuromorphic properties into machine learning systems, encouraged by over two decades of neuroscience research that has provided parameters that characterize the brain's interdependent genomic, proteomic, metabolomic, anatomic, and electrophysiological networks. Given the complexity of neural systems, developing tenable models to capture the essence of natural intelligence for real-time application requires that we discriminate features underlying information processing and intrinsic motivation from those reflecting biological constraints (such as maintaining structural integrity and transporting metabolic products). We propose herein a conceptual framework and an iterative method of virtual neurorobotics (VNR) intended to rapidly forward-engineer and test progressively more complex putative neuromorphic brain prototypes for their ability to support intrinsically intelligent, intentional interaction with humans. The VNR system is based on the viewpoint that a truly intelligent system must be driven by emotion rather than programmed tasking, incorporating intrinsic motivation and intentionality. We report pilot results of a closed-loop, real-time interactive VNR system with a spiking neural brain, and provide a video demonstration as online supplemental material.

Dynamics of feature categorization.

PubMed

Martí, Daniel; Rinzel, John

2013-01-01

In visual and auditory scenes, we are able to identify shared features among sensory objects and group them according to their similarity. This grouping is preattentive and fast and is thought of as an elementary form of categorization by which objects sharing similar features are clustered in some abstract perceptual space. It is unclear what neuronal mechanisms underlie this fast categorization. Here we propose a neuromechanistic model of fast feature categorization based on the framework of continuous attractor networks. The mechanism for category formation does not rely on learning and is based on biologically plausible assumptions, for example, the existence of populations of neurons tuned to feature values, feature-specific interactions, and subthreshold-evoked responses upon the presentation of single objects. When the network is presented with a sequence of stimuli characterized by some feature, the network sums the evoked responses and provides a running estimate of the distribution of features in the input stream. If the distribution of features is structured into different components or peaks (i.e., is multimodal), recurrent excitation amplifies the response of activated neurons, and categories are singled out as emerging localized patterns of elevated neuronal activity (bumps), centered at the centroid of each cluster. The emergence of bump states through sequential, subthreshold activation and the dependence on input statistics is a novel application of attractor networks. We show that the extraction and representation of multiple categories are facilitated by the rich attractor structure of the network, which can sustain multiple stable activity patterns for a robust range of connectivity parameters compatible with cortical physiology.

Apparatus and Methods for Manipulation and Optimization of Biological Systems

NASA Technical Reports Server (NTRS)

Sun, Ren (Inventor); Ho, Chih-Ming (Inventor); Wong, Pak Kin (Inventor); Yu, Fuqu (Inventor)

2014-01-01

The invention provides systems and methods for manipulating biological systems, for example to elicit a more desired biological response from a biological sample, such as a tissue, organ, and/or a cell. In one aspect, the invention operates by efficiently searching through a large parametric space of stimuli and system parameters to manipulate, control, and optimize the response of biological samples sustained in the system. In one aspect, the systems and methods of the invention use at least one optimization algorithm to modify the actuator's control inputs for stimulation, responsive to the sensor's output of response signals. The invention can be used, e.g., to optimize any biological system, e.g., bioreactors for proteins, and the like, small molecules, polysaccharides, lipids, and the like. Another use of the apparatus and methods includes is for the discovery of key parameters in complex biological systems.

Parameter discovery in stochastic biological models using simulated annealing and statistical model checking.

PubMed

Hussain, Faraz; Jha, Sumit K; Jha, Susmit; Langmead, Christopher J

2014-01-01

Stochastic models are increasingly used to study the behaviour of biochemical systems. While the structure of such models is often readily available from first principles, unknown quantitative features of the model are incorporated into the model as parameters. Algorithmic discovery of parameter values from experimentally observed facts remains a challenge for the computational systems biology community. We present a new parameter discovery algorithm that uses simulated annealing, sequential hypothesis testing, and statistical model checking to learn the parameters in a stochastic model. We apply our technique to a model of glucose and insulin metabolism used for in-silico validation of artificial pancreata and demonstrate its effectiveness by developing parallel CUDA-based implementation for parameter synthesis in this model.