Evaluating Prion Models Based on Comprehensive Mutation Data of Mouse PrP

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Bayesian Markov Random Field Analysis for Protein Function Prediction Based on Network Data

Inference of protein functions is one of the most important aims of modernbiology. To fully exploit the large volumes of genomic data typically producedin modern-day genomic experiments, automated computational methods for proteinfunction prediction are urgently needed. Established methods use sequence orstructure similarity to infer functions but those types of data do not sufficeto determine the biological context in which proteins act. Currenthigh-throughput biological experiments produce large amounts of data on theinteractions between proteins. Such data can be used to infer interactionnetworks and to predict the biological process that the protein is involved in.Here, we develop a probabilistic approach for protein function prediction usingnetwork data, such as protein-protein interaction measurements. We take aBayesian approach to an existing Markov Random Field method by performingsimultaneous estimation of the model parameters and prediction of proteinfunctions. We use an adaptive Markov Chain Monte Carlo algorithm that leads tomore accurate parameter estimates and consequently to improved predictionperformance compared to the standard Markov Random Fields method. We tested ourmethod using a high quality S.cereviciae validation networkwith 1622 proteins against 90 Gene Ontology terms of different levels ofabstraction. Compared to three other protein function prediction methods, ourapproach shows very good prediction performance. Our method can be directlyapplied to protein-protein interaction or coexpression networks, but also can beextended to use multiple data sources. We apply our method to physical proteininteraction data from S. cerevisiae and provide novelpredictions, using 340 Gene Ontology terms, for 1170 unannotated proteins and weevaluate the predictions using the available literature.     

Defining and Evaluating Classification Algorithm for High-Dimensional Data Based on Latent Topics

Automatic text categorization is one of the key techniques in information retrieval and the data mining field. The classification is usually time-consuming when the training dataset is large and high-dimensional. Many methods have been proposed to solve this problem, but few can achieve satisfactory efficiency. In this paper, we present a method which combines the Latent Dirichlet Allocation (LDA) algorithm and the Support Vector Machine (SVM). LDA is first used to generate reduced dimensional representation of topics as feature in VSM. It is able to reduce features dramatically but keeps the necessary semantic information. The Support Vector Machine (SVM) is then employed to classify the data based on the generated features. We evaluate the algorithm on 20 Newsgroups and Reuters-21578 datasets, respectively. The experimental results show that the classification based on our proposed LDA+SVM model achieves high performance in terms of precision, recall and F1 measure. Further, it can achieve this within a much shorter time-frame. Our process improves greatly upon the previous work in this field and displays strong potential to achieve a streamlined classification process for a wide range of applications.     

An Evaluation of the MM+ Force Field

Hyperchem′s MM+ force field, based on Allinger′s MM2 is described and evaluated with respect to other MM2 variants, in terms of rotation barriers, conformational energy differences, and conjugation. Its ability to take missing parameters into account is also evaluated with respect to the Dreiding force field. This evaluation also intends to clearly separate the two different force fields MM+(91) and MM+(^**) hiding under the MM+ denomination. It is shown that, whereas MM+ proves to be generally robust, caution must be the rule when dealing with conjugated molecules, particularly with heteroaromatics.     

Force Field Dependence of NMR-Based,Restrained Molecular Dynamics DNA Structure Calculations Including an Analysis of the Influence of Residual Dipolar Coupling Restraints

Abstract

Restrained molecular dynamics is widely used to calculate DNA structures from NMR data. Here, results of an in silico experiment show that the force field can be significant compared to the NMR restraints in driving the final structures to converge. Specifically, we observed that i) the influence of the force field leads to artificially tight convergence within final families of structures and ii) the precision and character of resulting structures depend on the choice of force field used in the calculations. A canonical B-DNA model was used as a target structure. Distances, dihedral angles, and simulated residual dipolar couplings were measured in the target structure and used as restraints. X-PLOR and Discover, which use force fields developed for CHARMM and AMBER programs, respectively, were tested and found to produce different final structures despite the use of identical distance and dihedral restraints. Incorporation of residual dipolar coupling restraints in X-PLOR improves convergence with the target structure and between families of structures indicating that the force field dependence can potentially be overcome if residual dipolar coupling restraints are employed.     

Field Tests for Evaluating the Aerobic Work Capacity of Firefighters

Working as a firefighter is physically strenuous, and a high level of physical fitness increases a firefighter’s ability to cope with the physical stress of their profession. Direct measurements of aerobic capacity, however, are often complicated, time consuming, and expensive. The first aim of the present study was to evaluate the correlations between direct (laboratory) and indirect (field) aerobic capacity tests with common and physically demanding firefighting tasks. The second aim was to give recommendations as to which field tests may be the most useful for evaluating firefighters’ aerobic work capacity. A total of 38 subjects (26 men and 12 women) were included. Two aerobic capacity tests, six field tests, and seven firefighting tasks were performed. Lactate threshold and onset of blood lactate accumulation were found to be correlated to the performance of one work task (r_s = −0.65 and −0.63, p<0.01, respectively). Absolute (mL·min⁻¹) and relative (mL·kg⁻¹·min⁻¹) maximal aerobic capacity was correlated to all but one of the work tasks (r_s = −0.79 to 0.55 and −0.74 to 0.47, p<0.01, respectively). Aerobic capacity is important for firefighters’ work performance, and we have concluded that the time to row 500 m, the time to run 3000 m relative to body weight (s·kg⁻¹), and the percent of maximal heart rate achieved during treadmill walking are the most valid field tests for evaluating a firefighter’s aerobic work capacity.     

Evaluating the Performance of Time-Gated Live-Cell Microscopy with Lanthanide Probes

Probes and biosensors that incorporate luminescent Tb(III) or Eu(III) complexes are promising for cellular imaging because time-gated microscopes can detect their long-lifetime (approximately milliseconds) emission without interference from short-lifetime (approximately nanoseconds) fluorescence background. Moreover, the discrete, narrow emission bands of Tb(III) complexes make them uniquely suited for multiplexed imaging applications because they can serve as Förster resonance energy transfer (FRET) donors to two or more differently colored acceptors. However, lanthanide complexes have low photon emission rates that can limit the image signal/noise ratio, which has a square-root dependence on photon counts. This work describes the performance of a wide-field, time-gated microscope with respect to its ability to image Tb(III) luminescence and Tb(III)-mediated FRET in cultured mammalian cells. The system employed a UV-emitting LED for low-power, pulsed excitation and an intensified CCD camera for gated detection. Exposure times of ∼1 s were needed to collect 5–25 photons per pixel from cells that contained micromolar concentrations of a Tb(III) complex. The observed photon counts matched those predicted by a theoretical model that incorporated the photophysical properties of the Tb(III) probe and the instrument’s light-collection characteristics. Despite low photon counts, images of Tb(III)/green fluorescent protein FRET with a signal/noise ratio ≥ 7 were acquired, and a 90% change in the ratiometric FRET signal was measured. This study shows that the sensitivity and precision of lanthanide-based cellular microscopy can approach that of conventional FRET microscopy with fluorescent proteins. The results should encourage further development of lanthanide biosensors that can measure analyte concentration, enzyme activation, and protein-protein interactions in live cells.     

基于联合锋电位-局部场电位的整合野调制特性研究

整合野调制在生物视觉系统的图形背景分离和轮廓检测中具有重要作用。为了研究整合野空间频率调制特性,首先测定单个神经元的感受野范围和整合类型,挑选出要研究的抑制性神经元;然后,用匹配追踪算法和希尔伯特变换提取Spike触发的伽马频带LFP瞬时能量;最后,将Spike触发的伽马频带LFP(local field potential,LFP)瞬时能量用于分析神经元的整合调制特性.对在大鼠初级视觉皮层(primary visual cortex,V1区)采集的96个神经元进行统计分析,实验结果表明:1)Spike触发的伽马频带LFP瞬时能量可以作为分析V1区整合野调制特性的有效指标;2)基于Spike触发的伽马频带LFP瞬时能量所获得的抑制指数要显著高于通过Spike发放率以及伽马频带LFP功率的结果(P0.001),并且整合野的调制规律性更加明显,个体适用性更好。     

A Randomised Trial Evaluating the Effects of the TRPV1 Antagonist SB705498 on Pruritus Induced by Histamine,and Cowhage Challenge in Healthy Volunteers

Background

Transient receptor potential vanilloid type 1 (TRPV1) is a non-selective cation channel widely expressed in skin tissues, and peripheral sensory nerve fibres. Activation of TRPV1 releases neuropeptides; the resulting neurogenic inflammation is believed to contribute to the development of pruritus. A TRPV1 antagonist has the potential to perform as an anti-pruritic agent. SB705498 is a TRPV1 antagonist that has demonstrated in vitro activity against cloned TRPV1 human receptors and when orally administered has demonstrated pharmacodynamic activity in animal models and clinical studies.

Objectives

To select a topical dose of SB705498 using the TRPV1 agonist capsaicin; to confirm engagement of the TRPV1 antagonistic action of SB705498 and assess whether the dose selected has an effect on itch induced by two challenge agents.

Methods

A clinical study was conducted in 16 healthy volunteers to assess the effects of 3 doses of SB705498 on skin flare induced by capsaicin. Subjects with a robust capsaicin response were chosen to determine if the selected topical formulation of SB705498 had an effect on challenge agent induced itch.

Results

Following capsaicin challenge the greatest average reduction in area of flare was seen for the 3% formulation. This dose was selected for further investigation. Itch intensity induced by two challenge agents (cowhage and histamine) was assessed on the Computerised Visual Analogue Scale. The difference in average itch intensity (Weighted Mean Over 15 Mins) between the 3% dose of SB705498 and placebo for the cowhage challenge was −0.64, whilst the histamine challenge showed on average a −4.65 point change.

Conclusions

The 3% topical formulation of SB705498 cream was clinically well tolerated and had target specific pharmacodynamic activity. However there were no clinically significant differences on pruritus induced by either challenge agent in comparison to placebo. SB705498 is unlikely to be of symptomatic benefit for histaminergic or non-histaminergic induced itch.

Trial Registration

ClinicalTrials.gov {"type":"clinical-trial","attrs":{"text":"NCT01673529","term_id":"NCT01673529"}}NCT01673529     

Evaluating the Applicability of Phi Coefficient in Indicating Habitat Preferences of Forest Soil Fauna Based on a Single Field Study in Subtropical China

Phi coefficient directly depends on the frequencies of occurrence of organisms and has been widely used in vegetation ecology to analyse the associations of organisms with site groups, providing a characterization of ecological preference, but its application in soil ecology remains rare. Based on a single field experiment, this study assessed the applicability of phi coefficient in indicating the habitat preferences of soil fauna, through comparing phi coefficient-induced results with those of ordination methods in charactering soil fauna-habitat(factors) relationships. Eight different habitats of soil fauna were implemented by reciprocal transfer of defaunated soil cores between two types of subtropical forests. Canonical correlation analysis (CCorA) showed that ecological patterns of fauna-habitat relationships and inter-fauna taxa relationships expressed, respectively, by phi coefficients and predicted abundances calculated from partial redundancy analysis (RDA), were extremely similar, and a highly significant relationship between the two datasets was observed (Pillai''s trace statistic = 1.998, P = 0.007). In addition, highly positive correlations between phi coefficients and predicted abundances for Acari, Collembola, Nematode and Hemiptera were observed using linear regression analysis. Quantitative relationships between habitat preferences and soil chemical variables were also obtained by linear regression, which were analogous to the results displayed in a partial RDA biplot. Our results suggest that phi coefficient could be applicable on a local scale in evaluating habitat preferences of soil fauna at coarse taxonomic levels, and that the phi coefficient-induced information, such as ecological preferences and the associated quantitative relationships with habitat factors, will be largely complementary to the results of ordination methods. The application of phi coefficient in soil ecology may extend our knowledge about habitat preferences and distribution-abundance relationships, which will benefit the understanding of biodistributions and variations in community compositions in the soil. Similar studies in other places and scales apart from our local site will be need for further evaluation of phi coefficient.     

Evaluating the Performance of Chemical Control in the Presence of Resistant Pathogens

Resistance to chemical control is a major impediment to combating many socially and economically important diseases. Theoretical and experimental studies have shown that reducing the intensity of treatment can slow, or even prevent, the invasion of resistance, yet reducing treatment levels also results in a net increase in disease severity. Clearly there is a need to identify control strategies that balance the conflicting aims of resistance management and disease suppression. Using a mathematical model for the dynamics of fungicide resistance in crop pathogens, we present a broadly applicable measure of the performance of chemical control in the presence of resistant pathogen strains. We illustrate how to optimise fungicide performance with respect to the intensity of treatment as a function of the duration of treatment and the fitness of the resistant strain. We find that in the short term, fungicide performance is optimised at high levels of treatment despite rapid selection for resistance, while the long-term optimum performance is achieved when treatment renders the fungicide-sensitive and fungicide-resistant pathogens equally fit. We further present evidence that under prescribed conditions, the ratio of dose size and frequency, and the fungicide mode of action, can have a significant effect on fungicide performance.     

Evaluating the Persistence of DNA from Decomposing Transgenic Watermelon Tissues in the Field

To analyze the persistence of the 35S promoter, nos terminator, and hpt, we buried the leaves and rootstocks of transgenic watermelons (Citrullus lanatus (Thunb.) Matsum. & Nakai) in 10 cm of soil. Qualitative and quantitative PCR analyses showed that the amount of transgenes in leaf samples was greatly decreased, by 70%, after 1 month, and only 2.5% remained after 2 months. No transgenes were detected in the leaves after 3 months. For buried rootstock samples, transgenes also degraded quickly, but a very small amount was still detectable up to 3 months later. In our investigation of possible gene transfer from decomposing transgenic watermelon to soil bacteria, only the 35S promoter was detected. However, further examination using colony dot hybridization tests indicated that such a transfer did not occur.     

Evaluating the Performance of Fine-Mapping Strategies at Common Variant GWAS Loci

The growing availability of high-quality genomic annotation has increased the potential for mechanistic insights when the specific variants driving common genome-wide association signals are accurately localized. A range of fine-mapping strategies have been advocated, and specific successes reported, but the overall performance of such approaches, in the face of the extensive linkage disequilibrium that characterizes the human genome, is not well understood. Using simulations based on sequence data from the 1000 Genomes Project, we quantify the extent to which fine-mapping, here conducted using an approximate Bayesian approach, can be expected to lead to useful improvements in causal variant localization. We show that resolution is highly variable between loci, and that performance is severely degraded as the statistical power to detect association is reduced. We confirm that, where causal variants are shared between ancestry groups, further improvements in performance can be obtained in a trans-ethnic fine-mapping design. Finally, using empirical data from a recently published genome-wide association study for ankylosing spondylitis, we provide empirical confirmation of the behaviour of the approximate Bayesian approach and demonstrate that seven of twenty-six loci can be fine-mapped to fewer than ten variants.     

A CHARMm Based Force Field for Carbohydrates Using the CHEAT Approach: Carbohydrate Hydroxyl Groups Represented by Extended Atoms

Abstract

Computational studies of carbohydrates that do not consider explicit solvent molecules suffer from the strong tendency of the carbohydrate pendant hydroxyl groups to form intramolecular hydrogen bonds that are unlikely to be present in protic media. In this paper a novel approach towards molecular modelling of carbohydrates is described. The average effect of intra- and intermolecular hydrogen bonding is introduced into the potential energy function by adding a new (extended) atom type representing a carbohydrate hydroxyl group to the CHARMm force field; we coin the name CHEAT (Carbohydrate Hydroxyls represented by Extended AToms) for the resulting force field. As a training set for the parametrisation of CHEAT we used ethylene glycol, 10 cyclohexanols, 5 inositols, and 12 glycopyranoses for which in total 64 conformational energy differences were estimated using a set of steric interaction energies between hydroxyl and/or methyl groups on six-membered ring compounds as derived by Angyal (Angew. Chem., 8, 172-182, (1969)). The root-mean-square deviation between the estimated energy differences and the corresponding values obtained by our CHEAT approach amounts to 0.37 kcal/mol (n = 64). The CHEAT approach, which is claimed to calculate aqueous state compatible energetical and conformational properties of carbohydrates, is computationally very efficient and facilitates the calculation of nanosecond range MD trajectories as well as systematic conformational searches of oligosaccharides.     

Evaluating the Pharmacological Mechanism of Chinese Medicine Si-Wu-Tang through Multi-Level Data Integration

Si-Wu-Tang (SWT) is a Traditional Chinese Medicine (TCM) formula widely used for the treatments of gynecological diseases. To explore the pharmacological mechanism of SWT, we incorporated microarray data of SWT with our herbal target database TCMID to analyze the potential activity mechanism of SWT''s herbal ingredients and targets. We detected 2,405 differentially expressed genes in the microarray data, 20 of 102 proteins targeted by SWT were encoded by these DEGs and can be targeted by 2 FDA-approved drugs and 39 experimental drugs. The results of pathway enrichment analysis of the 20 predicted targets were consistent with that of 2,405 differentially expressed genes, elaborating the potential pharmacological mechanisms of SWT. Further study from a perspective of protein-protein interaction (PPI) network showed that the predicted targets of SWT function cooperatively to perform their multi-target effects. We also constructed a network to combine herbs, ingredients, targets and drugs together which bridges the gap between SWT and conventional medicine, and used it to infer the potential mechanisms of herbal ingredients. Moreover, based on the hypothesis that the same or similar effects between different TCM formulae may result from targeting the same proteins, we analyzed 27 other TCM formulae which can also treat the gynecological diseases, the subsequent result provides additional insight to understand the potential mechanisms of SWT in treating amenorrhea. Our bioinformatics approach to detect the pharmacology of SWT may shed light on drug discovery for gynecological diseases and could be utilized to investigate other TCM formulae as well.