A Theoretical Analysis of Neuronal Variability

A simple neuronal model is assumed in which, after a refractory period, excitatory and inhibitory exponentially decaying inputs of constant size occur at random intervals and sum until a threshold is reached. The distribution of time intervals between successive neuronal firings (interresponse time histogram), the firing rate as a function of input frequency, the variability in the time course of depolarization from trial to trial, and the strength-duration curve are derived for this model. The predictions are compared with data from the literature and good qualitative agreement is found. All parameters are experimentally measurable and a direct test of the theory is possible with present techniques. The assumptions of the model are relaxed and the effects of such experimentally found phenomena as relative refractory and supernormal periods, adaptation, potentiation, and rhythmic slow potentials are discussed. Implications for gross behavior studies are considered briefly.     

Assessing Heart Rate Variability Using A 12 lead ECG In Patients With Alcohol Dependence Syndrome

Heavy or hazardous drinking is associated with an increased risk of cardiac morbidity and mortality and this has been attributed to abnormalities in cardiac autonomic regulation. Current study aimed to assess the role of simple indices derived from 12 lead ECG in subjects with chronic alcohol dependence. Data suggested that alcohol group had significantly lower 12 lead ECG derived RR variability compared to age and gender matched controls. Study further supports the implication of 12 lead derived RR variability indices in various clinical settings.     

Phytoscreening with SPME: Variability Analysis

Phytoscreening has been demonstrated at a variety of sites over the past 15 years as a low-impact, sustainable tool in delineation of shallow groundwater contaminated with chlorinated solvents. Collection of tree cores is rapid and straightforward, but low concentrations in tree tissues requires sensitive analytics. Solid-phase microextraction (SPME) is amenable to the complex matrix while allowing for solvent-less extraction. Accurate quantification requires the absence of competitive sorption, examined here both in laboratory experiments and through comprehensive examination of field data. Analysis of approximately 2,000 trees at numerous field sites also allowed testing of the tree genus and diameter effects on measured tree contaminant concentrations. Collectively, while these variables were found to significantly affect site-adjusted perchloroethylene (PCE) concentrations, the explanatory power of these effects was small (adjusted R² = 0.031). 90th quantile chemical concentrations in trees were significantly reduced by increasing Henry's constant and increasing hydrophobicity. Analysis of replicate tree core data showed no correlation between replicate relative standard deviation (RSD) and wood type or tree diameter, with an overall median RSD of 30%. Collectively, these findings indicate SPME is an appropriate technique for sampling and analyzing chlorinated solvents in wood and that phytoscreening is robust against changes in tree type and diameter.     

RAPD Analysis of Pathogenic Variability in Ascochyta rabiei

Thirty Italian isolates of the phytopathogenic fungus Ascochyta rabiei (Pass.) Labr., the causal organism of Ascochyta blight on chickpea (Cicer arietinum L.), were analysed by a random oligonucleotide primer dependent polymerase chain, reaction (PCR) technique called random amplified polymorphic DNA analysis (RAPD) using three decamer primers. In previous investigations these isolates had been differentiated in six pathogenic groups. RAPD results were summarized in an analysis using the program PAUP. With each of the primers several amplification products were observed which were common to all isolates. The results of the RAPD analyses also showed that all isolates could be identified by a unique RAPD pattern. No correlation between RAPD patterns and the division of the isolates in pathogenic groups could be established. The application of the RAPD technique for cataloguing isolates and to obtain specific genetic markers for all isolates of the species Ascochyta rabiei is discussed.     

Analysis of Heart Rate Variability in Masked Hypertension

To investigate heart rate variability (HRV) in patients with masked hypertension (MH), participants were classified based on clinic and 24-h ambulatory blood-pressure monitoring: essential hypertension (EH, n = 40; MH, n = 36) and normotension (NT, n = 48). The HRV parameters were observed using a 24-h Holter monitor. Compared with NT controls, the parameters of HRV (SDNN, SDANN, SDNN Index, RMSSD, HF) and parameters in EH and MH patients had significantly decreased. No statistically significant difference in the HRV parameters was found between the EH and MH groups. The changes in HRV parameters show cardiac autonomic nerve dysfunction in patients with MH.     

Analysis of Heart Rate Variability in Space Medicine

Space medicine was one of the first fields of science and practice to use the analysis of the heart rate variability (HRV) for obtaining new scientific information and solving the tasks of exercising medical control over humans working under extreme conditions. The theoretical basis of HRV analysis and different approaches to the assessment of the data obtained are presented in the work. The technique for HRV analysis with regard to the specifics of space studies is described. The results of investigations at different stages of the space flight, including the use of Holter monitoring, are presented. Special attention is given to the results of the investigations in a long-term 14-month space flight. The adaptation to long-term weightlessness was shown to be of a multistep character with the gradual involvement of additional regulatory mechanisms.     

Characterization and Simulation of Uncertain Frequency Distributions: Effects of Distribution Choice,Variability, Uncertainty,and Parameter Dependence

We use bootstrap simulation to characterize uncertainty in parametric distributions, including Normal, Lognormal, Gamma, Weibull, and Beta, commonly used to represent variability in probabilistic assessments. Bootstrap simulation enables one to estimate sampling distributions for sample statistics, such as distribution parameters, even when analytical solutions are not available. Using a two-dimensional framework for both uncertainty and variability, uncertainties in cumulative distribution functions were simulated. The mathematical properties of uncertain frequency distributions were evaluated in a series of case studies during which the parameters of each type of distribution were varied for sample sizes of 5, 10, and 20. For positively skewed distributions such as Lognormal, Weibull, and Gamma, the range of uncertainty is widest at the upper tail of the distribution. For symmetric unbounded distributions, such as Normal, the uncertainties are widest at both tails of the distribution. For bounded distributions, such as Beta, the uncertainties are typically widest in the central portions of the distribution. Bootstrap simulation enables complex dependencies between sampling distributions to be captured. The effects of uncertainty, variability, and parameter dependencies were studied for several generic functional forms of models, including models in which two-dimensional random variables are added, multiplied, and divided, to show the sensitivity of model results to different assumptions regarding model input distributions, ranges of variability, and ranges of uncertainty and to show the types of errors that may be obtained from mis-specification of parameter dependence. A total of 1,098 case studies were simulated. In some cases, counter-intuitive results were obtained. For example, the point value of the 95th percentile of uncertainty for the 95th percentile of variability of the product of four Gamma or Weibull distributions decreases as the coefficient of variation of each model input increases and, therefore, may not provide a conservative estimate. Failure to properly characterize parameter uncertainties and their dependencies can lead to orders-of-magnitude mis-estimates of both variability and uncertainty. In many cases, the numerical stability of two-dimensional simulation results was found to decrease as the coefficient of variation of the inputs increases. We discuss the strengths and limitations of bootstrap simulation as a method for quantifying uncertainty due to random sampling error.     

Cholinesterase Active Center. Statistical Analysis of Structure Variability

The cluster and factor analyses of the data on variability of active center structure of 41 cholinesterases from different animals were carried out. As characteristics of 32 variable amino acid residues, their hydrophobicity, isoelectric point, polarity, and volume were chosen. As a result of the factor analysis, seven factors were extracted (which, based on the factor scores analysis are called the factors of insect AChE, of nematode AChE-3,4, of nematode AChE-1, of nematode AChE-2,B,C, of mammalian BuChE, of squid AChE, and of tick AChE); they are responsible for 79% of the observed variability. The areas of the active center and the characteristics of the residues, which are the material substrate of these factors, are specified. The hierarchical cluster analysis has shown that dendrograms reflecting similarity in summarized reactivity of the active center do not coincide with the phylogenetic tree of the animals. The conclusion has been made that the direction of evolution of the ChE active center, on one hand, does not have a gradual and regular character and, on the other hand, does not correlate with evolution of ChE protein as a whole.     

Association Analysis of GABRB3 Promoter Variants with Heroin Dependence

GABRB3 encoding the β3 subunit of GABAA receptor has been implicated in multiple neuropsychiatric disorders, including substance abuse. Previous studies reported that SNPs at the 5′ regulatory region of GABRB3 could regulate GABRB3 gene expression and associated with childhood absence epilepsy (CAE). The study aimed to investigate whether SNPs at the 5′ regulatory region of GABRB3 were associated with heroin dependence in our population. We first re-sequenced 1.5 kb of the 5′regulatory region of GABRB3 gene to examine the SNP profile in the genomic DNA of 365 control subjects. Then, we conducted a case-control association analysis between 576 subjects with heroin dependence (549 males, 27 females) and 886 controls (472 males, 414 females) by genotyping the rs4906902 as a tag SNP. We also conducted a reporter gene assay to assess the promoter activity of two major haplotypes derived from SNPs at this region. We detected 3 common SNPs (rs4906902, rs8179184 and rs20317) at this region that had strong pair-wise linkage disequilibrium. The C allele of rs4906902 was found to be associated with increased risk of heroin dependence (odds ratio:1.27, p = 0.002). Two major haplotypes (C-A-G and T-G-C) derived from these 3 SNPs accounted for 99% of this sample, and reporter gene activity assay showed that haplotype C-A-G that contained the C allele of the tag SNP rs4906902 had higher activity than haplotype T-G-C. Our data suggest that GABRB3 might be associated with heroin dependence, and increased expression of GABRB3 might contribute to the pathogenesis of heroin dependence.     

基于复杂度的心率变异性分析研究进展

心率变异性（HRV）是当前心电图分析的一个前沿热点,它反映了交感神经和副交感神经对心血管系统的综合调节作用,是评价心血管系统功能的重要指标。随着非线性动力学和复杂性科学的发展,HRV信号被普遍认为是混沌或含有混沌成分的信号。复杂度是用来表征一个心率非线性动力学系统复杂程度的量度,以其简单快速的优点引起了众多研究者的兴趣,并广泛应用于心率变异性分析。本文综述了国内外复杂度算法的研究进展及基于复杂度的心率变异性分析的临床应用及前景。     

基于基因表达变异性的通路富集方法研究

当前的通路富集方法主要是基于基因的表达差异,很少有方法从通路变异性(方差)角度对其富集分析．我们注意到用合适的统计量描述通路的变异性时,在疾病表型下一些通路的变异性有明显的上升或者下降．因此本研究假设：通路变异性程度在不同表型中存在差异．本文设计了14种描述通路变异性的统计量与检验方法,检测不同表型下变异性有差异的通路即富集通路,并将富集结果与文献检索结果进行比较,同时,分析不同芯片预处理方法对数据和结果的影响．研究结果表明：5种预处理方法中,多阵列对数健壮算法(RMA)是数据预处理的最优方法;不同表型下通路的变异性程度存在差异;根据文献检索的通路结果,14种基于变异性的通路富集方法中,以通路中各基因欧氏距离的方差做统计量进行permutation检验(方法11)能有效识别显著通路,其富集结果优于基因集富集分析(GSEA)．综上所述,基于通路变异性的通路富集策略具有可行性,不仅对通路富集分析有一定的理论指导意义,而且为人类疾病研究提供新的视角．     

Analysis of Heart Rate Variability Based on the Graph Method

A method of analysis of heart rate variability based on the graph theory principle was suggested. The main parameters of the heart rate graph structure were determined and analyzed using models of harmonic oscillations, white noise, and various functional tests (including controllable respiration and mental load). The efficiency of the use of parameters of the heart rate graph for diagnosing some functional states was considered. A correlation of the parameters of the heart rate graph structure with the frequency characteristics of heart rate variability was studied. A general model of changes in the heart rate graph structure parameters at different levels of mental activity was constructed in terms of entropy changes.     

中国主要农作物产量波动影响因素分析

为研究我国主要农作物(粮食、水果、油料、糖料和棉花作物)产量波动特征及相关影响因素,以我国1981 ～2010年主要农作物产量和种植面积资料为基础,同时利用4种方法对农作物单产进行趋势拟合与分解.结果表明:(1)近30年来我国农作物总产和单产都逐步提高,特别是水果产量的增长最快,其中柑橘单产年均增长率达7.09％;各类作物趋势产量也呈上升趋势;但气象产量波动剧烈,年际间缺乏连续性,其中水果气象产量波动幅度最大(柑橘为17.76％、苹果为15.83％).(2)作物总产的年际波动中,种植面积和单产因素的贡献率因作物类型不同而有所差异,其中粮食作物和水果总产波动的主要原因是单产波动,糖料作物和棉花产量波动主要因种植面积波动导致,油料作物总产的波动中单产和种植面积贡献相当.(3)各类作物单产年际波动均取决于气象因素,农业政策和科技进步等社会因素对单产年际波动的贡献较低.(4)作物趋势产量的4种拟合方法,其结果无显著差异.各影响因素对我国农作物产量波动的贡献率因作物类型不同而有所差异;重视作物单产提高、关注气候变化对农作物生产的影响是目前我国农业安全生产的重要任务.     

Estimation of Genetic Variability of Vigna radiata Cultivars by RAPD Analysis

DNA was isolated from 14 cultivars of Vigna radiata (L.) Wilczek and subjected to RAPD analysis using 14 random decamer primers. These cultivars revealed polymorphism with respect to RAPD markers and were subjected to hierarchical cluster analysis. A dendrogram was prepared based on these data. Analysis of banding patterns confirmed that two strongly aromatic cultivars IC1, IC4, were closely linked. But another aromatic cultivar, B1, formed a separate cluster. The high yielding cultivars were closely related to B1. The phylogenetic tree constructed by the neighbour joining method showed that RAPD results were correlated with morphological characters like plant height, leaf and seed size, seed colour, etc. This revised version was published online in July 2006 with corrections to the Cover Date.     

Quantifying Inter-Laboratory Variability in Stable Isotope Analysis of Ancient Skeletal Remains

Over the past forty years, stable isotope analysis of bone (and tooth) collagen and hydroxyapatite has become a mainstay of archaeological and paleoanthropological reconstructions of paleodiet and paleoenvironment. Despite this method''s frequent use across anthropological subdisciplines (and beyond), the present work represents the first attempt at gauging the effects of inter-laboratory variability engendered by differences in a) sample preparation, and b) analysis (instrumentation, working standards, and data calibration). Replicate analyses of a ¹⁴C-dated ancient human bone by twenty-one archaeological and paleoecological stable isotope laboratories revealed significant inter-laboratory isotopic variation for both collagen and carbonate. For bone collagen, we found a sizeable range of 1.8‰ for δ¹³C_col and 1.9‰ for δ¹⁵N_col among laboratories, but an interpretatively insignificant average pairwise difference of 0.2‰ and 0.4‰ for δ¹³C_col and δ¹⁵N_col respectively. For bone hydroxyapatite the observed range increased to a troublingly large 3.5‰ for δ¹³C_ap and 6.7‰ for δ¹⁸O_ap, with average pairwise differences of 0.6‰ for δ¹³C_ap and a disquieting 2.0‰ for δ¹⁸O_ap. In order to assess the effects of preparation versus analysis on isotopic variability among laboratories, a subset of the samples prepared by the participating laboratories were analyzed a second time on the same instrument. Based on this duplicate analysis, it was determined that roughly half of the isotopic variability among laboratories could be attributed to differences in sample preparation, with the other half resulting from differences in analysis (instrumentation, working standards, and data calibration). These findings have serious implications for choices made in the preparation and extraction of target biomolecules, the comparison of results obtained from different laboratories, and the interpretation of small differences in bone collagen and hydroxyapatite isotope values. To address the issues arising from inter-laboratory comparisons, we devise a novel measure we term the Minimum Meaningful Difference (MMD), and demonstrate its application.