A database of computational models of a half-center oscillator for analyzing how neuronal parameters influence network activity

A half-center oscillator (HCO) is a common circuit building block of central pattern generator networks that produce rhythmic motor patterns in animals. Here we constructed an efficient relational database table with the resulting characteristics of the Hill et al.’s (J Comput Neurosci 10:281–302, 2001) HCO simple conductance-based model. The model consists of two reciprocally inhibitory neurons and replicates the electrical activity of the oscillator interneurons of the leech heartbeat central pattern generator under a variety of experimental conditions. Our long-range goal is to understand how this basic circuit building block produces functional activity under a variety of parameter regimes and how different parameter regimes influence stability and modulatability. By using the latest developments in computer technology, we simulated and stored large amounts of data (on the order of terabytes). We systematically explored the parameter space of the HCO and corresponding isolated neuron models using a brute-force approach. We varied a set of selected parameters (maximal conductance of intrinsic and synaptic currents) in all combinations, resulting in about 10 million simulations. We classified these HCO and isolated neuron model simulations by their activity characteristics into identifiable groups and quantified their prevalence. By querying the database, we compared the activity characteristics of the identified groups of our simulated HCO models with those of our simulated isolated neuron models and found that regularly bursting neurons compose only a small minority of functional HCO models; the vast majority was composed of spiking neurons.     

Bifurcation analysis and effects of changing ionic conductances on pacemaker rhythm in a sinoatrial node cell model

The electrical excitation (action potential generation) of sinoatrial node (cardiac pacemaker) cells is directly related to various ion channels (pore-forming proteins) in cell membranes. In order to analyze the relation between action potential generation and ion channels, we use the Yanagihara-Noma-Irisawa (YNI) model of sinoatrial node cells, which is described by the Hodgkin-Huxley-type equations with seven variables. In this paper, we analyze the global bifurcation structure of the YNI model by varying various conductances of ion channels, and examine the effects of these conductance changes on pacemaker rhythm (frequency of action potential generation). The coupling effect on pacemaker rhythm is also examined approximately by applying external current to the YNI model.     

Estimating utilization distributions with kernel versus local convex hull methods

Estimates of utilization distributions (UDs) are used in analyses of home-range area, habitat and resource selection, and social interactions. We simulated data from 12 parent UDs, representing 3 series of increasingly intense space-use patterns (clustering of points around a home site, restriction of locations to a network of nodes and corridors, and dominance of a central hole in the UD) and compared the ability of kernel density estimation (KDE) and local convex hull (LCH) construction to reconstruct known UDs from samples of 10, 50, 250, and 1,000 location points. For KDE, we considered 4 bandwidth selectors: the reference bandwidth, least-squares cross-validation (LSCV), direct plug-in (DPI), and solve-the-equation (STE). For the sample sizes and UD patterns tested here, KDE achieved significantly higher volume-of-intersection (VI) scores with known parent UDs than did LCH; KDE also provided less biased home-range area estimates under many conditions. However, LCH minimized the UD volume that occurred outside the true home range boundary (V_out). Among the KDE bandwidth estimators, relative performance depended on the type and intensity of space use patterns, sample size, and the metric used to evaluate performance. Biologists should use KDE for UD and home range estimation within a probabilistic context, unless their objective is to exclude potentially unused areas by defining the area delimited by data. © 2011 The Wildlife Society.     

采用三次样条拟合胎儿体格发育指标百分位数参考值

目的:生长发育评价标准的最佳形式是年龄别百分位数,然而,目前我国缺乏胎儿的孕周别体格发育指标百分位数评价标准,影响了胎儿宫内生长发育水平的准确评价,本研究拟建立陕西省正常单胎妊娠孕妇胎儿体格发育指标百分位数参考标准。方法:以陕西省西安、汉中、延安5所大型综合医院超声科或妇产科超声室为数据采集点,选择2010-01-01到2010-12-31间进行常规孕期检查的正常单胎妊娠胎儿的超声测量数据,随机抽取一次测量结果,共收集到6832个单胎正常妊娠胎儿的超声测量数据。采用三次样条法对陕西省孕16-41周正常单胎妊娠胎儿的双顶径、腹围、股骨长百分位数进行拟合。结果:三次样条拟合胎儿的双顶径、腹围、股骨长百分位数,各百分位数的决定系数均在0.95以上,均方差均在各指标重复测量的容许误差内,拟合结果满意。计算出了胎儿的孕周别双顶径、腹围、股骨长的P3、P10、P25、P50、P75、P90、P97百分位数。结论:三次样条兼顾了曲线拟合中的拟合优度和光滑度,能更好的实现曲线拟合的目的。所建立的孕周别胎儿体格发育指标百分位数符合胎儿宫内生长发育规律,为胎儿宫内生长发育的准确评价提供了科学、准确的评价工具,可用于产科临床和研究工作中。     

Regularized EM algorithm for sparse parameter estimation in nonlinear dynamic systems with application to gene regulatory network inference

Parameter estimation in dynamic systems finds applications in various disciplines, including system biology. The well-known expectation-maximization (EM) algorithm is a popular method and has been widely used to solve system identification and parameter estimation problems. However, the conventional EM algorithm cannot exploit the sparsity. On the other hand, in gene regulatory network inference problems, the parameters to be estimated often exhibit sparse structure. In this paper, a regularized expectation-maximization (rEM) algorithm for sparse parameter estimation in nonlinear dynamic systems is proposed that is based on the maximum a posteriori (MAP) estimation and can incorporate the sparse prior. The expectation step involves the forward Gaussian approximation filtering and the backward Gaussian approximation smoothing. The maximization step employs a re-weighted iterative thresholding method. The proposed algorithm is then applied to gene regulatory network inference. Results based on both synthetic and real data show the effectiveness of the proposed algorithm.     

Performance of individual vs. group sampling for inferring dispersal under isolation‐by‐distance

Models of isolation‐by‐distance formalize the effects of genetic drift and gene flow in a spatial context where gene dispersal is spatially limited. These models have been used to show that, at an appropriate spatial scale, dispersal parameters can be inferred from the regression of genetic differentiation against geographic distance between sampling locations. This approach is compelling because it is relatively simple and robust and has rather low sampling requirements. In continuous populations, dispersal can be inferred from isolation‐by‐distance patterns using either individuals or groups as sampling units. Intrigued by empirical findings where individual samples seemed to provide more power, we used simulations to compare the performances of the two methods in a range of situations with different dispersal distributions. We found that sampling individuals provide more power in a range of dispersal conditions that is narrow but fits many realistic situations. These situations were characterized not only by the general steepness of isolation‐by‐distance but also by the intrinsic shape of the dispersal kernel. The performances of the two approaches are otherwise similar, suggesting that the choice of a sampling unit is globally less important than other settings such as a study's spatial scale.     

An individual and dynamic Body Segment Inertial Parameter validation method using ground reaction forces

Over the last decades a variety of research has been conducted with the goal to improve the Body Segment Inertial Parameters (BSIP) estimations but to our knowledge a real validation has never been completely successful, because no ground truth is available. The aim of this paper is to propose a validation method for a BSIP identification method (IM) and to confirm the results by comparing them with recalculated contact forces using inverse dynamics to those obtained by a force plate. Furthermore, the results are compared with the recently proposed estimation method by Dumas et al. (2007). Additionally, the results are cross validated with a high velocity overarm throwing movement. Throughout conditions higher correlations, smaller metrics and smaller RMSE can be found for the proposed BSIP estimation (IM) which shows its advantage compared to recently proposed methods as of Dumas et al. (2007). The purpose of the paper is to validate an already proposed method and to show that this method can be of significant advantage compared to conventional methods.     

野生经济植物资源橡籽仁可利用价值的研究

以京白种鸡作鸡作试验动,以玉米、稻谷作对照,采用鸡真代谢能（ＴＭＥ）法研究野生经济植物资源橡胶籽仁的可利用营养价值。结果表明,橡籽仁１ｋｇ含量总能（ＧＥ）１６．５３ＭＪ,表观代谢能（ＡＭＥ）１１．１３ＭＪ,真代谢能（ＴＭＥ）１１．６６ＭＪ,,含粗蛋白（ＣＰ）１０．６３％,ＣＰ的表观利用率（ＣＰＡＡ）４５．５５％,真利用率（ＣＰＴＡ）４９．８３％,１７种氨基酸（ＡＡ）总含量９．２３％,必需氨基酸（Ｅ     

利用次序统计量估计种群的平均寿命

本文讨论威布尔分布Ｗ（α,λ）中次序统计量的分布;建立了用次序统计量对威布尔分布进行参数估计,进而估计种群平均寿命和方差的方法,该方法可广泛用于可靠性统计产品平均寿命和方差的估计。     

银杏综合开发利用

本文综述近年来国内对银杏叶、外种皮、种仁、木材及银杏组织培养等方面的综合开发利用。