离子通道数学模型

介绍了离子通道记录的记忆性及其反映这种记忆的齐次Markov模型和具有随机环境的Markov模型,并且上述模型较好的解决“Omission”问题,讨论了模型反映的离子通道记录的物理及生理机制,认为离子通道记录记忆性反映离子通道记忆性。     

离子通道亚型与其基因共表达的关联研究

离子通道亚型与其基因共表达的关联对研究离子通道功能有重要意义。文章采用主成分分析和模糊C-均值聚类算法对数据进行分析, 将方法应用到人类和小鼠两套表达谱数据, 结果发现离子通道亚型中钾离子通道、钙离子通道、氯离子通道和受体激活型离子通道的表达谱聚类结果与生物学分类有较好的一致性, 体现了离子通道亚型在mRNA水平上的共表达, 并证实了通过离子通道表达谱能很好的对离子通道的功能亚型进行分类。     

一种模型模拟结果的统计检验方法

模拟结果的准确性是衡量生态学模型是否成功的关键,但采用统计学方法判别模型模拟结果与观察值相符程度的报道较少。根据两个直线回归方程能否合并为一个方程的统计学检验方法,提出了通过检验观察值与模拟值直线回归方程和1∶1直线方程截距与斜率是否相同,进而在统计显著水平上判断生态学模型模拟值与观察值一致性的统计学检验方法。数据检验表明,此方法可以较好解决判断生态学模型模拟结果准确性的问题。     

单离子通道电信号的依赖性

运用时间序列关于信号依赖性的基本理论,讨论了单离子通道电信号的依赖性,得到关于依赖性的简明判别准则．     

DICE：电压门控离子通道电生理实验数据库

针对现有相关文献中离子通道电生理数据繁多且分散的特点,开发了一套电压门控离子通道电生理实验数据库。数据库中目前主要包括钠离子通道序列数据、调制剂分子结构和序列数据,并收集整理了文献中调制剂和通道相互作用时的电生理学数据和药理学数据。系统实现了数据的收集、录入、存储和查询,为后期进行数据挖掘奠定了基础。用户可以通过网址http：／／biodb．sgst．cn／DICE对数据库进行访问。     

下颌骨的性别判别分析研究

对183例国人成年下颌骨的统计检验表明,13项测量数据中有12项性别差异显著。其中下颌枝高性别差异最为明显,其单项性别判别率达80％。采用Fisher判别分析法建立了11项判定国人下颌骨性别的判别函数,判别率为85.2％—87.4％。     

常用的生物统计方法及其R语言实现

统计分析是科学研究中一个极其重要的环节。本文以昆虫学研究为实例,利用模拟数据,总结了14种常用的生物统计方法及其R语言实现,重点强调了如何根据科学问题和样本数据的具体情形选取合适的统计方法。这些统计方法包括可用于均值比较分析的符号检验、Wilcoxon符号秩检验、t-检验、Wilcoxon秩和检验、Kruskal-Wallis检验、Nemenyi检验、Tukey检验、Friedman检验、单因素方差分析、重复测量方差分析和可用于相关性分析的卡方检验、Fisher精确检验、Spearman秩相关分析、Pearson相关分析,可为生物统计或R语言基础薄弱的昆虫学工作者提供参考。     

蚕茧近红外反射(NIR)光谱的模式识别II.光谱识别中特征值选取方法的探讨

为提高蚕茧近红外光谱识别中雌雄茧的判别效果,从四个方面探讨了从光谱数据中提取特征向量的方法。对中系品种、日系品种及其杂交种１３２３颗蚕茧的光谱数据分析的结果表明：以减少错判率为目标选取特征向量,距离逐步判别方法优于Ｂａｙｅｓ逐步判别方法和Ｆｉｓｈｅｒ逐步判别方法;手动选择特征值优于自动选择特征值;２群逐步判别优于３群逐步判别;２阶导数光谱优于１阶导数光谱。从而给出蚕茧光谱识别中的特征向量选取及雌雄判别方法。     

安徽鹞落坪国家级自然保护区落叶阔叶林树种多样性、种间联结及群落稳定性变化

基于样方法的种间联结性研究多集中于群落不同层次联结性与相关性,群落内主要物种的生态位与种间联结特征,但对群落内物种的种间联结及群落稳定性变化系统性研究不足。研究利用鹞落坪落叶阔叶林11.56 hm²森林动态监测样地间隔5年(2016—2021年)的2次群落调查数据,采用α多样性指数、方差比率法(VR)、χ²检验、Pearson相关检验、Spearman秩相关检验和M. Godron稳定性等方法,对鹞落坪落叶阔叶林群落树种多样性、种间联结及群落稳定性变化进行分析。2021年与2016年比较结果表明：(1)群落优势种重要值增加,其中杜鹃、大果山胡椒和垂枝泡花树等灌木或小乔木数量急增导致累积重要值增加。(2)方差比率从1.35提升为2.87,总体正联结有了显著提高;χ²检验结果显示主要物种间正负关联种对比值由0.97提升为1.25,正关联种对开始占据优势。(3)Pearson相关检验和Spearman秩相关检验显示极显著和显著相关种对分别由132对和160对增加到152对和226对,种间相关性增强。(4)M. Godron稳定...     

辽东山区次生林优势木本植物种间联结与相关分析

为了解辽东山区次生林群落结构特征,判别优势树种在群落中的地位和作用,基于2×2联列表,方差比率(VR)、!2检验、Pearson相关系数和Spearman秩相关系数等指标,对群落重要值较高的17个优势树种进行种间联结和相关性的定量研究。结果表明,17个优势树种在不同样方尺度下总体关联性表现为正联结;!2检验显示,在20 m×20 m样方尺度下,17个优势种组成的136个种对中,86个种对呈正联结,50个种对呈负联结;Pearson相关系数检验显示,69个种对呈正相关,67个种对呈负相关;Spearman秩相关系数检验显示,81个种对呈正相关,55个种对呈负相关。对种间联结及相关性的研究可为进一步揭示物种生物学特性、种间关系和生境条件等综合作用下的种群分布格局提供依据。     

Exploration of the structural features defining the conduction properties of a synthetic ion channel.

The finite-difference Poisson-Boltzmann methodology was applied to a series of parallel, alpha-helical bundle models of the designed ion channel peptide Ac-(LSSLLSL)3-CONH2. This method is able to fully describe the current-voltage curves for this channel and quantitatively explains their cation selectivity and rectification. We examined a series of energy-minimized models representing different aggregation states, side-chain rotamers, and helical rotations, as well as an ensemble of structures from a molecular dynamics trajectory. Potential energies were computed for single, permeating K+ and Cl- ions at a series of positions along a central pathway through the models. A variable-electric-field Nernst-Planck electrodiffusion model was used, with two adjustable parameters representing the diffusion coefficients of K+ and Cl- to scale the individual ion current magnitudes. The ability of a given DelPhi potential profile to fit the experimental data depended strongly on the magnitude of the desolvation of the permeating ion. Below a pore radius of 3.8 A, the predicted profiles showed large energy barriers, and the experimental data could be fit only with unrealistically high values for the K+ and Cl- diffusion coefficients. For pore radii above 3.8 A, the desolvation energies were 2kT or less. The electrostatic calculations were sensitive to positioning of the Ser side chains, with the best fits associated with maximum exposure of the Ser side-chain hydroxyls to the pore. The backbone component was shown to be the major source of asymmetry in the DelPhi potential profiles. Only two of the energy-minimized structures were able to explain the experimental data, whereas an average of the dynamics structures gave excellent agreement with experimental results. Thus this method provides a promising approach to prediction of current-voltage curves from three-dimensional structures of ion channel proteins.     

A physical model of potassium channel activation: from energy landscape to gating kinetics

We have developed a method for rapidly computing gating currents from a multiparticle ion channel model. Our approach is appropriate for energy landscapes that can be characterized by a network of well-defined activation pathways with barriers. To illustrate, we represented the gating apparatus of a channel subunit by an interacting pair of charged gating particles. Each particle underwent spatial diffusion along a bistable potential of mean force, with electrostatic forces coupling the two trajectories. After a step in membrane potential, relaxation of the smaller barrier charge led to a time-dependent reduction in the activation barrier of the principal gate charge. The resulting gating current exhibited a rising phase similar to that measured in voltage-dependent ion channels. Reduction of the two-dimensional diffusion landscape to a circular Markov model with four states accurately preserved the time course of gating currents on the slow timescale. A composite system containing four subunits leading to a concerted opening transition was used to fit a series of gating currents from the Shaker potassium channel. We end with a critique of the model with regard to current views on potassium channel structure.     

Strengths and Limits of Beta Distributions as a Means of Reconstructing the True Single-Channel Current in Patch Clamp Time Series with Fast Gating

Single-channel current seems to be one of the most obvious characteristics of ion transport. But in some cases, its determination is more complex than anticipated at first glance. Problems arise from fast gating in time series of patch-clamp current, which can lead to a reduced apparent (measured) single-channel current. Reduction is caused by undetected averaging over closed and open intervals in the anti-aliasing filter. Here it is shown that fitting the measured amplitude histograms by Beta distributions is an efficient tool of reconstructing the true current level from measured data. This approach becomes even more powerful when it is applied to amplitude distributions-per-level. Simulated time series are employed to show that the error sum is a good guideline for finding the correct current level. Furthermore, they show that a Markov model smaller than the one used for gating analysis can be used for current determination (mostly O-C, i.e., open-closed). This increases the reliability of the Beta fit. The knowledge of the true current level is not only important for the understanding of the biophysical properties of the channel. It is also a prerequisite for the correct determination of the rate constants of gating. The approach is applied to measured data. The examples reveal the limits of the analysis imposed by the signal-to-noise ratio and the shape of the amplitude distribution. One application shows that the negative slope of the I-V curve of the human MaxiK channel expressed in HEK293 cells is caused by fast gating.     

Calculation of local Hurst exponents in the Ca(2+)-activated K(+)-channel dwell time

A novel method based on the maximum overlap wavelet transform of dwell time series is proposed. Information on local multifractal properties of the series, namely local Hurst exponents or Holder exponents, was obtained. The results confirm the presence of multifractality and intrinsic correlations in the Ca(2+)-activated K+ channel dwell time series. The data on the local multifractal structure of the series can be interpreted in terms of processes having self-organized criticality. The proposed approach allows one to widen the store of methods for the analysis of single ion channel activity.     

Existence of memory in membrane channels: analysis of ion current through a voltage‐dependent potassium single channel

Ion current fluctuation of voltage‐dependent potassium channel in LβT2 cells has been investigated by autocorrelation function and DFA (detrended fluctuation analysis) methods. The calculation of the autocorrelation function exponent and DFA exponent of the sample was based on the digital signals or the 0–1 series corresponding to closing and opening of channels after routine evolution, rather than the sequence of sojourn times. The persistent character of the correlation of the time series was evident from the slow decay of the autocorrelation function. DFA exponent α was significantly greater than 0.5. The main outcome has been the demonstration of the existence of memory in this ion channel. Thus, the ion channel current fluctuation provided information about the kinetics of the channel protein. The result suggests the correlation character of the ion channel protein non‐linear kinetics indicates whether the channel is open or not.     

Single-channel dose-response studies in single, cell-attached patches.

A method for carrying out dose-response studies of ion channel currents in cell-attached patches has been devised. Patch pipettes are filled at the tip with a solution containing one concentration of ligand and then backfilled with another. The concentration of ligand at the membrane is described as a function of time by the equation for diffusion in a cone, allowing response vs. time data to be transformed into a dose-response curve. For Xenopus myocyte cholinergic receptors, examples of the use of this method are given for several concentration-dependent reactions including blockade by the local anesthetic QX-222, activation by acetylcholine, and modulation of current amplitude by sodium ions. Several methods of analyzing the nonstationary channel kinetics are presented, including a pseudo-stationary approach that uses interval likelihood maximization.     

Correlation character of ionic current fluctuations: analysis of ion current through a voltage-dependent potassium single channel

The gating of ion channels has widely been modeled by assuming the transition between open and closed states is a memoryless process. Nevertheless, the statistical analysis of an ionic current signal recorded from voltage dependence K(+) single channel is presented. Calculating the sample auto-correlation function of the ionic current based on the digitized signals, rather than the sequence of open and closed states duration time. The results provide evidence for the existence of memory. For different voltages, the ion channel current fluctuation has different correlation attributions. The correlations in data generated by simulation of two Markov models, on one hand, auto-correlation function of the ionic current shows a weaker memory, after a delayed period of time, the attribute of memory does not exist; on the other hand, the correlation depends on the number of states in the Markov model. For V(p)=-60 mV pipette potential, spectral analysis of ion channel current was conducted, the result indicates that the spectrum is not a flat spectrum, the data set from ionic current fluctuations shows considerable variability with a broad 1/f -like spectrum, alpha=1.261+/-0.24. Thus the ion current fluctuations give information about the kinetics of the channel protein, the results suggest the correlation character of ion channel protein nonlinear kinetics regardless of whether the channel is in open or closed state.     

Fast and accurate fitting of relaxation dispersion data using the flexible software package GLOVE

Relaxation dispersion spectroscopy is one of the most widely used techniques for the analysis of protein dynamics. To obtain a detailed understanding of the protein function from the view point of dynamics, it is essential to fit relaxation dispersion data accurately. The grid search method is commonly used for relaxation dispersion curve fits, but it does not always find the global minimum that provides the best-fit parameter set. Also, the fitting quality does not always improve with increase of the grid size although the computational time becomes longer. This is because relaxation dispersion curve fitting suffers from a local minimum problem, which is a general problem in non-linear least squares curve fitting. Therefore, in order to fit relaxation dispersion data rapidly and accurately, we developed a new fitting program called GLOVE that minimizes global and local parameters alternately, and incorporates a Monte-Carlo minimization method that enables fitting parameters to pass through local minima with low computational cost. GLOVE also implements a random search method, which sets up initial parameter values randomly within user-defined ranges. We demonstrate here that the combined use of the three methods can find the global minimum more rapidly and more accurately than grid search alone.