Distributions-per-Level: A Means of Testing Level Detectors and Models of Patch-Clamp Data

Level or jump detectors generate the reconstructed time series from a noisy record of patch-clamp current. The reconstructed time series is used to create dwell-time histograms for the kinetic analysis of the Markov model of the investigated ion channel. It is shown here that some additional lines in the software of such a detector can provide a powerful new means of patch-clamp analysis. For each current level that can be recognized by the detector, an array is declared. The new software assigns every data point of the original time series to the array that belongs to the actual state of the detector. From the data sets in these arrays distributions-per-level are generated. Simulated and experimental time series analyzed by Hinkley detectors are used to demonstrate the benefits of these distributions-per-level. First, they can serve as a test of the reliability of jump and level detectors. Second, they can reveal beta distributions as resulting from fast gating that would usually be hidden in the overall amplitude histogram. Probably the most valuable feature is that the malfunctions of the Hinkley detectors turn out to depend on the Markov model of the ion channel. Thus, the errors revealed by the distributions-per-level can be used to distinguish between different putative Markov models of the measured time series. Abbreviations: AMFE = anomalous mole fraction effect; C, Z = closed state; DHD = sublevel Hinkley detector; HMM = Hidden Markov model; O, F = openstate; S = subconductance level     

Multivariate analysis of noise in genetic regulatory networks

Stochasticity is an intrinsic property of genetic regulatory networks due to the low copy numbers of the major molecular species, such as, DNA, mRNA, and regulatory proteins. Therefore, investigation of the mechanisms that reduce the stochastic noise is essential in understanding the reproducible behaviors of real organisms and is also a key to design synthetic genetic regulatory networks that can reliably work. We use an analytical and systematic method, the linear noise approximation of the chemical master equation along with the decoupling of a stoichiometric matrix. In the analysis of fluctuations of multiple molecular species, the covariance is an important measure of noise. However, usually the representation of a covariance matrix in the natural coordinate system, i.e. the copy numbers of the molecular species, is intractably complicated because reactions change copy numbers of more than one molecular species simultaneously. Decoupling of a stoichiometric matrix, which is a transformation of variables, significantly simplifies the representation of a covariance matrix and elucidates the mechanisms behind the observed fluctuations in the copy numbers. We apply our method to three types of fundamental genetic regulatory networks, that is, a single-gene autoregulatory network, a two-gene autoregulatory network, and a mutually repressive network. We have found that there are multiple noise components differently originating. Each noise component produces fluctuation in the characteristic direction. The resulting fluctuations in the copy numbers of the molecular species are the sum of these fluctuations. In the examples, the limitation of the negative feedback in noise reduction and the trade-off of fluctuations in multiple molecular species are clearly explained. The analytical representations show the full parameter dependence. Additionally, the validity of our method is tested by stochastic simulations.     

文拉法辛联合团体人际心理疗法对社交恐惧症患者心理状态、自我效能感和社会功能的影响

摘要 目的：探讨团体人际心理疗法联合文拉法辛对社交恐惧症（SAD）患者心理状态、自我效能感和社会功能的影响。方法：选取2017年4月~2020年4月期间我院收治的98例SAD患者,根据奇偶数法将患者分为对照组49例和联合组49例。对照组给予文拉法辛治疗,联合组在对照组的基础上联合团体人际心理疗法治疗,对比两组SAD症状改善情况、心理状态、自我效能感和社会功能。结果：两组干预后社交回避、社交苦恼评分均下降,且联合组低于对照组（P<0.05）。两组干预后焦虑自评量表（SAS)、抑郁自评量表（SDS)评分均下降,且联合组低于对照组（P<0.05）。两组干预后表达积极、管理沮丧、管理生气自我效能感评分均升高,且联合组高于对照组（P<0.05）。两组干预后社会功能缺陷筛选量表（SDSS）、社会适应能力评定量表（SAFE）评分均降低,且联合组低于对照组（P<0.05）。结论：团体人际心理疗法联合文拉法辛治疗SAD患者,可缓解其抑郁、焦虑症状,提高自我效能感及社会功能,疗效较好。     

Investigating interaction of ligands with voltage dependent anion channel through noise analyses

Ion channel-protein complexes inserted in the membrane act as molecular gates for transport across the membrane. The opening and closing of these gates can be controlled by one or more variables like ligands (small molecules, proteins, etc.), transmembrane voltage, and the concentration gradient of a chemical across the membrane. We have shown how current noise profile of voltage dependent anion channel can be used to monitor change in the gating of the channel after its modulation by various ligands. This is being proposed as a novel method to probe the interaction of ion channels with ligands.     

Spectral processing methods for the removal of t1 noise and solvent artifacts from NMR spectra

Summary A data processing method is described which reduces the effects of t₁ noise artifacts and improves the presentation of 2D NMR spectral data. A t₁ noise profile is produced by measuring the average noise in each column. This profile is then used to determine weighting coefficients for a sliding weighted smoothing filter that is applied to each row, such that the amount of smoothing each point receives is proportional to both its estimated t₁ noise level and the level of t₁ noise of neighbouring points. Thus, points in the worst t₁ noise bands receive the greatest smoothing, whereas points in low-noise regions remain relatively unaffected. In addition, weighted smoothing allows points in low-noise regions to influence neighbouring points in noisy regions. This method is also effective in reducing the noise artifacts associated with the solvent resonance in spectra of biopolymers in aqueous solution. Although developed primarily to improve the quality of 2D NMR spectra of biopolymers prior to automated analysis, this approach should enhance processing of spectra of a wide range of compounds and can be used whenever noise occurs in discrete bands in one dimension of a multi-dimensional spectrum.     

Changes in Purinoceptor Distribution and Intracellular Calcium Levels following Noise Exposure in the Outer Hair Cells of the Guinea Pig

Among the cells of the inner ear, the outer hair cells (OHCs) are the most important targets of noise-induced effects, being the most sensitive cell types. The aim of this study was to examine the effects of noise (50 Hz-20 kHz, 80 dB sound pressure level, 14 days) on intracellular calcium levels and on the expression pattern of purinoceptors in the membrane of the OHCs of the guinea pig and to measure the stiffness changes of the lateral membrane of these cells. In noise-exposed animals, the resting intracellular calcium concentration increased compared to nontreated animals and was slightly higher in the cells of the basal (219 ± 29 nM) than in the apical (181 ± 24 nM) turns of the cochlea. After application of 180 μM adenosine triphosphate, the intracellular calcium level rose by 60 ± 22 nM in cells from the apical and by 44 ± 10 nM in cells from the basal turns, significantly less than in nontreated animals. Expression of the P_2X1, P_2X2, P_2X4, P_2X7, P_2Y1 and P_2Y4 receptor subtypes was suppressed, while expression of the P_2Y2 subtype did not decrease in either of the two preparations. In parallel with the increase in intracellular calcium concentration, the stiffness of the lateral wall of the OHCs was increased. Noise-induced changes in intracellular calcium homeostasis and subsequently in the calcium-dependent regulatory mechanisms may modify OHC lateral wall stiffness and may lead to reduction of the efficacy of the cochlear amplifier.     

Stochastic models for inferring genetic regulation from microarray gene expression data

Microarray expression profiles are inherently noisy and many different sources of variation exist in microarray experiments. It is still a significant challenge to develop stochastic models to realize noise in microarray expression profiles, which has profound influence on the reverse engineering of genetic regulation. Using the target genes of the tumour suppressor gene p53 as the test problem, we developed stochastic differential equation models and established the relationship between the noise strength of stochastic models and parameters of an error model for describing the distribution of the microarray measurements. Numerical results indicate that the simulated variance from stochastic models with a stochastic degradation process can be represented by a monomial in terms of the hybridization intensity and the order of the monomial depends on the type of stochastic process. The developed stochastic models with multiple stochastic processes generated simulations whose variance is consistent with the prediction of the error model. This work also established a general method to develop stochastic models from experimental information.     

Non-Stationary Fluctuation Analysis of Macroscopic Gap Junction Channel Records

Non-stationary fluctuation analysis was applied to macroscopic records of junctional currents arising from homotypic Cx37 and Cx43 gap junction channels expressed in RIN cells. The data were analyzed by a modification of existing analytical methods that takes endemic uncoupling into account. The results are consistent with both channels having open probabilities ranging from 0.7 to near unity for low transjunctional voltages. The analysis also yielded estimates of single-channel conductances for the two channel types similar to those seen in single-channel recordings. The results presented here show that fluctuation analysis can be used to extract single-channel gap junctional conductances from macroscopic double whole-cell recordings. These results also constitute empirically determined estimates of the open probability that are not model-dependent.     

Biophysical and biological meanings of healthspan from C. elegans cohort

Lifespan among individuals ranges widely in organisms from yeast to mammals, even in an isogenic cohort born in a nearly uniform environment. Needless to say, genetic and environmental factors are essential for aging and lifespan, but in addition, a third factor or the existence of a stochastic element must be reflected in aging and lifespan. An essential point is that lifespan or aging is an unpredictable phenomenon. The present study focuses on elucidating the biophysical and biological meanings of healthspan that latently indwells a stochastic nature. To perform this purpose, the nematode Caenorhabditis elegans served as a model animal. C. elegans fed a healthy food had an extended healthspan as compared to those fed a conventional diet. Then, utilizing this phenomenon, we clarified a mechanism of healthspan extension by measuring the single-worm ATP and estimating the ATP noise (or the variability of the ATP content) among individual worms and by quantitatively analyzing biodemographic data with the lifespan equation that was derived from a fluctuation theory.