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。     

EEG gamma-band activity during audiovisual speech comprehension in different noise environments

The presence of cross-modal stochastic resonance in different noise environments has been proved in previous behavioral and event-related potential studies, while it was still unclear whether the gamma-band oscillation study was another evidence of cross-modal stochastic resonance. The multisensory gain of gamma-band activity between the audiovisual (AV) and auditory-only conditions in different noise environments was analyzed. Videos of face motion articulating words concordant with different levels of pink noise were used as stimuli. Signal-to-noise ratios (SNRs) of 0, −4, −8, −12 and −16 dB were selected to measure the speech recognition accuracy and EEG activity for 20 healthy subjects. The power and phase of EEG gamma-band oscillations increased in a time window of 50–90 ms. The multisensory gains of evoked and total activity, as well as phase-locking factor, were greatest at the −12 dB SNR, which were consistent with the behavioral result. The multisensory gain of gamma-band activity showed an inverted U-shaped curve as a function of SNR. This finding confirmed the presence of cross-modal stochastic resonance. In addition, there was a significant correlation between evoked activity and phase-locking factor of gamma-band at five different SNRs. Gamma-band oscillation was believed to play a role in the rapid processing and information linkage strengthening of AV modalities in the early stage of cognitive processes.     

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.     

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.     

Feature extraction in the analysis of proteomic mass spectra

Feature extraction or biomarker selection is a critical step in disease diagnosis and knowledge discovery based on protein MS. Many studies have discussed the classification methods applied in proteomics; however, few could be found to address feature extraction in detail. In this paper, we developed a systematic approach for the extraction of mass spectrum peak apex and peak area with special emphasis on noise filtration and peak calibration. Application to a head and neck cancer data generated at the Eastern Virginia Medical School [Wadsworth, J. T., Somers, K. D., Cazares, L. H., Malik, G. et al.., Clin. Cancer Res. 2004, 10, 1625-1632] revealed that the new feature extraction method would yield consistent and highly discriminatory biomarkers.     

On the dynamics of random Boolean networks subject to noise: Attractors, ergodic sets and cell types

The asymptotic dynamics of random Boolean networks subject to random fluctuations is investigated. Under the influence of noise, the system can escape from the attractors of the deterministic model, and a thorough study of these transitions is presented. We show that the dynamics is more properly described by sets of attractors rather than single ones. We generalize here a previous notion of ergodic sets, and we show that the Threshold Ergodic Sets so defined are robust with respect to noise and, at the same time, that they do not suffer from a major drawback of ergodic sets. The system jumps from one attractor to another of the same Threshold Ergodic Set under the influence of noise, never leaving it. By interpreting random Boolean networks as models of genetic regulatory networks, we also propose to associate cell types to Threshold Ergodic Sets rather than to deterministic attractors or to ergodic sets, as it had been previously suggested. We also propose to associate cell differentiation to the process whereby a Threshold Ergodic Set composed by several attractors gives rise to another one composed by a smaller number of attractors. We show that this approach accounts for several interesting experimental facts about cell differentiation, including the possibility to obtain an induced pluripotent stem cell from a fully differentiated one by overexpressing some of its genes.     

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.     

随机力对激光育种频率影响的研究

本文对ＤＮＡ分子势场用辏力场近似,建立了该近似了Ｆｏｋｋｅｒ－Ｐｌａｎｃｋ方程并用数值法求解了本征值,发现处于生物体内的ＤＮＡ分子,由于受随机力噪声作用,影响了能级分立状态,使其振吸收频率拓宽,从而使激光育种中使用有效激光范围较广。     

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     

Modulation of proton-induced current fluctuations in the human nicotinic acetylcholine receptor channel

The nicotinic acetylcholine receptor (nAChR) is a ligand-gated ion channel that switches upon activation from a closed state to a full conducting state. We found that the mutation δ S268K, located at 12′ position of the second transmembrane domain of the δ subunit of the human nAChR generates a long-lived intermediate conducting state, from which openings to a wild-type like conductance level occur on a submillisecond time scale. Aiming to understand the interplay between structural changes near the 12′ position and channel gating, we investigated the influence of various parameters: different ligands (acetylcholine, choline and epibatidine), ligand concentrations, transmembrane voltages and both fetal and adult nAChRs. Since sojourns in the high conductance state are not fully resolved in time, spectral noise analysis was used as a complement to dwell time analysis to determine the gating rate constants. Open channel current fluctuations are described by a two-state Markov model. The characteristic time of the process is markedly influenced by the ligand and the receptor type, whereas the frequency of openings to the high conductance state increases with membrane hyperpolarization. Conductance changes are discussed with regard to reversible transfer reaction of single protons at the lysine 12′ side chain.