Neighbor-Dependent Ramachandran Probability Distributions of Amino Acids Developed from a Hierarchical Dirichlet Process Model

Distributions of the backbone dihedral angles of proteins have been studied for over 40 years. While many statistical analyses have been presented, only a handful of probability densities are publicly available for use in structure validation and structure prediction methods. The available distributions differ in a number of important ways, which determine their usefulness for various purposes. These include: 1) input data size and criteria for structure inclusion (resolution, R-factor, etc.); 2) filtering of suspect conformations and outliers using B-factors or other features; 3) secondary structure of input data (e.g., whether helix and sheet are included; whether beta turns are included); 4) the method used for determining probability densities ranging from simple histograms to modern nonparametric density estimation; and 5) whether they include nearest neighbor effects on the distribution of conformations in different regions of the Ramachandran map. In this work, Ramachandran probability distributions are presented for residues in protein loops from a high-resolution data set with filtering based on calculated electron densities. Distributions for all 20 amino acids (with cis and trans proline treated separately) have been determined, as well as 420 left-neighbor and 420 right-neighbor dependent distributions. The neighbor-independent and neighbor-dependent probability densities have been accurately estimated using Bayesian nonparametric statistical analysis based on the Dirichlet process. In particular, we used hierarchical Dirichlet process priors, which allow sharing of information between densities for a particular residue type and different neighbor residue types. The resulting distributions are tested in a loop modeling benchmark with the program Rosetta, and are shown to improve protein loop conformation prediction significantly. The distributions are available at http://dunbrack.fccc.edu/hdp.     

A Bayesian Hierarchical Model for Classification with Selection of Functional Predictors

Summary In functional data classification, functional observations are often contaminated by various systematic effects, such as random batch effects caused by device artifacts, or fixed effects caused by sample‐related factors. These effects may lead to classification bias and thus should not be neglected. Another issue of concern is the selection of functions when predictors consist of multiple functions, some of which may be redundant. The above issues arise in a real data application where we use fluorescence spectroscopy to detect cervical precancer. In this article, we propose a Bayesian hierarchical model that takes into account random batch effects and selects effective functions among multiple functional predictors. Fixed effects or predictors in nonfunctional form are also included in the model. The dimension of the functional data is reduced through orthonormal basis expansion or functional principal components. For posterior sampling, we use a hybrid Metropolis–Hastings/Gibbs sampler, which suffers slow mixing. An evolutionary Monte Carlo algorithm is applied to improve the mixing. Simulation and real data application show that the proposed model provides accurate selection of functional predictors as well as good classification.     

Computer Simulation and Additive-Based Refolding Process of Cysteine-Rich Proteins: VEGF-A as a Model

Refolding of cysteine-rich protein for establishing native conformation and a biologically active form is the most challenging step in recombinant protein synthesis. In this study, expressed vascular endothelial growth factor-A (VEGF-A), as a cysteine-rich protein, in a prokaryotic expression cell was refolded based on computer simulation technique and multiple chemical additive-based buffers to recover its biologically active form. For this purpose, cloned and expressed VEGF-A in Escherichia coli BL21 (DE3) was purified and dialyzed by a basic buffer containing nine diverse chemical additives. In parallel with the evaluations of the applied additives, professional computer simulation software was also used. The activity of refolded protein was evaluated in differentiation of mesenchymal stem cells (MSCs) to the endothelial cells (ECs). The results showed that dialyzing the produced recombinant VEGF-A in chemical additive-based buffers containing cysteine, 1, 4-dithiothreitol (DTT), arginine, and Triton X-100 led to efficient VEGF-A refolding. The results of flowcytometry analysis indicated that CD31 and CD144 as the specific ECs markers in VEGF-A treated MSCs were 31 and 73%, respectively. Protein refolding method using chemical additive-based buffers containing cysteine, DTT, arginine and Triton X-100 was the best accessible technique for refolding cysteine-rich recombinant VEGF-A.     

复杂性结石患者术前应用3D数字打印肾脏仿真技术及手术过程模拟的效果分析

摘要 目的：探讨复杂性结石患者术前应用3D数字打印肾脏仿真技术及手术过程模拟的效果。方法：选入2020年9月至2021年5月在本院就诊的复杂性肾结石患者60例,分为对照组与研究组,各30例。对照组行经皮肾镜碎石术（PCNL）联合输尿管软镜手术,研究组在对照组基础上应用3D打印技术。评价并比较两组的围术期情况、肾功能指标、结石清石率、术后并发症情况等。结果：研究组总手术时间等围手术期指标较对照组低（P＜0.05）;研究组术后血清Scr水平明显低于对照组,BUN显著高于对照组（P＜0.05）,两组术后血清Cys-C水平无明显差异（P＞0.05）;研究组残留结石直径明显小于对照组,结石清除率显著高于对照组（P＜0.05）;两组并发症发生率无明显差异（P>0.05）。结论：术前应用3D数字打印肾脏仿真技术及手术过程模拟可帮助术者快速、准确定位结石位置,提高手术效率及一次性结石清除率,减轻肾脏损伤,降低手术风险。     

Dialysis Continuous Process for Ammonium-Lactate Fermentation of Whey: Mathematical Model and Computer Simulation

A mathematical model was developed to describe a dialysis process for the continuous fermentation of whey lactose to lactic acid, with neutralization to a constant pH by ammonia. In the process, whey of a relatively high concentration is fed into the fermentor circuit at a relatively low rate so that the residual concentration of lactose is low. The fermentor effluent contains ammonium lactate, bacterial cells, and residual whey solids and could be used as a nitrogen-enriched feedstuff for ruminant animals. Only water is fed into the dialysate circuit at a relatively high rate. The dialysate effluent contains purified ammonium lactate and could be converted to lactic acid and ammonium sulfate for industry. The fermentation was specifically modeled as a set of equations representing material balances and rate relationships in the two circuits. Dialysis continuous fermentations, in general, were modeled by combining these equations and by using dimensionless parameters. The generalized model was then solved for the steady state and used to simulate the specific fermentation on a digital computer. The results showed the effects of various material and operational and kinetic parameters on the process and predicted that it could be operated efficiently.     

右美托咪定经鼻滴注对脊柱手术患者围术期血流动力学变化及镇静作用的临床研究

目的:观察右美托咪定经鼻滴注对脊柱手术患者围术期的镇静作用及对血流动力学变化的影响。方法:将90名ASAⅠ~Ⅲ级、18~65岁、拟在全身麻醉下行脊柱手术、且术后须拔除气管导管的患者,随机分为三组:对照组(C组)、右美托咪定1μg/kg组(D1组)和右美托咪定1.5μg/kg组(D2组),n=30。分别记录给药前(T0)、诱导前(T1)、插管前1 min(T2)、插管后1 min(T3)、手术开始即刻(T4)、术毕停全麻药时(T5)、拔管前1 min(T6)、拔管后3 min(T7)和入PACU(T8)时患者的心率(HR)、平均动脉压(MAP)、氧饱和度(SPO_2),术毕停全麻药至拔除气管导管的时间、患者在术后恢复室停留时间、Ramsay镇静评分。结果:T0时3组患者HR、MAP、SPO_2、Ramsay镇静评分无统计学差异(P≥0.05);与C组相比,D1组和D2组各时间点HR、MAP明显降低,Ramsay镇静评分提高(P≤0.05),SPO_2无明显变化(P≥0.05);与D1组相比,D2组各时间点HR、MAP明显降低、Ramsay镇静评分提高(P≤0.05),SPO_2无明显变化(P≥0.05);D1组各时间点HR、MAP、SPO_2、Ramsay镇静评分无明显差异(P≥0.05);D2组HR、MAP、SPO_2、Ramsay镇静评分明显无差异(P≥0.05)。C组T3、T4、T5、T6、T7、T8各时间点HR、MAP均较T1、T2升高,Ramsay镇静评分均明显提高(P≤0.05),SPO_2无明显变化(P≥0.05)。结论:麻醉诱导前40 min右美托咪定经鼻滴注可有效抑制插管和拔管期反应、使血流动力学变化更加稳定,并显著降低降低患者术后躁动的发生率。     

应用多层次结构的功能反应模型比较捕食螨对不同猎物的捕食行为

在害虫生物防治研究中,选择适合的天敌种类或类型是能否有效控制害虫的关键.虽然传统的功能反应试验能够为评价天敌的捕食行为与猎物(或寄主)密度的关系提供有益的依据,但不能根据这些结果对天敌捕食能力进行统计比较.本文在Michaelis-Menten模型的基础上,提出多级层次结构的功能反应模型,使试验习子(如天敌类型、猎物种类等)对捕食行为的影响,表达为模型参数的改变.并根据Ibralim和Rahman(1997)发表的12组功能反应试验结果,应用这一多层次结构模型统计比较不同天敌类型的捕食行为、及猎物种类、猎物生长期对试验结果的影响.取得如下结论:1.根据模型预测值与试验观测结果的吻合程度及模型误差的分布,说明以Michaelis-Menton为基础的多层次结构的功能反应模型能够用于统计比较捕食螨种类间的捕食行为,以及猎物类型、猎物生长阶段和其它环境因子对天敌捕食行为的影响作用.2.这一模型的分析结果不仅从统计角度证实了Ibahim和Rahman(1997)的推测,即红色叶螨是更适于这种捕食螨的猎物.同时为捕食螨种类的选择及田间释放技术提供统计依据.     

A Model of the Effect of Uncertainty on the C elegans L2/L2d Decision

At the end of the first larval stage, the C elegans larva chooses between two developmental pathways, an L2 committed to reproductive development and an L2d, which has the option of undergoing reproductive development or entering the dauer diapause. I develop a quantitative model of this choice using mathematical tools developed for pricing financial options. The model predicts that the optimal decision must take into account not only the expected potential for reproductive growth, but also the uncertainty in that expected potential. Because the L2d has more flexibility than the L2, it is favored in unpredictable environments. I estimate that the ability to take uncertainty into account may increase reproductive value by as much as 5%, and discuss possible experimental tests for this ability.     

基于最大熵模型的中国兜兰属植物潜在分布模拟

基于已知分布点和20个环境因子,该研究利用MaxEnt模型模拟在现在(1970—2000年)气候条件和2种不同共享经济路径情景下(SSP1-2.6、SSP5-8.5)未来(2081—2100年)兜兰属(Paphiopedilum)植物的潜在分布格局,找出影响物种分布的环境因子。结果表明,兜兰属植物的最适宜分布区位于滇东南地区、贵州西南、广西西部、广东南部、海南北部。影响该属植物分布的主要环境因子是年降水量、年温度变化和最干旱季降水量。随着全球变暖,适生区有向北和西北方向扩张的趋势,逐渐往西北亚热带方向延伸。在SSP5-8.5的情景下,高适生区出现大幅度收缩。在未来气候情景下,不同种群的分布区变化规律并不一致,其分布格局响应气候变化的趋势也有所不同,因此该文针对分布区变化趋势不同的物种提出了不同的保护策略。     

A Discrete Event Simulation Model for Evaluating the Performances of an M/G/C/C State Dependent Queuing System

M/G/C/C state dependent queuing networks consider service rates as a function of the number of residing entities (e.g., pedestrians, vehicles, and products). However, modeling such dynamic rates is not supported in modern Discrete Simulation System (DES) software. We designed an approach to cater this limitation and used it to construct the M/G/C/C state-dependent queuing model in Arena software. Using the model, we have evaluated and analyzed the impacts of various arrival rates to the throughput, the blocking probability, the expected service time and the expected number of entities in a complex network topology. Results indicated that there is a range of arrival rates for each network where the simulation results fluctuate drastically across replications and this causes the simulation results and analytical results exhibit discrepancies. Detail results that show how tally the simulation results and the analytical results in both abstract and graphical forms and some scientific justifications for these have been documented and discussed.     

Temporal Expression of Peripheral Blood Leukocyte Biomarkers in a Macaca fascicularis Infection Model of Tuberculosis; Comparison with Human Datasets and Analysis with Parametric/Non-parametric Tools for Improved Diagnostic Biomarker Identification

A temporal study of gene expression in peripheral blood leukocytes (PBLs) from a Mycobacterium tuberculosis primary, pulmonary challenge model Macaca fascicularis has been conducted. PBL samples were taken prior to challenge and at one, two, four and six weeks post-challenge and labelled, purified RNAs hybridised to Operon Human Genome AROS V4.0 slides. Data analyses revealed a large number of differentially regulated gene entities, which exhibited temporal profiles of expression across the time course study. Further data refinements identified groups of key markers showing group-specific expression patterns, with a substantial reprogramming event evident at the four to six week interval. Selected statistically-significant gene entities from this study and other immune and apoptotic markers were validated using qPCR, which confirmed many of the results obtained using microarray hybridisation. These showed evidence of a step-change in gene expression from an ‘early’ FOS-associated response, to a ‘late’ predominantly type I interferon-driven response, with coincident reduction of expression of other markers. Loss of T-cell-associate marker expression was observed in responsive animals, with concordant elevation of markers which may be associated with a myeloid suppressor cell phenotype e.g. CD163. The animals in the study were of different lineages and these Chinese and Mauritian cynomolgous macaque lines showed clear evidence of differing susceptibilities to Tuberculosis challenge. We determined a number of key differences in response profiles between the groups, particularly in expression of T-cell and apoptotic makers, amongst others. These have provided interesting insights into innate susceptibility related to different host `phenotypes. Using a combination of parametric and non-parametric artificial neural network analyses we have identified key genes and regulatory pathways which may be important in early and adaptive responses to TB. Using comparisons between data outputs of each analytical pipeline and comparisons with previously published Human TB datasets, we have delineated a subset of gene entities which may be of use for biomarker diagnostic test development.     

A Continuous Model of Three Scenarios of the Infection Process with Delayed Immune Response Factors

Biophysics - The course of an infection was modeled as a controlled nonlinear process. Understanding the substantial differences observed in the trajectory of the disease caused by the new...     

Reduced Model and Simulation of Neuron with Passive Dendritic Cable: An Eigenfunction Expansion Approach

The neuron models with passive dendritic cables are often used for detailed cortical network simulations (Protopapas et al., 1998; Suarez et al., 1995). For this, the compartment model based on finite volume or finite difference discretization was used. In this paper, we propose an eigenfunction expansion approach combined with singular perturbation and demonstrate that the proposed scheme can achieve an order of magnitude accuracy improvement with the same number of equations. Moreover, it is also shown that the proposed scheme converges much faster to attain a given accuracy. Hence, for a network simulation of the neurons with passive dendritic cables, the proposed scheme can be an attractive alternative to the compartment model, that leads to a low order model with much higher accuracy or that converges faster for a given accuracy.     

Risk of Malaria Reemergence in Southern France: Testing Scenarios with a Multiagent Simulation Model

The Camargue, a region in southern France, is considered a potential site for malaria reemergence. All the suitable factors of the disease transmission system are present—competent mosquito vectors, habitats for their breeding, and susceptible people—except for the parasite. The objective of this study was to test potential drivers of malaria reemergence in this system after possible changes in biological attributes of vectors, agricultural practices, land use, tourism activities, and climate. Scenarios of plausible futures were formulated and then simulated using a spatially explicit and dynamic multiagent simulation: the MALCAM model. Scenarios were developed by varying the value of model inputs. Model outputs were compared based on the contact rate between people and potential malaria vectors, and the number of new infections in case of reintroduction of the parasite in the region. Model simulations showed that the risk of malaria reemergence is low in the Camargue. If the disease would reemerge, it would be the result of a combination of unfavorable conditions: introduction of a large population of infectious people or mosquitoes, combined with high levels of people–vector contacts resulting from significant changes in land use, tourism activities, agricultural policies, biological evolution of mosquitoes, and climate changes. The representation in the MALCAM model of interactions and feedbacks between different agents, and between agents and their environment, led in some cases to counterintuitive results. Results from scenario analyses can help local public health authorities in policy formulation.     

Simulation of a bounded symport/antiport P system with Brane calculi

Membrane systems (also called P systems) and Brane calculi have been recently introduced as formal models inspired by the structure and the functioning of living cells, but having in mind different goals. The aim of Membrane systems was the formal investigation of the computational nature and power of various features of the cell, while Brane calculi aims to define a model capable of a faithful and intuitive representation of various biological processes. The common background of the two formalisms and the recent growing of interests in applying P systems in Systems Biology have raised the natural question of bridging this two research areas. The present paper goes in this direction, as it presents a direct simulation of a variant of P systems by means of Brane calculi. In particular, we consider a Brane calculus based on three operations called Mate/Bud/Drip, and we show how to use such system to simulate Simple symport/antiport P systems, a variant of P systems purely based on communication of objects. As an example, a simplified sodium-potassium pump modeled in Simple SA is encoded in Mate/Bud/Drip Brane calculus.     

综述——新型纳米生物材料的研发：医学纳米颗粒对类细胞膜作用的仿真研究进展

细胞膜是包围细胞质、维持细胞内部组分动态平衡的一个半透膜,参与细胞黏附、离子传导、信号传导等分子生物学过程．类细胞膜提供了有效的模型研究这些生物学过程,故而分子层面上研究医学纳米颗粒对类细胞膜的作用有助于评估纳米颗粒的生物安全性以及促进纳米颗粒的生物医学应用．本文初步探讨了医学纳米颗粒对类细胞膜作用的仿真研究进展,并在此基础上结合膜生物物理学的研究热点对后续的研究进行了展望．     

酿酒酵母糖酵解途径中酶量变化对乙醇浓度影响的模拟分析

代谢组学是系统生物学的一个重要组成部分,应用相关方法获得了大量的数据。如何处理这些数据以及如何将这些数据与其他组学数据结合起来的问题不容忽视。在酶的反应动力学方程中引入“酶量倍数因子”能够解决其中的部分问题。如果反应动力学方程中酶的量发生变化,只需要改变相应的酶量倍数因子的数值。为了观察酿酒酵母糖酵解途径中酶量变化对乙醇浓度的影响,设定了高低两个酶量水平进行计算机模拟,对应的酶量倍数因子分别为10和0.1。基于计算机模拟结果,使用聚类分析方法,12种酶被分为两类。属于第一大类的四种酶ADH、HK、PFK和PDC,均催化不可逆反应。第二大类8种酶中的6种,ALD、GAPDH、GlcTrans、lpPEP、PGI和TIM均催化可逆反应。第二大类中另外两种酶lpGlyc和PK催化不可逆反应。按照这种方法,代谢组和蛋白质组数据能较容易地结合起来对系统作出较全面的分析。