A comparison of three maximum likelihood models for stage-frequency data

A comparison has been made between the estimates obtained from maximum likelihood estimation of gamma, inverse normal, and normal distribution models for stage-frequency data. Results have been compared for six of sets of test data, and from many sets of simulated data. It is concluded that (1) some estimates may differ substantially between the models, (2) estimates from the correct model have little bias, and estimated standard errors are generally close to theoretical values, (3) there are problems in determining degrees of freedom for chi-squared goodness of fit tests, so that it is best to compare test statistics with simulated distributions, and (4) goodness of fit tests may not discriminate well between the three models.     

Equivalence relationships between stage-structured population models

Matrix population models are widely applied in conservation ecology to help predict future population trends and guide conservation effort. Researchers must decide upon an appropriate level of model complexity, yet there is little theoretical work to guide such decisions. In this paper we present an analysis of a stage-structured model, and prove that the model's structure can be simplified and parameterised in such a way that the long-term growth rate, the stable-stage distribution and the generation time are all invariant to the simplification. We further show that for certain structures of model the simplified models require less effort in data collection. We also discuss features of the models which are not invariant to the simplification and the implications of our results for the selection of an appropriate model. We illustrate the ideas using a population model for short-tailed shearwaters (Puffinus tenuirostris). In this example, model simplification can increase parameter elasticity, indicating that an intermediate level of complexity is likely to be preferred.     

类别学习的双系统模型

概念和类别学习是认知心理学研究的核心问题之一,以往的理论主要基于类别学习的单系统理论假设,而近十多年来概念和类别的研究关注类别学习的双重系统问题。目前双系统模型不仅得到了行为学实验的支持,更重要的是得到了临床神经心理和认知神经研究的广泛支持,本文回顾了双系统模型的非行为学研究证据,并指出了今后概念和类别研究应该注意的问题。     

基于模板的蛋白质结构预测

基于模板的蛋白结构预测和不依赖模板的蛋白结构预测是计算预测蛋白质三维结构的两种方法,前者由于具有快速和较高准确性的优点,而得到了广泛的应用.基于模板的结构预测是通过寻找与目标蛋白序列相似并且有实验测定的结构作为模板,进而构建目标序列的结构模型的方法.文章详细综述了基于模板的结构预测方法的步骤、关键环节,并对影响结构预测...     

外周神经源性疼痛的实验模型研究进展

神经源性疼痛是严重困扰人类的临床问题之一。为了探索其发病机理及治疗方法,研究人员建立了多种神经损伤性疼痛模型,其中大鼠部分脊神经结扎,慢性压迫性神经损伤和L5／L6脊神经结扎的外周神经损伤的模型应用最为广泛。细胞模型也显示出了很好的应用前景,原代和永久性感觉神经元,作为研究疼痛发生和发展的分子机理,特别是神经递质的释放和信号转导的研究非常有用。     

A bioenergetic model for simulating athletic performance of intermediate duration

Simulating factors affecting human athletic performance, including fatigue, requires a dynamic model of the bioenergetic capabilities of the athlete. To address general cases, the model needs inputs, outputs, and states with a set of differential equations describing how the inputs affect the states and outputs as functions of time. We improve an existing phenomenological muscle model, removing unnecessarily fast dynamic behavior, adding force–velocity dependence, and generalizing it to task level activities. This makes it more suitable for simulating and calculating optimal strategies of athletic events of medium duration (longer than a sprint but shorter than a marathon). To examine the validity and limitations of the model, parameters have been identified from numerical fits to published experimental data.     

建立胎儿生长受限动物模型的研究进展

动物模型法对于人类疾病病因学及病理生理学的研究有着独特的作用。将动物模型法引入对胎儿生长受限（fetal growth restriction,FGR）的探索,不仅可以让我们观察FGR患者及胎儿在不同孕期各自的表现,还可以让我们对发病胎儿在出生后不同年龄阶段的自然表现进行继续研究。人们在FGR动物模型的建立和利用方面已经积累了大量的宝贵经验,这为进一步阐明FGR的病因学及发病机制创造了条件。     

动物内温性进化研究进展

对动物内温性进化的研究进行了较为系统的论述,包括内温性动物概念的由来、特点和起源的选择因子。内温性起源的选择因子包括8个模型：热生态位扩展模型、恒温与代谢效率模型、降低个体大小模型、姿势改变模型、增加脑大小模型、有氧呼吸能力模型、双亲行为模型和同化能力模型。其中后3个模型较为重要。有氧呼吸能力模型认为,选择提高支持物理运动的最大呼吸能力,而增加的静止代谢作为其相关反应而得以进化。该假说得到种内研究数据的支持,而种问的数据并小完全支持。双亲行为模型是指在鸟兽类中,内温性是对双亲行为选择的结果,因为内温性为双亲控制抚育温度提供了保证。同化能力模型认为,在鸟类和兽类中内温性进化由以下两个因素所推动：①子代出生后双亲行为加强;②为支持每日总体能量高速消耗所需,动物内脏器官能力增强而导致的较高维持消耗。     

Goodness-of-fit diagnostics for Bayesian hierarchical models

This article proposes methodology for assessing goodness of fit in Bayesian hierarchical models. The methodology is based on comparing values of pivotal discrepancy measures (PDMs), computed using parameter values drawn from the posterior distribution, to known reference distributions. Because the resulting diagnostics can be calculated from standard output of Markov chain Monte Carlo algorithms, their computational costs are minimal. Several simulation studies are provided, each of which suggests that diagnostics based on PDMs have higher statistical power than comparable posterior-predictive diagnostic checks in detecting model departures. The proposed methodology is illustrated in a clinical application; an application to discrete data is described in supplementary material.     

遗传性BALB／c白内障小鼠模型培育初报

在生产实践中发现了两只自然突变的白内障雄小鼠,后与BALB／c和C3H／HEJ雌鼠交配,它们的后代雌雄均有白内障个体出现,提示这是一个常染色体显性基因。用传统的方法与BALB／c回交,试图把白内障基因导入BALB／c品系中．旨在建寺一个溃传性BALB／ccat/Cat白内障小鼠模犁。     

模型实验教学在组织学与胚胎学实验教学中的尝试

组织学与胚胎学是重要的医学基础课,属于形态学科。目前,组织学与胚胎学实验教学多采用数码互动实验教学,切片观察为主要手段,而切片观察主要是观察组织的平面结构,欠缺立体结构的观察。模型实验教学是以组织学与胚胎学的形态为中心组织学生制作立体模型,启发学生思维,充分发挥想象力,培养学生的动手能力和实践能力。     

Development and use of a Mathematical model for an antarctic Lake

We describe the development and use of the first mathematical computer model for a polar lake. This dynamic model graphically illustrates seasonal and annual predictions of the changes in the biomass of plankton and attached primary producers, decomposers and consumers, changes in the quantities of potential nutrients and organic matter. The model consists of 100 submodels of which 79 are algebraic equations and 21 are differential equations. It has proven valuable as a means of identifying voids in our limnological program and probable errors in field measurements.Department of StatisticsDepartment of Biology     

Latent class model diagnosis

In many areas of medical research, such as psychiatry and gerontology, latent class variables are used to classify individuals into disease categories, often with the intention of hierarchical modeling. Problems arise when it is not clear how many disease classes are appropriate, creating a need for model selection and diagnostic techniques. Previous work has shown that the Pearson chi 2 statistic and the log-likelihood ratio G2 statistic are not valid test statistics for evaluating latent class models. Other methods, such as information criteria, provide decision rules without providing explicit information about where discrepancies occur between a model and the data. Identifiability issues further complicate these problems. This paper develops procedures for assessing Markov chain Monte Carlo convergence and model diagnosis and for selecting the number of categories for the latent variable based on evidence in the data using Markov chain Monte Carlo techniques. Simulations and a psychiatric example are presented to demonstrate the effective use of these methods.     

Lipid peroxidation modifies the picture of membranes from the "Fluid Mosaic Model" to the "Lipid Whisker Model"

The “Fluid Mosaic Model”, described by Singer and Nicolson, explain both how a cell membrane preserves a critical barrier function while it concomitantly facilitates rapid lateral diffusion of proteins and lipids within the planar membrane surface. However, the lipid components of biological plasma membranes are not regularly distributed. They are thought to contain “rafts” - nano-domains enriched in sphingolipids and cholesterol that are distinct from surrounding membranes of unsaturated phospholipids. Cholesterol and fatty acids adjust the transport and diffusion of molecular oxygen in membranes. The presence of cholesterol and saturated phospholipids decreases oxygen permeability across the membrane. Alpha-tocopherol, the main antioxidant in biological membranes, partition into domains that are enriched in polyunsaturated phospholipids increasing the concentration of the vitamin in the place where it is most required. On the basis of these observations, it is possible to assume that non-raft domains enriched in phospholipids containing PUFAs and vitamin E will be more accessible by molecular oxygen than lipid raft domains enriched in sphingolipids and cholesterol. This situation will render some nano-domains more sensitive to lipid peroxidation than others. Phospholipid oxidation products are very likely to alter the properties of biological membranes, because their polarity and shape may differ considerably from the structures of their parent molecules. Addition of a polar oxygen atom to several peroxidized fatty acids reorients the acyl chain whereby it no longer remains buried within the membrane interior, but rather projects into the aqueous environment “Lipid Whisker Model”. This exceptional conformational change facilitates direct physical access of the oxidized fatty acid moiety to cell surface scavenger receptors.     

延河流域本氏针茅(Stipa bungeana)分布预测——广义相加模型及其应用

物种分布预测,对于物种的保护、利用和恢复具有重要意义.利用广义相加模型(GAM,Generalized Additive Model),对延河流域典型地带性物种本氏针茅(Stipa bungeana)的空间分布预测进行研究,以期为该流域本氏针茅草地的保护、恢复等提供依据.结果表明,本氏针茅分布的环境梯度较广,在坡度、坡向、温度与降雨的各个梯度上都有分布,除高平地和侵蚀剧烈的沟道外,各种地形部位上亦可以存在.建立的广义相加模型表明,本氏针茅的分布主要取决于年均蒸发量和温度季节变化两个因子,而非单纯的降雨、温度因素.从其分布概率看,本氏针茅在延河流域大部分地区都有可能分布,但其分布集中区主要在中北部,与实际观测相符.模型检验表明,建立的模型满足统计要求.     

Computer simulations of in vitro morphogenesis

One of the most important challenges of contemporary biology is understanding how cells assemble into tissues. The complexity of morphogenesis calls for computational tools able to identify the dominant mechanisms involved in shaping tissues. This narrative review presents individual-based computational models that proved useful in simulating phenomena of interest in tissue engineering (TE), a research field that aims to create tissue replacements in the laboratory. First, we briefly describe morphogenetic mechanisms. Then, we present several computational models of cellular and subcellular resolution, along with applications that illustrate their potential to address problems of TE. Finally, we analyze experiments that may be used to validate computational models of tissue constructs made of cohesive cells. Our analysis shows that the models available in the literature are not exploited to their full potential. We argue that, upon validation, a computational model can be used to optimize cell culture conditions and to design new experiments.     

Information-Theoretic Model Selection and Model Averaging for Closed-Population Capture-Recapture Studies

Specification of an appropriate model is critical to valid statistical inference. Given the “true model” for the data is unknown, the goal of model selection is to select a plausible approximating model that balances model bias and sampling variance. Model selection based on information criteria such as AIC or its variant AIC_c, or criteria like CAIC, has proven useful in a variety of contexts including the analysis of open-population capture-recapture data. These criteria have not been intensively evaluated for closed-population capture-recapture models, which are integer parameter models used to estimate population size (N), and there is concern that they will not perform well. To address this concern, we evaluated AIC, AIC_c, and CAIC model selection for closed-population capture-recapture models by empirically assessing the quality of inference for the population size parameter N. We found that AIC-, AIC_c-, and CAIC-selected models had smaller relative mean squared errors than randomly selected models, but that confidence interval coverage on N was poor unless unconditional variance estimates (which incorporate model uncertainty) were used to compute confidence intervals. Overall, AIC and AIC_c outperformed CAIC, and are preferred to CAIC for selection among the closed-population capture-recapture models we investigated. A model averaging approach to estimation, using AIC, AIC_c, or CAIC to estimate weights, was also investigated and proved superior to estimation using AIC-, AIC_c-, or CAIC-selected models. Our results suggested that, for model averaging, AIC or AIC_c should be favored over CAIC for estimating weights.