The use of mixed logit models to reflect heterogeneity in capture-recapture studies

We examine issues in estimating population size N with capture-recapture models when there is variable catchability among subjects. We focus on a logistic-normal mixed model, for which the logit of the probability of capture is an additive function of a random subject and a fixed sampling occasion parameter. When the probability of capture is small or the degree of heterogeneity is large, the log-likelihood surface is relatively flat and it is difficult to obtain much information about N. We also discuss a latent class model and a log-linear model that account for heterogeneity and show that the log-linear model has greater scope. Models assuming homogeneity provide much narrower intervals for N but are usually highly overly optimistic, the actual coverage probability being much lower than the nominal level.     

Photochemical studies of iron-only hydrogenase model compounds

FTIR studies of the photochemical reaction of Fe₂(SCH₂CH₂CH₂S)(CO)₆ (1) in both acetonitrile and toluene are described. Photochemical and thermal reactivity was studied under air, nitrogen and CO, and results are consistent with the loss of CO from 1 upon photolysis and the generation of a solvento species in both coordinating and non-coordinating solvents.     

Azolla--a model organism for plant genomic studies

The aquatic ferns of the genus Azolla are nitrogen-fixing plants that have great potentials in agricultural production and environmental conservation. Azolla in many aspects is qualified to serve as a model organism for genomic studies because of its importance in agriculture, its unique position in plant evolution, its symbiotic relationship with the N2-fixing cyanobacterium, Anabaena azollae, and its moderate-sized genome. The goals of this genome project are not only to understand the biology of the Azolla genome to promote its applications in biological research and agriculture practice but also to gain critical insights about evolution of plant genomes. Together with the strategic and technical improvement as well as cost reduction of DNA sequencing, the deciphering of their genetic code is imminent.     

Thermal and NMR studies of chick embryo lecithins

Proton magnetic resonance and differential scanning calorimetry have been used to investigate model membranes composed of known molecular species of lecithins from liver, lung and brain of 19-day chick embryos.Above the chain-melting temperature the three systems studied show a similar behaviour, with the T₁ increasing with temperature and giving a similar activation energy in each case. Throughout the temperature range analyzed only a single T₁ is observed. These T₁ values can be interpreted in terms of the chemical composition of molecular species of lecithins.Calorimetric techniques show different behaviour in the three models. Thermodynamic parameters of the gel-to-liquid transition are calculated and interpreted in terms of the molecular species of lecithins.     

家域研究进展

家域是动物行为学和保护生物学的重要概念之一,它在动物对资源环境的适应与选择,种群密度及社会关系等生态学过程研究中有着重要的作用.对家域的内涵、特征、估算方法(包括取样方法,样本含量,位点数据自相关,模型评价等)等方面进行阐述,总结了家域估算模型的发展过程及发展方向,评述了3种主要家域估算模型的优势与不足,并结合最新的理论和应用,对未来的研究方向提出建议.     

Meta-analysis of studies with missing data

Summary .  Consider a meta-analysis of studies with varying proportions of patient-level missing data, and assume that each primary study has made certain missing data adjustments so that the reported estimates of treatment effect size and variance are valid. These estimates of treatment effects can be combined across studies by standard meta-analytic methods, employing a random-effects model to account for heterogeneity across studies. However, we note that a meta-analysis based on the standard random-effects model will lead to biased estimates when the attrition rates of primary studies depend on the size of the underlying study-level treatment effect. Perhaps ignorable within each study, these types of missing data are in fact not ignorable in a meta-analysis. We propose three methods to correct the bias resulting from such missing data in a meta-analysis: reweighting the DerSimonian–Laird estimate by the completion rate; incorporating the completion rate into a Bayesian random-effects model; and inference based on a Bayesian shared-parameter model that includes the completion rate. We illustrate these methods through a meta-analysis of 16 published randomized trials that examined combined pharmacotherapy and psychological treatment for depression.     

Predicting biofilm deformation with a viscoelastic phase-field model: Modeling and experimental studies

Biofilms commonly develop in flowing aqueous environments, where the flow causes the biofilm to deform. Because biofilm deformation affects the flow regime, and because biofilms behave as complex heterogeneous viscoelastic materials, few models are able to predict biofilm deformation. In this study, a phase-field (PF) continuum model coupled with the Oldroyd-B constitutive equation was developed and used to simulate biofilm deformation. The accuracy of the model was evaluated using two types of biofilms: a synthetic biofilm, made from alginate mixed with bacterial cells, and a Pseudomonas aeruginosa biofilm. Shear rheometry was used to experimentally determine the mechanical parameters for each biofilm, used as inputs for the model. Biofilm deformation under fluid flow was monitored experimentally using optical coherence tomography. The comparison between the experimental and modeling geometries, for selected horizontal cross sections, after fluid-driven deformation was good. The relative errors ranged from 3.2 to 21.1% for the synthetic biofilm and from 9.1 to 11.1% for the P. aeruginosa biofilm. This is the first demonstration of the effectiveness of a viscoelastic PF biofilm model. This model provides an important tool for predicting biofilm viscoelastic deformation. It also can benefit the design and control of biofilms in engineering systems.     

Combining longitudinal studies of PSA

Prostate-specific antigen (PSA) is a biomarker commonly used to screen for prostate cancer. Several studies have examined PSA growth rates prior to prostate cancer diagnosis. However, the resulting estimates are highly variable. In this article we propose a non-linear Bayesian hierarchical model to combine longitudinal data on PSA growth from three different studies. Our model enables novel investigations into patterns of PSA growth that were previously impossible due to sample size limitations. The goals of our analysis are twofold: first, to characterize growth rates of PSA accounting for differences when combining data from different studies; second, to investigate the impact of clinical covariates such as advanced disease and unfavorable histology on PSA growth rates.     

进化基因组学在昆虫天然免疫研究中的应用前景

整合基因组学和进化论而发展起来的进化基因组学正在逐渐改变传统昆虫学的研究模式。对昆虫天然免疫的研究已不再仅仅依靠实验学方法。3种全基因组序列被破译的模式昆虫(黑腹果蝇、冈比亚按蚊和意大利蜜蜂)将为这些研究引入新的方向。该文将以模式昆虫为代表,简要介绍如何利用进化上的趋同和趋异概念建立一特定昆虫物种的抗微生物肽基因蓝图;以及如何利用基因组数据和进化分析方法鉴定控制昆虫Toll信号通路关键组分Spatzle配体的进化优势位点。     

Poisson-Boltzmann model studies of molecular electrostatic properties of the cAMP-dependent protein kinase

Protonation equilibria of residues important in the catalytic mechanism of a protein kinase were analyzed on the basis of the Poisson-Boltzmann electrostatic model along with a cluster-based treatment of the multiple titration state problem. Calculations were based upon crystallographic structures of the mammalian cAMP-dependent protein kinase, one representing the so called closed form of the enzyme and the other representing an open conformation. It was predicted that at pH 7 the preferred form of the phosphate group at the catalytically essential threonine 197 (P-Thr197) in the closed form is dianionic, whereas in the open form a monoanionic ionization state is preferred. This dianionic state of P-Thr197, in the closed form, is stabilized by interactions with ionizable residues His87, Arg165, and Lys189. Our calculations predict that the hydroxyl of the Ser residue in the peptide substrate is very difficult to ionize, both in the closed and open structures of the complex. Also, the supposed catalytic base, Asp166, does not seem to have a pK _a appropriate to remove the hydroxyl group proton of the peptide substrate. However, when Ser of the peptide substrate is forced to remain ionized, the predicted pK _a of Asp166 increases strongly, which suggests that the Asp residue is a likely candidate to attract the proton if the Ser residue becomes deprotonated, possibly during some structural change preceding formation of the transition state. Finally, in accord with suggestions made on the basis of the pH-dependence of kinase kinetics, our calculations predict that Glu230 and His87 are the residues responsible for the molecular pK _a values of 6.2 and 8.5, observed in the experiment. Received: 19 October 1998 / Revised version: 12 April 1999 / Accepted: 15 April 1999     

Sample-size redetermination for repeated measures studies

Clinical trialists recently have shown interest in two-stage procedures for updating the sample-size calculation at an interim point in a trial. Because many clinical trials involve repeated measures designs, it is desirable to have available practical two-stage procedures for such designs. Shih and Gould (1995, Statistics in Medicine 14, 2239-2248) discuss sample-size redetermination for repeated measures studies but under a highly simplified setup. We develop two-stage procedures under the general mixed linear model, allowing for dropouts and missed visits. We present a range of procedures and compare their Type I error and power by simulation. We find that, in general, the achieved power is brought considerably closer to the required level without inflating the Type I error rate. We also derive an inflation factor that ensures the power requirement is more closely met.     

Molecular genetic system for regenerative studies using newts

Urodele newts have the remarkable capability of organ regeneration, and have been used as a unique experimental model for more than a century. However, the mechanisms underlying regulation of the regeneration are not well understood, and gene functions in particular remain largely unknown. To elucidate gene function in regeneration, molecular genetic analyses are very powerful. In particular, it is important to establish transgenic or knockout (mutant) lines, and systematically cross these lines to study the functions of the genes. In fact, such systems have been developed for other vertebrate models. However, there is currently no experimental model system using molecular genetics for newt regenerative research due to difficulties with respect to breeding newts in the laboratory. Here, we show that the Iberian ribbed newt (Pleurodeles waltl) has outstanding properties as a laboratory newt. We developed conditions under which we can obtain a sufficient number and quality of eggs throughout the year, and shortened the period required for sexual maturation from 18 months to 6 months. In addition, P. waltl newts are known for their ability, like other newts, to regenerate various tissues. We revealed that their ability to regenerate various organs is equivalent to that of Japanese common newts. We also developed a method for efficient transgenesis. These studies demonstrate that P. waltl newts are a suitable model animal for analysis of regeneration using molecular genetics. Establishment of this experimental model will enable us to perform comparable studies using these newts and other vertebrate models.     

Morphometric studies of the heart in normal rhesus monkeys (Macaca mulatta)

The hearts of 47 rhesus monkeys were examined at necropsy. Normal morphometric parameters of the heart were established. Included in the values are measurements of weight of the heart as a percentage of body weight, overall dimensions of the heart, and measurements of ventricular morphology.     

A Bayesian mixture model for metaanalysis of microarray studies

The increased availability of microarray data has been calling for statistical methods to integrate findings across studies. A common goal of microarray analysis is to determine differentially expressed genes between two conditions, such as treatment vs control. A recent Bayesian metaanalysis model used a prior distribution for the mean log-expression ratios that was a mixture of two normal distributions. This model centered the prior distribution of differential expression at zero, and separated genes into two groups only: expressed and nonexpressed. Here, we introduce a Bayesian three-component truncated normal mixture prior model that more flexibly assigns prior distributions to the differentially expressed genes and produces three groups of genes: up and downregulated, and nonexpressed. We found in simulations of two and five studies that the three-component model outperformed the two-component model using three comparison measures. When analyzing biological data of Bacillus subtilis, we found that the three-component model discovered more genes and omitted fewer genes for the same levels of posterior probability of differential expression than the two-component model, and discovered more genes for fixed thresholds of Bayesian false discovery. We assumed that the data sets were produced from the same microarray platform and were prescaled.     

Model choice and influential cases for survival studies

Deletion diagnostics are developed for identifying observations that influence the estimates of regression parameters and the mixture parameter in the families of relative risk functions for failure time data. The diagnostic for the regression parameters is a generalization of Cain and Lange's (1984, Biometrics 40, 493-499) measure of individual influence. The generalizations of martingale residuals, Schoenfeld's partial residuals (1982, Biometrika 69, 239-241), and score residuals by Therneau, Grambsch, and Fleming (1990, Biometrika 77, 147-160) are also obtained. The influence of some observations on regression parameters can be drastically modified as the mixture parameter changes, even for a very small change. In addition, adding or deleting some observations might result in choosing different models. The diagnostics are applied to a family proposed by Guerrero and Johnson (1982, Biometrika 69, 309-314). One illustrative example is presented.