Inter- and intra-rater reliability of 3D kinematics during maximum mouth opening of asymptomatic subjects

Previous studies evaluated 3D human jaw movements using kinematic analysis systems during mouth opening, but information on the reliability of such measurements is still scarce. The purpose of this study was to analyze within- and between-session reliabilities, inter-rater reliability, standard error of measurement (SEM), minimum detectable change (MDC) and consistency of agreement across raters and sessions of 3D kinematic variables during maximum mouth opening (MMO). Thirty-six asymptomatic subjects from both genders were evaluated on two different days, five to seven days apart. Subjects performed three MMO movements while kinematic data were collected. Intraclass correlation coefficient (ICC), SEM and MDC were calculated for all variables, and Bland-Altman plots were constructed. Jaw radius and width were the most reproducible variables (ICC > 0.81) and demonstrated minor error. Incisor displacement during MMO and angular movements in the sagittal plane presented good reliability (ICC from 0.61 to 0.8) and small errors and, consequently, could be used in future studies with the same methodology and population. The variables with smaller amplitudes (condylar translations during mouth opening and closing and mandibular movements on the frontal and transversal planes) were less reliable (ICC < 0.61) and presented larger SEM and MDC. Although ICC, SEM and MDC showed less between-session reproducibility than within-session and inter-rater, the limits of agreement were larger in inter-rater comparisons. In future studies care must be taken with variables collected on different days and with mandibular movements in the frontal and transversal planes.     

Bayesian design of biosimilars clinical programs involving multiple therapeutic indications

In this paper, we propose a Bayesian design framework for a biosimilars clinical program that entails conducting concurrent trials in multiple therapeutic indications to establish equivalent efficacy for a proposed biologic compared to a reference biologic in each indication to support approval of the proposed biologic as a biosimilar. Our method facilitates information borrowing across indications through the use of a multivariate normal correlated parameter prior (CPP), which is constructed from easily interpretable hyperparameters that represent direct statements about the equivalence hypotheses to be tested. The CPP accommodates different endpoints and data types across indications (eg, binary and continuous) and can, therefore, be used in a wide context of models without having to modify the data (eg, rescaling) to provide reasonable information-borrowing properties. We illustrate how one can evaluate the design using Bayesian versions of the type I error rate and power with the objective of determining the sample size required for each indication such that the design has high power to demonstrate equivalent efficacy in each indication, reasonably high power to demonstrate equivalent efficacy simultaneously in all indications (ie, globally), and reasonable type I error control from a Bayesian perspective. We illustrate the method with several examples, including designing biosimilars trials for follicular lymphoma and rheumatoid arthritis using binary and continuous endpoints, respectively.     

Paraoxonase 1 polymorphisms L55M and Q192R were not risk factors for Parkinson's disease: a HuGE review and meta-analysis

Purpose

The Paraoxonase 1 (PON1) has been studied as a potential candidate gene for Parkinson's disease risk, but direct evidence from genetic association studies remains inconclusive. We performed a meta-analysis pooling data from all relevant studies in order to determine the effects of two PON 1 polymorphisms (L55M and Q192R) on Parkinson's disease.

Methods

We applied a random effects to combine odds ratio (OR) and 95% confidence intervals. Q statistic was used to evaluate the homogeneity, and Egger's test and Funnel plot were used to assess publication bias. In secondary analyses, we examined dominant and recessive models as well.

Results

Concerning the PON1 L55M polymorphism, we identified 9 eligible studies (a total of 2582 cases and 3997 controls). The random effects pooled OR was OR = 1.29, (0.90, 1.84). Concerning the Q192R polymorphism, we identified 7 eligible studies (a total of 2582 cases and 3997 controls). The random effects pooled OR was OR = 1.08(0.81, 1.43). Analysis with dominant and recessive genetic models yielded the same inferences as genotype-based comparisons for both of the two polymorphisms.

Conclusion

The results of this meta-analysis suggested that both PON1 L55M and Q192R were not responsible for PD.     

空间误差模型在黑龙江省森林碳储量空间分布的应用

基于黑龙江省2010年一类调查数据和重点公益林检测样地（5075块）数据以及同期黑龙江省、吉林省和内蒙古自治区59个气象站的气象数据,以森林碳储量为因变量,以胸径、每公顷株数、海拔、坡度及降雨与温度的乘积因子作为自变量,利用GeoDA软件构建空间误差模型,用全局Moran I 来描述不同空间尺度下模型残差的空间自相关性,计算最佳带宽（25 km）下的局域Moran I来表现模型残差的空间分布,计算组内方差来解释模型残差的空间异质性,最后将模型的预估结果生成黑龙江省森林碳储量的空间分布图.结果表明： 黑龙江省森林碳储量的分布具有空间效应;本文所选林分因子、地形因子及气象因子都显著影响森林碳储量的空间分布,胸径是最主要的因子.空间误差模型可以很好地解决模型残差的空间自相关性及空间异质性.由模型的预估结果可以看出,森林碳储量的空间分布存在很大差异,张广才岭、小兴安岭及大兴安岭地区是森林分布较密集的区域,松嫩平原地区的森林碳储量分布较少,完达山地区处于中等水平.
     

Soluble glucomannan isolated from Candida utilis primes blood phagocytes

It is well documented that the polysaccharide glucomannan (GM), an abundant constituent of the fungal cell wall, in the form of particulate induces strong activation of phagocytes, however, the effects of soluble GM are not known. Activation of phagocyte anti-microbial mechanisms is a crucial part of the innate host defense against invading pathogens. However, under uncontrolled inflammatory conditions they contribute to damage of surrounding tissues. Thus, to prevent these deleterious effects, the activation of phagocytes is a tightly regulated process. Therefore, in this study we analyzed the effect of soluble GM on some neutrophil functions such as reactive oxygen species production, degranulation, and receptor mobilization at the plasma membrane. Soluble GM at the tested concentrations did not stimulate oxidative burst of phagocytes directly but significantly potentiated oxidative burst in response to opsonized zymosan particles. GM induced significant phosphorylation of p47phox subunit of NADPH oxidase on Ser345. This priming effect of GM was accompanied by time and concentration dependent degranulation characterized by increased surface expression of receptors stored in neutrophil granules (CD10, CD11b, CD14, CD35, and CD66b). Degranulation was further confirmed by increase of elastase activity in media. Thus, it could be suggested that soluble GM induces priming of phagocytes connected with their degranulation, the increase of surface receptor expression, and potentiation of oxidative burst response to opsonized particles through the activation of NADPH oxidase.     

重庆市城市化与生态环境交互关系的协整分析

运用协整理论和误差修正模型考察了重庆市1978-2007年期间城市化与生态环境相互作用的关系,遴选出作用于生态环境的2项主要的城市化指标和影响城市化的4项主要的生态环境指标,它们能反映出交互作用的机制。结果发现:1978-2007年,重庆市城市化与生态环境之间存在长期均衡关系,城市化对生态环境的正向作用明显强于生态环境对城市化的反向影响,误差修正系数较长期协整方程中的系数要小。从长期来看,城市化水平对生态环境变化的解释能力正在逐步增强,这充分证明生态环境功能的弱化是城市化步伐推进的必然结果。就城市化对生态环境的响应效果而言,一方面城市化是影响重庆市生态环境的重要原因,另一方面生态环境对城市化也存在着反作用。生态环境对城市化进程产生外在压力,但这一反馈机制往往具有一定的滞后效应。城市化对解释生态环境预测方差分解起着重要作用,然而生态环境对城市化预测方差的贡献度较小。     

Predicting and correcting bias caused by measurement error in line transect sampling using multiplicative error models

Line transect sampling is one of the most widely used methods for animal abundance assessment. Standard estimation methods assume certain detection on the transect, no animal movement, and no measurement errors. Failure of the assumptions can cause substantial bias. In this work, the effect of error measurement on line transect estimators is investigated. Based on considerations of the process generating the errors, a multiplicative error model is presented and a simple way of correcting estimates based on knowledge of the error distribution is proposed. Using beta models for the error distribution, the effect of errors and of the proposed correction is assessed by simulation. Adequate confidence intervals for the corrected estimates are obtained using a bootstrap variance estimate for the correction and the delta method. As noted by Chen (1998, Biometrics 54, 899-908), even unbiased estimators of the distances might lead to biased density estimators, depending on the actual error distribution. In contrast with the findings of Chen, who used an additive model, unbiased estimation of distances, given a multiplicative model, lead to overestimation of density. Some error distributions result in observed distance distributions that make efficient estimation impossible, by removing the shoulder present in the original detection function. This indicates the need to improve field methods to reduce measurement error. An application of the new methods to a real data set is presented.     

Effects of Global Positioning System Collar Weight on Zebra Behavior and Location Error

ABSTRACT Global Positioning System (GPS) collars are increasingly being used to study fine-scale patterns of animal behavior. Previous studies on GPS collars have tried to determine the causes of location error without attempting to investigate whether the accuracy of fixes provides a correspondingly accurate measure of the animal's natural behavior. When comparing 2 types of GPS collar, we found a significant effect of collar weight and fit on the rate of travel of plains zebra (Equus burchelli antiquorum) females in the Makgadikgadi, Botswana. Although both types of collar were well within accepted norms of collar weight, the slightly heavier collars (0.6% of total body mass [TBM]) reduced rate of travel by >50% when foraging compared with the collar that was 0.4% of TBM. Collar effect was activity specific, particularly interfering with grazing behavior; the effect was less noticeable when zebras crossed larger interpatch distances. We highlight that small differences in collar weight or fit can affect specific behaviors, limiting the extrapolation of fine-scaled GPS data. This has important implications for wildlife biologists, who hitherto have assumed that collars within accepted weight limits have little or no effect on animal movement parameters.     

Mitochondrial targeting signals and mature peptides of 3-methylcrotonyl-CoA carboxylase

Inherited deficiency of 3-methylcrotonyl-CoA carboxylase (MCC), an enzyme of leucine degradation, is an organic acidemia detectable by expanded newborn screening with a variable phenotype that ranges from asymptomatic to death in infancy. Here, we show that the two subunits of the enzyme (MCCalpha; MCCbeta) are imported into the mitochondrial matrix by the classical pathway involving cleavable amino-terminal targeting presequences. We identified the cleavage sites (Tyr41/Thr42 and Ala22/Tyr23 for MCCalpha and MCCbeta, respectively) of the targeting signals and the amino-termini of the mature polypeptides of MCC and propionyl-CoA carboxylase, a mitochondrial paralog. The amino-termini containing 39 (MCCalpha) or 20 amino acids (MCCbeta) were both necessary and sufficient for targeting. Structural requirements for mitochondrial import were defined by site-directed mutagenesis. Our studies provide the prerequisite to understand the impact of specific mutations on the clinical phenotype of MCC deficiency.     

Modeling markers of disease progression by a hidden Markov process: application to characterizing CD4 cell decline

Multistate models have been increasingly used to model natural history of many diseases as well as to characterize the follow-up of patients under varied clinical protocols. This modeling allows describing disease evolution, estimating the transition rates, and evaluating the therapy effects on progression. In many cases, the staging is defined on the basis of a discretization of the values of continuous markers (CD4 cell count for HIV application) that are subject to great variability due mainly to short time-scale noise (intraindividual variability) and measurement errors. This led us to formulate a Bayesian hierarchical model where, at a first level, a disease process (Markov model on the true states, which are unobserved) is introduced and, at a second level, the measurement process making the link between the true states and the observed marker values is modeled. This hierarchical formulation allows joint estimation of the parameters of both processes. Estimation of the quantities of interest is performed via stochastic algorithms of the family of Markov chain Monte Carlo methods. The flexibility of this approach is illustrated by analyzing the CD4 data on HIV patients of the Concorde clinical trial.