Assessment of arbovirus vector infection rates using variable size pooling

Pool testing of vector samples for arboviruses is widely used in surveillance programmes. The proportion of infected mosquitoes (Diptera: Culicidae) is often estimated from the minimum infection rate (MIR), based on the assumption of only one infected mosquito per positive pool. This assumption becomes problematic when pool size is large and/or infection rate is high. By relaxing this constraint, maximum likelihood estimation (MLE) is more useful for a wide range of infection levels that may be encountered in the field. We demonstrate the difference between these two estimation approaches using West Nile virus (WNV) surveillance data from vectors collected by gravid traps in Chicago during 2002. MLE of infection rates of Culex mosquitoes was as high as 60 per 1000 at the peak of transmission in August, whereas MIR was less than 30 per 1000. More importantly, we demonstrate roles of various pooling strategies for better estimation of infection rates based on simulation studies with hypothetical mosquito samples of 18 pools. Variable size pooling (with a serial pool sizes of 5, 10, 20, 30, 40 and 50 individuals) performed consistently better than a constant size pooling of 50 individuals. We conclude that variable pool size coupled with MLE is critical for accurate estimates of mosquito infection rates in WNV epidemic seasons.     

Comparison of parameters from rhythmometric models with multiple components on hybrid data

Population multiple components is a statistical tool useful for the analysis of time-dependent hybrid data. With a small number of parameters, it is possible to model and to predict the periodic behavior of a population. In this article, we propose two methods to compare among populations rhythmometric parameters obtained by multiple component analysis. The first is a parametric method based in the usual statistical techniques for comparison of mean vectors in multivariate normal populations. The method, through MANOVA analysis, allows comparison of the MESOR and amplitude-acrophase pair of each component among two or more populations. The second is a nonparametric method, based in bootstrap techniques, to compare parameters from two populations. This test allows one to compare the MESOR, the amplitude, and the acrophase of each fitted component, as well as the global amplitude, orthophase, and bathyphase estimated when all fitted components are harmonics of a fundamental period. The idea is to calculate a confidence interval for the difference of the parameters of interest. If this interval does not contain zero, it can be concluded that the parameters from the two models are different with high probability. An estimation of p-value for the corresponding test can also be calculated. Both methods are illustrated with an example, based on clinical data. The nonparametric test can also be applied to paired data, a special situation of great interest in practice. By the use of similar bootstrap techniques, we illustrate how to construct confidence intervals for any rhythmometric parameter estimated from population multiple components models, including the orthophase, bathyphase, and global amplitude. These tests for comparison of parameters among populations are a needed tool when modeling the nonsinusoidal rhythmic behavior of hybrid data by population multiple component analysis.     

Model-free Analysis of Protein Dynamics: Assessment of Accuracy and Model Selection Protocols Based on Molecular Dynamics Simulation

The popular model-free approach to analyze NMR relaxation measurements has been examined using artificial amide (15)N relaxation data sets generated from a 10 nanosecond molecular dynamics trajectory of a dihydrofolate reductase ternary complex in explicit water. With access to a detailed picture of the underlying internal motions, the efficacy of model-free analysis and impact of model selection protocols on the interpretation of NMR data can be studied. In the limit of uncorrelated global tumbling and internal motions, fitting the relaxation data to the model-free models can recover a significant amount of quantitative information on the internal dynamics. Despite a slight overestimation, the generalized order parameter is quite accurately determined. However, the model-free analysis appears to be insensitive to the presence of nanosecond time scale motions with relatively small magnitude. For such cases, the effective correlation time can be significantly underestimated. As a result, proteins appear to be more rigid than they really are. The model selection protocols have a major impact on the information one can reliably obtain. The commonly employed protocol based on step-up hypothesis testing has severe drawbacks of oversimplification and underfitting. The consequences are that the order parameter is more severely overestimated and the correlation time more severely underestimated. Instead, model selection based on Bayesian Information Criteria (BIC), recently introduced to the model-free analysis by d'Auvergne and Gooley (2003), provides a better balance between bias and variance. More appropriate models can be selected, leading to improved estimate of both the order parameter and correlation time. In addition, the computational cost is significantly reduced and subjective parameters such as the significance level are unnecessary.     

Development and evaluation of a protein microarray chip for diagnosis of hepatitis C virus

A protein chip diagnostic kit was developed for the diagnosis of hepatitis C virus (HCV) based on the protein chip technique and the immuno-concentration method. This kit was designed for low-density protein chips and also for the availability of multiple sample screening. Applicability of the chip was evaluated using 96 blood specimens and the results were compared to results of an anti-HCV enzyme immunoassay (EIA) test. With further development, the technology associated with the development of this chip could be applied to the simultaneous detection of multiple protein-protein, protein-ligand interactions.     

Exploiting the potential of insects for in vivo pathogenicity testing of microbial pathogens

Conventional assays for quantifying the virulence of microbial pathogens and mutants have traditionally relied upon the use of a range of mammalian species. A number of workers have demonstrated that insects can be used for evaluating microbial pathogenicity and provide results comparable to those that can be obtained with mammals since one component of the vertebrate immune system, the innate immune response, remains similar to that found in insects. Larvae of the Greater Wax Moth Galleria mellonella have been used to evaluate the virulence of a range of bacterial and fungal pathogens and a correlation with the virulence of these microbes in mice has been established. This review highlights the similarities of the vertebrate and insect innate immune responses to infection and identifies the potential use of insects for the in vivo evaluation of the microbial pathogenicity.     

Two-dimensional tension tests in plant biomechanics--sweet cherry fruit skin as a model system

Splitting of fruits is a function of two-dimensional tension caused by different growth rates of tissues and turgor, especially water uptake shortly before harvest. In order to analyse the mechanical properties of spheroid plant material close to stress-strain conditions in vivo, a new hydraulic two-dimensional testing device was set up. Sweet cherry (Prunus avium L.) fruit skin was chosen as a model system. The recorded pressure-deflection curves were non-linear, with a considerable initial "lag phase" and a distinct increasing end part. Taking into account the special geometry, these curves could be modelled with a newly developed analytical approach based on linear elastic material behaviour. The results demonstrated good correlation if a modulus of elasticity ranging from 160 to 250 MPa for the cherry fruit skin was chosen. In addition, a mean strength value of 47 MPa was calculated based on the theory of thin shells and spheres. The results are compared with mechanical data found for fruits and other plant material. In order to test the theoretical approach, two- and one-dimensional tension tests were performed on packaging PE foil, revealing a mean modulus of 171 MPa in bi-axial tension, and 193 and 242 MPa in uni-axial tension, depending on the test speed. The results demonstrate that it seems to be feasible to use this method to analyse the two-dimensional stress-strain conditions of spheroid plant materials such as cherry fruit skins. It may be applied as a tool for crop testing to elucidate the mechanical basis of cracking susceptibility of fruits.     

The comet assay for DNA damage and repair

The comet assay (single-cell gel electrophoresis) is a simple method for measuring deoxyribonucleic acid (DNA) strand breaks in eukaryotic cells. Cells embedded in agarose on a microscope slide are lysed with detergent and high salt to form nucleoids containing supercoiled loops of DNA linked to the nuclear matrix. Electrophoresis at high pH results in structures resembling comets, observed by fluorescence microscopy; the intensity of the comet tail relative to the head reflects the number of DNA breaks. The likely basis for this is that loops containing a break lose their supercoiling and become free to extend toward the anode. The assay has applications in testing novel chemicals for genotoxicity, monitoring environmental contamination with genotoxins, human biomonitoring and molecular epidemiology, and fundamental research in DNA damage and repair. The sensitivity and specificity of the assay are greatly enhanced if the nucleoids are incubated with bacterial repair endonucleases that recognize specific kinds of damage in the DNA and convert lesions to DNA breaks, increasing the amount of DNA in the comet tail. DNA repair can be monitored by incubating cells after treatment with damaging agent and measuring the damage remaining at intervals. Alternatively, the repair activity in a cell extract can be measured by incubating it with nucleoids containing specific damage.     

The milk protein promoter is a useful tool for developing a rat with tolerance to a human protein

Biopharmaceuticals intended for humans are immunogenic in animals. Antibodies associated with their administration make it difficult to perform repeated-dose pharmacology and toxicology studies in animals. Despite suggestions to solve this problem with transgenic animal technology, an effective strategy has not yet been reported. The objective of the present study was to provide an efficient strategy to develop rats tolerant to biopharmaceuticals such as human gene-based proteins. The present study used transgenic rat lines (lines 311-6, 308-5, and 305-1) carrying a fusion gene designed to express the human growth hormone (hGH) gene under the control of the bovine S1 casein gene promoter. Three lactating females with the transgene, produced approximately 4mg/ml, 300g/ml, and 10ng/ml in their milk. Male 8-week-old rats from these three lines were immunized with hGH three times (week 0, 1, and 3 ) and the production of antibodies against hGH in their sera were examined at week 4. While the hGH serum antibody titers increased over 1000-fold in wild-type control rats, there was no detectable antibody against hGH in the sera of these three transgenic lines. Human growth hormone in their sera was undetectable (lines 308-5 and 305-1) or much lower than the endogenous biologic level of rat growth hormone (line 311-6). Importantly, lines 308-5 and 305-1 developed tolerance to hGH without detectable hGH in their sera and these lines will be very useful for the repeated dose pharmacology and toxicology studies. These results suggest that a milk protein promoter can be a useful tool to develop transgenic rats that are tolerant to biopharmaceuticals intended for humans.     

Hypothesis testing for the genetic background of quantitative traits

The testing of Bayesian point null hypotheses on variance component models have resulted in a tough assignment for which no clear and generally accepted method exists. In this work we present what we believe is a succeeding approach to such a task. It is based on a simple reparameterization of the model in terms of the total variance and the proportion of the additive genetic variance with respect to it, as well as on the explicit inclusion on the prior probability of a discrete component at origin. The reparameterization was used to bypass an arbitrariness related to the impropriety of uninformative priors onto unbounded variables while the discrete component was necessary to overcome the zero probability assigned to sets of null measure by the usual continuous variable models. The method was tested against computer simulations with appealing results.     

不测土条件下半定量施肥原理和模型评述

1　不测土条件下半定量推荐施肥的需求矿质营养学说是施肥最基本原理 ,它的诞生标志着人类主动施肥时期的开始。从早期的定性施肥阶段 ,发展到今天的定量施肥阶段 ,如何确定施肥量一直是施肥技术的核心和难点。测土是定量施肥或精确施肥的前提。然而 ,测土本身存在各种偏差或精度、测土需要费用 ,本文仅对代表性的不测土施肥模型及其原理进行评述。即使有了土壤有效养分的测定结果 ,如何将其转化为一季内土壤提供的养分量一直是个理论难题 ,特别是Ｎ素土壤供应量更为难测或难以估算。因此 ,如何在使用定量施肥模型的同时 ,而又将土壤养分因…