Regression as a method to predict copy numbers in comparative genomic hybridization studies on bacteria

Comparative genomic hybridizations (CGH) using microarrays are performed with bacteria in order to determine the level of genomic similarity between various strains. The microarrays applied in CGH experiments are constructed on the basis of the genome sequence of one strain, which is used as a control, or reference, in each experiment. A strain being compared with the known strain is called the unknown strain. The ratios of fluorescent intensities obtained from the spots on the microarrays can be used to determine which genes are divergent in the unknown strain, as well as to predict the copy number of actual genes in the unknown strain. In this paper, we focus on the prediction of gene copy number based on data from CGH experiments. We assumed a linear connection between the log2 of the copy number and the observed log2-ratios, then predictors based on the factor analysis model and the linear random model were proposed in an attempt to identify the copy numbers. These predictors were compared to using the ratio of the intensities directly. Simulations indicated that the proposed predictors improved the prediction of the copy number in most situations. The predictors were applied on CGH data obtained from experiments with Enterococcus faecalis strains in order to determine copy number of relevant genes in five different strains.     

一类大尺度系统中昆虫种群时空动态模拟方法

本文介绍了一类描述大尺度作物系统害虫种群时空动态的模型,该模型包含了寄主作物,昆虫密度以及天敌间的相互作用,并简要介绍了该模型的一些模拟结果在IPM中的应用。     

Colon cancer metastasis in mouse liver is not affected by hypercoagulability due to Factor V Leiden mutation

Clinical trials have shown life-prolonging effects of antithrombotics in cancer patients, but the molecular mechanisms remain unknown due to the multitude of their effects. We investigated in a mouse model whether one of the targets of antithrombotic therapy, fibrin deposition, stimulates tumour development. Fibrin may provide either protection of cancer cells in the circulation against mechanical stress and the immune system, or form a matrix for tumours and/or angiogenesis in tumours to develop. Mice homozygous for Factor V Leiden (FVL), a mutation in one of the coagulation factors that facilitates fibrin formation, were used to investigate whether hypercoagulability affects tumour development in an experimental metastasis model. Liver metastases of colon cancer were induced in mice with the FVL mutation and wild-type littermates. At day 21, number and size of tumours at the liver surface, fibrin/fibrinogen distribution, vessel density and the presence of newly formed vessels in tumours were analysed. Number and size of tumours did not differ between mice with and without the FVL mutation. Fibrin/fibrinogen was found in the cytoplasm of hepatocytes and cancer cells, in blood vessels in liver and tumour tissue and diffusely distributed outside vessels in tumours, indicating leaky vessels. Vessel density and angiogenesis varied widely between tumours, but a pre-dominance for vessel-rich or vessel-poor tumours or vessel formation could not be found in either genotype. In conclusion, the FVL mutation has no effect on the development of secondary tumours of colon cancer in livers of mice. Fibrin deposition and thus inhibition of fibrin formation by anticoagulants do not seem to affect tumour development in this model.     

Biogeographic multi‐species occupancy models for large‐scale survey data

Ecologists often seek to infer patterns of species occurrence or community structure from survey data. Hierarchical models, including multi‐species occupancy models (MSOMs), can improve inference by pooling information across multiple species via random effects. Originally developed for local‐scale survey data, MSOMs are increasingly applied to larger spatial scales that transcend major abiotic gradients and dispersal barriers. At biogeographic scales, the benefits of partial pooling in MSOMs trade off against the difficulty of incorporating sufficiently complex spatial effects to account for biogeographic variation in occupancy across multiple species simultaneously. We show how this challenge can be overcome by incorporating preexisting range information into MSOMs, yielding a “biogeographic multi‐species occupancy model” (bMSOM). We illustrate the bMSOM using two published datasets: Parulid warblers in the United States Breeding Bird Survey and entire avian communities in forests and pastures of Colombia''s West Andes. Compared with traditional MSOMs, the bMSOM provides dramatically better predictive performance at lower computational cost. The bMSOM avoids severe spatial biases in predictions of the traditional MSOM and provides principled species‐specific inference even for never‐observed species. Incorporating preexisting range data enables principled partial pooling of information across species in large‐scale MSOMs. Our biogeographic framework for multi‐species modeling should be broadly applicable in hierarchical models that predict species occurrences, whether or not false absences are modeled in an occupancy framework.     

Toward community predictions: Multi‐scale modelling of mountain breeding birds' habitat suitability,landscape preferences,and environmental drivers

Across a large mountain area of the western Swiss Alps, we used occurrence data (presence‐only points) of bird species to find suitable modelling solutions and build reliable distribution maps to deal with biodiversity and conservation necessities of bird species at finer scales. We have performed a multi‐scale method of modelling, which uses distance, climatic, and focal variables at different scales (neighboring window sizes), to estimate the efficient scale of each environmental predictor and enhance our knowledge on how birds interact with their complex environment. To identify the best radius for each focal variable and the most efficient impact scale of each predictor, we have fitted univariate models per species. In the last step, the final set of variables were subsequently employed to build ensemble of small models (ESMs) at a fine spatial resolution of 100 m and generate species distribution maps as tools of conservation. We could build useful habitat suitability models for the three groups of species in the national red list. Our results indicate that, in general, the most important variables were in the group of bioclimatic variables including “Bio11” (Mean Temperature of Coldest Quarter), and “Bio 4” (Temperature Seasonality), then in the focal variables including “Forest”, “Orchard”, and “Agriculture area” as potential foraging, feeding and nesting sites. Our distribution maps are useful for identifying the most threatened species and their habitat and also for improving conservation effort to locate bird hotspots. It is a powerful strategy to improve the ecological understanding of the distribution of bird species in a dynamic heterogeneous environment.     

Hybrids between chum Oncorhynchus keta and pink Oncorhynchus gorbuscha salmon: age,growth and morphology and effects on salmon production

Mature hybrids between chum salmon Oncorhynchus keta and pink salmon Oncorhynchus gorbuscha, which were identified by an intermediate colour pattern, were caught at the Kurilsky Hatchery, Iturup Island, Russia. Most of them were female and 3 years old (a partial freshwater year and 2 marine years), which is intermediate between the ages of maturity of the parental species. The hybrids exceed both parental species in the rate of growth, are large in size and robust and might successfully compete for mating in the wild or be chosen for artificial reproduction. The ratio of the scale length over width, R, is oblate (R < 1), whereas scales of the parental species are prolate (R > 1). From scale analyses, the c.v. in body size of hybrid females at the second marine year is twice that of O. keta, which suggests developmental instability in the hybrid. A dynamic model predicted that continuing hybridization at a low rate does not produce a substantial hybrid load due to selection against advanced‐generation hybrids and backcrosses. A high hybridization rate, however, may be an additional risk for genetic management and should be taken into account in programmes of artificial reproduction of Pacific salmon Oncorhynchus spp., although such hybrids might have commercial use in confined production systems.     

遗传算法在转录因子结合位点识别中的应用

遗传算法是模拟生物进化过程的计算模型,是一种全局优化搜索算法。将遗传算法与转录因子结合位点识别问题相结合的新方法,以一致性序列模型作为保守motif的描述模型,通过对motif序列与待测序列的比对问题进行编码,将其转化成搜索空间中的优化问题,利用遗传算法来搜索最优解,预测转录因子的结合位点。实验结果表明,这种新的方法是有效的,它在占用少量内存的情况下能够准确地识别出待测转录因子结合位点。     

影响林火灾变生态阈值数学模拟的潜在因子的数学模型

用多元统计分析方法对大兴安岭林区的林火灾变的有关观测数据进行综合分析,提出了影响林火灾变性生态阈值数学模拟的潜在因子的数学模型,并对该模型作出了一些有益的讨论。     

Parameterization of Multivariate Random Effects Models for Categorical Data

Alternative parameterizations and problems of identification and estimation of multivariate random effects models for categorical responses are investigated. The issues are illustrated in the context of the multivariate binomial logit-normal (BLN) model introduced by Coull and Agresti (2000, Biometrics 56, 73-80). We demonstrate that the BLN model is poorly identified unless proper restrictions are imposed on the parameters. Moreover, estimation of BLN models is unduly computationally complex. In the first application considered by Coull and Agresti, an identification problem results in highly unstable, highly correlated parameter estimates and large standard errors. A probit-normal version of the specified BLN model is demonstrated to be underidentified, whereas the BLN model is empirically underidentified. Identification can be achieved by constraining one of the parameters. We show that a one-factor probit model is equivalent to the probit version of the specified BLN model and that a one-factor logit model is empirically equivalent to the BLN model. Estimation is greatly simplified by using a factor model.     

Issues in the development of medical products based on human plasma

Product development and process validation are shown in the case of several products obtained from human plasma. These are virus-inactivated plasma, intravenous immunoglobulins and the clotting factors VIII and IX. Different analytical methods are presented, which are used for product control and in-process control. For the production of virus-inactivated human plasma a down-scale protocol is presented, allowing a simulation of the production on a laboratory scale. Virus validation has shown that the reduction of transfusion-relevant viruses in the process was higher than six log steps. Determination of leachables from the RP-column, which was used in this production, proved that they appear in the final product in quantities below the detection limits only. It was also shown that the chemicals used for virus inactivation could be quantitatively removed from the product. For the isolation of other products, here intravenous gamma globulins and the clotting factors VIII and IX, similar validation steps had to be taken. In the case of clotting factor VIII the following data were determined, the reduction of viruses, the amount of leachables from the column, the residues of chemicals from the solvent/detergent treatment for virus inactivation. Virus reduction was successfully performed as well as the removal of chemicals used for virus inactivation. The amount of leachables from the columns used for chromatographic purification was found to be far below the permissible levels.     

长白山不同演替阶段针阔混交林群落物种多度分布格局

为解释长白山温带森林群落构建和物种多度格局的形成过程, 该文以不同演替阶段的针阔混交林监测样地数据为基础, 采用中性理论模型、生物统计模型(对数正态分布模型)和生态位模型(Zifp模型、分割线段模型、生态位优先模型)拟合森林群落物种多度分布, 并用χ ²检验、Kolmogorov-Smirnov (K-S)检验和赤池信息准则(AIC)选择最佳拟合模型。结果显示: 中性模型能很好地预测长白山温带森林不同演替阶段植物群落的物种多度分布。在10 m × 10 m尺度上, 5种模型均可被χ ²检验和K-S检验接受, 但中性模型拟合效果不如对数正态分布模型、Zifp模型、分割线段模型和生态位优先模型, 表明小尺度上中性过程和生态位过程均能解释群落物种多度分布, 但生态位过程的解释能力相对较大。而在中大尺度上(30 m × 30 m、60 m × 60 m和90 m × 90 m), 中性模型为最优拟合模型, 并且随着研究尺度增加, 生态位模型和生物统计模型逐渐被χ ²检验拒绝, 表明中性过程在长白山针阔混交林群落物种多度分布格局形成中的作用随着研究尺度增加而逐渐增大。该文证实了中性过程在长白山温带针阔混交林群落结构形成中具有重要作用, 但未否认生态位机制在群落构建中的贡献。因此, 温带森林群落构建过程中中性理论和生态位理论并非相互矛盾, 而是相互融合的。在研究森林群落物种多度分布时, 应重视取样尺度和演替阶段的影响, 并采用多种模型进行拟合。     

Ten Years of the Relative Risk Model and Regional Scale Ecological Risk Assessment

It has been 10 years since the publication of the relative risk model (RRM) for regional scale ecological risk assessment. The approach has since been used successfully for a variety of freshwater, marine, and terrestrial environments in North America, South America, and Australia. During this period the types of stressors have been expanded to include more than contaminants. Invasive species, habitat loss, stream alteration and blockage, temperature, change in land use, and climate have been incorporated into the assessments. Major developments in the RRM have included the extensive use of geographical information systems, uncertainty analysis using Monte Carlo techniques, and its application to retrospective assessments to determine causation. The future uses of the RRM include assessments for forestry and conservation management, an increasing use in invasive species evaluation, and in sustainability. Developments in risk communication, the use of Bayesian approaches, and in uncertainty analyses are on the horizon.     

Geoadditive latent variable modeling of count data on multiple sexual partnering in Nigeria

The 2005 National HIV/AIDS and Reproductive Health Survey (NARHS) in Nigeria provides evidence that multiple sexual partnering increases the risk of contracting HIV and other sexually transmitted diseases. Therefore, partner reduction is one of the prevention strategies to accomplish the Millenium Development Goal of halting and reversing the spread of HIV/AIDS. We consider the numbers of girlfriends, casual, and commercial partners of heterosexual men, reported in the NARHS study, as observed indicators of their latent attitude toward multiple partnering. To explore the influence of risk factors on this latent variable, we extend semiparametric methodology for latent variable models with continuous and categorical indicators to include count indicators. This allows us to simultaneously analyze linear and nonlinear effects of covariates, such as sociodemographic factors and knowledge about HIV/AIDS, on attitude toward multiple sexual partnering, which in turn influences the observable count indicators. The results provide insights for policy makers who are aiming to reduce the spread of HIV and AIDS among the Nigerian populace through partner reduction.     

Purification of factor X by hydrophobic interaction chromatography

Human factor X has been purified to homogeneity by hydrophobic interaction chromatography on phenyl-sepharose. The coagulation protein did not interact with the resin in the presence of 2–3 M NaCl whereas contaminants were retained. This single purification step, in conjunction with classical purification strategies, is a powerful tool in generating high purity factor X and is based on resins which are readily available.     

Modeling of scale-down effects on the hydrodynamics of expanded bed adsorption columns

Expanded-bed adsorption (EBA) is a technique for primary recovery of proteins starting from unclarified broths. This process combines centrifugation, concentration, filtration, and initial capturing of the proteins in a single step. An expanded bed (EB) is comparable to a packed bed in terms of separation performance but its hydrodynamics are that of a fluidized bed. Downstream process development involving EBA is normally carried out in small columns to minimize time and costs. Our purpose here is to characterize the hydrodynamics of expanded beds of different diameters, to develop scaling parameters that can be reliably used to predict separation efficiency of larger EBA columns. A hydrodynamic model has been developed which takes into account the radial liquid velocity profile in the column. The scale-down effect can be characterized in terms of apparent axial dispersion, D(axl,app), and plate number, N(EB), adapted for expanded bed. The model is in good agreement with experimental results obtained from 1- and 5-cm column diameters with buffer solutions of different viscosities. The model and the experiments show an increase of apparent axial dispersion with an increase in column diameter. Furthermore, the apparent axial dispersion is affected by an increase in liquid velocity and viscosity. Supported by visual observations and predictions from the model, it was concluded that operating conditions (liquid viscosity and superficial velocity) resulting in a bed-void fraction between 0.7 and 0.75 would provide the optimal separation efficiency in terms of N(EB).     

Reduced scale model qualification of 5-L and 250-ml bioreactors using multivariant visualization and Bayesian inferential methods

A novel method for the qualification of reduced scale models (RSMs) was illustrated using data from both a 250-ml advanced microscale bioreactor (ambr) and a 5-L bioreactor RSM for a 2,000-L manufacturing scale process using a CHO cell line to produce a recombinant monoclonal antibody. The example study showed how the method was used to identify process performance attributes and product quality attributes that capture important aspects of the RSM qualification process. The method uses two novel statistical approaches: multivariate dimension reduction and data visualization techniques, via partial least squares discriminant analysis (PLS-DA), and Bayesian multivariate linear modeling for inferential analysis. Bayesian multivariate linear modeling allows for individual probability distributions of the differences of the mean of each attribute for each scale, as well as joint probability statements on the differences of the means for multiple attributes. Depending on the results of this inferential procedure, PLS-DA is used to identify the process performance outputs at the different scales which have the greatest negative impact on the multivariate Bayesian joint probabilities. Experience with that particular process can then be leveraged to adjust operating conditions to minimize these differences, and then equivalence can be reassessed using the multivariate linear model.     

An episodic model of honeydew production in scale insects

Honeydew produced by sooty beech scale insects (Ultracoelostoma spp., Homoptera: Coelostomidiidae) is a keystone ecological process in New Zealand beech (Nothofagus spp., Nothofagaceae) forest. This work puts forward a model of honeydew production based on individual insects that presumes feeding and excretion are episodic processes driven by the insect rather than the passive processes that were previously assumed. The model is parameterized using existing data and then compared to an independent pre‐existing dataset. The model suggests that over a 12‐h period, on average the insects suck sap for 2 h, and excrete waste sap for 12 min. Resource uptake by the insects appears to be limited by the time required to process the sap, consistent with the observed relationship between honeydew production rates and ambient temperature. This implies that insect feeding rates may be ultimately limited by the low nitrogen content of phloem sap.     

基因组规模代谢网络模型的约束算法及其应用

工业微生物是微生物制造的核心,而微生物制造过程中微生物的生产性能是提高微生物制造过程效率的关键。结合基于约束条件的优化算法的基因组规模代谢网络模型是全局规模上认识、调控和优化工业微生物生理功能的重要平台。本文在简述基因组规模代谢网络模型构建的基础上,详细介绍了基于约束条件的优化算法的原理、分类和应用实例,为提高微生物制造过程效率奠定了坚实的基础。