Anaerobic protozoa and their growth in biomethanation systems

This study was to investigate growth of protozoa and its influence on biodegradation in anaerobic treatment systems. It was done by specifically controlling and monitoring growth of protozoa versus degradation in continuous stirred anaerobic reactors and batch anaerobic reactors. Occurrence of a diverse protozoa population such as the ciliates, Prorodon, Vorticella, Cyclidium, Spathidium, Loxodes, Metopus were observed in stable anaerobic systems and the flagellates, Rhynchomonas, Naeglaria, Amoeboflagellates, Tetramitus, Trepomonas and Bodo during increased VFA concentration and affected periods of biomethanation. The abundance of ciliates in the anaerobic system had significant correlation with the reduction of MLSS, increased rate of COD removal and higher methane production. The results of this study thus tend to relate increased anaerobic degradation with the abundance of protozoa, mainly ciliates, which indicate their possible involvement in the process. Present study also reveals that performance of anaerobic process can be assessed by monitoring the protozoa population in the system.     

Nearest neighbour adjustment and linear variance models in plant breeding trials

This paper reviews methods for nearest neighbour analysis that adjust for local trend in one dimension. Such methods are commonly used in plant breeding and variety testing. The focus is on simple differencing methods, including first differences and the Papadakis method. We discuss mixed model representations of these methods on the scale of the observed data. Modelling observed data has a number of practical advantages compared to differencing, for example the facility to conveniently compute adjusted cultivar means. Most models considered involve a linear variance-covariance structure and can be represented as state-space models. The reviewed methods and models are exemplified using three datasets.     

Spatial multistate transitional models for longitudinal event data

Summary .   Follow-up medical studies often collect longitudinal data on patients. Multistate transitional models are useful for analysis in such studies where at any point in time, individuals may be said to occupy one of a discrete set of states and interest centers on the transition process between states. For example, states may refer to the number of recurrences of an event, or the stage of a disease. We develop a hierarchical modeling framework for the analysis of such longitudinal data when the processes corresponding to different subjects may be correlated spatially over a region. Continuous-time Markov chains incorporating spatially correlated random effects are introduced. Here, joint modeling of both spatial dependence as well as dependence between different transition rates is required and a multivariate spatial approach is employed. A proportional intensities frailty model is developed where baseline intensity functions are modeled using parametric Weibull forms, piecewise-exponential formulations, and flexible representations based on cubic B-splines. The methodology is developed within the context of a study examining invasive cardiac procedures in Quebec. We consider patients admitted for acute coronary syndrome throughout the 139 local health units of the province and examine readmission and mortality rates over a 4-year period.     

液蜡发酵制取混合二元酸的研究

A mutant of Candida tropicalis FYD-2 was obtained from its parental strain SFP-1186 by ultraviolet treatments.On shaking flask,the yield of mixed dicarboxylic acid(DCA) by the mutant was 21.4% higher than that by its ancestor.The amount of mixed DCA reached 156g/L for 120h incubation in a 10 L autoconrolled fermentor where the culture medium contained 25% n-paraffin.The process of induced and screening mutant was introduced and the time course of fermentation in 10 L fermentor was discussed.     

A note on joint versus gene-specific mixed model analysis of microarray gene expression data

Currently, linear mixed model analyses of expression microarray experiments are performed either in a gene-specific or global mode. The joint analysis provides more flexibility in terms of how parameters are fitted and estimated and tends to be more powerful than the gene-specific analysis. Here we show how to implement the gene-specific linear mixed model analysis as an exact algorithm for the joint linear mixed model analysis. The gene-specific algorithm is exact, when the mixed model equations can be partitioned into unrelated components: One for all global fixed and random effects and the others for the gene-specific fixed and random effects for each gene separately. This unrelatedness holds under three conditions: (1) any gene must have the same number of replicates or probes on all arrays, but these numbers can differ among genes; (2) the residual variance of the (transformed) expression data must be homogeneous or constant across genes (other variance components need not be homogeneous) and (3) the number of genes in the experiment is large. When these conditions are violated, the gene-specific algorithm is expected to be nearly exact.     

Mixed acetals of cyclodextrins. Preparation of hexakis-, heptakis- and octakis[2,6-di-O-(methoxydimethyl)methyl]-alpha-, beta- and gamma-cyclodextrins

The proton-catalyzed addition of 2-methoxypropene to alpha-, beta- and gamma-cyclodextrins resulted in hexakis-, heptakis-, and octakis[2,6-di-O-(methoxydimethyl)methyl]-alpha-, beta- and gamma-cyclodextrins, but no reaction was observed of CD-s with 2,2-dimethoxypropane. The mixed acetal-type compounds can be alkylated under basic conditions. The preparation of hexakis(3-O-benzyl)-alpha-cyclodextrin demonstrates the synthetic value of this methodology.     

Conditional analysis of mixed Poisson processes with baseline counts: implications for trial design and analysis

The design of clinical trials is typically based on marginal comparisons of a primary response under two or more treatments. The considerable gains in efficiency afforded by models conditional on one or more baseline responses has been extensively studied for Gaussian models. The purpose of this article is to present methods for the design and analysis of clinical trials in which the response is a count or a point process, and a corresponding baseline count is available prior to randomization. The methods are based on a conditional negative binomial model for the response given the baseline count and can be used to examine the effect of introducing selection criteria on power and sample size requirements. We show that designs based on this approach are more efficient than those proposed by McMahon et al. (1994).     

Linkage and association studies of QTL for nuclear families by mixed models

The transmission disequilibrium test (TDT) has been utilized to test the linkage and association between a genetic trait locus and a marker. Spielman et al. (1993) introduced TDT to test linkage between a qualitative trait and a marker in the presence of association. In the presence of linkage, TDT can be applied to test for association for fine mapping (Martin et al., 1997; Spielman and Ewens, 1996). In recent years, extensive research has been carried out on the TDT between a quantitative trait and a marker locus (Allison, 1997; Fan et al., 2002; George et al., 1999; Rabinowitz, 1997; Xiong et al., 1998; Zhu and Elston, 2000, 2001). The original TDT for both qualitative and quantitative traits requires unrelated offspring of heterozygous parents for analysis, and much research has been carried out to extend it to fit for different settings. For nuclear families with multiple offspring, one approach is to treat each child independently for analysis. Obviously, this may not be a valid method since offspring of one family are related to each other. Another approach is to select one offspring randomly from each family for analysis. However, with this method much information may be lost. Martin et al. (1997, 2000) constructed useful statistical tests to analyse the data for qualitative traits. In this paper, we propose to use mixed models to analyse sample data of nuclear families with multiple offspring for quantitative traits according to the models in Amos (1994). The method uses data of all offspring by taking into account their trait mean and variance-covariance structures, which contain all the effects of major gene locus, polygenic loci and environment. A test statistic based on mixed models is shown to be more powerful than the test statistic proposed by George et al. (1999) under moderate disequilibrium for nuclear families. Moreover, it has higher power than the TDT statistic which is constructed by randomly choosing a single offspring from each nuclear family.     

Observation of complex thermal transitions for mixed micelle solutions containing alkyldimethylphosphine oxides and phospholipids and the accompanying cloud points

The thermal properties of various mixtures of two nonionic surfactants, decyldimethylphosphine oxide (APO10) and dodecyldimethylphosphine oxide (APO12) and two phospholipids, dimyristoylphosphatidyl choline (DMPC) and dipalmitoylphosphatidyl choline (DPPC), were examined by differential scanning calorimetry at various mole fractions. The addition of APO12 to DMPC multilamellar vesicles lowered the temperature of the main transition, produced considerable broadening, and eliminated the pre-transition. Phase separation, as evidenced by the existence of a cloud point, T(cp), occurred when the mole fraction of APO12, with respect to DMPC was 0.58 and above. A small abrupt increase in heat capacity was observed at, or slightly above, the cloud point of APO12 and all mixed micelle solutions. It appeared that mixed micelles coexisted with mixed bilayers when the mole fraction was between 0.58 and 0.75 and perhaps as low as a mole ratio of 0.32. All of the mixtures, except APO12/DMPC, exhibited a clear endotherm below the temperature corresponding to the cloud point, which likely reflects the growth in micellar size. Overlapping chain length dependent endothermic peaks, perhaps resulting from reorganization and/or continued association of the micelles, were observed above the cloud point for all of the mixtures except for APO10/DMPC solutions. However, solutions of mixed micelles consisting of APO10/DMPC with mole fractions of surfactant between 0.81 and 0.93 portrayed a broad unidentified exotherm of about 2+/-1 kcal/mol, which was centered nearly 10-20 degrees C above the cloud point.