An Approach to Quantitative Nutrition of Phytoplankton

SYNOPSIS. An outline is given of the 2-compartment model of algal growth developed by the author over the last decade, The model, as fully developed, claims to be able to handle simultaneously as many nutrients and organisms as desired in an environment of changing inputs and outputs.     

A Note on Sire Evaluation with Uncertain Paternity

We consider sire evaluation for situations in which paternity is uncertain. We show how mixed models equations can be used to obtain the best linear unbiased predictors for sire evaluation in such situations.     

Correction of Eye-estimation by Using Shrunken Predictors

The eye-estimation method is widely used in practice. Several agronomic and biological measures are currently estimated by this method. If a simple linear regression is the kernel model a shrinkage technique can be used for correcting the bias associated with this method. Two predictors of the population total are proposed and the corresponding model-based errors are deduced. A simulation study fixes the behaviour of the predictors.     

Metabolic engineering of Torulopsis glabrata for malate production

The yeast Torulopsis glabrata CCTCC M202019, which is used for industrial pyruvate production, was chosen to explore the suitability of engineering this multi-vitamin auxotrophic yeast for increased malate production. Various metabolic engineering strategies were used to manipulate carbon flux from pyruvate to malate: (i) overexpression of pyruvate carboxylase and malate dehydrogenase; (ii) identification of the bottleneck in malate production by model iNX804; (iii) simultaneous overexpression of genes RoPYC, RoMDH and SpMAE1. Using these strategies, 8.5 g L^–1 malate was accumulated in the engineered strain T.G-PMS, which was about 10-fold greater than that of the control strain T.G-26. The results presented here suggest that T. glabrata CCTCC M202019 is a promising candidate for industrial malate production.     

On Model-Choice in Discrimination with Categorical Variables

An algorithm for model selection in discrimination with categorical variables is presented. It is based on four models applied hierarchically and linked with a build-up procedure of feature-selection. The choice of models and features is ensured by a consequent cross-validation. Results of an application in medical diagnostics are described.     

A mouse model of Haemophilus ducreyi infection (chancroid)

Abstract Six- to 8-week-old CBA mice were inoculated intradermally and/or subcutaneously on each flank with one of 3 strains of Haemophilus ducreyi , 2 of these being recent isolates and the other a reference strain. Pustular nodules developed at all sites the day after 10⁷ organisms had been given. Severe ulceration similar to chancroid occurred in about half of the lesions which took at least 13 days to heal. All three strains of H. ducreyi were isolated from the mice during the first week. The model is invaluable in helping to understand the pathogenicity of H. ducreyi as well as the immunopathogenesis and other aspects of chancroid.     

Species co‐occurrence patterns and dietary resource competition in primates

Diamond (Assembly of species communities. In: Cody ML, Diamond JM, editors. Ecology and evolution of communities. Cambridge: Belknap. p 342–444 ( 1975 )) argued that interspecific competition between species occupying similar niches results in a nonrandom pattern of species distributions. In particular, some species pairs may never be found in the same community due to competitive exclusion. Rigorous analytical methods have been developed to investigate the possible role that interspecific competition has on the evolution of communities. Many studies that have implemented these methods have shown support for Diamond's assembly rules, yet there are numerous exceptions. We build on this previous research by examining the co‐occurrence patterns of primate species in 109 communities from across the world. We used EcoSim to calculate a checkerboard (C) score for each region. The C score provides a measure of the proportion of species pairs that do not co‐occur in a set of communities. High C scores indicate that species are nonrandomly distributed throughout a region, and interspecific competition may be driving patterns of competitive exclusion. We conducted two sets of analyses. One included all primate species per region, and the second analysis assigned each species to one of four dietary guilds: frugivores, folivores, insectivores, and frugivore‐insectivores. Using all species per region, we found significantly high C scores in 9 of 10 regions examined. For frugivores, we found significantly high‐C scores in more than 50% of regions. In contrast, only 23% of regions exhibited significantly high‐C scores for folivores. Our results suggest that communities are nonrandomly structured and may be the result of greater levels of interspecific competition between frugivores compared to folivores. Am J Phys Anthropol, 2010. © 2010 Wiley‐Liss, Inc.