Visiting the cell biology of Salmonella infection

Salmonella, a Gram-negative facultative intracellular pathogen is capable of infecting vast array of hosts. The striking ability of Salmonella to overcome every hurdle encountered in the host proves that they are true survivors. In the host, Salmonella infects various cell types and needs to survive and replicate by countering the defense mechanism of the specific cell. In this review, we will summarize the recent insights into the cell biology of Salmonella infection. Here, we will focus on the findings that deal with the specific mechanism of various cell types to control Salmonella infection. Further, the survival strategies of the pathogen in response to the host immunity will also be discussed in detail. Better understanding of the mechanisms by which Salmonella evade the host defense system and establish pathogenesis will be critical in disease management. (C) 2010 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved.

Spinodal decomposition of a Co-Ti-Nb alloy

The microstructural evolution on aging a Co-3 wt pct Ti-2 wt pct Nb alloy has been followed by transmission electron microscopy and diffraction to show that the solid solution decomposed by the spinodal mode. The strengthening observed has been correlated with the differences in lattice parameters of the coexisting phases. The several stages of coarsening have been documented to yield information about their kinetics and morphological changes.Formerly Visiting Assistant Professor, Department of Mechanical and Industrial Engineering, University of Illinois at Urbana-Champaign, 1206 West Green Street, Urbana, IL 61801, is with .

A Genetic Study of Immunoglobulin E and Atopic Disease Based on Families Ascertained through Asthmatic Children

In order to investigate the modes of inheritance of serum immunoglobulin E (IgE) levels and atopic disease, serum IgE levels and data on allergic disease were obtained from 42 families ascertained through asthmatic children visiting an allergy clinic. Although the mean IgE levels were elevated (mean 637 U/ml), the prevalence of atopic disease in this population was surprisingly low. When the data were analyzed using complex segregation analysis, no major locus could be detected. Moreover, the polygenic heritability was unexpectedly small even though the correlation between serum IgE levels and the liability to atopic disease was around 0.4. Given this unusual set of findings, it is postulated that parasitic infections in this population have (in accordance with well-established results of parasitic disease) caused both elevated levels of serum IgE and a decreased prevalence of allergic disease with the possible masking of the various genetic components of serum IgE levels and atopic disease.

Composition of Extrafloral Nectar Influences Interactions between the Myrmecophyte Humboldtia brunonis and its Ant Associates

Ant-plant interactions often are mediated by extrafloral nectar (EFN) composition that may influence plant visitation by ants. Over a 300 km range in the Indian Western Ghats, we investigated the correlation between the EFN composition of the myrmecophytic ant-plant Humboldtia brunonis (Fabaceae) and the number and species of ants visiting EFN. EFN composition varied among H. brunonis populations and between plant organs (floral bud vs. young leaf EFN). In general, EFN was rich in sugars with small quantities of amino acids, especially essential amino acids, and had moderate invertase activity. In experiments at the study sites with sugar and amino acid solutions and with leaf or floral bud EFN mimics, dominant EFN-feeding ants differentiated between solutions as well as between mimics. The castration parasite Crematogaster dohrni (northern study site) was the least selective and did not exhibit any clear feeding preferences, while the largely trophobiont-tending non-protective Myrmicaria brunnea (middle study site) preferred higher sucrose concentrations and certain essential/non-essential amino acid mixtures. The mutualistic Technomyrmex albipes (southern study site) preferred sucrose over glucose or fructose solutions and consumed the leaf EFN mimic to a greater extent than the floral bud EFN mimic. This young leaf EFN mimic had low sugar concentrations, the lowest viscosity and sugar: amino acid ratio, was rich in essential amino acids, and appeared ideally suited to the digestive physiology of T. albipes. This preference for young leaf EFN may explain the greater protection afforded to young leaves than to floral buds by T. albipes, and may also help to resolve ant-pollinator conflicts. The differential response of dominant ants to sugar, amino acids, or solution viscosity suggests that plants can fine-tune their interactions with local ants via EFN composition. Thus, EFN can mediate local partner-choice mechanisms in ant-plant interactions.

Scalable sequential alternating proximal methods for sparse structural SVMs and CRFs

Structural Support Vector Machines (SSVMs) and Conditional Random Fields (CRFs) are popular discriminative methods used for classifying structured and complex objects like parse trees, image segments and part-of-speech tags. The datasets involved are very large dimensional, and the models designed using typical training algorithms for SSVMs and CRFs are non-sparse. This non-sparse nature of models results in slow inference. Thus, there is a need to devise new algorithms for sparse SSVM and CRF classifier design. Use of elastic net and L1-regularizer has already been explored for solving primal CRF and SSVM problems, respectively, to design sparse classifiers. In this work, we focus on dual elastic net regularized SSVM and CRF. By exploiting the weakly coupled structure of these convex programming problems, we propose a new sequential alternating proximal (SAP) algorithm to solve these dual problems. This algorithm works by sequentially visiting each training set example and solving a simple subproblem restricted to a small subset of variables associated with that example. Numerical experiments on various benchmark sequence labeling datasets demonstrate that the proposed algorithm scales well. Further, the classifiers designed are sparser than those designed by solving the respective primal problems and demonstrate comparable generalization performance. Thus, the proposed SAP algorithm is a useful alternative for sparse SSVM and CRF classifier design.