1,200 research outputs found

    Genetic Mechanisms Underlying the Pathogenicity of Cold-Stressed Salmonella Enterica Serovar Typhimurium in Cultured Intestinal Epithelial Cells

    Get PDF
    Salmonella encounters various stresses in the environment and in the host during infection. The effects of cold (5 C, 48 h), peroxide (5 mM H2O2, 5 h) and acid stress (pH 4.0, 90 min) were tested on pathogenicity of Salmonella. Prior exposure of Salmonella to cold stress significantly (P \u3c 0.05) increased adhesion and invasion of cultured intestinal epithelial (Caco-2) cells. This increased Salmonella-host cell association was also correlated with significant induction of several virulence-associated genes, implying an increased potential of cold-stressed Salmonella to cause an infection. In Caco-2 cells infected with cold-stressed Salmonella, genes involved in the electron transfer chain were significantly induced, but no simultaneous significant increase in expression of antioxidant genes that neutralize the effect of superoxide radicals or reactive oxygen species was observed. Increased production of caspase 9 and caspase 3/7 was confirmed during host cell infection with cold-stressed Salmonella. Further, a prophage gene, STM2699, induced in cold-stressed Salmonella and a spectrin gene, SPTAN1, induced in Salmonella-infected intestinal epithelial cells were found to have a significant contribution in increased adhesion and invasion of cold-stressed Salmonella in epithelial cells

    Salmonella Degrades the Host Glycocalyx Leading to Altered Infection and Glycan Remodeling.

    Get PDF
    Complex glycans cover the gut epithelial surface to protect the cell from the environment. Invasive pathogens must breach the glycan layer before initiating infection. While glycan degradation is crucial for infection, this process is inadequately understood. Salmonella contains 47 glycosyl hydrolases (GHs) that may degrade the glycan. We hypothesized that keystone genes from the entire GH complement of Salmonella are required to degrade glycans to change infection. This study determined that GHs recognize the terminal monosaccharides (N-acetylneuraminic acid (Neu5Ac), galactose, mannose, and fucose) and significantly (p < 0.05) alter infection. During infection, Salmonella used its two GHs sialidase nanH and amylase malS for internalization by targeting different glycan structures. The host glycans were altered during Salmonella association via the induction of N-glycan biosynthesis pathways leading to modification of host glycans by increasing fucosylation and mannose content, while decreasing sialylation. Gene expression analysis indicated that the host cell responded by regulating more than 50 genes resulting in remodeled glycans in response to Salmonella treatment. This study established the glycan structures on colonic epithelial cells, determined that Salmonella required two keystone GHs for internalization, and left remodeled host glycans as a result of infection. These data indicate that microbial GHs are undiscovered virulence factors

    Large-Scale Release of Campylobacter Draft Genomes: Resources for Food Safety and Public Health from the 100K Pathogen Genome Project.

    Get PDF
    Campylobacter is a food-associated bacterium and a leading cause of foodborne illness worldwide, being associated with poultry in the food supply. This is the initial public release of 202 Campylobacter genome sequences as part of the 100K Pathogen Genome Project. These isolates represent global genomic diversity in the Campylobacter genus

    Heat flux operator, current conservation and the formal Fourier's law

    Full text link
    By revisiting previous definitions of the heat current operator, we show that one can define a heat current operator that satisfies the continuity equation for a general Hamiltonian in one dimension. This expression is useful for studying electronic, phononic and photonic energy flow in linear systems and in hybrid structures. The definition allows us to deduce the necessary conditions that result in current conservation for general-statistics systems. The discrete form of the Fourier's Law of heat conduction naturally emerges in the present definition

    The Role of Language in Anatomy and Physiology Instruction

    Get PDF
    Research indicates that student learning of science, student attitudes toward science, and their motivation to learn science and pursue science-related careers is related to classroom instruction. This study examined anatomy and physiology (A&P) classes in a south Texas high school where 97 percent of students are Hispanic bilingual learners. Classes were assigned to control or treatment groups, with the treatment group receiving instruction designed to help students develop a deeper understanding of anatomy vocabulary related to brain structures by making connections to these words in everyday life as well as to their understanding of Spanish. Main effects between group and test scores were significant, with the control group reporting higher test scores than the treatment group. We attribute this finding to a bleed-over of the treatment group instructional design to the control group. In addition, significant differences in mean and median scores were observed with respect to intrinsic motivation and self-efficacy. The statistically significant increases in learning for both groups suggests the activity-, problem-, and project-based (APB) curriculum has the potential to be an effective type of instruction, especially for bilingual learners

    BlinkML: Efficient Maximum Likelihood Estimation with Probabilistic Guarantees

    Full text link
    The rising volume of datasets has made training machine learning (ML) models a major computational cost in the enterprise. Given the iterative nature of model and parameter tuning, many analysts use a small sample of their entire data during their initial stage of analysis to make quick decisions (e.g., what features or hyperparameters to use) and use the entire dataset only in later stages (i.e., when they have converged to a specific model). This sampling, however, is performed in an ad-hoc fashion. Most practitioners cannot precisely capture the effect of sampling on the quality of their model, and eventually on their decision-making process during the tuning phase. Moreover, without systematic support for sampling operators, many optimizations and reuse opportunities are lost. In this paper, we introduce BlinkML, a system for fast, quality-guaranteed ML training. BlinkML allows users to make error-computation tradeoffs: instead of training a model on their full data (i.e., full model), BlinkML can quickly train an approximate model with quality guarantees using a sample. The quality guarantees ensure that, with high probability, the approximate model makes the same predictions as the full model. BlinkML currently supports any ML model that relies on maximum likelihood estimation (MLE), which includes Generalized Linear Models (e.g., linear regression, logistic regression, max entropy classifier, Poisson regression) as well as PPCA (Probabilistic Principal Component Analysis). Our experiments show that BlinkML can speed up the training of large-scale ML tasks by 6.26x-629x while guaranteeing the same predictions, with 95% probability, as the full model.Comment: 22 pages, SIGMOD 201
    corecore