Search results for "EXPRESSION"
showing 10 items of 5168 documents
Tribolium castaneum immune defense genes are differentially expressed in response to Bacillus thuringiensis toxins sharing common receptor molecules …
2015
In Tribolium castaneum larvae we have demonstrated by RNA interference knockdown that the Bacillus thuringiensis Cry3Ba toxin receptors Cadherin-like and Sodium solute symporter proteins are also functional receptors of the less active Cry3Aa toxin. Differences in susceptibility to B. thuringiensis infection might not only rely on toxin-receptor interaction but also on host defense mechanisms. We compared the expression of the immune related genes encoding Apolipophorin-III and two antimicrobial peptides, Defensin3 and Defensin2 after B. thuringiensis challenge. All three genes were up-regulated following Cry3Ba spore-crystal intoxication whereas only Defensins gene expression was induced u…
Subcytocidal attack by staphylococcal alpha-toxin activates NF-kappaB and induces interleukin-8 production.
2001
ABSTRACTFormation of transmembrane pores by staphylococcal alpha-toxin can provoke a spectrum of events depending on target cell species and toxin dose, and in certain cases, repair of the lesions has been observed. Here, we report that transcriptional processes are activated as a response of cells to low toxin doses. Exposure of monocytic (THP-1) or epithelial (ECV304) cells to 40 to 160 ng/ml alpha-toxin provoked a drop in cellular ATP level that was followed by secretion of substantial amounts of interleukin-8 (IL-8). Cells transfected with constructs comprising the proximal IL-8 promoter fused to luciferase or to green fluorescent protein cDNA exhibited enhanced reporter gene expression…
Cellular, physiological, and molecular adaptive responses of Erwinia amylovora to starvation.
2013
Erwinia amylovora causes fire blight, a destructive disease of rosaceous plants distributed worldwide. This bacterium is a nonobligate pathogen able to survive outside the host under starvation conditions, allowing its spread by various means such as rainwater. We studied E. amylovora responses to starvation using water microcosms to mimic natural oligotrophy. Initially, survivability under optimal (28 °C) and suboptimal (20 °C) growth temperatures was compared. Starvation induced a loss of culturability much more pronounced at 28 °C than at 20 °C. Natural water microcosms at 20 °C were then used to characterize cellular, physiological, and molecular starvation responses of E. amylovora. Ch…
El origen del error de inversión y las bases neuronales subyacentes
2018
Una línea de investigación importante en la enseñanza-aprendizaje de las matemáticas, más concretamente en la resolución algebraica de problemas verbales, es la centrada en identificar los procesos cognitivos que se ponen en juego desde que un sujeto identifica una relación matemática en un problema hasta que la expresan mediante una expresión algebraica. Un caso en el que un número importante de estudiantes reconocen el esquema conceptual, pero no son capaces de plasmar una expresión matemática correcta sería el conocido como error de inversión. Este error aparece en los problemas en los que se plantean proposiciones verbales de comparación aditiva y multiplicativa. El nombre del error pro…
Sample size planning for survival prediction with focus on high-dimensional data
2011
Sample size planning should reflect the primary objective of a trial. If the primary objective is prediction, the sample size determination should focus on prediction accuracy instead of power. We present formulas for the determination of training set sample size for survival prediction. Sample size is chosen to control the difference between optimal and expected prediction error. Prediction is carried out by Cox proportional hazards models. The general approach considers censoring as well as low-dimensional and high-dimensional explanatory variables. For dimension reduction in the high-dimensional setting, a variable selection step is inserted. If not all informative variables are included…
Sparse relative risk regression models
2020
Summary Clinical studies where patients are routinely screened for many genomic features are becoming more routine. In principle, this holds the promise of being able to find genomic signatures for a particular disease. In particular, cancer survival is thought to be closely linked to the genomic constitution of the tumor. Discovering such signatures will be useful in the diagnosis of the patient, may be used for treatment decisions and, perhaps, even the development of new treatments. However, genomic data are typically noisy and high-dimensional, not rarely outstripping the number of patients included in the study. Regularized survival models have been proposed to deal with such scenarios…
Pathway analysis of high-throughput biological data within a Bayesian network framework
2011
Abstract Motivation: Most current approaches to high-throughput biological data (HTBD) analysis either perform individual gene/protein analysis or, gene/protein set enrichment analysis for a list of biologically relevant molecules. Bayesian Networks (BNs) capture linear and non-linear interactions, handle stochastic events accounting for noise, and focus on local interactions, which can be related to causal inference. Here, we describe for the first time an algorithm that models biological pathways as BNs and identifies pathways that best explain given HTBD by scoring fitness of each network. Results: Proposed method takes into account the connectivity and relatedness between nodes of the p…
mRNAStab—a web application for mRNA stability analysis
2013
Abstract Eukaryotic gene expression is regulated both at the transcription and the mRNA degradation levels. The implementation of functional genomics methods that allow the simultaneous measurement of transcription (TR) and degradation (DR) rates for thousands of mRNAs is a huge improvement in this field. One of the best established methods for mRNA stability determination is genomic run-on (GRO). It allows the measurement of DR, TR and mRNA levels during cell dynamic responses. Here, we offer a software package that provides improved algorithms for determination of mRNA stability during dynamic GRO experiments. Availability and implementation: The program mRNAStab is freely accessible at h…
Identifying Causal Effects with the R Package causaleffect
2017
Do-calculus is concerned with estimating the interventional distribution of an action from the observed joint probability distribution of the variables in a given causal structure. All identifiable causal effects can be derived using the rules of do-calculus, but the rules themselves do not give any direct indication whether the effect in question is identifiable or not. Shpitser and Pearl constructed an algorithm for identifying joint interventional distributions in causal models, which contain unobserved variables and induce directed acyclic graphs. This algorithm can be seen as a repeated application of the rules of do-calculus and known properties of probabilities, and it ultimately eit…
dglars: An R Package to Estimate Sparse Generalized Linear Models
2014
dglars is a publicly available R package that implements the method proposed in Augugliaro, Mineo, and Wit (2013), developed to study the sparse structure of a generalized linear model. This method, called dgLARS, is based on a differential geometrical extension of the least angle regression method proposed in Efron, Hastie, Johnstone, and Tibshirani (2004). The core of the dglars package consists of two algorithms implemented in Fortran 90 to efficiently compute the solution curve: a predictor-corrector algorithm, proposed in Augugliaro et al. (2013), and a cyclic coordinate descent algorithm, proposed in Augugliaro, Mineo, and Wit (2012). The latter algorithm, as shown here, is significan…