Oral rehydration versus intravenous therapy for treating dehydration due to gastroenteritis in children: a meta-analysis of randomised controlled trials

BACKGROUND: Despite treatment recommendations from various organizations, oral rehydration therapy (ORT) continues to be underused, particularly by physicians in high-income countries. We conducted a systematic review of randomised controlled trials (RCTs) to compare ORT and intravenous therapy (IVT) for the treatment of dehydration secondary to acute gastroenteritis in children. METHODS: RCTs were identified through MEDLINE, EMBASE, CENTRAL, authors and references of included trials, pharmaceutical companies, and relevant organizations. Screening and inclusion were performed independently by two reviewers in order to identify randomised or quasi-randomised controlled trials comparing ORT and IVT in children with acute diarrhea and dehydration. Two reviewers independently assessed study quality using the Jadad scale and allocation concealment. Data were extracted by one reviewer and checked by a second. The primary outcome measure was failure of rehydration. We analyzed data using standard meta-analytic techniques. RESULTS: The quality of the 14 included trials ranged from 0 to 3 (Jadad score); allocation concealment was unclear in all but one study. Using a random effects model, there was no significant difference in treatment failures (risk difference [RD] 3%; 95% confidence intervals [CI]: 0, 6). The Mantel-Haenzsel fixed effects model gave a significant difference between treatment groups (RD 4%; 95% CI: 2, 5) favoring IVT. Based on the four studies that reported deaths, there were six in the IVT groups and two in ORT. There were no significant differences in total fluid intake at six and 24 hours, weight gain, duration of diarrhea, or hypo/hypernatremia. Length of stay was significantly shorter for the ORT group (weighted mean difference [WMD] -1.2 days; 95% CI: -2.4,-0.02). Phlebitis occurred significantly more often with IVT (number needed to treat [NNT] 33; 95% CI: 25,100); paralytic ileus occurred more often with ORT (NNT 33; 95% CI: 20,100). These results may not be generalizable to children with persistent vomiting. CONCLUSION: There were no clinically important differences between ORT and IVT in terms of efficacy and safety. For every 25 children (95% CI: 20, 50) treated with ORT, one would fail and require IVT. The results support existing practice guidelines recommending ORT as the first course of treatment in appropriate children with dehydration secondary to gastroenteritis

Moonlighting Proteins Hal3 and Vhs3 Form a Heteromeric PPCDC with Ykl088w in Yeast CoA Biosynthesis

Premi a l'excel·lència investigadora. 2010Unlike most other organisms, the essential five-step Coenzyme A biosynthetic pathway has not been fully resolved in yeast. Specifically, the gene(s) encoding the phosphopantothenoylcysteine decarboxylase (PPCDC) activity still remains unidentified. Sequence homology analyses suggest three candidates, namely Ykl088w, Hal3 and Vhs3, as putative PPCDC enzymes in Saccharomyces cerevisiae. Interestingly, Hal3 and Vhs3 have been characterized as negative regulatory subunits of the Ppz1 protein phosphatase. Here we show that YKL088w does not encode a third Ppz1 regulatory subunit, and that the essential roles of Ykl088w and the Hal3/Vhs3 pair are complementary, cannot be interchanged and can be attributed to PPCDC-related functions. We demonstrate that while known eukaryotic PPCDCs are homotrimers, the active yeast enzyme is a heterotrimer which consists of Ykl088w and Hal3/Vhs3 monomers that separately provides two essential catalytic residues. Our results unveil Hal3/Vhs3 as moonlighting proteins, involved in both CoA biosynthesis and protein phosphatase regulation

Predictive Power Estimation Algorithm (PPEA) - A New Algorithm to Reduce Overfitting for Genomic Biomarker Discovery

Toxicogenomics promises to aid in predicting adverse effects, understanding the mechanisms of drug action or toxicity, and uncovering unexpected or secondary pharmacology. However, modeling adverse effects using high dimensional and high noise genomic data is prone to over-fitting. Models constructed from such data sets often consist of a large number of genes with no obvious functional relevance to the biological effect the model intends to predict that can make it challenging to interpret the modeling results. To address these issues, we developed a novel algorithm, Predictive Power Estimation Algorithm (PPEA), which estimates the predictive power of each individual transcript through an iterative two-way bootstrapping procedure. By repeatedly enforcing that the sample number is larger than the transcript number, in each iteration of modeling and testing, PPEA reduces the potential risk of overfitting. We show with three different cases studies that: (1) PPEA can quickly derive a reliable rank order of predictive power of individual transcripts in a relatively small number of iterations, (2) the top ranked transcripts tend to be functionally related to the phenotype they are intended to predict, (3) using only the most predictive top ranked transcripts greatly facilitates development of multiplex assay such as qRT-PCR as a biomarker, and (4) more importantly, we were able to demonstrate that a small number of genes identified from the top-ranked transcripts are highly predictive of phenotype as their expression changes distinguished adverse from nonadverse effects of compounds in completely independent tests. Thus, we believe that the PPEA model effectively addresses the over-fitting problem and can be used to facilitate genomic biomarker discovery for predictive toxicology and drug responses

Skeletal muscle gene expression in response to resistance exercise: sex specific regulation

<p>Abstract</p> <p>Background</p> <p>The molecular mechanisms underlying the sex differences in human muscle morphology and function remain to be elucidated. The sex differences in the skeletal muscle transcriptome in both the resting state and following anabolic stimuli, such as resistance exercise (RE), might provide insight to the contributors of sexual dimorphism of muscle phenotypes. We used microarrays to profile the transcriptome of the biceps brachii of young men and women who underwent an acute unilateral RE session following 12 weeks of progressive training. Bilateral muscle biopsies were obtained either at an early (4 h post-exercise) or late recovery (24 h post-exercise) time point. Muscle transcription profiles were compared in the resting state between men (n = 6) and women (n = 8), and in response to acute RE in trained exercised vs. untrained non-exercised control muscle for each sex and time point separately (4 h post-exercise, n = 3 males, n = 4 females; 24 h post-exercise, n = 3 males, n = 4 females). A logistic regression-based method (LRpath), following Bayesian moderated t-statistic (IMBT), was used to test gene functional groups and biological pathways enriched with differentially expressed genes.</p> <p>Results</p> <p>This investigation identified extensive sex differences present in the muscle transcriptome at baseline and following acute RE. In the resting state, female muscle had a greater transcript abundance of genes involved in fatty acid oxidation and gene transcription/translation processes. After strenuous RE at the same relative intensity, the time course of the transcriptional modulation was sex-dependent. Males experienced prolonged changes while females exhibited a rapid restoration. Most of the biological processes involved in the RE-induced transcriptional regulation were observed in both males and females, but sex specificity was suggested for several signaling pathways including activation of notch signaling and TGF-beta signaling in females. Sex differences in skeletal muscle transcriptional regulation might implicate a mechanism behind disproportional muscle growth in males as compared with female counterparts after RE training at the same relative intensity.</p> <p>Conclusions</p> <p>Sex differences exist in skeletal muscle gene transcription both at rest and following acute RE, suggesting that sex is a significant modifier of the transcriptional regulation in skeletal muscle. The findings from the present study provide insight into the molecular mechanisms for sex differences in muscle phenotypes and for muscle transcriptional regulation associated with training adaptations to resistance exercise.</p

Germline bias dictates cross-serotype reactivity in a common dengue-virus-specific CD8(+) T cell response.

Adaptive immune responses protect against infection with dengue virus (DENV), yet cross-reactivity with distinct serotypes can precipitate life-threatening clinical disease. We found that clonotypes expressing the T cell antigen receptor (TCR) β-chain variable region 11 (TRBV11-2) were 'preferentially' activated and mobilized within immunodominant human-leukocyte-antigen-(HLA)-A*11:01-restricted CD8(+) T cell populations specific for variants of the nonstructural protein epitope NS3133 that characterize the serotypes DENV1, DENV3 and DENV4. In contrast, the NS3133-DENV2-specific repertoire was largely devoid of such TCRs. Structural analysis of a representative TRBV11-2(+) TCR demonstrated that cross-serotype reactivity was governed by unique interplay between the variable antigenic determinant and germline-encoded residues in the second β-chain complementarity-determining region (CDR2β). Extensive mutagenesis studies of three distinct TRBV11-2(+) TCRs further confirmed that antigen recognition was dependent on key contacts between the serotype-defined peptide and discrete residues in the CDR2β loop. Collectively, these data reveal an innate-like mode of epitope recognition with potential implications for the outcome of sequential exposure to heterologous DENVs

Hunger Artists: Yeast Adapted to Carbon Limitation Show Trade-Offs under Carbon Sufficiency

As organisms adaptively evolve to a new environment, selection results in the improvement of certain traits, bringing about an increase in fitness. Trade-offs may result from this process if function in other traits is reduced in alternative environments either by the adaptive mutations themselves or by the accumulation of neutral mutations elsewhere in the genome. Though the cost of adaptation has long been a fundamental premise in evolutionary biology, the existence of and molecular basis for trade-offs in alternative environments are not well-established. Here, we show that yeast evolved under aerobic glucose limitation show surprisingly few trade-offs when cultured in other carbon-limited environments, under either aerobic or anaerobic conditions. However, while adaptive clones consistently outperform their common ancestor under carbon limiting conditions, in some cases they perform less well than their ancestor in aerobic, carbon-rich environments, indicating that trade-offs can appear when resources are non-limiting. To more deeply understand how adaptation to one condition affects performance in others, we determined steady-state transcript abundance of adaptive clones grown under diverse conditions and performed whole-genome sequencing to identify mutations that distinguish them from one another and from their common ancestor. We identified mutations in genes involved in glucose sensing, signaling, and transport, which, when considered in the context of the expression data, help explain their adaptation to carbon poor environments. However, different sets of mutations in each independently evolved clone indicate that multiple mutational paths lead to the adaptive phenotype. We conclude that yeasts that evolve high fitness under one resource-limiting condition also become more fit under other resource-limiting conditions, but may pay a fitness cost when those same resources are abundant

Memory in Microbes: Quantifying History-Dependent Behavior in a Bacterium

Memory is usually associated with higher organisms rather than bacteria. However, evidence is mounting that many regulatory networks within bacteria are capable of complex dynamics and multi-stable behaviors that have been linked to memory in other systems. Moreover, it is recognized that bacteria that have experienced different environmental histories may respond differently to current conditions. These “memory” effects may be more than incidental to the regulatory mechanisms controlling acclimation or to the status of the metabolic stores. Rather, they may be regulated by the cell and confer fitness to the organism in the evolutionary game it participates in. Here, we propose that history-dependent behavior is a potentially important manifestation of memory, worth classifying and quantifying. To this end, we develop an information-theory based conceptual framework for measuring both the persistence of memory in microbes and the amount of information about the past encoded in history-dependent dynamics. This method produces a phenomenological measure of cellular memory without regard to the specific cellular mechanisms encoding it. We then apply this framework to a strain of Bacillus subtilis engineered to report on commitment to sporulation and degradative enzyme (AprE) synthesis and estimate the capacity of these systems and growth dynamics to ‘remember’ 10 distinct cell histories prior to application of a common stressor. The analysis suggests that B. subtilis remembers, both in short and long term, aspects of its cell history, and that this memory is distributed differently among the observables. While this study does not examine the mechanistic bases for memory, it presents a framework for quantifying memory in cellular behaviors and is thus a starting point for studying new questions about cellular regulation and evolutionary strategy

Module-based multiscale simulation of angiogenesis in skeletal muscle

<p>Abstract</p> <p>Background</p> <p>Mathematical modeling of angiogenesis has been gaining momentum as a means to shed new light on the biological complexity underlying blood vessel growth. A variety of computational models have been developed, each focusing on different aspects of the angiogenesis process and occurring at different biological scales, ranging from the molecular to the tissue levels. Integration of models at different scales is a challenging and currently unsolved problem.</p> <p>Results</p> <p>We present an object-oriented module-based computational integration strategy to build a multiscale model of angiogenesis that links currently available models. As an example case, we use this approach to integrate modules representing microvascular blood flow, oxygen transport, vascular endothelial growth factor transport and endothelial cell behavior (sensing, migration and proliferation). Modeling methodologies in these modules include algebraic equations, partial differential equations and agent-based models with complex logical rules. We apply this integrated model to simulate exercise-induced angiogenesis in skeletal muscle. The simulation results compare capillary growth patterns between different exercise conditions for a single bout of exercise. Results demonstrate how the computational infrastructure can effectively integrate multiple modules by coordinating their connectivity and data exchange. Model parameterization offers simulation flexibility and a platform for performing sensitivity analysis.</p> <p>Conclusions</p> <p>This systems biology strategy can be applied to larger scale integration of computational models of angiogenesis in skeletal muscle, or other complex processes in other tissues under physiological and pathological conditions.</p