Perinatal Environmental Tobacco Smoke Exposure in Rhesus Monkeys: Critical Periods and Regional Selectivity for Effects on Brain Cell Development and Lipid Peroxidation

Perinatal environmental tobacco smoke (ETS) exposure in humans elicits neurobehavioral deficits. We exposed rhesus monkeys to ETS during gestation and through 13 months postnatally, or postnatally only (6–13 months). At the conclusion of exposure, we examined cerebrocortical regions and the midbrain for cell damage markers and lipid peroxidation. For perinatal ETS, two archetypal patterns were seen in the various regions, one characterized by cell loss (reduced DNA concentration) and corresponding increases in cell size (increased protein/DNA ratio), and a second pattern suggesting replacement of larger neuronal cells with smaller and more numerous glia (increased DNA concentration, decreased protein/DNA ratio). The membrane/total protein ratio, a biomarker of neurite formation, also indicated potential damage to neuronal projections, accompanied by reactive sprouting. When ETS exposure was restricted to the postnatal period, the effects were similar in regional selectivity, direction, and magnitude. These patterns resemble the effects of prenatal nicotine exposure in rodent and primate models. Surprisingly, perinatal ETS exposure reduced the level of lipid peroxidation as assessed by the concentration of thiobarbituric acid reactive species, whereas postnatal ETS did not. The heart, a tissue that, like the brain, has high oxygen demand, displayed a similar but earlier decrease (2–3 months) in lipid peroxidation in the perinatal exposure model, whereas values were reduced at 13 months with the postnatal exposure paradigm. Our results provide a mechanistic connection between perinatal ETS exposure and neurobehavioral anomalies, reinforce the role of nicotine in these effects, and buttress the importance of restricting or eliminating ETS exposure in young children

Assessing and reporting heterogeneity in treatment effects in clinical trials: a proposal

Mounting evidence suggests that there is frequently considerable variation in the risk of the outcome of interest in clinical trial populations. These differences in risk will often cause clinically important heterogeneity in treatment effects (HTE) across the trial population, such that the balance between treatment risks and benefits may differ substantially between large identifiable patient subgroups; the "average" benefit observed in the summary result may even be non-representative of the treatment effect for a typical patient in the trial. Conventional subgroup analyses, which examine whether specific patient characteristics modify the effects of treatment, are usually unable to detect even large variations in treatment benefit (and harm) across risk groups because they do not account for the fact that patients have multiple characteristics simultaneously that affect the likelihood of treatment benefit. Based upon recent evidence on optimal statistical approaches to assessing HTE, we propose a framework that prioritizes the analysis and reporting of multivariate risk-based HTE and suggests that other subgroup analyses should be explicitly labeled either as primary subgroup analyses (well-motivated by prior evidence and intended to produce clinically actionable results) or secondary (exploratory) subgroup analyses (performed to inform future research). A standardized and transparent approach to HTE assessment and reporting could substantially improve clinical trial utility and interpretability

CompaGB: An open framework for genome browsers comparison

<p>Abstract</p> <p>Background</p> <p>Tools to visualize and explore genomes hold a central place in genomics and the diversity of genome browsers has increased dramatically over the last few years. It often turns out to be a daunting task to compare and choose a well-adapted genome browser, as multidisciplinary knowledge is required to carry out this task and the number of tools, functionalities and features are overwhelming.</p> <p>Findings</p> <p>To assist in this task, we propose a community-based framework based on two cornerstones: (i) the implementation of industry promoted software qualification method (QSOS) adapted for genome browser evaluations, and (ii) a web resource providing numerous facilities either for visualizing comparisons or performing new evaluations. We formulated 60 criteria specifically for genome browsers, and incorporated another 65 directly from QSOS's generic section. Those criteria aim to answer versatile needs, ranging from a biologist whose interest primarily lies into user-friendly and informative functionalities, a bioinformatician who wants to integrate the genome browser into a wider framework, or a computer scientist who might choose a software according to more technical features. We developed a dedicated web application to enrich the existing QSOS functionalities (weighting of criteria, user profile) with features of interest to a community-based framework: easy management of evolving data, user comments...</p> <p>Conclusions</p> <p>The framework is available at <url>http://genome.jouy.inra.fr/CompaGB</url>. It is open to anyone who wishes to participate in the evaluations. It helps the scientific community to (1) choose a genome browser that would better fit their particular project, (2) visualize features comparatively with easily accessible formats, such as tables or radar plots and (3) perform their own evaluation against the defined criteria. To illustrate the CompaGB functionalities, we have evaluated seven genome browsers according to the implemented methodology. A summary of the features of the compared genome browsers is presented and discussed.</p

Competing risk and heterogeneity of treatment effect in clinical trials

It has been demonstrated that patients enrolled in clinical trials frequently have a large degree of variation in their baseline risk for the outcome of interest. Thus, some have suggested that clinical trial results should routinely be stratified by outcome risk using risk models, since the summary results may otherwise be misleading. However, variation in competing risk is another dimension of risk heterogeneity that may also underlie treatment effect heterogeneity. Understanding the effects of competing risk heterogeneity may be especially important for pragmatic comparative effectiveness trials, which seek to include traditionally excluded patients, such as the elderly or complex patients with multiple comorbidities. Indeed, the observed effect of an intervention is dependent on the ratio of outcome risk to competing risk, and these risks – which may or may not be correlated – may vary considerably in patients enrolled in a trial. Further, the effects of competing risk on treatment effect heterogeneity can be amplified by even a small degree of treatment related harm. Stratification of trial results along both the competing and the outcome risk dimensions may be necessary if pragmatic comparative effectiveness trials are to provide the clinically useful information their advocates intend

Do rare variant genotypes predict common variant genotypes?

The synthetic association hypothesis proposes that common genetic variants detectable in genome-wide association studies may reflect the net phenotypic effect of multiple rare polymorphisms distributed broadly within the focal gene rather than, as often assumed, the effect of common functional variants in high linkage disequilibrium with the focal marker. In a recent study, Dickson and colleagues demonstrated synthetic association in simulations and in two well-characterized, highly polymorphic human disease genes. The converse of this hypothesis is that rare variant genotypes must be correlated with common variant genotypes often enough to make the phenomenon of synthetic association possible. Here we used the exome genotype data provided for Genetic Analysis Workshop 17 to ask how often, how well, and under what conditions rare variant genotypes predict the genotypes of common variants within the same gene. We found nominal evidence of correlation between rare and common variants in 21-30% of cases examined for unrelated individuals; this rate increased to 38-44% for related individuals, underscoring the segregation that underlies synthetic association

Getting into hot water:sick guppies frequent warmer thermal conditions

Ectotherms depend on the environmental temperature for thermoregulation and exploit thermal regimes that optimise physiological functioning. They may also frequent warmer conditions to up-regulate their immune response against parasite infection and/or impede parasite development. This adaptive response, known as ‘behavioural fever’, has been documented in various taxa including insects, reptiles and fish, but only in response to endoparasite infections. Here, a choice chamber experiment was used to investigate the thermal preferences of a tropical freshwater fish, the Trinidadian guppy (Poecilia reticulata), when infected with a common helminth ectoparasite Gyrodactylus turnbulli, in female-only and mixed-sex shoals. The temperature tolerance of G. turnbulli was also investigated by monitoring parasite population trajectories on guppies maintained at a continuous 18, 24 or 32 °C. Regardless of shoal composition, infected fish frequented the 32 °C choice chamber more often than when uninfected, significantly increasing their mean temperature preference. Parasites maintained continuously at 32 °C decreased to extinction within 3 days, whereas mean parasite abundance increased on hosts incubated at 18 and 24 °C. We show for the first time that gyrodactylid-infected fish have a preference for warmer waters and speculate that sick fish exploit the upper thermal tolerances of their parasites to self medicate

Features of mammalian microRNA promoters emerge from polymerase II chromatin immunoprecipitation data

Background: MicroRNAs (miRNAs) are short, non-coding RNA regulators of protein coding genes. miRNAs play a very important role in diverse biological processes and various diseases. Many algorithms are able to predict miRNA genes and their targets, but their transcription regulation is still under investigation. It is generally believed that intragenic miRNAs (located in introns or exons of protein coding genes) are co-transcribed with their host genes and most intergenic miRNAs transcribed from their own RNA polymerase II (Pol II) promoter. However, the length of the primary transcripts and promoter organization is currently unknown. Methodology: We performed Pol II chromatin immunoprecipitation (ChIP)-chip using a custom array surrounding regions of known miRNA genes. To identify the true core transcription start sites of the miRNA genes we developed a new tool (CPPP). We showed that miRNA genes can be transcribed from promoters located several kilobases away and that their promoters share the same general features as those of protein coding genes. Finally, we found evidence that as many as 26% of the intragenic miRNAs may be transcribed from their own unique promoters. Conclusion: miRNA promoters have similar features to those of protein coding genes, but miRNA transcript organization is more complex. © 2009 Corcoran et al

MethCancerDB – aberrant DNA methylation in human cancer

Early detection, classification and prognosis of human cancers by analysis of CpG methylation carry huge diagnostic potential. MethCancerDB collects and annotates genes and sequences from the abundance of published methylation studies and interlinks them to all methylation-relevant bioinformatical resources. MethCancerDB starts with 4720 entries from 348 sources and is freely accessible at http://www.methcancerdb.net

An Experimental Biomimetic Platform for Artificial Olfaction

Artificial olfactory systems have been studied for the last two decades mainly from the point of view of the features of olfactory neuron receptor fields. Other fundamental olfaction properties have only been episodically considered in artificial systems. As a result, current artificial olfactory systems are mostly intended as instruments and are of poor benefit for biologists who may need tools to model and test olfactory models. Herewith, we show how a simple experimental approach can be used to account for several phenomena observed in olfaction

Stochastic Gravity: Theory and Applications

Whereas semiclassical gravity is based on the semiclassical Einstein equation with sources given by the expectation value of the stress-energy tensor of quantum fields, stochastic semiclassical gravity is based on the Einstein-Langevin equation, which has in addition sources due to the noise kernel. In the first part, we describe the fundamentals of this new theory via two approaches: the axiomatic and the functional. In the second part, we describe three applications of stochastic gravity theory. First, we consider metric perturbations in a Minkowski spacetime, compute the two-point correlation functions of these perturbations and prove that Minkowski spacetime is a stable solution of semiclassical gravity. Second, we discuss structure formation from the stochastic gravity viewpoint. Third, we discuss the backreaction of Hawking radiation in the gravitational background of a black hole and describe the metric fluctuations near the event horizon of an evaporating black holeComment: 100 pages, no figures; an update of the 2003 review in Living Reviews in Relativity gr-qc/0307032 ; it includes new sections on the Validity of Semiclassical Gravity, the Stability of Minkowski Spacetime, and the Metric Fluctuations of an Evaporating Black Hol