The role of dwelling type when estimating the effect of magnetic fields on childhood leukemia in the California Power Line Study (CAPS).

PurposeThe type of dwelling where a child lives is an important factor when considering residential exposure to environmental agents. In this paper, we explore its role when estimating the potential effects of magnetic fields (MF) on leukemia using data from the California Power Line Study (CAPS). In this context, dwelling type could be a risk factor, a proxy for other risk factors, a cause of MF exposure, a confounder, an effect-measure modifier, or some combination.MethodsWe obtained information on type of dwelling at birth on over 2,000 subjects. Using multivariable-adjusted logistic regression, we assessed whether dwelling type was a risk factor for childhood leukemia, which covariates and MF exposures were associated with dwelling type, and whether dwelling type was a potential confounder or an effect-measure modifier in the MF-leukemia relationship under the assumption of no-uncontrolled confounding.ResultsA majority of children lived in single-family homes or duplexes (70%). Dwelling type was associated with race/ethnicity and socioeconomic status but not with childhood leukemia risk, after other adjustments, and did not alter the MF-leukemia relationship upon adjustment as a potential confounder. Stratification revealed potential effect-measure modification by dwelling type on the multiplicative scale.ConclusionDwelling type does not appear to play a significant role in the MF-leukemia relationship in the CAPS dataset as a leukemia risk factor or confounder. Future research should explore the role of dwelling as an effect-measure modifier of the MF-leukemia association

Exploring inconsistencies between observational and experimental studies of selenium and diabetes risk.

Background: Observational and experimental epidemiologic studies that have addressed the relation between intake of the trace element selenium and cancer risk have yielded strongly conflicting results, as recently reported by a Cochrane review. Most observational studies suggest an inverse association, while randomized controlled trials (RCTs) have indicated a null or direct relation. Little is known about the replication of such inconsistencies when dealing with the risk of other chronic disease. Objectives: We investigated the results of observational and experimental studies linking selenium exposure to the occurrence of type 2 diabetes. Methods: After a literature search we identified 12 observational studies (8 cross-sectional and 4 cohort) and 5 RCTs. Using a random-effects model, we computed the summary relative risk (RR) of type-2 diabetes along with its 95% confidence interval (CI) in subjects with the highest versus the lowest selenium exposure category in observational studies, and in subjects allocated to selenium compared to placebo in the RCTs. Results: Summary RRs were 1.98 (95% CI 1.22-3.23) and 1.13 (0.15-8.45) for cross-sectional studies using serum and toenail selenium for exposure assessment, respectively. Cohort studies based on toenail selenium yielded a summary RR of 0.78 (0.62-0.98), while the only study assessing dietary selenium intake gave a RR of 2.39, (1.32-4.32). For RCTs, summary RR was 1.10 (1.00-1.21) among selenium-supplemented versus placebo. The distinctive feature of the two observational studies (one cross-sectional and one prospective) that failed to find an excess diabetes risk associated with higher selenium exposure was that the subjects were health professionals. Age, gender, study area and other demographic characteristics did not appear to have influenced the results. Conclusions: These results suggest that the ability of observational studies to predict results of RCTs when addressing the health effects of selenium may differ on the basis of the outcome studied (diabetes versus cancer) as well as the indicator used for exposure assessment and the type of population under study

Selenium for preventing cancer.

BACKGROUND: This review is an update of the first Cochrane publication on selenium for preventing cancer (Dennert 2011).Selenium is a metalloid with both nutritional and toxicological properties. Higher selenium exposure and selenium supplements have been suggested to protect against several types of cancers. OBJECTIVES: Two research questions were addressed in this review: What is the evidence for:1. an aetiological relation between selenium exposure and cancer risk in humans? and2. the efficacy of selenium supplementation for cancer prevention in humans? SEARCH METHODS: We conducted electronic searches of the Cochrane Central Register of Controlled Trials (CENTRAL, 2013, Issue 1), MEDLINE (Ovid, 1966 to February 2013 week 1), EMBASE (1980 to 2013 week 6), CancerLit (February 2004) and CCMed (February 2011). As MEDLINE now includes the journals indexed in CancerLit, no further searches were conducted in this database after 2004. SELECTION CRITERIA: We included prospective observational studies (cohort studies including sub-cohort controlled studies and nested case-control studies) and randomised controlled trials (RCTs) with healthy adult participants (18 years of age and older). DATA COLLECTION AND ANALYSIS: For observational studies, we conducted random effects meta-analyses when five or more studies were retrieved for a specific outcome. For RCTs, we performed random effects meta-analyses when two or more studies were available. The risk of bias in observational studies was assessed using forms adapted from the Newcastle-Ottawa Quality Assessment Scale for cohort and case-control studies; the criteria specified in the Cochrane Handbook for Systematic Reviews of Interventions were used to evaluate the risk of bias in RCTs. MAIN RESULTS: We included 55 prospective observational studies (including more than 1,100,000 participants) and eight RCTs (with a total of 44,743 participants). For the observational studies, we found lower cancer incidence (summary odds ratio (OR) 0.69, 95% confidence interval (CI) 0.53 to 0.91, N = 8) and cancer mortality (OR 0.60, 95% CI 0.39 to 0.93, N = 6) associated with higher selenium exposure. Gender-specific subgroup analysis provided no clear evidence of different effects in men and women (P value 0.47), although cancer incidence was lower in men (OR 0.66, 95% CI 0.42 to 1.05, N = 6) than in women (OR 0.90, 95% CI 0.45 to 1.77, N = 2). The most pronounced decreases in risk of site-specific cancers were seen for stomach, bladder and prostate cancers. However, these findings have limitations due to study design, quality and heterogeneity that complicate interpretation of the summary statistics. Some studies suggested that genetic factors may modify the relation between selenium and cancer risk-a hypothesis that deserves further investigation.In RCTs, we found no clear evidence that selenium supplementation reduced the risk of any cancer (risk ratio (RR) 0.90, 95% CI 0.70 to 1.17, two studies, N = 4765) or cancer-related mortality (RR 0.81, 95% CI 0.49 to 1.32, two studies, N = 18,698), and this finding was confirmed when the analysis was restricted to studies with low risk of bias. The effect on prostate cancer was imprecise (RR 0.90, 95% CI 0.71 to 1.14, four studies, N = 19,110), and when the analysis was limited to trials with low risk of bias, the interventions showed no effect (RR 1.02, 95% CI 0.90 to 1.14, three studies, N = 18,183). The risk of non-melanoma skin cancer was increased (RR 1.44, 95% CI 0.95 to 1.17, three studies, N = 1900). Results of two trials-the Nutritional Prevention of Cancer Trial (NPCT) and the Selenium and Vitamin E Cancer Trial (SELECT)-also raised concerns about possible increased risk of type 2 diabetes, alopecia and dermatitis due to selenium supplements. An early hypothesis generated by NPCT that individuals with the lowest blood selenium levels at baseline could reduce their risk of cancer, particularly of prostate cancer, by increasing selenium intake has not been confirmed by subsequent trials. As the RCT participants were overwhelmingly male (94%), gender differences could not be systematically assessed. AUTHORS' CONCLUSIONS: Although an inverse association between selenium exposure and the risk of some types of cancer was found in some observational studies, this cannot be taken as evidence of a causal relation, and these results should be interpreted with caution. These studies have many limitations, including issues with assessment of exposure to selenium and to its various chemical forms, heterogeneity, confounding and other biases. Conflicting results including inverse, null and direct associations have been reported for some cancer types.RCTs assessing the effects of selenium supplementation on cancer risk have yielded inconsistent results, although the most recent studies, characterised by a low risk of bias, found no beneficial effect on cancer risk, more specifically on risk of prostate cancer, as well as little evidence of any influence of baseline selenium status. Rather, some trials suggest harmful effects of selenium exposure. To date, no convincing evidence suggests that selenium supplements can prevent cancer in humans

What traits are carried on mobile genetic elements, and why?

Although similar to any other organism, prokaryotes can transfer genes vertically from mother cell to daughter cell, they can also exchange certain genes horizontally. Genes can move within and between genomes at fast rates because of mobile genetic elements (MGEs). Although mobile elements are fundamentally self-interested entities, and thus replicate for their own gain, they frequently carry genes beneficial for their hosts and/or the neighbours of their hosts. Many genes that are carried by mobile elements code for traits that are expressed outside of the cell. Such traits are involved in bacterial sociality, such as the production of public goods, which benefit a cell's neighbours, or the production of bacteriocins, which harm a cell's neighbours. In this study we review the patterns that are emerging in the types of genes carried by mobile elements, and discuss the evolutionary and ecological conditions under which mobile elements evolve to carry their peculiar mix of parasitic, beneficial and cooperative genes

Animal model integration to AutDB, a genetic database for autism

<p>Abstract</p> <p>Background</p> <p>In the post-genomic era, multi-faceted research on complex disorders such as autism has generated diverse types of molecular information related to its pathogenesis. The rapid accumulation of putative candidate genes/loci for Autism Spectrum Disorders (ASD) and ASD-related animal models poses a major challenge for systematic analysis of their content. We previously created the Autism Database (AutDB) to provide a publicly available web portal for ongoing collection, manual annotation, and visualization of genes linked to ASD. Here, we describe the design, development, and integration of a new module within AutDB for ongoing collection and comprehensive cataloguing of ASD-related animal models.</p> <p>Description</p> <p>As with the original AutDB, all data is extracted from published, peer-reviewed scientific literature. Animal models are annotated with a new standardized vocabulary of phenotypic terms developed by our researchers which is designed to reflect the diverse clinical manifestations of ASD. The new Animal Model module is seamlessly integrated to AutDB for dissemination of diverse information related to ASD. Animal model entries within the new module are linked to corresponding candidate genes in the original "Human Gene" module of the resource, thereby allowing for cross-modal navigation between gene models and human gene studies. Although the current release of the Animal Model module is restricted to mouse models, it was designed with an expandable framework which can easily incorporate additional species and non-genetic etiological models of autism in the future.</p> <p>Conclusions</p> <p>Importantly, this modular ASD database provides a platform from which data mining, bioinformatics, and/or computational biology strategies may be adopted to develop predictive disease models that may offer further insights into the molecular underpinnings of this disorder. It also serves as a general model for disease-driven databases curating phenotypic characteristics of corresponding animal models.</p

Measuring the impact of cancer: a comparison of non-Hodgkin lymphoma and breast cancer survivors

Introduction Self-report instruments such as the Impact of Cancer (IOC) are designed to measure quality of life (QOL) impacts that cancer survivors attribute to their cancer experience. Generalizability of QOL findings across dis-tinct diagnostic categories of survivors is untested. W