430 research outputs found

    a report from the Children's Oncology Group and the Utah Population Database

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    Relatively little is known about the epidemiology and factors underlying susceptibility to childhood rhabdomyosarcoma (RMS). To better characterize genetic susceptibility to childhood RMS, we evaluated the role of family history of cancer using data from the largest case–control study of RMS and the Utah Population Database (UPDB). RMS cases (n = 322) were obtained from the Children's Oncology Group (COG). Population-based controls (n = 322) were pair-matched to cases on race, sex, and age. Conditional logistic regression was used to evaluate the association between family history of cancer and childhood RMS. The results were validated using the UPDB, from which 130 RMS cases were identified and matched to controls (n = 1300) on sex and year of birth. The results were combined to generate summary odds ratios (ORs) and 95% confidence intervals (CI). Having a first-degree relative with a cancer history was more common in RMS cases than controls (ORs = 1.39, 95% CI: 0.97–1.98). Notably, this association was stronger among those with embryonal RMS (ORs = 2.44, 95% CI: 1.54–3.86). Moreover, having a first-degree relative who was younger at diagnosis of cancer (<30 years) was associated with a greater risk of RMS (ORs = 2.37, 95% CI: 1.34–4.18). In the largest analysis of its kind, we found that most children diagnosed with RMS did not have a family history of cancer. However, our results indicate an increased risk of RMS (particularly embryonal RMS) in children who have a first-degree relative with cancer, and among those whose relatives were diagnosed with cancer at <30 years of age

    Development and validation of a rapid method for the detection of latrunculol A in plasma

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    Latrunculol A is a recently discovered 6,7-dihydroxy analog of the potent actin inhibitor latrunculin A. Latrunculol A has exhibited greater cytotoxicity than latrunculin A against both murine and human colon tumor cell lines in vitro. Currently, there are no reports regarding the bioavailability of latrunculol A in vivo. This study was undertaken as a prelude to pharmacokinetic assessments and it is the first work where bioavailability of latrunculol A was studied. In the present work, a simple plasma preparation and a rapid HPLC method have been developed. Mouse plasma containing latrunculol A was first treated by acetonitrile and then centrifuged at 14,000 rpm at 4 °C for 25 min. The supernatant was injected in an HPLC system comprising a Waters Symmetry NH2 column, a mobile phase of acetonitrile/water (95/5, v/v), a flow rate of 1.0 mL/min, at 220 nm. The method was validated by parameters including a good linear correlation, a limit of quantification of 9 ng/mL, and a good precision with a coefficient variation of 1.65, 1.86, and 1.26% for 20, 400, and 800 ng/mL, respectively. With this simple method, excellent separation and sensitivity of latrunculol A are achieved, thus allowing a rapid analysis of the plasma samples for absorption, distribution, and metabolism studies

    Job dissatisfaction and the older worker:Baseline findings from the Health and Employment After Fifty study

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    Objectives: Demographic changes are requiring people to work longer. Labour force participation might be promoted by tackling sources of job dissatisfaction. We aimed to describe the epidemiology of job dissatisfaction in older British workers, to explore which perceptions of work contribute most importantly, and to assess possible impacts on health.Methods: Participants aged 50–64?years were recruited from 24 English general practices. At baseline, those currently in work (N=5437) reported on their demographic and employment circumstances, overall job satisfaction, perceptions of their work that might contribute to dissatisfaction, and their general health, mood and well-being. Associations of job dissatisfaction with risk factors and potential health outcomes were assessed cross-sectionally by logistic regression, and the potential contributions of different negative perceptions to overall dissatisfaction were summarised by population attributable fractions (PAFs).Results: Job dissatisfaction was more common among men, below age 60?years, those living in London and the South East, in the more educated and in those working for larger employers. The main contributors to job dissatisfaction among employees were feeling unappreciated and/or lacking a sense of achievement (PAF 55–56%), while in the self-employed, job insecurity was the leading contributor (PAF 79%). Job dissatisfaction was associated with all of the adverse health outcomes examined (ORs of 3–5), as were most of the negative perceptions of work that contributed to overall dissatisfaction.Conclusions: Employment policies aimed at improving job satisfaction in older workers may benefit from focussing particularly on relationships in the workplace, fairness, job security and instilling a sense of achievement.<br/

    Hundreds of variants clustered in genomic loci and biological pathways affect human height

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    Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.
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