Plos One
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Reduced TOR signaling has been shown to significantly increase lifespan in a variety of organisms [1], [2], [3], [4]. It was recently demonstrated that long-term treatment with rapamycin, an inhibitor of the mTOR pathway[5], or ablation of the mTOR target p70S6K[6] extends lifespan in mice, possibly by delaying aging. Whether inhibition of the mTOR pathway would delay or prevent age-associated disease such as AD remained to be determined. ⋯ Our data suggest that inhibition of mTOR by rapamycin, an intervention that extends lifespan in mice, can slow or block AD progression in a transgenic mouse model of the disease. Rapamycin, already used in clinical settings, may be a potentially effective therapeutic agent for the treatment of AD.
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Editorial peer review is universally used but little studied. We examined the relationship between external reviewers' recommendations and the editorial outcome of manuscripts undergoing external peer-review at the Journal of General Internal Medicine (JGIM). ⋯ Reviewers at JGIM agreed on recommendations to reject vs. accept/revise at levels barely beyond chance, yet editors placed considerable weight on reviewers' recommendations. Efforts are needed to improve the reliability of the peer-review process while helping editors understand the limitations of reviewers' recommendations.
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The number of dental implant treatments increases annually. Dental implants are manufactured by competing companies. Systematic reviews and meta-analysis have shown a clear association between pharmaceutical industry funding of clinical trials and pro-industry results. So far, the impact of industry sponsorship on the outcomes and conclusions of dental implant clinical trials has never been explored. The aim of the present study was to examine financial sponsorship of dental implant trials, and to evaluate whether research funding sources may affect the annual failure rate. ⋯ When controlling for other factors, the probability of annual failure for industry associated trials is significantly lower compared with non-industry associated trials. This bias may have significant implications on tooth extraction decision making, research on tooth preservation, and governmental health care policies.
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Fibromyalgia syndrome (FMS), a common, chronic, widespread musculoskeletal pain disorder found in 2% of the general population and with a preponderance of 85% in females, has both genetic and environmental contributions. Patients and their parents have high plasma levels of the chemokines MCP-1 and eotaxin, providing evidence for both a genetic and an immunological/inflammatory origin for the syndrome (Zhang et al., 2008, Exp. Biol. Med. 233: 1171-1180). ⋯ Since misregulation of IL-1beta expression has been predicted for patients with mutations in the MEFV gene, we conclude that patients heterozygous for rare missense variants of this gene may be predisposed to FMS, possibly triggered by environmental factors.
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Microarray data has a high dimension of variables but available datasets usually have only a small number of samples, thereby making the study of such datasets interesting and challenging. In the task of analyzing microarray data for the purpose of, e.g., predicting gene-disease association, feature selection is very important because it provides a way to handle the high dimensionality by exploiting information redundancy induced by associations among genetic markers. Judicious feature selection in microarray data analysis can result in significant reduction of cost while maintaining or improving the classification or prediction accuracy of learning machines that are employed to sort out the datasets. ⋯ Overall, our approach outperforms other compared methods. The biological functional analysis based on the MAQC-II breast cancer dataset convinced us to apply our method for phenotype prediction. Additionally, learning classifiers also play important roles in the classification of microarray data and our experimental results indicate that the Nearest Mean Scale Classifier (NMSC) is a good choice due to its prediction reliability and its stability across the three performance measurements: Testing accuracy, MCC values, and AUC errors.