ISOWN: accurate somatic mutation identification in the absence of normal tissue controls.

BackgroundA key step in cancer genome analysis is the identification of somatic mutations in the tumor. This is typically done by comparing the genome of the tumor to the reference genome sequence derived from a normal tissue taken from the same donor. However, there are a variety of common scenarios in which matched normal tissue is not available for comparison.ResultsIn this work, we describe an algorithm to distinguish somatic single nucleotide variants (SNVs) in next-generation sequencing data from germline polymorphisms in the absence of normal samples using a machine learning approach. Our algorithm was evaluated using a family of supervised learning classifications across six different cancer types and ~1600 samples, including cell lines, fresh frozen tissues, and formalin-fixed paraffin-embedded tissues; we tested our algorithm with both deep targeted and whole-exome sequencing data. Our algorithm correctly classified between 95 and 98% of somatic mutations with F1-measure ranges from 75.9 to 98.6% depending on the tumor type. We have released the algorithm as a software package called ISOWN (Identification of SOmatic mutations Without matching Normal tissues).ConclusionsIn this work, we describe the development, implementation, and validation of ISOWN, an accurate algorithm for predicting somatic mutations in cancer tissues in the absence of matching normal tissues. ISOWN is available as Open Source under Apache License 2.0 from https://github.com/ikalatskaya/ISOWN

The association between family and community social capital and health risk behaviours in young people: an integrative review

Background: Health risk behaviours known to result in poorer outcomes in adulthood are generally established in late childhood and adolescence. These ‘risky’ behaviours include smoking, alcohol and illicit drug use and sexual risk taking. While the role of social capital in the establishment of health risk behaviours in young people has been explored, to date, no attempt has been made to consolidate the evidence in the form of a review. Thus, this integrative review was undertaken to identify and synthesise research findings on the role and impact of family and community social capital on health risk behaviours in young people and provide a consolidated evidence base to inform multi-sectorial policy and practice.<p></p> Methods: Key electronic databases were searched (i.e. ASSIA, CINAHL, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, Database of Abstracts of Reviews of Effects, Embase, Medline, PsycINFO, Sociological Abstracts) for relevant studies and this was complemented by hand searching. Inclusion/exclusion criteria were applied and data was extracted from the included studies. Heterogeneity in study design and the outcomes assessed precluded meta-analysis/meta-synthesis; the results are therefore presented in narrative form.<p></p> Results: Thirty-four papers satisfied the review inclusion criteria; most were cross-sectional surveys. The majority of the studies were conducted in North America (n=25), with three being conducted in the UK. Sample sizes ranged from 61 to 98,340. The synthesised evidence demonstrates that social capital is an important construct for understanding the establishment of health risk behaviours in young people. The different elements of family and community social capital varied in terms of their saliency within each behavioural domain, with positive parent–child relations, parental monitoring, religiosity and school quality being particularly important in reducing risk.<p></p> Conclusions: This review is the first to systematically synthesise research findings about the association between social capital and health risk behaviours in young people. While providing evidence that may inform the development of interventions framed around social capital, the review also highlights key areas where further research is required to provide a fuller account of the nature and role of social capital in influencing the uptake of health risk behaviours.<p></p&gt

How did the latest increase in fees in England affect student enrolment and inequality?

This paper presents a first analysis of the increase of undergraduate tuition fees to £9,000 (€11.000) in English higher education in 2012. I use a semi-experimental research design to estimate the effect of the reforms, based on student enrolment data drawn from the Higher Education Statistics Agency (HESA). Taking into account possible anticipation effects of the fee increase, I find that enrolment declined by 15 % in the treated groups as a result of the tuition fee increase. This number is almost three times higher than what previous studies have found, and may represent a serious long term cost for the English economy. The decline in enrolments is particularly pronounced for students in older age groups and students from the service class and the middle class. No effect is visible for students from the working class, indicating that the reforms did not lead to a much-feared increase in class bias in higher education enrolment. The reforms also seem not to have exacerbated ethnic inequality in higher education, as all ethnic groups were negatively affected by the reforms. These results are consistent with earlier research in the United States and the United Kingdom, although they expand our understanding of student price responsiveness in other important ways. The paper argues that younger and older students face different costs and benefits. Older students may be less certain about their benefits, and therefore be more sensitive towards price increases. The strong decrease in mature learners may require a policy response, taking into account these differing incentives

Effectiveness, safety and acceptability of ‘see and treat' with cryotherapy by nurses in a cervical screening study in India

We evaluated a ‘see and treat' procedure involving screening, colposcopy, biopsy and cryotherapy by trained nurses in one-visit in field clinics in a cervical screening study in South India for its acceptability, safety and effectiveness in curing cervical intraepithelial neoplasia (CIN). Women positive on visual inspection with acetic acid (VIA) were advised colposcopy, directed biopsies and cryotherapy if they had colposcopic impression of CIN in one visit by nurses in field clinics supervised by a doctor. Side effects and complications were assessed and cure rates were evaluated with VIA, colposcopy and biopsy if colposcopic abnormalities were suspected. Cure was defined as no clinical or histological evidence of CIN at ⩾6 months from treatment. Of the 2513 women offered ‘see and treat' procedure, 1879 (74.8%) accepted. Of the 1397 women with histologically proved CIN treated with cryotherapy, 1026 reported for follow-up evaluation. Cure rates were 81.4% (752 out of 924) for women with CIN 1; 71.4% (55 out of 77) for CIN 2 and 68.0% (17 out of 25) for CIN 3. Minor side effects and complications were documented in less than 3% of women. ‘See and treat' with cryotherapy by nurses under medical supervision is acceptable, safe and effective for cervical cancer prevention in low-resource settings

Single port/incision laparoscopic surgery compared with standard three-port laparoscopic surgery for appendicectomy : a randomised controlled trial

PMID: 23111090 [PubMed - indexed for MEDLINE] PMCID: PMC3543288 Free PMC ArticlePeer reviewedPublisher PD

Common Variants at 10 Genomic Loci Influence Hemoglobin A(1C) Levels via Glycemic and Nonglycemic Pathways

OBJECTIVE-Glycated hemoglobin (HbA(1c)), used to monitor and diagnose diabetes, is influenced by average glycemia over a 2- to 3-month period. Genetic factors affecting expression, turnover, and abnormal glycation of hemoglobin could also be associated with increased levels of HbA(1c). We aimed to identify such genetic factors and investigate the extent to which they influence diabetes classification based on HbA(1c) levels.RESEARCH DESIGN AND METHODS-We studied associations with HbA(1c) in up to 46,368 nondiabetic adults of European descent from 23 genome-wide association studies (GWAS) and 8 cohorts with de novo genotyped single nucleotide polymorphisms (SNPs). We combined studies using inverse-variance meta-analysis and tested mediation by glycemia using conditional analyses. We estimated the global effect of HbA(1c) loci using a multilocus risk score, and used net reclassification to estimate genetic effects on diabetes screening.RESULTS-Ten loci reached genome-wide significant association with HbA(1c), including six new loci near FN3K (lead SNP/P value, rs1046896/P = 1.6 x 10(-26)), HFE (rs1800562/P = 2.6 x 10(-20)), TMPRSS6 (rs855791/P = 2.7 x 10(-14)), ANK1 (rs4737009/P = 6.1 x 10(-12)), SPTA1 (rs2779116/P = 2.8 x 10(-9)) and ATP11A/TUBGCP3 (rs7998202/P = 5.2 x 10(-9)), and four known HbA(1c) loci: HK1 (rs16926246/P = 3.1 x 10(-54)), MTNR1B (rs1387153/P = 4.0 X 10(-11)), GCK (rs1799884/P = 1.5 x 10(-20)) and G6PC2/ABCB11 (rs552976/P = 8.2 x 10(-18)). We show that associations with HbA(1c) are partly a function of hyperglycemia associated with 3 of the 10 loci (GCK, G6PC2 and MTNR1B). The seven nonglycemic loci accounted for a 0.19 (%HbA(1c)) difference between the extreme 10% tails of the risk score, and would reclassify similar to 2% of a general white population screened for diabetes with HbA(1c).CONCLUSIONS-GWAS identified 10 genetic loci reproducibly associated with HbA(1c). Six are novel and seven map to loci where rarer variants cause hereditary anemias and iron storage disorders. Common variants at these loci likely influence HbA(1c) levels via erythrocyte biology, and confer a small but detectable reclassification of diabetes diagnosis by HbA(1c) Diabetes 59: 3229-3239, 201