31 research outputs found

    Pan-cancer analysis of whole genomes

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    Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe

    Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

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    Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (proportion of patients who did not have appendicitis correctly classified as low risk) whilst maintaining a failure rate below 5 per cent (proportion of patients identified as low risk who actually had appendicitis). Results Some 5345 patients across 154 UK hospitals were identified, of which two‐thirds (3613 of 5345, 67·6 per cent) were women. Women were more than twice as likely to undergo surgery with removal of a histologically normal appendix (272 of 964, 28·2 per cent) than men (120 of 993, 12·1 per cent) (relative risk 2·33, 95 per cent c.i. 1·92 to 2·84; P < 0·001). Of 15 validated risk prediction models, the Adult Appendicitis Score performed best (cut‐off score 8 or less, specificity 63·1 per cent, failure rate 3·7 per cent). The Appendicitis Inflammatory Response Score performed best for men (cut‐off score 2 or less, specificity 24·7 per cent, failure rate 2·4 per cent). Conclusion Women in the UK had a disproportionate risk of admission without surgical intervention and had high rates of normal appendicectomy. Risk prediction models to support shared decision‐making by identifying adults in the UK at low risk of appendicitis were identified

    Possibilities and Challenges of Scanning Hard X-ray Spectro-microscopy Techniques in Material Sciences

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    Understanding potato with the help of genomics

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    Sensitization to cell death induced by soluble Fas ligand and agonistic antibodies with exogenous agents: A review

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    Mechanical behaviors and biomedical applications of shape memory materials: A review

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    Steroid hormones as interkingdom signaling molecules: Innate immune function and microbial colonization modulation

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    Surface modification of materials to encourage beneficial biofilm formation

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    Biofilms are communities of sessile microorganisms that grow and produce extrapolymeric substances on an abiotic or biotic surface. Although biofilms are often associated with negative impacts, the role of beneficial biofilms is wide and include applications in bioremediation, wastewater treatment and microbial fuel cells. Microbial adhesion to a surface, which is highly dependent on the physicochemical properties of the cells and surfaces, is an essential step in biofilm formation. Surface modification therefore represents an important way to modulate microbial attachment and ultimately biofilm formation by microorganisms. In this review different surface modification processes such as organosilane surface modification, plasma treatment, and chemical modification of carbon nanotubes, electro-oxidation and covalent-immobilization with neutral red and methylene blue molecules are outlined. The effectiveness of these modifications and their industrial applications are also discussed. There is inadequate literature on surface modification as a process to enhance beneficial biofilm formation. These methods need to be safe, economically viable, scalable and environmental friendly and their potential to fulfil these criteria for many applications has yet to be determined

    The Contribution of Cell Surface Components to the Neutrophil Mechanosensitivity to Shear Stresses

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    Recent Advances in Biophysical stimulation of MSC for bone regeneration

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