93 research outputs found

    The Protection of Traditional Knowledge in Peru: A Comparative Perspective

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    This Article analyzes the policy and legal context for the protection of traditional knowledge, focusing on Peruvian Law 27811, Regime for the Protection of Indigenous Peoples’ Collective Knowledge Associated with Biodiversity (enacted on July 24, 2002) [Law 27811], as a case study

    sodC-Based Real-Time PCR for Detection of Neisseria meningitidis

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    Real-time PCR (rt-PCR) is a widely used molecular method for detection of Neisseria meningitidis (Nm). Several rt-PCR assays for Nm target the capsule transport gene, ctrA. However, over 16% of meningococcal carriage isolates lack ctrA, rendering this target gene ineffective at identification of this sub-population of meningococcal isolates. The Cu-Zn superoxide dismutase gene, sodC, is found in Nm but not in other Neisseria species. To better identify Nm, regardless of capsule genotype or expression status, a sodC-based TaqMan rt-PCR assay was developed and validated. Standard curves revealed an average lower limit of detection of 73 genomes per reaction at cycle threshold (Ct) value of 35, with 100% average reaction efficiency and an average R2 of 0.9925. 99.7% (624/626) of Nm isolates tested were sodC-positive, with a range of average Ct values from 13.0 to 29.5. The mean sodC Ct value of these Nm isolates was 17.6±2.2 (±SD). Of the 626 Nm tested, 178 were nongroupable (NG) ctrA-negative Nm isolates, and 98.9% (176/178) of these were detected by sodC rt-PCR. The assay was 100% specific, with all 244 non-Nm isolates testing negative. Of 157 clinical specimens tested, sodC detected 25/157 Nm or 4 additional specimens compared to ctrA and 24 more than culture. Among 582 carriage specimens, sodC detected Nm in 1 more than ctrA and in 4 more than culture. This sodC rt-PCR assay is a highly sensitive and specific method for detection of Nm, especially in carriage studies where many meningococcal isolates lack capsule genes

    Toward interoperable bioscience data

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    © The Author(s), 2012. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Nature Genetics 44 (2012): 121-126, doi:10.1038/ng.1054.To make full use of research data, the bioscience community needs to adopt technologies and reward mechanisms that support interoperability and promote the growth of an open 'data commoning' culture. Here we describe the prerequisites for data commoning and present an established and growing ecosystem of solutions using the shared 'Investigation-Study-Assay' framework to support that vision.The authors also acknowledge the following funding sources in particular: UK Biotechnology and Biological Sciences Research Council (BBSRC) BB/I000771/1 to S.-A.S. and A.T.; UK BBSRC BB/I025840/1 to S.-A.S.; UK BBSRC BB/I000917/1 to D.F.; EU CarcinoGENOMICS (PL037712) to J.K.; US National Institutes of Health (NIH) 1RC2CA148222-01 to W.H. and the HSCI; US MIRADA LTERS DEB-0717390 and Alfred P. Sloan Foundation (ICoMM) to L.A.-Z.; Swiss Federal Government through the Federal Office of Education and Science (FOES) to L.B. and I.X.; EU Innovative Medicines Initiative (IMI) Open PHACTS 115191 to C.T.E.; US Department of Energy (DOE) DE-AC02- 06CH11357 and Arthur P. Sloan Foundation (2011- 6-05) to J.G.; UK BBSRC SysMO-DB2 BB/I004637/1 and BBG0102181 to C.G.; UK BBSRC BB/I000933/1 to C.S. and J.L.G.; UK MRC UD99999906 to J.L.G.; US NIH R21 MH087336 (National Institute of Mental Health) and R00 GM079953 (National Institute of General Medical Science) to A.L.; NIH U54 HG006097 to J.C. and C.E.S.; Australian government through the National Collaborative Research Infrastructure Strategy (NCRIS); BIRN U24-RR025736 and BioScholar RO1-GM083871 to G.B. and the 2009 Super Science initiative to C.A.S

    Analysis of the genetic phylogeny of multifocal prostate cancer identifies multiple independent clonal expansions in neoplastic and morphologically normal prostate tissue.

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    Genome-wide DNA sequencing was used to decrypt the phylogeny of multiple samples from distinct areas of cancer and morphologically normal tissue taken from the prostates of three men. Mutations were present at high levels in morphologically normal tissue distant from the cancer, reflecting clonal expansions, and the underlying mutational processes at work in morphologically normal tissue were also at work in cancer. Our observations demonstrate the existence of ongoing abnormal mutational processes, consistent with field effects, underlying carcinogenesis. This mechanism gives rise to extensive branching evolution and cancer clone mixing, as exemplified by the coexistence of multiple cancer lineages harboring distinct ERG fusions within a single cancer nodule. Subsets of mutations were shared either by morphologically normal and malignant tissues or between different ERG lineages, indicating earlier or separate clonal cell expansions. Our observations inform on the origin of multifocal disease and have implications for prostate cancer therapy in individual cases

    The FAIR Guiding Principles for scientific data management and stewardship

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    There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A diverse set of stakeholders—representing academia, industry, funding agencies, and scholarly publishers—have come together to design and jointly endorse a concise and measureable set of principles that we refer to as the FAIR Data Principles. The intent is that these may act as a guideline for those wishing to enhance the reusability of their data holdings. Distinct from peer initiatives that focus on the human scholar, the FAIR Principles put specific emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals. This Comment is the first formal publication of the FAIR Principles, and includes the rationale behind them, and some exemplar implementations in the community

    Genetic mechanisms of critical illness in COVID-19.

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    Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 ×  10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice

    Genetic Variants Related to Longer Telomere Length are Associated with Increased Risk of Renal Cell Carcinoma.

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    BACKGROUND: Relative telomere length in peripheral blood leukocytes has been evaluated as a potential biomarker for renal cell carcinoma (RCC) risk in several studies, with conflicting findings. OBJECTIVE: We performed an analysis of genetic variants associated with leukocyte telomere length to assess the relationship between telomere length and RCC risk using Mendelian randomization, an approach unaffected by biases from temporal variability and reverse causation that might have affected earlier investigations. DESIGN, SETTING, AND PARTICIPANTS: Genotypes from nine telomere length-associated variants for 10 784 cases and 20 406 cancer-free controls from six genome-wide association studies (GWAS) of RCC were aggregated into a weighted genetic risk score (GRS) predictive of leukocyte telomere length. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Odds ratios (ORs) relating the GRS and RCC risk were computed in individual GWAS datasets and combined by meta-analysis. RESULTS AND LIMITATIONS: Longer genetically inferred telomere length was associated with an increased risk of RCC (OR=2.07 per predicted kilobase increase, 95% confidence interval [CI]:=1.70-2.53, p0.5) with GWAS-identified RCC risk variants (rs10936599 and rs9420907) from the telomere length GRS; despite this exclusion, a statistically significant association between the GRS and RCC risk persisted (OR=1.73, 95% CI=1.36-2.21, p<0.0001). Exploratory analyses for individual histologic subtypes suggested comparable associations with the telomere length GRS for clear cell (N=5573, OR=1.93, 95% CI=1.50-2.49, p<0.0001), papillary (N=573, OR=1.96, 95% CI=1.01-3.81, p=0.046), and chromophobe RCC (N=203, OR=2.37, 95% CI=0.78-7.17, p=0.13). CONCLUSIONS: Our investigation adds to the growing body of evidence indicating some aspect of longer telomere length is important for RCC risk. PATIENT SUMMARY: Telomeres are segments of DNA at chromosome ends that maintain chromosomal stability. Our study investigated the relationship between genetic variants associated with telomere length and renal cell carcinoma risk. We found evidence suggesting individuals with inherited predisposition to longer telomere length are at increased risk of developing renal cell carcinoma
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