El enfoque basado en derechos humanos : evaluación e indicadores

Colabora en la publicación la AECIDBibliografía: p. 69-7

Identification of genes expressed by immune cells of the colon that are regulated by colorectal cancer-associated variants.

A locus on human chromosome 11q23 tagged by marker rs3802842 was associated with colorectal cancer (CRC) in a genome-wide association study; this finding has been replicated in case-control studies worldwide. In order to identify biologic factors at this locus that are related to the etiopathology of CRC, we used microarray-based target selection methods, coupled to next-generation sequencing, to study 103 kb at the 11q23 locus. We genotyped 369 putative variants from 1,030 patients with CRC (cases) and 1,061 individuals without CRC (controls) from the Ontario Familial Colorectal Cancer Registry. Two previously uncharacterized genes, COLCA1 and COLCA2, were found to be co-regulated genes that are transcribed from opposite strands. Expression levels of COLCA1 and COLCA2 transcripts correlate with rs3802842 genotypes. In colon tissues, COLCA1 co-localizes with crystalloid granules of eosinophils and granular organelles of mast cells, neutrophils, macrophages, dendritic cells and differentiated myeloid-derived cell lines. COLCA2 is present in the cytoplasm of normal epithelial, immune and other cell lineages, as well as tumor cells. Tissue microarray analysis demonstrates the association of rs3802842 with lymphocyte density in the lamina propria (p = 0.014) and levels of COLCA1 in the lamina propria (p = 0.00016) and COLCA2 (tumor cells, p = 0.0041 and lamina propria, p = 6 × 10(-5)). In conclusion, genetic, expression and immunohistochemical data implicate COLCA1 and COLCA2 in the pathogenesis of colon cancer. Histologic analyses indicate the involvement of immune pathways

The Fourteenth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the extended Baryon Oscillation Spectroscopic Survey and from the second phase of the Apache Point Observatory Galactic Evolution Experiment

The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since July 2014. This paper describes the second data release from this phase, and the fourteenth from SDSS overall (making this, Data Release Fourteen or DR14). This release makes public data taken by SDSS-IV in its first two years of operation (July 2014-2016). Like all previous SDSS releases, DR14 is cumulative, including the most recent reductions and calibrations of all data taken by SDSS since the first phase began operations in 2000. New in DR14 is the first public release of data from the extended Baryon Oscillation Spectroscopic Survey (eBOSS); the first data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2), including stellar parameter estimates from an innovative data driven machine learning algorithm known as "The Cannon"; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total). This paper describes the location and format of the publicly available data from SDSS-IV surveys. We provide references to the important technical papers describing how these data have been taken (both targeting and observation details) and processed for scientific use. The SDSS website (www.sdss.org) has been updated for this release, and provides links to data downloads, as well as tutorials and examples of data use. SDSS-IV is planning to continue to collect astronomical data until 2020, and will be followed by SDSS-V.Comment: SDSS-IV collaboration alphabetical author data release paper. DR14 happened on 31st July 2017. 19 pages, 5 figures. Accepted by ApJS on 28th Nov 2017 (this is the "post-print" and "post-proofs" version; minor corrections only from v1, and most of errors found in proofs corrected

Comparative toxicoproteogenomics of mouse and rat liver identifies TCDD-resistance genes

The aryl hydrocarbon receptor (AHR) mediates many toxic effects of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). However, the AHR alone does not explain the widely different outcomes among organisms. To identify the other factors involved, we evaluated three transgenic mouse lines, each expressing a different rat AHR isoform (rWT, DEL, and INS) providing widely different resistance to TCDD toxicity, as well as C57BL/6 and DBA/2 mice which exhibit a similar to tenfold divergence in TCDD sensitivity (exposures of 5-1000 mu g/kg TCDD). We supplement these with whole-genome sequencing, together with transcriptomic and proteomic analyses of the corresponding rat models, Long-Evans (L-E) and Han/Wistar (H/W) rats (having a similar to 1000-fold difference in their TCDD sensitivities; 100 mu g/kg TCDD), to identify genes associated with TCDD-response phenotypes. Overall, we identified up to 50% of genes with altered mRNA abundance following TCDD exposure are associated with a single AHR isoform (33.8%, 11.7%, 5.2% and 0.3% of 3076 genes altered unique to rWT, DEL, C57BL/6 and INS respectively following 1000 mu g/kg TCDD). Hepatic Pxdc1 was significantly repressed in all three TCDD-sensitive animal models (C57BL/6 and rWT mice, and L-E rat) after TCDD exposure. Three genes, including Cxxc5, Sugp1 and Hgfac, demonstrated different AHRE-1 (full) motif occurrences within their promoter regions between rat strains, as well as different patterns of mRNA abundance. Several hepatic proteins showed parallel up- or downward alterations with their RNAs, with three genes (SNRK, IGTP and IMPA2) showing consistent, strain-dependent changes. These data show the value of integrating genomic, transcriptomic and proteomic evidence across multi-species models in toxicologic studies.Peer reviewe

Actigraph Accelerometer-Defined Boundaries for Sedentary Behaviour and Physical Activity Intensities in 7 Year Old Children

Background: Accurate objective assessment of sedentary and physical activity behaviours during childhood is integral to the understanding of their relation to later health outcomes, as well as to documenting the frequency and distribution of physical activity within a population.Purpose: To calibrate the Actigraph GT1M accelerometer, using energy expenditure (EE) as the criterion measure, to define thresholds for sedentary behaviour and physical activity categories suitable for use in a large scale epidemiological study in young children.Methods: Accelerometer-based assessments of physical activity (counts per minute) were calibrated against EE measures (kcal.kg(-1).hr(-1)) obtained over a range of exercise intensities using a COSMED K4b(2) portable metabolic unit in 53 seven-year-old children. Children performed seven activities: lying down viewing television, sitting upright playing a computer game, slow walking, brisk walking, jogging, hopscotch and basketball. Threshold count values were established to identify sedentary behaviour and light, moderate and vigorous physical activity using linear discriminant analysis (LDA) and evaluated using receiver operating characteristic (ROC) curve analysis.Results: EE was significantly associated with counts for all non-sedentary activities with the exception of jogging. Threshold values for accelerometer counts (counts. minute(-1)) were = 3841 for light, moderate and vigorous physical activity respectively. The area under the ROC curves for discrimination of sedentary behaviour and vigorous activity were 0.98. Boundaries for light and moderate physical activity were less well defined (0.61 and 0.60 respectively). Sensitivity and specificity were higher for sedentary (99% and 97%) and vigorous (95% and 91%) than for light (60% and 83%) and moderate (61% and 76%) thresholds.Conclusion: The accelerometer cut points established in this study can be used to classify sedentary behaviour and to distinguish between light, moderate and vigorous physical activity in children of this age

Characterization of patients in the International Severe Asthma Registry with high steroid exposure who did or did not initiate biologic therapy

Peer reviewedPostprin

Commentaries on viewpoint : physiology and fast marathons

Q2Q1N/