Marcadores moleculares como herramienta para la selección animal. Perfil de acidos grasos en carne

El perfil de ácidos grasos es de gran importancia en la industria global, y en los recientes años, se ha incrementado la atención del mercado en mejorar los aspecto

A fast and sensitive method for the continuous in situ determination of dissolved methane and its d13C-isotope ratio in surface waters

A fast and sensitive method for the continuous determination of methane (CH4) and its stable carbon isotopic values (d13C-CH4) in surface waters was developed by applying a vacuum to a gas/liquid exchange membrane and measuring the extracted gases by a portable cavity ring-down spectroscopy analyser (M-CRDS). The M-CRDS was calibrated and characterized for CH4 concentration and d13C-CH4 with synthetic water standards. The detection limit of the M-CRDS for the simultaneous determination of CH4 and d13CCH4 is 3.6 nmol L21 CH4. A measurement precision of CH4 concentrations and d13C-CH4 in the range of 1.1%, respectively, 1.7& (1r) and accuracy (1.3%, respectively, 0.8& [1r]) was achieved for single measurements and averaging times of 10 min. The response time s of 5765 s allow determination of d13C-CH4 values more than twice as fast than other methods. The demonstrated M-CRDS method was applied and tested for Lake Stechlin (Germany) and compared with the headspace-gas chromatography and fast membrane CH4 concentration methods. Maximum CH4 concentrations (577 nmol L21) and lightest d13C-CH4 (235.2&) were found around the thermocline in depth profile measurements. The M-CRDS-method was in good agreement with other methods. Temporal variations in CH4 concentration and d13C-CH4 obtained in 24 h measurements indicate either local methane production/oxidation or physical variations in the thermocline. Therefore, these results illustrate the need of fast and sensitive analyses to achieve a better understanding of different mechanisms and pathways of CH4 formation in aquatic environments

Anaerobic oxidation of methane and associated microbiome in anoxic water of Northwestern Siberian lakes

Arctic lakes emit methane (CH4) to the atmosphere. The magnitude of this flux could increase with permafrost thaw but might also be mitigated by microbial CH4 oxidation. Methane oxidation in oxic water has been extensively studied, while the contribution of anaerobic oxidation of methane (AOM) to CH4 mitigation is not fully understood. We have investigated four Northern Siberian stratified lakes in an area of discontinuous permafrost nearby Igarka, Russia. Analyses of CH4 concentrations in the water column demonstrated that 60 to 100% of upward diffusing CH4 was oxidized in the anoxic layers of the four lakes. A combination of pmoA and mcrA gene qPCR and 16S rRNA gene metabarcoding showed that the same taxa, all within Methylomonadaceae and including the predominant genus Methylobacter as well as Crenothrix, could be the major methane-oxidizing bacteria (MOB) in the anoxic water of the four lakes. Correlation between Methylomonadaceae and OTUs within Methylotenera, Geothrix and Geobacter genera indicated that AOM might occur in an interaction between MOB, denitrifiers and iron-cycling partners. We conclude that MOB within Methylomonadaceae could have a crucial impact on CH4 cycling in these Siberian Arctic lakes by mitigating the majority of produced CH4 before it leaves the anoxic zone. This finding emphasizes the importance of AOM by Methylomonadaceae and extends our knowledge about CH4 cycle in lakes, a crucial component of the global CH4 cycle

Thermokarst-lake methanogenesis along a complete talik (thaw bulb) profile

Thermokarst (thaw) lakes emit methane (CH4) to the atmosphere, with the carbon (C) originating from terrestrial sources such as the Holocene soils of the lakes’ watersheds, thaw of Holocene- and Pleistoceneaged permafrost soil beneath and surrounding the lakes, and decomposition of contemporary organic matter (OM) in the lakes. However, the relative magnitude of CH4 production in surface lake sediments versus deeper thawed permafrost horizons is not well understood. We assessed anaerobic CH4 production potentials from 22 depths along a 590 cm long lake sediment core from the center of an interior Alaska thermokarst lake, Vault Lake, that captured the entire package of surface lake sediments, the talik (thaw bulb), and the top 40 cm of thawing permafrost beneath the talik. We also studied the adjacent Vault Creek permafrost tunnel that extends through icerich yedoma permafrost soils surrounding the lake and into underlying fluvial gravel. Our results show, in the center of a first generation thermokarst-lake, whole-column CH4 production is dominated by methanogenesis in the organic-rich surface lake sediments [151 cm thick; mean ± SD 5.95 ± 1.67 μg C-CH4 per g dry weight sediment per day (g dw−1 d−1); 125.9 ± 36.2 μg C-CH4 per g organic carbon per day (g Corg−1 d−1)]. The organic-rich surface sediments contribute the most (67%) to whole-column CH4 production despite occupying a lesser fraction (26%) of sediment column thickness. High CH4 production potentials were also observed in recently-thawed permafrost (1.18 ± 0.61 μg C-CH4 g dw−1 d−1; 59.60 ± 51.5 μg CCH4 g Corg−1 d−1) at the bottom of the talik, but the narrow thicknesses (43 cm) of this horizon limited its overall contribution to total sediment column CH4 production in the core. Lower rates of CH4 production were observed in sediment horizons representing permafrost that has been thawed in the talik for longer periods of time. The thickest sequence in the Vault Lake core, which consisted of combined Lacustrine silt and Taberite facies (60% of total core thickness), had low CH4 production potentials, contributing only 21% of whole sediment column CH4 production potential. No CH4 production was observed in samples obtained from the permafrost tunnel, whose sediments represent a non-lake environment. Our findings imply that CH4 production is highly variable in thermokarstlake systems and that both modern OM supplied to surface sediments and ancient OM supplied to both surface and deep lake sediments by in situ thaw, as well as shore erosion of yedoma permafrost, are important to lake CH4 production. Knowing where CH4 originates and what proportion of produced CH4 is emitted will aid in estimations of how C release and processing in a thermokarst-lake environment differs from other thawing permafrost and non-permafrost environments. References: Heslop, J.K.; Walter Anthony, K.M.; Sepulveda-Jauregui, A.; Martinez-Cruz, K.; Bondurant, A.; Grosse, G. and Jones, M.C. [2015]: Thermokarst lake methanogenesis along a complete talik profile. Biogeosciences, 12:4317–4331, doi:10.5194/bg-12-4317-2015

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Determinants of intensive insulin therapeutic regimens in patients with type 1 diabetes: data from a nationwide multicenter survey in Brazil

Background: To evaluate the determinants of intensive insulin regimens (ITs) in patients with type 1 diabetes (T1D).Methods: This multicenter study was conducted between December 2008 and December 2010 in 28 public clinics in 20 Brazilian cities. Data were obtained from 3,591 patients (56.0% female, 57.1% Caucasian). Insulin regimens were classified as follows: group 1, conventional therapy (CT) (intermediate human insulin, one to two injections daily); group 2 (three or more insulin injections of intermediate plus regular human insulin); group 3 (three or more insulin injections of intermediate human insulin plus short-acting insulin analogues); group 4, basal-bolus (one or two insulin injections of long-acting plus short-acting insulin analogues or regular insulin); and group 5, basal-bolus with continuous subcutaneous insulin infusion (CSII). Groups 2 to 5 were considered IT groups.Results: We obtained complete data from 2,961 patients. Combined intermediate plus regular human insulin was the most used therapeutic regimen. CSII was used by 37 (1.2%) patients and IT by 2,669 (90.2%) patients. More patients on IT performed self-monitoring of blood glucose and were treated at the tertiary care level compared to CT patients (p < 0.001). the majority of patients from all groups had HbA1c levels above the target. Overweight or obesity was not associated with insulin regimen. Logistic regression analysis showed that economic status, age, ethnicity, and level of care were associated with IT (p < 0.001).Conclusions: Given the prevalence of intensive treatment for T1D in Brazil, more effective therapeutic strategies are needed for long term-health benefits.Farmanguinhos/Fundacao Oswaldo Cruz/National Health MinistryBrazilian Diabetes SocietyFundacao do Amparo a Pesquisa do Estado do Rio de JaneiroConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Univ Estado Rio de Janeiro, Unit Diabet, BR-20551030 Rio de Janeiro, BrazilBaurus Diabet Assoc, São Paulo, BrazilFed Univ São Paulo State, Diabet Unit, São Paulo, BrazilFed Univ Hosp Porto Alegre, Porto Alegre, BrazilUniv Hosp São Paulo, Diabet Unit, São Paulo, BrazilUniv Fed Rio de Janeiro, Rio de Janeiro, BrazilUniv Fed Ceara, Fortaleza, Ceara, BrazilSanta Casa Misericordia, Belo Horizonte, MG, BrazilSanta Casa Misericordia São Paulo, São Paulo, BrazilUniv Fed Amazonas, Manaus, Amazonas, BrazilHosp Geral de Bonsucesso, Rio de Janeiro, BrazilHosp Univ Clementino Fraga Filho IPPMG, Rio de Janeiro, BrazilUniv Hosp São Paulo, São Paulo, BrazilFac Ciencias Med Santa Casa São Paulo, São Paulo, BrazilUniv São Paulo, Inst Crianca, Hosp Clin, São Paulo, BrazilUniv São Paulo, Fac Med Ribeirao Preto, Hosp Clin, Ribeirao Preto, BrazilAmbulatorio Fac Estadual Med Sao Jose Rio Preto, Ribeirao Preto, BrazilEscola Paulista Med, Ctr Diabet, Ribeirao Preto, BrazilClin Endocrinol Santa Casa Belo Horizonte, Belo Horizonte, MG, BrazilUniv Estadual Londrina, Londrina, BrazilUniv Fed Parana, Hosp Clin, Porto Alegre, RS, BrazilInst Crianca Com Diabet Rio Grande Sul, Rio Grande Do Sul, RS, BrazilGrp Hosp Conceicao, Inst Crianca Com Diabet, Porto Alegre, RS, BrazilHosp Univ Santa Catarina, Florianopolis, SC, BrazilInst Diabet Endocrinol Joinville, Joinville, BrazilHosp Reg Taguatinga, Brasilia, DF, BrazilHosp Geral Goiania, Goiania, Go, BrazilCtr Diabet & Endocrinol Estado Bahia, Goiania, Go, BrazilUniv Fed Maranhao, Sao Luis, BrazilCtr Integrado Diabet & Hipertensao Ceara, Fortaleza, Ceara, BrazilUniv Fed Sergipe, Aracaju, BrazilHosp Univ Alcides Carneiro, Campina Grande, BrazilHosp Univ Joao de Barros Barreto, Belem, Para, BrazilFed Univ São Paulo State, Diabet Unit, São Paulo, BrazilUniv Hosp São Paulo, Diabet Unit, São Paulo, BrazilUniv Hosp São Paulo, São Paulo, BrazilEscola Paulista Med, Ctr Diabet, Ribeirao Preto, BrazilWeb of Scienc