Avaliação de quatro genótipos de sorgo pela técnica "in vitro" semi-automática de produção de gases.

Neste ensaio, foram estudadas a cinética de fermentação e a degradabilidade in vitro de quatro genótipos de sorgo (ATF53*9929036, ATF54*9929036, CMSXS217*9929012 e Volumax), através da técnica in vitro semi-automatica de produção de gases. Os tempos de incubação utilizados para a produção de gases foram: 2, 4, 6, 8, 10, 12, 15, 18, 21, 24, 30, 36, 48, 60, 72 e 96. Para a degradabilidade in vitro, utilizaram-se os tempos 6, 12, 24, 48, 72 e 96. O coeficiente de determinação obtido entre a produção acumulativa de gases e degradabilidade da materia seca foi de r2 = 0,99, demonstrando que os gases oriundos da fermentação representam a fermentabilidade dos substratos. O genótipo Volumax apresentou numericamente a maior taxa de fermentação (µ) (0,043 (mL/g de MS/h), com a menor ?lag phase? (L) (1 h e 16 min). Os demais genótipos apresentaram valores de µ entre 0,038 e 0,034 mL/g de MS/h e de L entre 1 h e 50 min e 1 h e 72 min. Os resultados deste experimento indicam o genótipo Volumax como o mais promissor para a produção de silagem

Qualidade e perfil de fermentação das silagens de três cultivares de milheto.

Objetivando avaliar a qualidade e o perfil de fermentacao da silagem de milheto, foram estudados tres genotipos (CMS01, CMS02 e BN02). Os silos foram abertos com 01, 03, 05, 07, 14, 28 e 56 dias. Os teores de MS variaram de 22,64 a 24,49, a silagem foi considerada de mediana qualidade. Os teores de PB variaram de 9,59% a 11,32% nao observou-se queda acentuada durante a ensilagem. As porcentagens de N-NH3/Ntotal variaram de 3,32% a 9,01%, classificando a silagem como bem preservada. Observou-se variacao de pH de 3,56 a 5,13, estabilizando a partir do dia 14

Whole-genome analysis uncovers loss of blaZ associated with carriage isolates belonging to methicillin-resistant Staphylococcus aureus (MRSA) clone ST5-VI in Cape Verde

Objectives: Surveillance studies for Staphylococcus aureus carriage are a primary tool to survey the prevalence of methicillin-resistant S. aureus (MRSA) in the general population, patients and healthcare workers. We have previously reported S. aureus carriage in various African countries, including Cape Verde. Methods: Whole-genome sequences of 106 S. aureus isolates from Cape Verde were determined. Results: Staphylococcus aureus carriage isolates in Cape Verde show high genetic variability, with the detection of 27 sequence types (STs) and three primary genetic clusters associated with ST152, ST15 and ST5. One transmission event with less than eight core-genome single nucleotide polymorphisms (cgSNP) differences was detected among the ST5-VI MRSA lineage. Genetic analysis confirmed the phenotypic resistance and allowed the identification of six independent events of plasmid or transposon loss associated with the deletion of blaZ in nine isolates. In the four ST5 MRSA isolates, loss of the blaZ plasmid coincided with the acquisition of SCCmec type VI and an unusual penicillin phenotype with a minimum inhibitory concentration (MIC) at the breakpoint, indicating an adaptation trend in this endemic lineage. Similar events of blaZ plasmid loss, with concomitant acquisition SCCmec elements, were detected among ST5 isolates from different geographical origins. Conclusion: Overall, the genome data allowed to place isolates in a phylogenetic context and to identify different blaZ gene deletions associated with plasmid or transposon loss. Genomic analysis unveiled adaptation and evolution trends, namely among emerging MRSA lineages in the country, which deserve additional consideration in the design of future infection control protocols

Machine Learning Framework to Identify Individuals at Risk of Rapid Progression of Coronary Atherosclerosis : From the PARADIGM Registry

Background Rapid coronary plaque progression (RPP) is associated with incident cardiovascular events. To date, no method exists for the identification of individuals at risk of RPP at a single point in time. This study integrated coronary computed tomography angiography-determined qualitative and quantitative plaque features within a machine learning (ML) framework to determine its performance for predicting RPP. Methods and Results Qualitative and quantitative coronary computed tomography angiography plaque characterization was performed in 1083 patients who underwent serial coronary computed tomography angiography from the PARADIGM (Progression of Atherosclerotic Plaque Determined by Computed Tomographic Angiography Imaging) registry. RPP was defined as an annual progression of percentage atheroma volume 651.0%. We employed the following ML models: model 1, clinical variables; model 2, model 1 plus qualitative plaque features; model 3, model 2 plus quantitative plaque features. ML models were compared with the atherosclerotic cardiovascular disease risk score, Duke coronary artery disease score, and a logistic regression statistical model. 224 patients (21%) were identified as RPP. Feature selection in ML identifies that quantitative computed tomography variables were higher-ranking features, followed by qualitative computed tomography variables and clinical/laboratory variables. ML model 3 exhibited the highest discriminatory performance to identify individuals who would experience RPP when compared with atherosclerotic cardiovascular disease risk score, the other ML models, and the statistical model (area under the receiver operating characteristic curve in ML model 3, 0.83 [95% CI 0.78-0.89], versus atherosclerotic cardiovascular disease risk score, 0.60 [0.52-0.67]; Duke coronary artery disease score, 0.74 [0.68-0.79]; ML model 1, 0.62 [0.55-0.69]; ML model 2, 0.73 [0.67-0.80]; all P<0.001; statistical model, 0.81 [0.75-0.87], P=0.128). Conclusions Based on a ML framework, quantitative atherosclerosis characterization has been shown to be the most important feature when compared with clinical, laboratory, and qualitative measures in identifying patients at risk of RPP

Measurement of the cross-section and charge asymmetry of WW bosons produced in proton-proton collisions at s=8\sqrt{s}=8 TeV with the ATLAS detector

This paper presents measurements of the $W^+ \rightarrow \mu^+\nu$ and $W^- \rightarrow \mu^-\nu$ cross-sections and the associated charge asymmetry as a function of the absolute pseudorapidity of the decay muon. The data were collected in proton--proton collisions at a centre-of-mass energy of 8 TeV with the ATLAS experiment at the LHC and correspond to a total integrated luminosity of 20.2~\mbox{fb^{-1}}. The precision of the cross-section measurements varies between 0.8% to 1.5% as a function of the pseudorapidity, excluding the 1.9% uncertainty on the integrated luminosity. The charge asymmetry is measured with an uncertainty between 0.002 and 0.003. The results are compared with predictions based on next-to-next-to-leading-order calculations with various parton distribution functions and have the sensitivity to discriminate between them.Comment: 38 pages in total, author list starting page 22, 5 figures, 4 tables, submitted to EPJC. All figures including auxiliary figures are available at https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/STDM-2017-13