Calibração do modelo CROPGRO-cowpea para simulação do crescimento e rendimento de grãos de feijão-caupi com e sem deficit hídrico.

O objetivo desta pesquisa foi calibrar o modelo CROPGRO-cowpea do DSSAT para possibilitar, futuramente, o desenvolvimento de uma metodologia técnico-científica para a elaboração de zoneamento agrícola de risco climático baseada em um índice de produtividade climática para a cultura do feijão-caupi

Efeito do flunixin meglumine e da somatotropina recombinante bovina sobre a taxa de prenhez de receptoras bovinas de embriões fecundados in vitro

Avaliou-se o efeito da aplicação da somatotropina bovina (bST) e do flunixin meglumine (FM) sobre as taxas de prenhez de receptoras de embriões produzidos in vitro (PIV). Utilizou-se 110 novilhas mestiças com ciclo estral regular, peso médio de 350 kg e estado de condição corporal equivalente a 3. Os ovócitos das doadoras foram coletados por aspiração folicular transvaginal guiada por ultrassom e a produção dos embriões foi realizada pela empresa InVitro®. Imediatamente antes da transferência dos embriões, as receptoras foram avaliadas, por palpação retal, quanto à presença de corpo lúteo (CL) e em seguida foram aleatoriamente distribuídas em três grupos experimentais. Os animais do G1 (n = 30) serviram como controle. Os do G2 (n = 40) receberam 500 mg de bST por via subcutânea e os do G3 (n = 40) receberam 500 mg de FM por via intramuscular. Os embriões que se encontravam no 7o dia de cultivo foram depositados no terço final do corno uterino ipsilateral ao ovário com CL presente e em seguida realizada a administração do bST e do FM. As taxas de prenhez foram de 53,33% (G1), 60,00 (G2) e de 55,00% (G3) e as de perda embrionária foram de 6,37% (G1), 7,50% (G2) e de 7,50% (G3), não havendo diferença (P > 0,05). Os resultados permitem concluir que tanto o bST quanto o FM não contribuem para aumentar as taxas de prenhez e tampouco para reduzir a perda embrionária

A prediction rule to stratify mortality risk of patients with pulmonary tuberculosis

Tuberculosis imposes high human and economic tolls, including in Europe. This study was conducted to develop a severity assessment tool for stratifying mortality risk in pulmonary tuberculosis (PTB) patients. A derivation cohort of 681 PTB cases was retrospectively reviewed to generate a model based on multiple logistic regression analysis of prognostic variables with 6-month mortality as the outcome measure. A clinical scoring system was developed and tested against a validation cohort of 103 patients. Five risk features were selected for the prediction model: hypoxemic respiratory failure (OR 4.7, 95% CI 2.8-7.9), age >= 50 years (OR 2.9, 95% CI 1.7-4.8), bilateral lung involvement (OR 2.5, 95% CI 1.44.4), >= 1 significant comorbidity-HIV infection, diabetes mellitus, liver failure or cirrhosis, congestive heart failure and chronic respiratory disease-(OR 2.3, 95% CI 1.3-3.8), and hemoglobin = 6) mortality risk. The mortality associated with each group was 2.9%, 22.9% and 53.9%, respectively. The model performed equally well in the validation cohort. We provide a new, easy-to-use clinical scoring system to identify PTB patients with high-mortality risk in settings with good healthcare access, helping clinicians to decide which patients are in need of closer medical care during treatment.This work was supported by Fundacao Amelia de Mello/Jose de Mello Saude and Sociedade Portuguesa de Pneumologia (SPP). This work was developed under the scope of the project NORTE-01-0145-FEDER-000013, supported by the Northern Portugal Regional Operational Programme (NORTE 2020), under the Portugal 2020 Partnership Agreement, through the European Regional Development Fund (FEDER). NSO is a FCT (Fundacao para a Ciencia e Tecnologia) investigator. MS is an Associate FCT Investigator. The fundershad no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Effects of alirocumab on types of myocardial infarction: insights from the ODYSSEY OUTCOMES trial

Aims  The third Universal Definition of Myocardial Infarction (MI) Task Force classified MIs into five types: Type 1, spontaneous; Type 2, related to oxygen supply/demand imbalance; Type 3, fatal without ascertainment of cardiac biomarkers; Type 4, related to percutaneous coronary intervention; and Type 5, related to coronary artery bypass surgery. Low-density lipoprotein cholesterol (LDL-C) reduction with statins and proprotein convertase subtilisin–kexin Type 9 (PCSK9) inhibitors reduces risk of MI, but less is known about effects on types of MI. ODYSSEY OUTCOMES compared the PCSK9 inhibitor alirocumab with placebo in 18 924 patients with recent acute coronary syndrome (ACS) and elevated LDL-C (≥1.8 mmol/L) despite intensive statin therapy. In a pre-specified analysis, we assessed the effects of alirocumab on types of MI. Methods and results  Median follow-up was 2.8 years. Myocardial infarction types were prospectively adjudicated and classified. Of 1860 total MIs, 1223 (65.8%) were adjudicated as Type 1, 386 (20.8%) as Type 2, and 244 (13.1%) as Type 4. Few events were Type 3 (n = 2) or Type 5 (n = 5). Alirocumab reduced first MIs [hazard ratio (HR) 0.85, 95% confidence interval (CI) 0.77–0.95; P = 0.003], with reductions in both Type 1 (HR 0.87, 95% CI 0.77–0.99; P = 0.032) and Type 2 (0.77, 0.61–0.97; P = 0.025), but not Type 4 MI. Conclusion  After ACS, alirocumab added to intensive statin therapy favourably impacted on Type 1 and 2 MIs. The data indicate for the first time that a lipid-lowering therapy can attenuate the risk of Type 2 MI. Low-density lipoprotein cholesterol reduction below levels achievable with statins is an effective preventive strategy for both MI types.For complete list of authors see http://dx.doi.org/10.1093/eurheartj/ehz299</p

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio