Adaptabilidade e estabilidade fenotípica de cultivares de café arábica em Minas Gerais

O objetivo deste trabalho foi avaliar a adaptabilidade e a estabilidade fenotípicas para a produtividade de cultivares de cafeeiro do grupo Catuaí, pela metododologia de Annicchiarico. Foram instalados e conduzidos experimentos em Três Pontas, Campos Altos e Capelinha, em Minas Gerais. O delineamento foi o de blocos ao acaso, com quatro repetições e seis plantas por parcela. Os tratamentos foram constituídos por 15 cultivares do grupo Catuaí e cinco testemunhas. As avaliações da produtividade foram realizadas em seis colheitas nas safras de 2003/2004 a 2008/2009. Posteriormente, foi realizada a análise conjunta dos três locais e a avaliação da adaptabilidade e da estabilidade das cultivares. Na safra 2008/2009, foi avaliado o percentual de frutos chochos e a percentagem de grãos em peneira alta. As cultivares Catuaí Vermelho IAC 15, Catuaí Amarelo IAC 30, Catuaí Amarelo IAC 62 e Catuaí Vermelho IAC 72 são mais promissoras, pois aliam maiores estabilidade e adaptabilidade em ambientes favoráveis e desfavoráveis com alta média de produtividade. As cultivares Catuaí Vermelho IAC 100, Catuaí Amarelo IAC 86, Rubi MG 1192 e Catuaí Vermelho IAC 144 têm o mais alto percentual de peneira alta. Todas as progênies têm baixo percentual de grãos chocho

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