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

Design and baseline characteristics of the finerenone in reducing cardiovascular mortality and morbidity in diabetic kidney disease trial

Background: Among people with diabetes, those with kidney disease have exceptionally high rates of cardiovascular (CV) morbidity and mortality and progression of their underlying kidney disease. Finerenone is a novel, nonsteroidal, selective mineralocorticoid receptor antagonist that has shown to reduce albuminuria in type 2 diabetes (T2D) patients with chronic kidney disease (CKD) while revealing only a low risk of hyperkalemia. However, the effect of finerenone on CV and renal outcomes has not yet been investigated in long-term trials. Patients and Methods: The Finerenone in Reducing CV Mortality and Morbidity in Diabetic Kidney Disease (FIGARO-DKD) trial aims to assess the efficacy and safety of finerenone compared to placebo at reducing clinically important CV and renal outcomes in T2D patients with CKD. FIGARO-DKD is a randomized, double-blind, placebo-controlled, parallel-group, event-driven trial running in 47 countries with an expected duration of approximately 6 years. FIGARO-DKD randomized 7,437 patients with an estimated glomerular filtration rate >= 25 mL/min/1.73 m(2) and albuminuria (urinary albumin-to-creatinine ratio >= 30 to <= 5,000 mg/g). The study has at least 90% power to detect a 20% reduction in the risk of the primary outcome (overall two-sided significance level alpha = 0.05), the composite of time to first occurrence of CV death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for heart failure. Conclusions: FIGARO-DKD will determine whether an optimally treated cohort of T2D patients with CKD at high risk of CV and renal events will experience cardiorenal benefits with the addition of finerenone to their treatment regimen. Trial Registration: EudraCT number: 2015-000950-39; ClinicalTrials.gov identifier: NCT02545049

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 understanding 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,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 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 underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities 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 organism 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 neglected 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 lost

Consultoria em patologia cirúrgica mamária: variabilidade interobservador no diagnóstico de lesões proliferativas intraductais atípicas Consultation in breast surgical pathology: interobserver diagnostic variability of atypical intraductal proliferative lesions

OBJETIVO: Avaliar a concordância nos diagnósticos histopatológicos de lesões mamárias proliferativas intraductais entre patologistas gerais e especialistas em patologia mamária. MÉTODOS: Trata-se de estudo observacional e transversal, com análise de 209 lesões encaminhadas ao Laboratório de Patologia Mamária da Faculdade de Medicina da Universidade Federal de Minas Gerais para consultoria, no período de 2007 a 2011, comparando os diagnósticos originais com os após a revisão. Foram incluídos apenas os casos com solicitação formal de revisão e que apresentavam diagnóstico histopatológico no laudo original ou de revisão de lesões proliferativas, carcinoma ductal in situ puro, carcinoma ductal in situ com microinvasão ou associado a carcinoma invasor. A concordância percentual e o índice kappa foram utilizados para a análise estatística. RESULTADOS: Observamos moderada concordância nos diagnósticos originais de benignidade ou malignidade versus os diagnósticos de revisão (kappa=0,5; concordância percentual=83%). Após a revisão, o diagnóstico de malignidade foi confirmado em 140/163 casos (86%) e o diagnóstico de benignidade foi confirmado em 34/46 casos (74%). Quanto aos diagnósticos específicos, observamos concordância moderada entre o laudo original e de revisão (136/209 casos; kappa=0,5; concordância percentual=65%). A maior discordância foi observada nos casos de carcinoma ductal in situ com microinvasão (6/6 casos; 100%). Grande discordância foi observada nos casos de hiperplasia ductal atípica (16/30 casos; 53%) e carcinoma ductal in situ (25/75 casos; 33%). Em relação ao grau histológico do carcinoma ductal in situ, observou-se boa concordância entre os laudos originais e de revisão (29/39 casos; kappa=0,6; concordância percentual=74%). CONCLUSÃO: Nossos dados confirmam que as lesões mamárias proliferativas intraductais, em especial as hiperplasias ductais atípicas, o carcinoma ductal in situ e o carcinoma ductal in situ com microinvasão apresentam relevantes discordâncias nos diagnósticos histopatológicos, que podem induzir o clínico a erros nas decisões terapêuticas.<br>PURPOSE: To evaluate the agreement about the histopathological diagnosis of intraductal proliferative breast lesions between general pathologists and a specialist in breast pathology. METHODS: This was an observational, cross-sectional study of 209 lesions received in consultation at the Breast Pathology Laboratory of the School of Medicine, Federal University of Minas Gerais, from 2007 to 2011, comparing the original diagnosis and the review. We included only cases with a formal request for review and cases in which the original diagnosis or reviewer's diagnosis showed proliferative lesions, pure ductal carcinoma in situ, ductal carcinoma in situ associated with microinvasion or associated with invasive carcinoma. The kappa index and percent concordance were used in the statistical analyses. RESULTS: A moderate agreement was observed between the original histopathological diagnosis and the second opinion (kappa=0.5; percentual concordance=83%). After the review, the diagnosis of malignancy was confirmed in 140/163 cases (86%) and the diagnosis of benign lesions was confirmed in 34/46 cases (74%). Regarding specific diagnosis, we observed moderate agreement between the original diagnosis and the reviewer's diagnosis (136/209 cases; kappa=0.5; percent concordance=65%). The highest disagreement was observed in cases of ductal carcinoma in situ with microinvasion (6/6 cases; 100%). Important discordance was observed in cases of atypical ductal hyperplasia (16/30 cases; 53%) and ductal carcinoma in situ (25/75 cases; 33%). Regarding the histological grade of ductal carcinoma in situ, we observed good agreement between the original diagnosis and the review (29/39 cases; kappa=0.6, percent agreement=74%). CONCLUSION: Our data confirm that intraductal proliferative breast lesions, especially atypical ductal hyperplasia, ductal carcinoma in situ and ductal carcinoma in situ with microinvasion show relevant discrepancies in the histopathological diagnoses, which may induce errors in therapeutic decisions