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

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

Surgical revascularization of posterior coronary arteries without cardiopulomonary bypass

OBJECTIVE: To assess the results observed during the early postoperative period in patients who had the posterior coronary arteries revascularized without cardiopulmonary bypass (CPB), in regard to the following parameters: age, sex,bypass grafts types, morbidity and mortality. METHODS: From January 1995 to June 1998, 673 patients underwent myocardial revascularization (MR). Of this total, 607 (90.20%) MR procedures were performed without CPB. The posterior coronary arteries (PCA) were revascularized in 298 (44.27%) patients, 280 (93.95%) without CPB. The age of the patients ranged from 37 to 88 years (mean, 61 years). The male gender predominated, with 198 men (70.7%). The revascularization of the posterior coronary arteries had the following distribution: diagonalis artery (31 patients, 10%); marginal branches of the circumflex artery (243 patients, 78.7%); posterior ventricular artery (4 patients, 1.3%); and posterior descending artery (31 patients, 10%). RESULTS: Procedure-related complications without death occurred in 7 cases, giving a morbidity of 2.5%. There were 11 deaths in the early postoperative period (mortality of 3.9%). CONCLUSION: Similarly to the anterior coronary arteries, the posterior coronary arteries may benefit from myocardial revascularization without CPB

Cancer inpatients with COVID-19: A report from the Brazilian National Cancer Institute.

ObjectiveThis study aimed to describe the demographic and clinical characteristics of cancer inpatients with COVID-19 exploring clinical outcomes.MethodsA retrospective search in the electronic medical records of cancer inpatients admitted to the Brazilian National Cancer Institute from April 30, 2020 to May 26, 2020 granted identification of 181 patients with COVID-19 confirmed by RT-PCR.ResultsThe mean age was 55.3 years (SD ± 21.1). Comorbidities were present in 110 (60.8%) cases. The most prevalent solid tumors were breast (40 [22.1%]), gastrointestinal (24 [13.3%]), and gynecological (22 [12.2%]). Among hematological malignancies, lymphoma (20 [11%]) and leukemia (10 [5.5%]) predominated. Metastatic disease accounted for 90 (49.7%) cases. In total, 63 (34.8%) had recently received cytotoxic chemotherapy. The most common complications were respiratory failure (70 [38.7%]), septic shock (40 [22.1%]) and acute kidney injury (33 [18.2%]). A total of 60 (33.1%) patients died due to COVID-19 complications. For solid tumors, the COVID-19-specific mortality rate was 37.7% (52 out of 138 patients) and for hematological malignancies, 23.5% (8 out of 34). According to the univariate analysis COVID-19-specific mortality was significantly associated with age over 75 years (P = .002), metastatic cancer (p ConclusionThis is the first Brazilian cohort of cancer patients with COVID-19. The rates of complications and COVID-19-specific death were significantly high