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

Atypical and anaplastic meningiomas in a public hospital in São Paulo State, Brazil

Atypical/anaplastic (World Health Organization (WHO) grades II and III) are less common and have poorer outcomes than benign meningiomas. This study aimed to analyze the outcome of patients with these tumors.Method Overall/recurrence-free survivals (RFS) and the Karnofsky Performance Scale of 52 patients with grades II (42) and III (9) meningiomas surgically treated were analyzed (uni/multivariate analysis).Results Total/subtotal resections were 60.8%/35.3%. Patients 60 years-old, de novo meningioma and radiotherapy had longer survival and patients <60 years-old and with grade II tumors had longer RFS (multivariate analysis). Recurrence rate was 51% (39.2% Grade II and 66.7% Grade III). Operative mortality was 1.9%.Conclusion Age <60 years-old, grade II tumors and de novomeningiomas were the main predictors for better prognosis among patients with grades II and III meningiomas

Foramen magnum meningiomas: surgical treatment in a single public institution in a developing country

Objective: To analyze the clinical outcome of patients with foramen magnum (FM) meningiomas. Method: Thirteen patients (11 Feminine / 2 Masculine with FM meningiomas operated on through lateral suboccipital approach were studied. Clinical outcome were analyzed using survival (SC) and recurrence-free survival curves (RFSC). Results: All tumors were World Health Organization grade I. Total, subtotal and partial resections were acchieved in 69.2%, 23.1% and 7.7%, respectively, and SC was better for males and RFSC for females. Tumor location, extent of resection and involvement of vertebral artery/lower cranial nerves did not influence SC and RFSC. Recurrence rate was 7.7%. Operative mortality was 0. Main complications were transient (38.5%) and permanent (7.7%) lower cranial nerve deficits, cerebrospinal fluid fistula (30.8%), and transient and permanent respiratory difficulties in 7.7% each. Conclusions: FM meningiomas can be adequately treated in public hospitals in developing countries if a multidisciplinary team is available for managing postoperative lower cranial nerve deficits

V diretriz da Sociedade Brasileira de Cardiologia sobre tratamento do infarto agudo do miocárdio com supradesnível do segmento ST

Resumo não disponíve

V diretriz da Sociedade Brasileira de Cardiologia sobre tratamento do infarto agudo do miocárdio com supradesnível do segmento ST

Resumo não disponíve

Genomic epidemiology reveals how restriction measures shaped the SARS-CoV-2 epidemic in Brazil

Abstract Brazil has experienced some of the highest numbers of COVID-19 infections and deaths globally and made Latin America a pandemic epicenter from May 2021. Although SARS-CoV-2 established sustained transmission in Brazil early in the pandemic, important gaps remain in our understanding of local virus transmission dynamics. Here, we describe the genomic epidemiology of SARS-CoV-2 using near-full genomes sampled from 27 Brazilian states and an adjacent country - Paraguay. We show that the early stage of the pandemic in Brazil was characterised by the co-circulation of multiple viral lineages, linked to multiple importations predominantly from Europe, and subsequently characterized by large local transmission clusters. As the epidemic progressed, the absence of effective restriction measures led to the local emergence and international spread of Variants of Concern (VOC) and under monitoring (VUM), including the Gamma (P.1) and Zeta (P.2) variants. In addition, we provide a preliminary genomic overview of the epidemic in Paraguay, showing evidence of importation from Brazil. These data reinforce the need for the implementation of widespread genomic surveillance in South America as a toolkit for pandemic monitoring and providing a means to follow the real-time spread of emerging SARS-CoV-2 variants with possible implications for public health and immunization strategies

AMAZONIA CAMTRAP: A data set of mammal, bird, and reptile species recorded with camera traps in the Amazon forest

The Amazon forest has the highest biodiversity on Earth. However, information on Amazonian vertebrate diversity is still deficient and scattered across the published, peer-reviewed, and gray literature and in unpublished raw data. Camera traps are an effective non-invasive method of surveying vertebrates, applicable to different scales of time and space. In this study, we organized and standardized camera trap records from different Amazon regions to compile the most extensive data set of inventories of mammal, bird, and reptile species ever assembled for the area. The complete data set comprises 154,123 records of 317 species (185 birds, 119 mammals, and 13 reptiles) gathered from surveys from the Amazonian portion of eight countries (Brazil, Bolivia, Colombia, Ecuador, French Guiana, Peru, Suriname, and Venezuela). The most frequently recorded species per taxa were: mammals: Cuniculus paca (11,907 records); birds: Pauxi tuberosa (3713 records); and reptiles: Tupinambis teguixin (716 records). The information detailed in this data paper opens up opportunities for new ecological studies at different spatial and temporal scales, allowing for a more accurate evaluation of the effects of habitat loss, fragmentation, climate change, and other human-mediated defaunation processes in one of the most important and threatened tropical environments in the world. The data set is not copyright restricted; please cite this data paper when using its data in publications and we also request that researchers and educators inform us of how they are using these data