Cigarette smoking among psychiatric patients in Brazil

The aim of this study was to estimate tobacco smoking prevalence among psychiatric patients attended in care facilities in Brazil and assess associated factors. A cross-sectional multicenter study was conducted of psychiatric patients (N = 2,475) selected from 26 care facilities. Current and ex-smokers were compared to those who had never smoked. Odds ratios were estimated using logistic regression. The current and past smoking prevalence rates were 52.7% and 18.9%, respectively. Being male, aged 40 years or over, drug and alcohol use, unprotected sex and a history of physical violence were factor associated with both current and past smoking, while a low education level (≤ 8 years of schooling), history of homelessness, not practicing a religion, current or previous psychiatric hospitalization, and main psychiatric diagnosis substance use disorders, were factors only associated with current smoking. Tobacco smoking prevalence among this population was high and was higher than the rate in the general population. Appropriate interventions and smoking prevention policies should be incorporated into mental health services

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

Diretriz sobre Diagnóstico e Tratamento da Cardiomiopatia Hipertrófica – 2024

Hypertrophic cardiomyopathy (HCM) is a form of genetically caused heart muscle disease, characterized by the thickening of the ventricular walls. Diagnosis requires detection through imaging methods (Echocardiogram or Cardiac Magnetic Resonance) showing any segment of the left ventricular wall with a thickness > 15 mm, without any other probable cause. Genetic analysis allows the identification of mutations in genes encoding different structures of the sarcomere responsible for the development of HCM in about 60% of cases, enabling screening of family members and genetic counseling, as an important part of patient and family management. Several concepts about HCM have recently been reviewed, including its prevalence of 1 in 250 individuals, hence not a rare but rather underdiagnosed disease. The vast majority of patients are asymptomatic. In symptomatic cases, obstruction of the left ventricular outflow tract (LVOT) is the primary disorder responsible for symptoms, and its presence should be investigated in all cases. In those where resting echocardiogram or Valsalva maneuver does not detect significant intraventricular gradient (> 30 mmHg), they should undergo stress echocardiography to detect LVOT obstruction. Patients with limiting symptoms and severe LVOT obstruction, refractory to beta-blockers and verapamil, should receive septal reduction therapies or use new drugs inhibiting cardiac myosin. Finally, appropriately identified patients at increased risk of sudden death may receive prophylactic measure with implantable cardioverter-defibrillator (ICD) implantation.La miocardiopatía hipertrófica (MCH) es una forma de enfermedad cardíaca de origen genético, caracterizada por el engrosamiento de las paredes ventriculares. El diagnóstico requiere la detección mediante métodos de imagen (Ecocardiograma o Resonancia Magnética Cardíaca) que muestren algún segmento de la pared ventricular izquierda con un grosor > 15 mm, sin otra causa probable. El análisis genético permite identificar mutaciones en genes que codifican diferentes estructuras del sarcómero responsables del desarrollo de la MCH en aproximadamente el 60% de los casos, lo que permite el tamizaje de familiares y el asesoramiento genético, como parte importante del manejo de pacientes y familiares. Varios conceptos sobre la MCH han sido revisados recientemente, incluida su prevalencia de 1 entre 250 individuos, por lo tanto, no es una enfermedad rara, sino subdiagnosticada. La gran mayoría de los pacientes son asintomáticos. En los casos sintomáticos, la obstrucción del tracto de salida ventricular izquierdo (TSVI) es el trastorno principal responsable de los síntomas, y su presencia debe investigarse en todos los casos. En aquellos en los que el ecocardiograma en reposo o la maniobra de Valsalva no detecta un gradiente intraventricular significativo (> 30 mmHg), deben someterse a ecocardiografía de esfuerzo para detectar la obstrucción del TSVI. Los pacientes con síntomas limitantes y obstrucción grave del TSVI, refractarios al uso de betabloqueantes y verapamilo, deben recibir terapias de reducción septal o usar nuevos medicamentos inhibidores de la miosina cardíaca. Finalmente, los pacientes adecuadamente identificados con un riesgo aumentado de muerte súbita pueden recibir medidas profilácticas con el implante de un cardioversor-desfibrilador implantable (CDI).A cardiomiopatia hipertrófica (CMH) é uma forma de doença do músculo cardíaco de causa genética, caracterizada pela hipertrofia das paredes ventriculares. O diagnóstico requer detecção por métodos de imagem (Ecocardiograma ou Ressonância Magnética Cardíaca) de qualquer segmento da parede do ventrículo esquerdo com espessura > 15 mm, sem outra causa provável. A análise genética permite identificar mutações de genes codificantes de diferentes estruturas do sarcômero responsáveis pelo desenvolvimento da CMH em cerca de 60% dos casos, permitindo o rastreio de familiares e aconselhamento genético, como parte importante do manejo dos pacientes e familiares. Vários conceitos sobre a CMH foram recentemente revistos, incluindo sua prevalência de 1 em 250 indivíduos, não sendo, portanto, uma doença rara, mas subdiagnosticada. A vasta maioria dos pacientes é assintomática. Naqueles sintomáticos, a obstrução do trato de saída do ventrículo esquerdo (OTSVE) é o principal distúrbio responsável pelos sintomas, devendo-se investigar a sua presença em todos os casos. Naqueles em que o ecocardiograma em repouso ou com Manobra de Valsalva não detecta gradiente intraventricular significativo (> 30 mmHg), devem ser submetidos à ecocardiografia com esforço físico para detecção da OTSVE.   Pacientes com sintomas limitantes e grave OTSVE, refratários ao uso de betabloqueadores e verapamil, devem receber terapias de redução septal ou uso de novas drogas inibidoras da miosina cardíaca. Por fim, os pacientes adequadamente identificados com risco aumentado de morta súbita podem receber medida profilática com implante de cardiodesfibrilador implantável (CDI)

ATLANTIC EPIPHYTES: a data set of vascular and non-vascular epiphyte plants and lichens from the Atlantic Forest

Epiphytes are hyper-diverse and one of the frequently undervalued life forms in plant surveys and biodiversity inventories. Epiphytes of the Atlantic Forest, one of the most endangered ecosystems in the world, have high endemism and radiated recently in the Pliocene. We aimed to (1) compile an extensive Atlantic Forest data set on vascular, non-vascular plants (including hemiepiphytes), and lichen epiphyte species occurrence and abundance; (2) describe the epiphyte distribution in the Atlantic Forest, in order to indicate future sampling efforts. Our work presents the first epiphyte data set with information on abundance and occurrence of epiphyte phorophyte species. All data compiled here come from three main sources provided by the authors: published sources (comprising peer-reviewed articles, books, and theses), unpublished data, and herbarium data. We compiled a data set composed of 2,095 species, from 89,270 holo/hemiepiphyte records, in the Atlantic Forest of Brazil, Argentina, Paraguay, and Uruguay, recorded from 1824 to early 2018. Most of the records were from qualitative data (occurrence only, 88%), well distributed throughout the Atlantic Forest. For quantitative records, the most common sampling method was individual trees (71%), followed by plot sampling (19%), and transect sampling (10%). Angiosperms (81%) were the most frequently registered group, and Bromeliaceae and Orchidaceae were the families with the greatest number of records (27,272 and 21,945, respectively). Ferns and Lycophytes presented fewer records than Angiosperms, and Polypodiaceae were the most recorded family, and more concentrated in the Southern and Southeastern regions. Data on non-vascular plants and lichens were scarce, with a few disjunct records concentrated in the Northeastern region of the Atlantic Forest. For all non-vascular plant records, Lejeuneaceae, a family of liverworts, was the most recorded family. We hope that our effort to organize scattered epiphyte data help advance the knowledge of epiphyte ecology, as well as our understanding of macroecological and biogeographical patterns in the Atlantic Forest. No copyright restrictions are associated with the data set. Please cite this Ecology Data Paper if the data are used in publication and teaching events. © 2019 The Authors. Ecology © 2019 The Ecological Society of Americ

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

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

Catálogo Taxonômico da Fauna do Brasil: setting the baseline knowledge on the animal diversity in Brazil

The limited temporal completeness and taxonomic accuracy of species lists, made available in a traditional manner in scientific publications, has always represented a problem. These lists are invariably limited to a few taxonomic groups and do not represent up-to-date knowledge of all species and classifications. In this context, the Brazilian megadiverse fauna is no exception, and the Catálogo Taxonômico da Fauna do Brasil (CTFB) (http://fauna.jbrj.gov.br/), made public in 2015, represents a database on biodiversity anchored on a list of valid and expertly recognized scientific names of animals in Brazil. The CTFB is updated in near real time by a team of more than 800 specialists. By January 1, 2024, the CTFB compiled 133,691 nominal species, with 125,138 that were considered valid. Most of the valid species were arthropods (82.3%, with more than 102,000 species) and chordates (7.69%, with over 11,000 species). These taxa were followed by a cluster composed of Mollusca (3,567 species), Platyhelminthes (2,292 species), Annelida (1,833 species), and Nematoda (1,447 species). All remaining groups had less than 1,000 species reported in Brazil, with Cnidaria (831 species), Porifera (628 species), Rotifera (606 species), and Bryozoa (520 species) representing those with more than 500 species. Analysis of the CTFB database can facilitate and direct efforts towards the discovery of new species in Brazil, but it is also fundamental in providing the best available list of valid nominal species to users, including those in science, health, conservation efforts, and any initiative involving animals. The importance of the CTFB is evidenced by the elevated number of citations in the scientific literature in diverse areas of biology, law, anthropology, education, forensic science, and veterinary science, among others