Caracterização molecular de espécies de Enterococci resistentes à vancomicina oito anos após seu primeiro isolamento em São Paulo, Brasil

E. faecium was the first reported VRE species, carrying the vanA gene in Brazil. In spite of this, vancomycin-resistant E. faecalis has become the predominant species in Brazilian hospitals. The aim of this study was to evaluate the genetic relatedness of VREs isolated in a Brazilian teaching hospital eight years apart from its first isolation. We analyzed 38 VRE strains obtained from 81 surveillance cultures of patients admitted to the four largest intensive care units in Hospital São Paulo in February, 2006. Presence of the vanA gene was assayed by PCR and PFGE analysis was used for molecular characterization. All VRE strains carried the vanA gene. Two distinct clonal groups were observed among vancomycin-resistant E. faecalis. Vancomycin-resistant E. faecium belonged to five distinct clones were demonstrated by molecular typing. All of these clones were different from the first vancomycin-resistant enterococci clone isolated eight years ago in our hospital.E. faecium contendo o gene vanA foi a primeira espécie de VRE descrita, no Brasil. Apesar disto, E. faecalis resistente a vancomicina tem se tornado a espécie predominante nos hospitais brasileiros.O objetivo desse estudo foi avaliar a relação genética de VREs isolados em um hospital de ensino brasileiro após oito anos de seu primeiro isolamento. Analisamos 37 isolados de VRE obtidos de 81 culturas de vigilância de pacientes admitidos nas quatro maiores Unidades de Tratamento Intensivo em Fevereiro de 2006. A presença do gene vanA foi analisada por PCR e a caracterização molecular por PFGE. Todas as amostras VRE carreavam o gene vanA. Entre os E. faecalis vancomicina-resistentes, dois distintos grupos clonais foram observados. E. faecium resistente a vancomicina pertencentes a cinco clones distintos foram demonstrados por tipagem molecular. Todos esses clones foram diferentes do primeiro clone de enterococo resistente a vancomicina isolado oito anos atrás em nosso hospital

Rapid detection of Vancomycin-Resistant Enterococci (VRE) in rectal samples from patients admitted to intensive care units

ABSTRACT: The reduction in time required to identify vancomycin-resistant enterococci (VRE) has gained increased importance during hospital outbreaks. In the present study, we implemented a laboratory protocol to speed up the VRE screening from rectal samples. The protocol combines a medium for selective VRE isolation (VREBAC®, Probac, São Paulo) and a multiplex PCR for detection and identification of vanA and vanB resistance genes. The screening performance was analyzed in 114 specimens collected from four intensive care units. The swabs were collected at two periods: (1) during a VRE outbreak (February 2006, n=83 patients) and (2) at the post-outbreak period, after adoption of infection control measures (June 2006, n=31 patients). Forty-one/83 VRE (49.4%) and 3/31(9.7%) VRE were found at the first and second period, respectively. All isolates harbored the vanA gene. In both periods, detection of the gene vanA parallels to the minimum inhibitory concentration values of >256 µg/mL and >48 µg/mL for vancomycin and teicoplanin, respectively. Multiplex PCR and conventional methods agreed in 90.2% for enterococci identification. Besides this accuracy, we also found a remarkable reduction in time to obtain results. Detection of enterococcal species and identification of vancomycin resistance genes were ready in 29.5 hours, in comparison to 72 hours needed by the conventional methods. In conclusion, our protocol identified properly and rapidly enterococci species and vancomycin-resistance genes. The results strongly encourage its adoption by microbiology laboratories for VRE screenning in rectal samples

Síndrome da Imunodeficiência adquirida em paciente psiquiátrico internado em Hospital Universitário: Acquired Immunodeficiency syndrome in a psychiatric patient admitted to a University Hospital

A Síndrome da Imunodeficiência Adquirida (SIDA/AIDS) leva a maior susceptibilidade de infecções oportunistas e a estigmatização da doença prejudica a adesão do tratamento. O paciente acometido pelo HIV tem muita suscetibilidade ao surgimento de depressões, alterações cognitivas, sinais e sintomas psiquiátricos e a terapia antirretroviral retarda o quadro de desorientação tempo espacial, assim, a psiquiatria e a neurologia estudam as consequências clínicas do HIV, patologias associadas, e suas complicações psiquiátricas. Objetivou-se avaliar a possível relação entre os transtornos psiquiátricos e o HIV em um paciente com doença psiquiátrica, em um Hospital Universitário, em Recife/Pernambuco. O presente estudo possui aprovação pelo Comitê de Ética em Pesquisa do Centro de Ciências da Saúde da Universidade Federal de Pernambuco (n° 06189212.6.0000.5208). Trata-se de um recorte do projeto sobre doenças infecciosas, realizado na enfermaria de doenças infecciosas e parasitárias, onde se realizou visitas ao paciente, consultando o prontuário e resultados de exames. Homem, 45 anos, portador de SIDA, deprimido com déficit cognitivo, recusa o tratamento, as medicações prescritas e orientações médicas, com alteração física. Faz-se necessário um diagnóstico e tratamento adequado, visando o bem-estar, retardo da evolução das doenças e aceitação de tratamento. O vírus acomete o sistema nervoso central, ocorrendo alterações psiquiátricas, sintomas são de origem psicológica ou relacionados à neuro-transmissão e fisiologia, tratados de forma adequada e separada. Dessa forma, na presença de comorbidades psiquiátricas em paciente soro positivo, o diagnóstico precoce juntamente com a terapia colaborou para retardo da evolução do quadro da infecção e déficit físico do paciente

Multi-Center Fetal Brain Tissue Annotation (FeTA) Challenge 2022 Results

Segmentation is a critical step in analyzing the developing human fetal brain. There have been vast improvements in automatic segmentation methods in the past several years, and the Fetal Brain Tissue Annotation (FeTA) Challenge 2021 helped to establish an excellent standard of fetal brain segmentation. However, FeTA 2021 was a single center study, and the generalizability of algorithms across different imaging centers remains unsolved, limiting real-world clinical applicability. The multi-center FeTA Challenge 2022 focuses on advancing the generalizability of fetal brain segmentation algorithms for magnetic resonance imaging (MRI). In FeTA 2022, the training dataset contained images and corresponding manually annotated multi-class labels from two imaging centers, and the testing data contained images from these two imaging centers as well as two additional unseen centers. The data from different centers varied in many aspects, including scanners used, imaging parameters, and fetal brain super-resolution algorithms applied. 16 teams participated in the challenge, and 17 algorithms were evaluated. Here, a detailed overview and analysis of the challenge results are provided, focusing on the generalizability of the submissions. Both in- and out of domain, the white matter and ventricles were segmented with the highest accuracy, while the most challenging structure remains the cerebral cortex due to anatomical complexity. The FeTA Challenge 2022 was able to successfully evaluate and advance generalizability of multi-class fetal brain tissue segmentation algorithms for MRI and it continues to benchmark new algorithms. The resulting new methods contribute to improving the analysis of brain development in utero.Comment: Results from FeTA Challenge 2022, held at MICCAI; Manuscript submitted. Supplementary Info (including submission methods descriptions) available here: https://zenodo.org/records/1062864

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

Worldwide trends in underweight and obesity from 1990 to 2022: a pooled analysis of 3663 population-representative studies with 222 million children, adolescents, and adults

Background Underweight and obesity are associated with adverse health outcomes throughout the life course. We estimated the individual and combined prevalence of underweight or thinness and obesity, and their changes, from 1990 to 2022 for adults and school-aged children and adolescents in 200 countries and territories. Methods We used data from 3663 population-based studies with 222 million participants that measured height and weight in representative samples of the general population. We used a Bayesian hierarchical model to estimate trends in the prevalence of different BMI categories, separately for adults (age ≥20 years) and school-aged children and adolescents (age 5–19 years), from 1990 to 2022 for 200 countries and territories. For adults, we report the individual and combined prevalence of underweight (BMI <18·5 kg/m2) and obesity (BMI ≥30 kg/m2). For schoolaged children and adolescents, we report thinness (BMI <2 SD below the median of the WHO growth reference) and obesity (BMI >2 SD above the median). Findings From 1990 to 2022, the combined prevalence of underweight and obesity in adults decreased in 11 countries (6%) for women and 17 (9%) for men with a posterior probability of at least 0·80 that the observed changes were true decreases. The combined prevalence increased in 162 countries (81%) for women and 140 countries (70%) for men with a posterior probability of at least 0·80. In 2022, the combined prevalence of underweight and obesity was highest in island nations in the Caribbean and Polynesia and Micronesia, and countries in the Middle East and north Africa. Obesity prevalence was higher than underweight with posterior probability of at least 0·80 in 177 countries (89%) for women and 145 (73%) for men in 2022, whereas the converse was true in 16 countries (8%) for women, and 39 (20%) for men. From 1990 to 2022, the combined prevalence of thinness and obesity decreased among girls in five countries (3%) and among boys in 15 countries (8%) with a posterior probability of at least 0·80, and increased among girls in 140 countries (70%) and boys in 137 countries (69%) with a posterior probability of at least 0·80. The countries with highest combined prevalence of thinness and obesity in school-aged children and adolescents in 2022 were in Polynesia and Micronesia and the Caribbean for both sexes, and Chile and Qatar for boys. Combined prevalence was also high in some countries in south Asia, such as India and Pakistan, where thinness remained prevalent despite having declined. In 2022, obesity in school-aged children and adolescents was more prevalent than thinness with a posterior probability of at least 0·80 among girls in 133 countries (67%) and boys in 125 countries (63%), whereas the converse was true in 35 countries (18%) and 42 countries (21%), respectively. In almost all countries for both adults and school-aged children and adolescents, the increases in double burden were driven by increases in obesity, and decreases in double burden by declining underweight or thinness. Interpretation The combined burden of underweight and obesity has increased in most countries, driven by an increase in obesity, while underweight and thinness remain prevalent in south Asia and parts of Africa. A healthy nutrition transition that enhances access to nutritious foods is needed to address the remaining burden of underweight while curbing and reversing the increase in obesit

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