Artrite meningocócica mediada imunologicamente e associada à infecção: combinação de ambas características no mesmo paciente

We present a case of a 16-year-old male patient with sudden-onset, rash, arthritis and meningitis by Neisseria meningitidis one week after an acute upper respiratory infection. On the 10th day of treatment followed by neurological and arthritis clinical improvement, he presented once again a tender and swollen left knee with a moderate effusion, and active and passive range of motion was severely limited secondary to pain, and when he was submitted to surgical drainage and synovial fluid analysis he showed inflammatory characteristics. A non-steroidal anti-inflammatory drug was taken for five days with complete improvement of symptoms. The case is notable for its combination of features of septic and immune-mediated arthritis, which has rarely been reported in the same patient.Paciente de 16 anos do sexo masculino apresentou-se ao serviço de emergência com quadro de erupção cutânea súbita, artrite e meningite por Neisseria meningitidis, uma semana após apresentar sintomas de infecção de vias aéreas superiores. No décimo dia de tratamento, seguido da melhora clínica neurológica e da artrite, ele volta a apresentar derrame articular moderado com limitação importante da amplitude dos movimentos passivo e ativo secundária à dor. Em seguida, foi submetido à drenagem cirúrgica e a análise do líquido sinovial mostra características inflamatórias. Foi iniciado tratamento com antiinflamatório não esteroidal por cinco dias com melhora completa dos sintomas. Esse caso tem como característica peculiar o fato do indivíduo apresentar tanto as características de artrite séptica pelo meningococo quanto de artrite imunomediada, o que tem sido pouco usual no mesmo paciente

Approach to Endoscopic Procedures: A Routine Protocol from a Quaternary University Referral Center Exclusively for Coronavirus Disease 2019 Patients

OBJECTIVES: The present coronavirus disease (COVID-19) pandemic has ushered in an unprecedented era of quality control that has necessitated advanced safety precautions and the need to ensure the adequate protection of healthcare professionals (HCPs). Endoscopy units, endoscopists, and other HCP may be at a significant risk for transmission of the virus. Given the immense burden on the healthcare system and surge in the number of patients with COVID-19, well-designed protocols and recommendations are needed. We aimed to systematically characterize our approach to endoscopic procedures in a quaternary university hospital setting and provide summary protocol recommendations. METHOD: This descriptive study details a COVID-19-specific protocol designed to minimize infection risks to patients and healthcare workers in the endoscopy unit. RESULTS: Our institution, located in Sa˜o Paulo, Brazil, includes a 900-bed hospital, with a 200-bed-specific intensive care unit exclusively designed for patients with moderate and severe COVID-19. We highlighted recommendations for infection prevention and control during endoscopic procedures, including appropriate triage and screening, outpatient management and procedural recommendations, role and usage of personal protective equipment (PPE), and role and procedural logistics involving COVID-19-positive patients. We also detailed hospital protocols for reprocessing endoscopes and cleaning rooms and also provided recommendations to minimize severe acute respiratory syndrome coronavirus 2 transmission. CONCLUSION: This COVID-19-specific administrative and clinical protocol can be replicated or adapted in multiple institutions and endoscopy units worldwide. Furthermore, the recommendations and summary protocol may improve patient and HCP safety in these trying times

Análise das complicações pós-operatórias de câncer colorretal / Analysis of post-operative complications of colorectal cancer

Objetivo: Esse estudo, através de uma revisão narrativa, objetiva determinar as possíveis complicações pós-operatórias do Câncer Colorretal (CCR), um dos 3 tumores mais prevalentes no mundo, baseado na abordagem escolhida. A cirurgia é a base do tratamento com potencial terapêutico, podendo variar desde ressecções endoscópicas até cirurgias abertas, a depender do estadiamento no momento do diagnóstico e do tipo de câncer. Métodos: Foram utilizados como base, estudos publicados nos bancos de dados eletrônicos PuBmed, LILACS, Science Direct e SciELO, entre 2015 e 2020. Resultados: Apesar de todos os procedimentos cirúrgicos para tratamento de CCR conferirem riscos de complicações, intervenções de urgência e cirurgias abertas apresentam maiores taxas quando comparados a cirurgias minimamente invasivas. A colectomia laparoscópica destaca-se dentre as outras opções pela menor taxa de complicações, seguida da ileocolectomia direita e prótese endoluminal. Conclusão: A cirurgia de escolha dependerá de diversos fatores incluindo eficiência e eficácia do método para cada estágio da doença, experiência do cirurgião e fatores de risco do paciente, sempre visando a menor probabilidade de complicações

Detection and Characterization of Oscillating Red Giants: First Results from the TESS Satellite

Since the onset of the "space revolution" of high-precision high-cadence photometry, asteroseismology has been demonstrated as a powerful tool for informing Galactic archeology investigations. The launch of the NASA Transiting Exoplanet Survey Satellite (TESS) mission has enabled seismic-based inferences to go full sky—providing a clear advantage for large ensemble studies of the different Milky Way components. Here we demonstrate its potential for investigating the Galaxy by carrying out the first asteroseismic ensemble study of red giant stars observed by TESS. We use a sample of 25 stars for which we measure their global asteroseimic observables and estimate their fundamental stellar properties, such as radius, mass, and age. Significant improvements are seen in the uncertainties of our estimates when combining seismic observables from TESS with astrometric measurements from the Gaia mission compared to when the seismology and astrometry are applied separately. Specifically, when combined we show that stellar radii can be determined to a precision of a few percent, masses to 5%-10%, and ages to the 20% level. This is comparable to the precision typically obtained using end-of-mission Kepler data

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

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