Tendências e Perfil Epidemiológico das Intoxicações Exógenas no Estado do Pará: Análise de uma Década

Introduction: Exogenous intoxication is a syndrome caused by the ingestion or contact with toxic substances. It encompasses a variety of different etiologies and holds significant importance, particularly in accident situations and suicide attempts. Correct semiological technique is essential for identifying the various clinical and personal aspects involved in cases of intoxication, as well as information regarding the most affected epidemiological profile. Objective: To assess the incidence and prevalence of exogenous intoxication cases in the state of Pará from 2012 to 2021. Methodology: This is a descriptive, cross-sectional epidemiological study with a quantitative approach, retrospectively analyzing cases of exogenous intoxications in the state of Pará, based on secondary data obtained through the Notifiable Diseases Information System. Results: The study revealed an increase in the incidence of exogenous intoxications during the study period. A total of 5,849 cases were reported, with the most common profile being female gender, aged 20 to 39 years, and of mixed race/ethnicity. Medications were the most commonly used toxic agents, and suicide attempts were the most prevalent circumstances. Conclusion: The significant relevance of exogenous intoxications in suicide attempt cases is evident, necessitating preventive policies in the field. However, the large number of notifications with ignored or blank variables hampers the development of a combat strategy.Introdução: Intoxicação exógena é uma síndrome causada pela ingestão ou contato com substâncias tóxicas. Possui uma série de etiologias diferentes e relevante importância principalmente em situações de acidentes e tentativas de suicídio. A correta técnica semiológica é essencial para se identificar os variados aspectos clínicos e pessoais que envolvem situações de intoxicação, assim como informações a respeito do perfil epidemiológico mais afetado. Objetivo: avaliar a incidência e a prevalência de casos de intoxicação exógena no estado do Pará no período de 2012 a 2021. Metodologia: Trata-se de um estudo epidemiológico descritivo, transversal, com abordagem quantitativa e retrospectiva dos casos de intoxicações exógenas no Estado do Pará, com base em dados secundários obtidos por meio do Sistema de Informação de Agravos de Notificação. Resultados: O estudo evidenciou um aumento na incidência de intoxicações exógenas no período estudado. Foram notificados 5849 casos, sendo o perfil mais comum sexo feminino, faixa etária 20 a 39 anos, cor/raça parda, sendo os medicamentos os agentes tóxicos mias utilizados e as tentativas de suicídio as circunstâncias mais prevalentes. Conclusão: Conclui-se a grande relevância das intoxicações exógenas em casos tentativa de suicídio, tornando necessária políticas de prevenção na área. Porém, o grande número de notificações com variáveis ignoradas ou em branco, prejudicam a construção de uma estratégia de combate

ANÁLISE CLÍNICA DE PACIENTES DIAGNOSTICADOS COM TRANSTORNO DE ESQUIZOAFETIVO: UM ESTUDO DETALHADO

This is a challenging but essential condition that requires an integrated and personalized approach. With proper diagnosis and treatment, patients can learn to manage their symptoms and achieve a better quality of life, allowing them to realize their potential and actively participate in society. The aim of this study was to investigate the benefits of clinical analysis in the analysis of patients diagnosed with schizoaffective disorder. To this end, a systematic literature review was carried out, with the search and selection of scientific articles published between 2019 and 2024, in the Scielo, Medline and Lilacs databases. The benefits of clinical analysis in this study include the identification of diagnostic instability and clinical overlap between schizoaffective disorder (SAD) and other conditions, such as schizophrenia, allowing for a deeper understanding of patients' clinical characteristics. In addition, the clinical analysis highlights the high prevalence of substance use, providing important insights for the clinical management of these patients. These results highlight the importance of clinical analysis in guiding appropriate and timely interventions aimed at improving the diagnosis and treatment of SAD.A análise clínica de pacientes com transtorno esquizoafetivo é um processo desafiador, porém essencial, que demanda uma abordagem integrada e personalizada. Com o diagnóstico e tratamento adequados, os pacientes podem aprender a gerenciar seus sintomas e alcançar uma melhor qualidade de vida, permitindo-lhes realizar seus potenciais e participar ativamente na sociedade. O presente estudo teve como objetivo estudar os benefícios da análise clínica na análise de pacientes diagnosticados com transtorno esquizoafetivo. Para isso, Para isso, realizou-se uma revisão sistemática da literatura, com a busca e seleção de artigos científicos publicados entre 2019 e 2024, nas bases de dados Scielo, Medline e Lilacs. Os benefícios da análise clínica neste estudo incluem a identificação da instabilidade diagnóstica e da sobreposição clínica entre transtorno esquizoafetivo (TAS) e outras condições, como esquizofrenia, permitindo uma compreensão mais profunda das características clínicas dos pacientes. Além disso, a análise clínica destaca a alta prevalência de uso de substâncias, fornecendo insights importantes para o manejo clínico desses pacientes. Esses resultados ressaltam a importância da análise clínica na orientação de intervenções adequadas e oportunas, visando melhorar o diagnóstico e o tratamento do TAS

ADESÃO AO TRATAMENTO NA CLÍNICA NEUROPSIQUIÁTRICA: UMA REVISÃO SISTEMÁTICA

Adherence to treatment in psychiatric outpatient clinics is a vital element of mental health care. Although significant challenges are faced, it is possible to improve adherence through educational strategies, support and collaboration between patients and healthcare professionals. By recognizing the importance of this aspect and working to overcome obstacles, we can improve outcomes for patients and promote more robust and resilient mental health in our communities. This study aimed to investigate the main factors influencing adherence to treatment in psychiatric outpatient clinics. To this end, a systematic literature review was conducted, selecting scientific articles published between 2019 and 2024, available in the Scielo, Medline and Lilacs databases. After an in-depth analysis and discussion of the results, it was concluded that adherence to treatment in psychiatric outpatient clinics is influenced by a variety of factors, including continuity in therapeutic follow-up, patients' mentalization capacity, the model of care and sociodemographic and clinical influences, highlighting the need for personalized and integrated approaches to improve care in these settings.A adesão ao tratamento em ambulatórios psiquiátricos é um elemento vital do cuidado em saúde mental. Embora sejam enfrentados desafios significativos, é possível melhorar a adesão por meio de estratégias educacionais, de suporte e de colaboração entre pacientes e profissionais de saúde. Ao reconhecer a importância desse aspecto e trabalhar para superar os obstáculos, pode-se melhorar os resultados para os pacientes e promover uma saúde mental mais robusta e resiliente em nossas comunidades. Este estudo teve como objetivo investigar os principais fatores que influenciam a adesão ao tratamento nos ambulatórios psiquiátricos. Para isso, foi conduzida uma revisão sistemática da literatura, selecionando artigos científicos publicados entre 2019 e 2024, disponíveis nas bases de dados Scielo, Medline e Lilacs. Após uma análise aprofundada e discussão dos resultados, chegou-se à conclusão de que a adesão ao tratamento nos ambulatórios psiquiátricos é influenciada por uma variedade de fatores, incluindo a continuidade no acompanhamento terapêutico, a capacidade de mentalização dos pacientes, o modelo de atendimento e as influências sociodemográficas e clínicas, destacando a necessidade de abordagens personalizadas e integradas para melhorar o cuidado nesses ambientes

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

ATLANTIC-PRIMATES: a dataset of communities and occurrences of primates in the Atlantic Forests of South America

Primates play an important role in ecosystem functioning and offer critical insights into human evolution, biology, behavior, and emerging infectious diseases. There are 26 primate species in the Atlantic Forests of South America, 19 of them endemic. We compiled a dataset of 5,472 georeferenced locations of 26 native and 1 introduced primate species, as hybrids in the genera Callithrix and Alouatta. The dataset includes 700 primate communities, 8,121 single species occurrences and 714 estimates of primate population sizes, covering most natural forest types of the tropical and subtropical Atlantic Forest of Brazil, Paraguay and Argentina and some other biomes. On average, primate communities of the Atlantic Forest harbor 2 ± 1 species (range = 1–6). However, about 40% of primate communities contain only one species. Alouatta guariba (N = 2,188 records) and Sapajus nigritus (N = 1,127) were the species with the most records. Callicebus barbarabrownae (N = 35), Leontopithecus caissara (N = 38), and Sapajus libidinosus (N = 41) were the species with the least records. Recorded primate densities varied from 0.004 individuals/km 2 (Alouatta guariba at Fragmento do Bugre, Paraná, Brazil) to 400 individuals/km 2 (Alouatta caraya in Santiago, Rio Grande do Sul, Brazil). Our dataset reflects disparity between the numerous primate census conducted in the Atlantic Forest, in contrast to the scarcity of estimates of population sizes and densities. With these data, researchers can develop different macroecological and regional level studies, focusing on communities, populations, species co-occurrence and distribution patterns. Moreover, the data can also be used to assess the consequences of fragmentation, defaunation, and disease outbreaks on different ecological processes, such as trophic cascades, species invasion or extinction, and community dynamics. There are no copyright restrictions. Please cite this Data Paper when the data are used in publications. We also request that researchers and teachers inform us of how they are using the data. © 2018 by the The Authors. Ecology © 2018 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

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements