A INFLUÊNCIA DAS VACINAS NA LUTA CONTRA A COVID-19: UMA REVISÃO NARRATIVA

The development of COVID-19 vaccines represents a significant milestone in the history of medicine, enabling a global response to the pandemic. This article reviewed the general principles of vaccine development, their efficacy, safety, and impact on global public health. Vaccines have proven to be highly effective in reducing disease severity and preventing hospitalizations and deaths. However, concerns have arisen about rare adverse events such as thrombosis and thrombocytopenia following vaccination, which require ongoing surveillance. Despite these challenges, COVID-19 vaccines continue to play a crucial role in containing the pandemic.O desenvolvimento das vacinas contra a COVID-19 representou um marco na história da medicina, permitindo uma resposta global à pandemia. Este artigo revisou os princípios gerais do desenvolvimento das vacinas, sua eficácia, segurança e impacto na saúde pública global. As vacinas demonstraram ser altamente eficazes na redução da gravidade da doença e na prevenção de hospitalizações e mortes. No entanto, surgiram preocupações com eventos adversos raros, como a trombose e trombocitopenia após a vacinação, que exigem uma vigilância contínua. Apesar desses desafios, as vacinas contra a COVID-19 continuam a desempenhar um papel crucial na contenção da pandemia

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

Desafio do Diagnóstico do Transtorno de Déficit de Atenção e Hiperatividade na população pediátrica e suas consequências / The challenge of diagnosing Attention Deficit Hyperactivity Disorder in the pediatric population and its consequences

O transtorno de déficit de atenção e hiperatividade é um transtorno neuropsiquiátrico com agitação, impulsividade e maior tendência à distração. Trata-se de uma doença de importante prevalência na infância, acometendo 4 a 10% das crianças, e que se perpetua ao longo da vida adulta, causando importantes prejuízos sociais, financeiros e emocionais. O diagnóstico é feito por entrevista, sendo necessário a presença insistente de sintomas antes dos doze anos de idade e pelo menos cinco critérios de desatenção e cinco de hiperatividade. Por ser um diagnóstico sem auxílio de propedêutica complementar, pode sofrer interferências da diversidade de variáveis sintomatológicas, inclusive pela possível interferência de terceiros - como pais, professores ou a indústria farmacêutica - em querer medicalizar desnecessariamente o paciente. O tratamento ideal envolve tanto o uso de medicação, sendo o metilfenidato o padrão-ouro, quanto o auxílio psicoterápico, principalmente por meio da terapia cognitiva comportamental, sendo ambos utilizados em longo prazo. A associação da psicoterapia permite à criança o aprendizado de técnicas de autocontrole para que possa lidar melhor com sua sintomatologia, enquanto o tratamento farmacológico atua por meio da interferência na dopamina e recaptação de noradrenalina, diminuindo a inquietação e distração e melhorando a memória e a regulação do humor

Guidance on mucositis assessment from the MASCC Mucositis Study Group and ISOO: an international Delphi studyResearch in context

Summary: Background: Mucositis is a common and highly impactful side effect of conventional and emerging cancer therapy and thus the subject of intense investigation. Although common practice, mucositis assessment is heterogeneously adopted and poorly guided, impacting evidence synthesis and translation. The Multinational Association of Supportive Care in Cancer (MASCC) Mucositis Study Group (MSG) therefore aimed to establish expert recommendations for how existing mucositis assessment tools should be used, in clinical care and trials contexts, to improve the consistency of mucositis assessment. Methods: This study was conducted over two stages (January 2022–July 2023). The first phase involved a survey to MASCC-MSG members (January 2022–May 2022), capturing current practices, challenges and preferences. These then informed the second phase, in which a set of initial recommendations were prepared and refined using the Delphi method (February 2023–May 2023). Consensus was defined as agreement on a parameter by >80% of respondents. Findings: Seventy-two MASCC-MSG members completed the first phase of the study (37 females, 34 males, mainly oral care specialists). High variability was noted in the use of mucositis assessment tools, with a high reliance on clinician assessment compared to patient reported outcome measures (PROMs, 47% vs 3%, 37% used a combination). The World Health Organization (WHO) and Common Terminology Criteria for Adverse Events (CTCAE) scales were most commonly used to assess mucositis across multiple settings. Initial recommendations were reviewed by experienced MSG members and following two rounds of Delphi survey consensus was achieved in 91 of 100 recommendations. For example, in patients receiving chemotherapy, the recommended tool for clinician assessment in clinical practice is WHO for oral mucositis (89.5% consensus), and WHO or CTCAE for gastrointestinal mucositis (85.7% consensus). The recommended PROM in clinical trials is OMD/WQ for oral mucositis (93.3% consensus), and PRO-CTCAE for gastrointestinal mucositis (83.3% consensus). Interpretation: These new recommendations provide much needed guidance on mucositis assessment and may be applied in both clinical practice and research to streamline comparison and synthesis of global data sets, thus accelerating translation of new knowledge into clinical practice. Funding: No funding was received