Ingestão de suplementos alimentares entre atletas de diferentes modalidades esportivas

Introdução: Atletas buscam a melhora do rendimento esportivo constantemente. Em relação a dieta, muitos atletas procuram por estratégias nutricionais lícitas, como exemplo, o consumo de alguns suplementos esportivos. Esses produtos são destinados a complementar as dietas tanto em energia como também em proteínas, carboidratos, lipídeos, vitaminas, minerais e fibras, juntas ou separadas, dependendo das necessidades de cada indivíduo (ANVISA, 2020). Dessa forma, sociedades esportivas frequentemente emitem recomendações específicas sobre a ingestão de energia, macronutrientes, micronutrientes e uso de suplementos alimentares entre atletas. Porém, poucos suplementos apresentam benefícios ergogênicos comprovados. Objetivos: Avaliar os tipos de suplementos alimentares consumidos por atletas de diferentes modalidades esportivas da cidade de Macaé. Metodologia: O estudo foi realizado com 57 atletas do sexo masculino das equipes de Triatlo= 5; Ciclismo= 14; futebol americano = 21; MMA = 17 da cidade de Macaé. A avaliação da ingestão dos suplementos alimentares foi realizada por meio da anamnese nutricional contendo informações sobre o tipo de suplementos usuais e a frequência da sua ingestão. Também foi questionado se os atletas realizavam acompanhamento com profissionais da saúde. Resultados: Foram avaliados 57 atletas na faixa etária de 19 a 42 anos, dos quais 74% (n=42) relataram consumir algum tipo de suplemento nutricional. Em relação ao consumo de suplementos, 80% (n=4) dos atletas no triatlo; 93% (n=13) no ciclismo, 38%(n=8) futebol americano e 100% (n=17) dos atletas do MMA consumiam algum tipo de suplemento. No triatlo, os suplementos mais consumidos foram Glutamina 75% (n=3), Whey Protein 50% (n=2), BCAA 50% (n=2), Maltodextrina 50% (n=2) e Ômega 3 50% (n=2). No ciclismo, os mais consumidos foram o Carboidrato em Gel 61,5% (n=8) e BCAA 61,5% (n=8). Do futebol americano o Whey Protein 75% (n=6) foi o mais consumido entre eles, o segundo mais consumido foi a Creatina 37,5% (n=3). No consumo de suplementos alimentares entre atletas de MMA, foi encontrada uma prevalência de consumo de Whey Protein 82% (n=14), BCAA 47% (n=8) e Glutamina 41,2% (n=7). Do total de atletas avaliados, a maioria os atletas recebiam recomendações profissionais 61,4% (n=35) quanto ao consumo dos suplementos relatados, sendo que 31% (n=16) dos que recebiam orientação profissional faziam acompanhamento com um nutricionista, 28,5% (n=12) por médicos e 23,8% (n=7) por treinadores e 38,5% (n=22) relatou não receber nenhum tipo de orientação profissional. Conclusão: O uso de suplementos nutricionais foi usual entre os atletas estudados, variando de acordo com a modalidade esportiva. Os atletas têm consumido mais suplementos do tipo proteicos, aminoácidos e de carboidratos. O perfil de consumo por modalidade também revelou uma 7 prática da poli suplementação e mostra que a educação nutricional é essencial para essa população. A maioria dos atletas fazia acompanhamento com profissional, porém variava entre nutricionistas, médicos e treinadores e uma parte não recebia nenhum tipo de orientação profissional

Post-intervention Status in Patients With Refractory Myasthenia Gravis Treated With Eculizumab During REGAIN and Its Open-Label Extension

OBJECTIVE: To evaluate whether eculizumab helps patients with anti-acetylcholine receptor-positive (AChR+) refractory generalized myasthenia gravis (gMG) achieve the Myasthenia Gravis Foundation of America (MGFA) post-intervention status of minimal manifestations (MM), we assessed patients' status throughout REGAIN (Safety and Efficacy of Eculizumab in AChR+ Refractory Generalized Myasthenia Gravis) and its open-label extension. METHODS: Patients who completed the REGAIN randomized controlled trial and continued into the open-label extension were included in this tertiary endpoint analysis. Patients were assessed for the MGFA post-intervention status of improved, unchanged, worse, MM, and pharmacologic remission at defined time points during REGAIN and through week 130 of the open-label study. RESULTS: A total of 117 patients completed REGAIN and continued into the open-label study (eculizumab/eculizumab: 56; placebo/eculizumab: 61). At week 26 of REGAIN, more eculizumab-treated patients than placebo-treated patients achieved a status of improved (60.7% vs 41.7%) or MM (25.0% vs 13.3%; common OR: 2.3; 95% CI: 1.1-4.5). After 130 weeks of eculizumab treatment, 88.0% of patients achieved improved status and 57.3% of patients achieved MM status. The safety profile of eculizumab was consistent with its known profile and no new safety signals were detected. CONCLUSION: Eculizumab led to rapid and sustained achievement of MM in patients with AChR+ refractory gMG. These findings support the use of eculizumab in this previously difficult-to-treat patient population. CLINICALTRIALSGOV IDENTIFIER: REGAIN, NCT01997229; REGAIN open-label extension, NCT02301624. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that, after 26 weeks of eculizumab treatment, 25.0% of adults with AChR+ refractory gMG achieved MM, compared with 13.3% who received placebo

Minimal Symptom Expression' in Patients With Acetylcholine Receptor Antibody-Positive Refractory Generalized Myasthenia Gravis Treated With Eculizumab

The efficacy and tolerability of eculizumab were assessed in REGAIN, a 26-week, phase 3, randomized, double-blind, placebo-controlled study in anti-acetylcholine receptor antibody-positive (AChR+) refractory generalized myasthenia gravis (gMG), and its open-label extension

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