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

Avaliação da resposta broncodilatadora imediata ao formoterol em doença pulmonar obstrutiva crônica (dpoc) com pouca reversibilidade

O formoterol é um fármaco beta-agonista de ação prolongada com rápido início de ação e eficácia broncodilatadora que podem determinar melhora significativa e imediata da função pulmonar. Pacientes com DPOC apresentam pouca ou nenhuma resposta ao broncodilatador (BD) no volume expiratório forçado no primeiro segundo (VEF1), podendo apresentar reversibilidade em outras variáveis se avaliados por pletismografia. O objetivo do estudo é avaliar por pletismografia a eficácia broncodilatadora do formoterol após 30 minutos de sua aplicação em portadores de DPOC. Foram estudados 40 pacientes portadores de DPOC com pobre resposta ao BD de curta ação. Encontravam-se no estágio II ou III da DPOC (SBPT/GOLD) e apresentavam VEF1 menor que 70% do valor previsto. Foram randomizados em dois grupos de 20 pacientes, com características clínicas semelhantes, recebendo cada um formoterol ou placebo, através de inalador de pó seco (aerolizer) com repetição das provas funcionais após 30 minutos. Foram observados aumentos significativos do VEF1 (12,4%) grupo formoterol (F) em relação ao grupo placebo (P) que foi de 0,1% (p=0,00065), da capacidade inspiratória (7,4% X 2,7%;p=0,05) e capacidade vital forçada (12,8% X 5,1%; p=0,017), redução importante da resistência das vias aéreas (-14% X 2,6% ; p=0,010). Foram ainda detectadas no grupo F modificações não expressivas do volume residual, da condutância das vias aéreas e da capacidade vital. Concluindo, em portadores de DPOC com pobre reversibilidade ao BD no teste espirométrico simples, o formoterol levou a uma melhora significativa da função pulmonar por pletismografia após 30 minutos de sua administração.Formoterol is a long-acting ß2 agonist drug with rapid onset of action and the bronchodilator efficacy determine a prompt improvement in lung function. Patients with COPD may show minimal improvement after bronchodilator (BD) on volume in first second (FEV1), but they can show reversibility in other parameters if plethysmography was realized. The objective of this study was to evaluate, by plethysmography, the effectiveness of formoterol as a bronchodilator after 30 minutes of administration to patients with COPD. Forty COPD patients with poorly reversible obstruction confirmed by shortacting bronchodilator use at the spirometric test were prospectively evaluated. All patients were classified as having stage II or III SBPT/GOLD, presenting FEV1 lower than 70% of predict. The patients were randomized in two groups of 20, both with similar clinical characteristics, each group receiving either formoterol or placebo by dry powder device (aerolizer) and the lung function tests were repeated in 30 minutes after the drug administration. Significant increases in FEV1 (12,4%) in formoterol group (F) and 0,1% in placebo group (P) (P=0,00065), in inspiratory capacity (7,4% X 2,7% ; p=0,05) and in forced vital capacity (12,8% X 5,1%; p=0,017) and decrease in airway resistence (p=0,010) were observed in the F= -14% when compared with P= 2,6%. Residual volume decreased while specific airways condutance and vital capacity increased less important. In conclusion COPD patients with poor reversibility, formoterol promoted significant improvement in lung function by plethysmography after 30 minutes of its administration

Obstructive sleep apnea-hypopnea syndrome : association with gender, obesity and sleepiness-related factors

Objetivo: Estudar os efeitos de gênero e obesidade e identificar fatores relacionados à sonolência diurna excessiva (SDE) em indivíduos com síndrome das apnéias-hipopnéias obstrutivas do sono (SAHOS). Métodos: Foram selecionados para inclusão no estudo 300 pacientes consecutivos, atendidos em clínica do sono, com índice de apnéia/hipopnéia (IAH) > 10 eventos/hora de sono, que completaram adequadamente a avaliação clínica. Resultados: A média de idade foi de 47 ± 11 anos e o IAH médio foi de 52,1 ± 29,2 eventos/hora de sono. As mulheres apresentaram maior média de idade, menos sonolência e menos tempo em apnéia. O escore médio de SDE foi de 14,7 ± 7,2. O escore de SDE correlacionou-se melhor com movimentos corpóreos (r = 0,43; p  10 events/hour of sleep were selected from a sleep clinic population for inclusion in the study. Results: Mean age was 47 ± 11 years, and mean AHI was 52.1 ± 29.2 events/hour of sleep. Females presented higher mean age, lower EDS scores and less time in apnea. Mean EDS score was 14.7 ± 7.2. The EDS score correlated better with body movements (r = 0.43; p < 0.01), respiratory events during sleep (r = 0.40; p < 0.01), duration of apnea (r = 0.40; p < 0.01), peripheral oxygen saturation (SpO2; r = –0.38; p < 0.01) and AHI (r = 0.37; p < 0.01). Mean body mass index (BMI) was 30.2 ± 5.3 kg/m2. Overweight, obesity and morbid obesity were observed in 41, 44 and 5.3% of cases, respectively. Disease severity correlated most strongly with BMI (r = 0.51; p < 0.01). Conclusions: Higher mean age, lower EDS scores and less time spent in sleep apnea time in apnea were associated with being female. Fragmented sleep, number/duration of respiratory events during sleep, SpO2 levels and obesity were associated with sleepiness. The BMI had a significant effect on OSAHS severity

Obstructive sleep apnea-hypopnea syndrome : association with gender, obesity and sleepiness-related factors

Objetivo: Estudar os efeitos de gênero e obesidade e identificar fatores relacionados à sonolência diurna excessiva (SDE) em indivíduos com síndrome das apnéias-hipopnéias obstrutivas do sono (SAHOS). Métodos: Foram selecionados para inclusão no estudo 300 pacientes consecutivos, atendidos em clínica do sono, com índice de apnéia/hipopnéia (IAH) > 10 eventos/hora de sono, que completaram adequadamente a avaliação clínica. Resultados: A média de idade foi de 47 ± 11 anos e o IAH médio foi de 52,1 ± 29,2 eventos/hora de sono. As mulheres apresentaram maior média de idade, menos sonolência e menos tempo em apnéia. O escore médio de SDE foi de 14,7 ± 7,2. O escore de SDE correlacionou-se melhor com movimentos corpóreos (r = 0,43; p  10 events/hour of sleep were selected from a sleep clinic population for inclusion in the study. Results: Mean age was 47 ± 11 years, and mean AHI was 52.1 ± 29.2 events/hour of sleep. Females presented higher mean age, lower EDS scores and less time in apnea. Mean EDS score was 14.7 ± 7.2. The EDS score correlated better with body movements (r = 0.43; p < 0.01), respiratory events during sleep (r = 0.40; p < 0.01), duration of apnea (r = 0.40; p < 0.01), peripheral oxygen saturation (SpO2; r = –0.38; p < 0.01) and AHI (r = 0.37; p < 0.01). Mean body mass index (BMI) was 30.2 ± 5.3 kg/m2. Overweight, obesity and morbid obesity were observed in 41, 44 and 5.3% of cases, respectively. Disease severity correlated most strongly with BMI (r = 0.51; p < 0.01). Conclusions: Higher mean age, lower EDS scores and less time spent in sleep apnea time in apnea were associated with being female. Fragmented sleep, number/duration of respiratory events during sleep, SpO2 levels and obesity were associated with sleepiness. The BMI had a significant effect on OSAHS severity