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

Prevalência de infecção por Helicobacter pylori em uma comunidade indígena em São Paulo e fatores associados: estudo transversal

ABSTRACT CONTEXT AND OBJECTIVE: The prevalence of Helicobacter pylori infection is unevenly distributed among different populations. The aim here was to evaluate the factors associated with Helicobacter pylori infection among children up to five years of age living in a high-risk community. DESIGN AND SETTING: Cross-sectional study in an indigenous community of Guarani Mbya ethnicity, Tekoa Ytu and Tekoa Pyau villages, Jaraguá district, city of São Paulo (SP), Brazil. METHODS: 74 children aged 0.4 to 4.9 years (mean 2.9 ± 1.3 years; median 3.1), and 145 family members (86 siblings, 43 mothers and 16 fathers) were evaluated for Helicobacter pylori infection using the validated 13C-urea breath test. Clinical and demographic data were collected. RESULTS: The prevalence was 8.3% among children aged 1-2 years and reached 64.3% among those aged 4-5 years (P = 0.018; overall 31.1%). The prevalence was 76.7% among siblings and 89.8% among parents. There was a negative association with previous use of antibiotics in multivariate analysis adjusted for age (odds ratio, OR: 0.07; 95% confidence interval, CI: 0.01 to 0.66; P = 0.02). The prevalence was higher among males (OR: 1.55), and was associated with maternal infection (OR: 1.81), infection of both parents (OR: 1.5), vomiting (OR: 1.28), intestinal parasitosis (OR: 2.25), previous hospitalization (OR: 0.69) and breastfeeding (OR: 1.87). CONCLUSIONS: The prevalence was high among subjects older than three years of age, thus suggesting that the incidence of infection was higher over the first three years of life. Previous use of antibiotics was inversely associated with current Helicobacter pylori infection

Núcleos de Ensino da Unesp: artigos 2007

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq

Núcleos de Ensino da Unesp: artigos 2008

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq