43 research outputs found
Refluxo gastroesofágico avaliado por impedâncio-pHmetria esofágica e pepsina a e c em secreção traqueal em crianças criticamente doentes com ventilação mecânica.
Atividade acaricida in vitro de Glechon spathulata Benth. sobre teleĂłginas de Rhipicephalus (Boophilus) microplus
Home-based exercise program in the indeterminate form of Chagas disease (PEDI-CHAGAS study): A study protocol for a randomized clinical trial
BackgroundChagas disease (CD) is a neglected endemic disease with worldwide impact due to migration. Approximately 50–70% of individuals in the chronic phase of CD present the indeterminate form, characterized by parasitological and/or serological evidence of Trypanosoma cruzi infection, but without clinical signs and symptoms. Subclinical abnormalities have been reported in indeterminate form of CD, including pro-inflammatory states and alterations in cardiac function, biomarkers and autonomic modulation. Moreover, individuals with CD are usually impacted on their personal and professional life, making social insertion difficult and impacting their mental health and quality of life (QoL). Physical exercise has been acknowledged as an important strategy to prevent and control numerous chronic-degenerative diseases, but unexplored in individuals with the indeterminate form of CD. The PEDI-CHAGAS study (which stands for “Home-Based Exercise Program in the Indeterminate Form of Chagas Disease” in Portuguese) aims to evaluate the effects of a home-based exercise program on physical and mental health outcomes in individuals with indeterminate form of CD.Methods and designThe PEDI-CHAGAS is a two-arm (exercise and control) phase 3 superiority randomized clinical trial including patients with indeterminate form of CD. The exclusion criteria are <18 years old, evidence of non-Chagasic cardiomyopathy, musculoskeletal or cognitive limitations that preclude the realization of exercise protocol, clinical contraindication for regular exercise, and regular physical exercise (≥1 × per week). Participants will be assessed at baseline, and after three and 6 months of follow-up. The primary outcome will be QoL. Secondary outcomes will include blood pressure, physical fitness components, nutritional status, fatigability, autonomic modulation, cardiac morphology and function, low back pain, depression and anxiety, stress, sleep quality, medication use and adherence, and biochemical, inflammatory and cardiac biomarkers. Participants in the intervention group will undergo a home-based exercise program whilst those in the control group will receive only general information regarding the benefits of physical activity. Both groups will receive the same general nutritional counseling consisting of general orientations about healthy diets.ConclusionThe findings from the present study may support public health intervention strategies to improve physical and mental health parameters to be implemented more effectively in this population.Clinical trial registration[https://ensaiosclinicos.gov.br/rg/RBR-10yxgcr9/], identifier [U1111-1263-0153]
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