Influence of multicomponent exercise program or self-selected physical activity on physical, mental, and biochemical health indicators of older women

The aim of this study was to compare physical, mental, and biochemical health indicators of 48 older women (67 ± 1 year) who practiced multicomponent exercise program (ME, n = 25) and self-selected physical activity (PA, n = 23) for 6 months. It was an observational study, which aimed to relate a prospective intervention. Displacement speed, lower limb (LL) power, functional capacity, body composition, biochemical profile, physical activity levels (PAL), sedentary behavior (SB), quality of life (QoL), and mental illness risk (MIR) were evaluated. ME presented better values compared to the PA in the gait speed (p = 0.001, large ES), aerobic capacity (p = 0.0001, large ES), agility/dynamic balance (p = 0.0001, large ES), LL flexibility (p = 0.0003, large ES), UL flexibility (p = 0.04, large ES), upper limb (UL) strength (p = 0.07, moderate ES), Total cholesterol (p = 0.009, large ES), triglycerides (p = 0.003, large ES), creatinine (p = 0.007, large ES), glycated hemoglobin (p= 0.007, large ES), and lower mean glucose value (p = 0.008, large ES). ME was more efficient than PA to improve indicators of gait speed, and functional capacity, regulate glycated hemoglobin, blood glucose, and serum creatinine. Thys study also brings practical applications for coaches, which could adapt and use creativity to develop different types of systematized ME, aiming to enhance positive adaptations in the older people at multilevel outcomes.info: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 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, and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space. While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes, vast areas of the tropics remain understudied. In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity, but it remains among the least known forests in America and is often underrepresented in biodiversity databases. To worsen this situation, human-induced modifications 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, 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

RAPD analysis of Nectomys squamipes (Rodentia, Sigmodontinae) populations

Random amplified of polymorphic DNA (RAPD) analysis was used to assess genetic distance and the genetic structure of populations of Nectomys squamipes, a semiaquatic rodent species distributed along watercourses. DNA samples of five populations were analyzed using three primers, producing 45 scorable bands, 31 of which were polymorphic. There was a significant differentiation among populations [F ST = 0.17; phiST = 0.14 (P < 0.004)] but gene flow (Nm = 1.25) was sufficient to overcome genetic drift effects. No fixed specific markers were found for any population. The Mantel's test and UPGMA cluster analysis showed a lack of relationship between genetic and geographic distances. The apparent homogeneity indicated by RAPD markers coincided with morphometric data, despite the wide geographic range of N. squamipes. Alternative hypotheses for explaining our results include recurrent processes of local extinction and recolonization or a recent and sudden increase in the geographic distribution of this species