β2-Adrenoceptors activation regulates muscle trophic-related genes following acute resistance exercise in mice

Resistance exercise (RE) training and pharmacological stimulation of β2-Adrenoceptors (β2-ARs) alone can promote muscle hypertrophy and prevent muscle atrophy. Although the activation of the sympathetic nervous system (SNS) is a well-established response during RE, the physiological contribution of the endogenous catecholamines and β2-ARs to the RE-induced changes on skeletal muscle protein metabolism remains unclear. This study investigated the effects of the β2-ARs blockade on the acute molecular responses induced by a single bout of RE in rodent skeletal muscles. Male C57BL6/J mice were subjected to a single bout of progressive RE (until exhaustion) on a vertical ladder under β2-AR blockade with ICI 118,551 (ICI; 10 mg kg-1, i. p.), or vehicle (sterile saline; 0.9%, i. p.), and the gene expression was analyzed in gastrocnemius (GAS) muscles by qPCR. We demonstrated that a single bout of RE acutely increased the circulating levels of stress-associated hormones norepinephrine (NE) and corticosterone (CORT), as well as the muscle phosphorylation levels of AMPK, p38 MAPK and CREB, immediately after the session. The acute increase in the phosphorylation levels of CREB was followed by the upregulation of CREB-target genes Sik1, Ppargc1a and Nr4a3 (a central regulator of the acute RE response), 3 h after the RE session. Conversely, β2-AR blockade reduced significantly the Sik1 and Nr4a3 mRNA levels in muscles of exercised mice. Furthermore, a single bout of RE stimulated the mRNA levels of the atrophic genes Map1lc3b and Gabarapl1 (autophagy-related genes) and Mstn (a well-known negative regulator of muscle growth). Unexpectedly, the gene expression of Igf-1 or Il-6 were not affected by RE, while the atrophic genes Murf1/Trim63 and Atrogin-1/Mafbx32 (ubiquitin-ligases) were increased only in muscles of exercised mice under β2-AR blockade. Interestingly, performing a single bout of RE under β2-AR blockade increased the mRNA levels of Mstn in muscles of exercised mice. These data suggest that β2-ARs stimulation during acute RE stimulates the hypertrophic gene Nr4a3 and prevents the overexpression of atrophic genes such as Mstn, Murf1/Trim63, and Atrogin-1/Mafbx32 in the first hours of postexercise recovery, indicating that he SNS may be physiologically important to muscle adaptations in response to resistance training

Brain imaging of the cortex in ADHD: a coordinated analysis of large-scale clinical and population-based samples

Objective: Neuroimaging studies show structural alterations of various brain regions in children and adults with attention deficit hyperactivity disorder (ADHD), although nonreplications are frequent. The authors sought to identify cortical characteristics related to ADHD using large-scale studies. Methods: Cortical thickness and surface area (based on the Desikan–Killiany atlas) were compared between case subjects with ADHD (N=2,246) and control subjects (N=1,934) for children, adolescents, and adults separately in ENIGMA-ADHD, a consortium of 36 centers. To assess familial effects on cortical measures, case subjects, unaffected siblings, and control subjects in the NeuroIMAGE study (N=506) were compared. Associations of the attention scale from the Child Behavior Checklist with cortical measures were determined in a pediatric population sample (Generation-R, N=2,707). Results: In the ENIGMA-ADHD sample, lower surface area values were found in children with ADHD, mainly in frontal, cingulate, and temporal regions; the largest significant effect was for total surface area (Cohen’s d=−0.21). Fusiform gyrus and temporal pole cortical thickness was also lower in children with ADHD. Neither surface area nor thickness differences were found in the adolescent or adult groups. Familial effects were seen for surface area in several regions. In an overlapping set of regions, surface area, but not thickness, was associated with attention problems in the Generation-R sample. Conclusions: Subtle differences in cortical surface area are widespread in children but not adolescents and adults with ADHD, confirming involvement of the frontal cortex and highlighting regions deserving further attention. Notably, the alterations behave like endophenotypes in families and are linked to ADHD symptoms in the population, extending evidence that ADHD behaves as a continuous trait in the population. Future longitudinal studies should clarify individual lifespan trajectories that lead to nonsignificant findings in adolescent and adult groups despite the presence of an ADHD diagnosis

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