Fototerapia com LED no reparo tecidual de feridas crônicas em pessoas com diabetes: revisão sistemática

Objetivo: Identificar evidências científicas da fotobiomodulação com LED no tratamento e reparo tecidual em feridas crônicas de pessoas com Diabetes Mellitus, tipo I e II.Método: Revisão sistemática realizada de setembro/2021 a abril/2022 na PubMed, LILACS, SCIELO, COHRANE, EMBASE e Web of Science. Incluídos ensaios clínicos randomizados e observacionais utilizando LED na cicatrização de feridas em diabéticos, publicados entre 2015 a 2022. Os dados foram analisados descritivamente com triagem de título/resumo, leitura dos artigos em texto completo e seleção definitiva após atender aos critérios de inclusão e exclusão pré-definidos.Resultados: Do total de 840 referências encontradas, foram selecionados oito artigos que avaliaram a eficácia da fototerapia LED em feridas de pacientes diabéticos.Conclusão: A luz LED mostrou-se benéfica no reparo tecidual, com aumento na produção de colágeno e fibroblastos, angiogênese, redução da inflamação e consequentemente, diminuição no tamanho da lesão.Palavras-chave: Fototerapia. Cicatrização. Diabetes Mellitus. Pé diabético. Úlcera do pé

Multi-trait multi-environment models for selecting high-performance and stable eucalyptus clones

Multi-trait multi-environment (MTME) models were fitted to eucalyptus breeding trials data to assess residual variance structure, genetic stability and adaptability. To do so, 215 eucalyptus clones were evaluated in a randomized complete block design with 30 replicates and one plant per plot in four environments. At 36 months of age, tree diameter at breast height (DBH) and pilodyn penetration (PP) were measured. Two MTME models were fitted, for which residuals were considered homoscedastic and heteroscedastic, with the best MTME model selected using Bayesian information criterion. The harmonic mean of the relative performance of the genotypic values (HMRPGV) was used to determine stability and adaptability. Of the two models, the heteroscedastic MTME model had better fit and provided greater accuracy. In addition, genotype-by-environment interaction was complex, and there was low genetic correlation between DBH and PP. Rank correlation between the clones selected by the MTME models was high for DBH but low for PP. The HMRPGV facilitated clone selection through simultaneous evaluation of stability, adaptability, and productivity. Thus, our results suggest that heteroscedastic MTME model / HMRPGV can be efficiently applied in the genetic evaluation and selection of eucalyptus clones

High-Intensity Interval Training Improves Markers of Oxidative Metabolism in Skeletal Muscle of Individuals With Obesity and Insulin Resistance

Background: The excess body fat characteristic of obesity is related to various metabolic alterations, which includes insulin resistance (IR). Among the non-pharmacological measures used to improve insulin sensitivity are aerobic physical training, such as high-intensity interval training (HIIT). This study investigated the effects of 8 weeks of HIIT on blood and skeletal muscle markers related to IR and oxidative metabolism in physically inactive individuals with obesity and compared the changes between insulin resistant and non-insulin resistant phenotypes.Methods: Initially to investigate the effect of obesity and IR in the analyzed parameters, insulin-sensitive eutrophic volunteers (CON; n = 9) and obese non-insulin (OB; n = 9) and insulin-resistant (OBR; n = 8) were enrolled. Volunteers with obesity completed 8 weeks of HIIT in a cycle ergometer. Venous blood and vastus lateralis muscle samples were obtained before and after the HIIT. Body composition and peak oxygen consumption (VO2peak) were estimated before and after HIIT.Results: HIIT reduced IR assessed by the homeostatic model assessment of insulin resistance (HOMA-IR) in OBR (4.4 ± 1.4 versus 4.1 ± 2.2 μU L−2), but not in OB (HOMA-IR 1.8 ± 0.5 versus 2.3 ± 1.0 μU L−2) volunteers. HIIT increased VO2peak with no change in body fat in both groups. In skeletal muscle, HIIT increased the phosphorylation of IRS (Tyr612), Akt (Ser473), and increased protein content of β-HAD and COX-IV in both groups. There was a reduction in ERK1/2 phosphorylation in OBR after HIIT.Conclusion: Eight weeks of HIIT increased the content of proteins related to oxidative metabolism in skeletal muscle of individuals with obesity, independent of changes total body fat

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

LED phototherapy in tissue repair of chronic wounds in people with diabetes: a systematic review

ABSTRACT Objective: To identify scientific evidence of LED photobiomodulation in the treatment and tissue repair of chronic wounds in people with Diabetes Mellitus, types I and II. Method: Systematic review conducted from September/2021 to April/2022 in PubMed, LILACS, SCIELO, COHRANE, EMBASE and Web of Science. Randomized and observational clinical trials using LED in wound healing in diabetics, published between 2015 and 2022 were included. Data were descriptively analyzed with title/abstract screening, full text articles reading and definitive selection after meeting the predefined inclusion and exclusion criteria. Results: Fromthe total of 840 references, eight articles were selected, that evaluated the effectiveness of LED phototherapy in wounds of diabetic patients. Conclusion: LED light proved to be beneficial in tissue repair, with increased production in collagen and fibroblasts, angiogenesis, reduction of inflammation and, consequently, a decrease in lesion size