Evaluation of Muscle Damage, Body Temperature, Peak Torque and Fatigue Index in Three Different Methods of Strength Gain

International Journal of Exercise Science 13(3): 1352-1365, 2020. The aim of this study was to evaluate and compare three different strength training protocols for the lower limbs by using biochemical indicators of muscle damage, thermographic analysis, and neuromuscular performance. In total, 10 men (age: 22.50 ± 2.84 years; weight, 75.45 ± 6.86 kg) completed the study. All the athletes were subjected to three methods of resistance training (RT): traditional, tension, and occlusion training. Serum concentrations of creatine kinase, lactate dehydrogenase, aspartate aminotransferase, and alanine aminotransferase were used as indicators of muscle damage. To measure muscle strength, the peak force, and fatigue index were determined using a Kratos load cell. Images were captured using an infrared camera (FLIR T640sc). The vascular occlusion method demonstrated a 33% reduction in post-training peak torque (p \u3c 0.001; ɳ2p: 2.74), which was recovered within 24 h (p \u3c 0.001; ɳ2p: 1.08). The thermographic analysis revealed a reduction in skin temperature in both thighs after the tension (−9.37%) and vascular occlusion (−6.01%) methods. In conclusion, the occlusion training seems to provide additional benefits as compared to the other two methods of strength training

Comparison of the Local Temperature, Lactate and Glucose After Three Different Strength Training Methods

International Journal of Exercise Science 14(4): 1408-1420, 2021. This study aimed to evaluate the local temperature, lactate, and blood glucose in three strength training methods. The study included 12 male subjects; (22.15 ± 5.77 years, 76.85 ± 9.15 kg, 1.72 ± 0.09 m), with minimum of 12 months of strength training experience, and all participated in the three training methods: the occlusion training (Kaatsu); the tension training (Tension); and the traditional training (Traditional). The Kaatsu training consisted in 3 sets of 10RM with occlusion device in both arms inflated to a 130% occlusion pressure. In addition, the tension method was performed with 30% of 1RM and the traditional training, consisted in 10 repetitions with 80% RM. Regarding the temperature variation, differences were observed between the Kaatsu and Traditional methods in relation to Tension (p = .049, ɳ2p = 0.187). While for blood glucose (p = .351, ɳ2p = 0.075) and lactate (p = .722, ɳ2p = 0.022) there were no differences between the methods. Regarding the temperature (°C) measured by thermography and asymmetry, the right side showed a decrease in the post-test, in relation to the pre-test, in all methods (p \u3c .05, ɳ2p \u3e 0.150). The left (p = .035, ɳ2p = 0.301) and right (p = .012, ɳ2p = 0.324) sides showed a decrease in temperature, in the post-test in relation to the pre-test, in the Kaatsu and traditional method. In asymmetry, the three methods showed an increase in the post-test in relation to the pre-test (p = .042, ɳ2p = 0.158). In conclusion, tension method seems to stimulate greater heat production than the other methods. This information can help coaches to choose among these training methods according to the desired physiological response

Brazilian recommendations on the safety and effectiveness of the yellow fever vaccination in patients with chronic immune-mediated inflammatory diseases

Background: In Brazil, we are facing an alarming epidemic scenario of Yellow fever (YF), which is reaching the most populous areas of the country in unvaccinated people. Vaccination is the only effective tool to prevent YF. In special situations, such as patients with chronic immune-mediated inflammatory diseases (CIMID), undergoing immunosuppressive therapy, as a higher risk of severe adverse events may occur, assessment of the risk-benefit ratio of the yellow fever vaccine (YFV) should be performed on an individual level. Main body of the abstract: Faced with the scarcity of specific orientation on YFV for this special group of patients, the Brazilian Rheumatology Society (BRS) endorsed a project aiming the development of individualized YFV recommendations for patients with CIMID, guided by questions addressed by both medical professionals and patients, followed an internationally validated methodology (GIN-McMaster Guideline Development). Firstly, a systematic review was carried out and an expert panel formed to take part of the decision process, comprising BRS clinical practitioners, as well as individuals from the Brazilian Dermatology Society (BDS), Brazilian Inflammatory Bowel Diseases Study Group (GEDIIB), and specialists on infectious diseases and vaccination (from Tropical Medicine, Infectious Diseases and Immunizations National Societies); in addition, two representatives of patient groups were included as members of the panel. When the quality of the evidence was low or there was a lack of evidence to determine the recommendations, the decisions were based on the expert opinion panel and a Delphi approach was performed. A recommendation was accepted upon achieving ≥80% agreement among the panel, including the patient representatives. As a result, eight recommendations were developed regarding the safety of YFV in patients with CIMID, considering the immunosuppression degree conferred by the treatment used. It was not possible to establish recommendations on the effectiveness of YFV in these patients as there is no consistent evidence to support these recommendations. Conclusion: This paper approaches a real need, assessed by clinicians and patient care groups, to address specific questions on the management of YFV in patients with CIMID living or traveling to YF endemic areas, involving specialists from many areas together with patients, and might have global applicability, contributing to and supporting vaccination practices. We recommended a shared decision-making approach on taking or not the YFV

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

Updated cardiovascular prevention guideline of the Brazilian Society of Cardiology: 2019

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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