Exercise training improves quality of life in women with subclinical hypothyroidism : a randomized clinical trial.

Objective: The aim was to evaluate the quality of life (HRQoL) in women with subclinical hypothyroidism (sHT) after 16 weeks of endurance training. Subjects and methods: In the first phase, a cross-sectional study was conducted in which 22 women with sHT (median age: 41.5 (interquartile range: 17.5) years, body mass index: 26.2 (8.7) kg/m2 , thyroid stimulating hormone > 4.94 mIU/L and free thyroxine between 0.8 and 1.3 ng/dL were compared to a group of 33 euthyroid women concerned to HRQoL. In the second phase, a randomized clinical trial was conducted where only women with sHT were randomly divided into two groups: sHT-Tr (n = 10) ? participants that performed an exercise program ? and sHT-Sed (n = 10) ? controls. Exercise training consisted of 60 minutes of aerobic activities (bike and treadmill), three times a week, for 16 weeks. The HRQoL was assessed by the SF-36 questionnaire in the early and at the end of four months. Results: Women with sHT had lower scores on functional capacity domain in relation to the euthyroid ones (77.0 ? 23.0 vs. 88.8 ? 14.6; p = 0.020). The sHT-Tr group improved functional capacity, general health, emotional aspects, mental and physical component of HRQoL after training period, while the sHT-Sed group showed no significant changes. Conclusion: After 16 weeks of aerobic exercise training, there were remarkable improvements in HRQoL in women with sHT

Specific Humoral Immunity versus Polyclonal B Cell Activation in Trypanosoma cruzi Infection of Susceptible and Resistant Mice

Chagas disease, caused by the protozoan parasite Trypanosoma cruzi, affects 10–12 million people in Latin America. Patent parasitemia develops during acute disease. During this phase, polyclonal B cell activation has been reported to generate high levels of serum antibody with low parasite specificity, and delayed protective humoral immunity, which is necessary to prevent the host from succumbing to infection. In this manuscript, data show that relatively resistant mice have improved parasite-specific humoral immunity and decreased polyclonal B cell activation compared to susceptible mice. Parasite-specific humoral immunity was associated with differential expansion of B cell subsets and T cells in the spleen, as well as with increased Th1 and decreased Th2 cytokine production. These data suggest that host susceptibility/genetic biases impact the development of humoral responses to infection. Th2 cytokines are generally associated with improved antibody responses. In the context of T. cruzi infection of susceptible mice, Th2 cytokines were associated with increased total antibody production concomitant with delayed pathogen-specific humoral immunity. This study highlights the need to consider the effect of host biases when investigating humoral immunity to any pathogen that has reported polyclonal B cell activation during infection

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