Evaluation of movements of lower limbs in non-professional ballet dancers: hip abduction and flexion

<p>Abstract</p> <p>Background</p> <p>The literature indicated that the majority of professional ballet dancers present static and active dynamic range of motion difference between left and right lower limbs, however, no previous study focused this difference in non-professional ballet dancers. In this study we aimed to evaluate active movements of the hip in non-professional classical dancers.</p> <p>Methods</p> <p>We evaluated 10 non professional ballet dancers (16-23 years old). We measured the active range of motion and flexibility through Well Banks. We compared active range of motion between left and right sides (hip flexion and abduction) and performed correlation between active movements and flexibility.</p> <p>Results</p> <p>There was a small difference between the right and left sides of the hip in relation to the movements of flexion and abduction, which suggest the dominant side of the subjects, however, there was no statistical significance. Bank of Wells test revealed statistical difference only between the 1^stand the 3^rdmeasurement. There was no correlation between the movements of the hip (abduction and flexion, right and left sides) with the three test measurements of the bank of Wells.</p> <p>Conclusion</p> <p>There is no imbalance between the sides of the hip with respect to active abduction and flexion movements in non-professional ballet dancers.</p

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