Chest associated to motor physiotherapy improves cardiovascular variables in newborns with respiratory distress syndrome

<p>Abstract</p> <p>Background</p> <p>We aimed to evaluate the effects of chest and motor physiotherapy treatment on hemodynamic variables in preterm newborns with respiratory distress syndrome.</p> <p>Methods</p> <p>We evaluated heart rate (HR), respiratory rate (RR), systolic (SAP), mean (MAP) and diastolic arterial pressure (DAP), temperature and oxygen saturation (SO₂%) in 44 newborns with respiratory distress syndrome. We compared all variables between before physiotherapy treatment vs. after the last physiotherapy treatment. Newborns were treated during 11 days. Variables were measured 2 minutes before and 5 minutes after each physiotherapy treatment. We applied paired Student t test to compare variables between the two periods.</p> <p>Results</p> <p>HR (148.5 ± 8.5 bpm vs. 137.1 ± 6.8 bpm - p < 0.001), SAP (72.3 ± 11.3 mmHg vs. 63.6 ± 6.7 mmHg - p = 0.001) and MAP (57.5 ± 12 mmHg vs. 47.7 ± 5.8 mmHg - p = 0.001) were significantly reduced after 11 days of physiotherapy treatment compared to before the first session. There were no significant changes regarding RR, temperature, DAP and SO₂%.</p> <p>Conclusions</p> <p>Chest and motor physiotherapy improved cardiovascular parameters in respiratory distress syndrome newborns.</p

Effect of the rest interval duration between contractions on muscle fatigue

Background: We aimed to investigate the effect of rest interval, between successive contractions, on muscular fatigue. Methods: Eighteen subjects performed elbow flexion and extension (30 repetitions) on an isokinetic dynamometer with 80 degrees of range of motion. The flexion velocity was 120 degrees/s, while for elbow extension we used 5 different velocities (30, 75, 120, 240, 360 degrees/s), producing 5 different rest intervals (2.89, 1.28, 0.85, 0.57 and 0.54 s). Results: We observed that when the rest interval was 2.89 s there was a reduction in fatigue. On the other hand, when the rest interval was 0.54 s the fatigue was increased. Conclusions: When the resting time was lower (0.54 s) the decline of work in the flexor muscle group was higher compared with different rest interval duration.Universidade do Vale do ParaibaCAPE

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

Measurement of the cosmic ray spectrum above 4×10184{\times}10^{18} eV using inclined events detected with the Pierre Auger Observatory

A measurement of the cosmic-ray spectrum for energies exceeding $4{\times}10^{18}$ eV is presented, which is based on the analysis of showers with zenith angles greater than $60^{\circ}$ detected with the Pierre Auger Observatory between 1 January 2004 and 31 December 2013. The measured spectrum confirms a flux suppression at the highest energies. Above $5.3{\times}10^{18}$ eV, the "ankle", the flux can be described by a power law $E^{-\gamma}$ with index $\gamma=2.70 \pm 0.02 \,\text{(stat)} \pm 0.1\,\text{(sys)}$ followed by a smooth suppression region. For the energy ($E_\text{s}$) at which the spectral flux has fallen to one-half of its extrapolated value in the absence of suppression, we find $E_\text{s}=(5.12\pm0.25\,\text{(stat)}^{+1.0}_{-1.2}\,\text{(sys)}){\times}10^{19}$ eV.Comment: Replaced with published version. Added journal reference and DO

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