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Objective: To examine the effect of plyometric jump training on skeletal muscle hypertrophy in healthy individuals.
Methods: A systematic literature search was conducted in the databases PubMed, SPORTDiscus, Web of Science, and Cochrane Library up to September 2021.
Results: Fifteen studies met the inclusion criteria. The main overall finding (44 effect sizes across 15 clusters median = 2, range = 1–15 effects per cluster) indicated that plyometric jump training had small to moderate effects [standardised mean difference (SMD) = 0.47 (95% CIs = 0.23–0.71); p < 0.001] on skeletal muscle hypertrophy. Subgroup analyses for training experience revealed trivial to large effects in non-athletes [SMD = 0.55 (95% CIs = 0.18–0.93); p = 0.007] and trivial to moderate effects in athletes [SMD = 0.33 (95% CIs = 0.16–0.51); p = 0.001]. Regarding muscle groups, results showed moderate effects for the knee extensors [SMD = 0.72 (95% CIs = 0.66–0.78), p < 0.001] and equivocal effects for the plantar flexors [SMD = 0.65 (95% CIs = −0.25–1.55); p = 0.143]. As to the assessment methods of skeletal muscle hypertrophy, findings indicated trivial to small effects for prediction equations [SMD = 0.29 (95% CIs = 0.16–0.42); p < 0.001] and moderate-to-large effects for ultrasound imaging [SMD = 0.74 (95% CIs = 0.59–0.89); p < 0.001]. Meta-regression analysis indicated that the weekly session frequency moderates the effect of plyometric jump training on skeletal muscle hypertrophy, with a higher weekly session frequency inducing larger hypertrophic gains [β = 0.3233 (95% CIs = 0.2041–0.4425); p < 0.001]. We found no clear evidence that age, sex, total training period, single session duration, or the number of jumps per week moderate the effect of plyometric jump training on skeletal muscle hypertrophy [β = −0.0133 to 0.0433 (95% CIs = −0.0387 to 0.1215); p = 0.101–0.751].
Conclusion: Plyometric jump training can induce skeletal muscle hypertrophy, regardless of age and sex. There is evidence for relatively larger effects in non-athletes compared with athletes. Further, the weekly session frequency seems to moderate the effect of plyometric jump training on skeletal muscle hypertrophy, whereby more frequent weekly plyometric jump training sessions elicit larger hypertrophic adaptations.
Objective: To examine the effect of plyometric jump training on skeletal muscle hypertrophy in healthy individuals.
Methods: A systematic literature search was conducted in the databases PubMed, SPORTDiscus, Web of Science, and Cochrane Library up to September 2021.
Results: Fifteen studies met the inclusion criteria. The main overall finding (44 effect sizes across 15 clusters median = 2, range = 1–15 effects per cluster) indicated that plyometric jump training had small to moderate effects [standardised mean difference (SMD) = 0.47 (95% CIs = 0.23–0.71); p < 0.001] on skeletal muscle hypertrophy. Subgroup analyses for training experience revealed trivial to large effects in non-athletes [SMD = 0.55 (95% CIs = 0.18–0.93); p = 0.007] and trivial to moderate effects in athletes [SMD = 0.33 (95% CIs = 0.16–0.51); p = 0.001]. Regarding muscle groups, results showed moderate effects for the knee extensors [SMD = 0.72 (95% CIs = 0.66–0.78), p < 0.001] and equivocal effects for the plantar flexors [SMD = 0.65 (95% CIs = −0.25–1.55); p = 0.143]. As to the assessment methods of skeletal muscle hypertrophy, findings indicated trivial to small effects for prediction equations [SMD = 0.29 (95% CIs = 0.16–0.42); p < 0.001] and moderate-to-large effects for ultrasound imaging [SMD = 0.74 (95% CIs = 0.59–0.89); p < 0.001]. Meta-regression analysis indicated that the weekly session frequency moderates the effect of plyometric jump training on skeletal muscle hypertrophy, with a higher weekly session frequency inducing larger hypertrophic gains [β = 0.3233 (95% CIs = 0.2041–0.4425); p < 0.001]. We found no clear evidence that age, sex, total training period, single session duration, or the number of jumps per week moderate the effect of plyometric jump training on skeletal muscle hypertrophy [β = −0.0133 to 0.0433 (95% CIs = −0.0387 to 0.1215); p = 0.101–0.751].
Conclusion: Plyometric jump training can induce skeletal muscle hypertrophy, regardless of age and sex. There is evidence for relatively larger effects in non-athletes compared with athletes. Further, the weekly session frequency seems to moderate the effect of plyometric jump training on skeletal muscle hypertrophy, whereby more frequent weekly plyometric jump training sessions elicit larger hypertrophic adaptations.
A very small fraction of (runaway) massive stars have masses exceeding 60-70 M-circle dot and are predicted to evolve as luminous blue variable and Wolf-Rayet stars before ending their lives as core-collapse supernovae. Our 2D axisymmetric hydrodynamical simulations explore how a fast wind (2000 km s(-1)) and high mass-loss rate (10(-5)M(circle dot) yr(-1)) can impact the morphology of the circumstellar medium. It is shaped as 100 pc-scale wind nebula that can be pierced by the driving star when it supersonically moves with velocity 20-40 km s(-1) through the interstellar medium (ISM) in the Galactic plane. The motion of such runaway stars displaces the position of the supernova explosion out of their bow shock nebula, imposing asymmetries to the eventual shock wave expansion and engendering Cygnus-loop-like supernova remnants. We conclude that the size (up to more than 200 pc) of the filamentary wind cavity in which the chemically enriched supernova ejecta expand, mixing efficiently the wind and ISM materials by at least 10 per cent in number density, can be used as a tracer of the runaway nature of the very massive progenitors of such 0.1Myr old remnants. Our results motivate further observational campaigns devoted to the bow shock of the very massive stars BD+43 degrees 3654 and to the close surroundings of the synchrotron-emitting Wolf-Rayet shell G2.4+1.4.
Cells and organelles are not homogeneous but include microcompartments that alter the spatiotemporal characteristics of cellular processes. The effects of microcompartmentation on metabolic pathways are however difficult to study experimentally. The pyrenoid is a microcompartment that is essential for a carbon concentrating mechanism (CCM) that improves the photosynthetic performance of eukaryotic algae. Using Chlamydomonas reinhardtii, we obtained experimental data on photosynthesis, metabolites, and proteins in CCM-induced and CCM-suppressed cells. We then employed a computational strategy to estimate how fluxes through the Calvin-Benson cycle are compartmented between the pyrenoid and the stroma. Our model predicts that ribulose-1,5-bisphosphate (RuBP), the substrate of Rubisco, and 3-phosphoglycerate (3PGA), its product, diffuse in and out of the pyrenoid, respectively, with higher fluxes in CCM-induced cells. It also indicates that there is no major diffusional barrier to metabolic flux between the pyrenoid and stroma. Our computational approach represents a stepping stone to understanding microcompartmentalized CCM in other organisms.
Core-collapse supernova remnants are structures of the interstellar medium (ISM) left behind the explosive death of most massive stars ( ?40 M-?). Since they result in the expansion of the supernova shock wave into the gaseous environment shaped by the star's wind history, their morphology constitutes an insight into the past evolution of their progenitor star. Particularly, fast-mo ving massiv e stars can produce asymmetric core-collapse superno va remnants. We inv estigate the mixing of materials in core-collapse supernova remnants generated by a moving massive 35 M-? star, in a magnetized ISM. Stellar rotation and the wind magnetic field are time-dependently included into the models which follow the entire evolution of the stellar surroundings from the zero-age main-sequence to 80 kyr after the supernova explosion. It is found that very little main-sequence material is present in remnants from moving stars, that the Wolf-Rayet wind mixes very efficiently within the 10 kyr after the explosion, while the red supergiant material is still unmixed by 30 per cent within 50 kyr after the supernova. Our results indicate that the faster the stellar motion, the more complex the internal organization of the supernova remnant and the more ef fecti ve the mixing of ejecta therein. In contrast, the mixing of stellar wind material is only weakly affected by progenitor motion, if at all.