Time Reallocations From Sedentary Behavior to Physical Activity and Cardiovascular Risk Factors in Children and Adolescents: A Systematic Review.

BACKGROUND: Recent statistical approaches have allowed consideration of the integrated relationships between sedentary behavior (SB) and physical activity (PA) with different health outcomes. The present paper aimed to systematically review the literature and synthesize evidence about associations between hypothetical reallocations from SB to different PA intensities and cardiovascular risk factors in youth. METHODS: A systematic search of 8 databases was performed. Observational studies with a population of children and/or adolescents and based on statistical analysis that investigated the associations between time reallocations from SB to PA and cardiovascular risk factors were included. RESULTS: Twenty-eight studies met the inclusion criteria. Level of evidence (derived from cross-sectional studies) indicated that the reallocation from SB to moderate to vigorous PA was beneficially associated with adiposity, cardiorespiratory fitness, and cardiometabolic biomarkers in youth. Reallocation from SB to light PA was not associated with the analyzed outcomes. Associations derived from longitudinal studies were mostly inconclusive. CONCLUSION: Cardiovascular risk factors could be improved by increasing moderate to vigorous PA at the expense of time spent in SB in pediatric populations. Prospective studies or studies investigating the effects of reallocating sedentary bouts to PA are needed.

Association between cardiorrespiratory fitness and cognitive control: is somatic maturity an important mediator?

BACKGROUND: Recently some articles presented information related to the possible effect of maturity over the cognitive control and cardiorespiratory fitness, however little is known about the real effects of maturity in the relation of these variables. In this sense, the purpose of this study was to examine the potential mediating role of somatic maturity on the association between cardiorespiratory fitness (CRF) and cognitive control. METHODS: This three-year longitudinal research comprises two data collection groups: a baseline conducted in 2016 with 394 adolescents (aged 11.7 ± 0.6 years) and a follow-up in 2019 with 134 adolescents (aged 14.9 ± 0.7 years). Anthropometry data, 20-m shuttle run test and peak height velocity (PHV) to determine the maximum oxygen uptake (VO2max) and somatic maturity, respectively, were collected at both sampling times. In parallel, the Sociodemographic and cognitive control function variables were included in the follow-up to evaluate the inhibitory control (by the Stroop test) and the visuo-spatial working memory (by the Corsi block-tapping test). Associations between CRF and cognitive functions were computed by multiple linear regression, with mediation as a function of PHV. RESULTS: CRF exhibited transversal associations with reaction time in congruent (ß = -0.004; p = 0.001) and incongruent (ß = -0.005; p = 0.004) stimulus-responses. Meanwhile, the variation in VO2max over the three year-study had a significant impact on the reaction time of congruent (ß = -0.006; p = 0.001) and incongruent (ß = -0.006; p = 0.012) responses at follow-up. However, PHV did not show a significant association with the cognitive functions, indicating no mediating role. CONCLUSIONS: Although the associations between CRF and the cognitive functions exhibited great transversal and longitudinal impacts, somatic maturity did not affect the cognitive control functions, associating exclusively with CRF.

Development of cardiorespiratory fitness standards for working memory using receiver operating curves in 15-year-old adolescents.

BACKGROUND: Working memory performance is associated with better academic achievements in children and adolescents, and it is positively related to CRF. However, what level of cardiorespiratory fitness (CRF) discriminates higher working memory performance is not known. The purpose of this study was to identify CRF thresholds linked to working memory in adolescents. METHODS: Data of 141 adolescents (53.2 % girls) were collected (14.9 years) from a cross-sectional study during the year 2019. CRF was assessed by the 20-m shuttle run test, and maximal oxygen uptake was calculated using the Mahar´s equation. Working memory was evaluated by the Corsi blocks test and performance was classified by percentiles. Receiver operating characteristic (ROC) curve analysis was used to identify CRF thresholds. RESULTS: The ROC analysis indicated that CRF could be used to discriminate working memory in adolescents. CRF thresholds of ≥45.03 ml.kg- 1.min- 1for boys and ≥36.63 ml.kg- 1.min- 1for girls were found to be indicative of "normal" working memory performance. CONCLUSIONS: CRF could discriminate low and normal working memory performance in 14-16- year-old adolescents. These thresholds could allow for earlier identification and intervention of low working memory performance using CRF.

High Throughput Field Phenotyping for Plant Height Using UAV-Based RGB Imagery in Wheat Breeding Lines: Feasibility and Validation.

Plant height (PH) is an essential trait in the screening of most crops. While in crops such as wheat, medium stature helps reduce lodging, tall plants are preferred to increase total above-ground biomass. PH is an easy trait to measure manually, although it can be labor-intense depending on the number of plots. There is an increasing demand for alternative approaches to estimate PH in a higher throughput mode. Crop surface models (CSMs) derived from dense point clouds generated via aerial imagery could be used to estimate PH. This study evaluates PH estimation at different phenological stages using plot-level information from aerial imaging-derived 3D CSM in wheat inbred lines during two consecutive years. Multi-temporal and high spatial resolution images were collected by fixed-wing (P l a t F W ) and multi-rotor (P l a t M R ) unmanned aerial vehicle (UAV) platforms over two wheat populations (50 and 150 lines). The PH was measured and compared at four growth stages (GS) using ground-truth measurements (PHground) and UAV-based estimates (PHaerial). The CSMs generated from the aerial imagery were validated using ground control points (GCPs) as fixed reference targets at different heights. The results show that PH estimations using P l a t F W were consistent with those obtained from P l a t M R , showing some slight differences due to image processing settings. The GCPs heights derived from CSM showed a high correlation and low error compared to their actual heights (R 2 ≥ 0.90, RMSE ≤ 4 cm). The coefficient of determination (R 2) between PHground and PHaerial at different GS ranged from 0.35 to 0.88, and the root mean square error (RMSE) from 0.39 to 4.02 cm for both platforms. In general, similar and higher heritability was obtained using PHaerial across different GS and years and ranged according to the variability, and environmental error of the PHground observed (0.06-0.97). Finally, we also observed high Spearman rank correlations (0.47-0.91) and R 2 (0.63-0.95) of PHaerial adjusted and predicted values against PHground values. This study provides an example of the use of UAV-based high-resolution RGB imagery to obtain time-series estimates of PH, scalable to tens-of-thousands of plots, and thus suitable to be applied in plant wheat breeding trials.

Light-intensity physical activity patterns and associated factors in adolescents

Abstract Aims: This study aimed to measure light-intensity physical activity (LPA) patterns in adolescents according to weekdays and school period and investigated associations between LPA patterns and associated factors. Methods: This is a cross-sectional study with 388 students of both genders, selected from public schools from Londrina city, Parana state. LPA was measured using accelerometry for seven consecutive days and was analyzed by the time spent in very short (15 to 30 s), short (30 to 60 s), intermediate (1 to 3 min), and long bouts (≥ 3 min). Results: Approximately 22% of the total daily time was spent in LPA. The time in LPA accumulated in short or intermediate bouts was higher than the time accumulated in very short or long bouts (P < 0.05). Gender was associated with short (β= 2.180; 95% confidence interval [CI], 0.357 to 4.003) and intermediate bouts (β = 2.822; 95% CI, 0.681 to 4.964), girls presented higher daily time. Age was inversely associated with very short (β = −0.925; 95% CI, −1.676 to −0.175) and intermediate bouts (β = −1.985; 95% CI, −3.579 to −0.390). The total time in LPA and time accumulated in very short, short, and intermediate bouts was higher in the school period when compared to the non-school period (P < 0.05). Conclusion: It could be concluded that the LPA patterns are predominantly composed of time spent in bouts between 30 seconds and three minutes. Gender, age, and school period appear to influence the LPA pattern in adolescents.

Multi-trait multi-environment models in the genetic selection of segregating soybean progeny.

At present, single-trait best linear unbiased prediction (BLUP) is the standard method for genetic selection in soybean. However, when genetic selection is performed based on two or more genetically correlated traits and these are analyzed individually, selection bias may arise. Under these conditions, considering the correlation structure between the evaluated traits may provide more-accurate genetic estimates for the evaluated parameters, even under environmental influences. The present study was thus developed to examine the efficiency and applicability of multi-trait multi-environment (MTME) models by the residual maximum likelihood (REML/BLUP) and Bayesian approaches in the genetic selection of segregating soybean progeny. The study involved data pertaining to 203 soybean F2:4 progeny assessed in two environments for the following traits: number of days to maturity (DM), 100-seed weight (SW), and average seed yield per plot (SY). Variance components and genetic and non-genetic parameters were estimated via the REML/BLUP and Bayesian methods. The variance components estimated and the breeding values and genetic gains predicted with selection through the Bayesian procedure were similar to those obtained by REML/BLUP. The frequentist and Bayesian MTME models provided higher estimates of broad-sense heritability per plot (or heritability of total effects of progeny; [Formula: see text]) and mean accuracy of progeny than their respective single-trait versions. Bayesian analysis provided the credibility intervals for the estimates of [Formula: see text]. Therefore, MTME led to greater predicted gains from selection. On this basis, this procedure can be efficiently applied in the genetic selection of segregating soybean progeny.