Effects of a school-based intervention on active commuting to school and health-related fitness

Background: Active commuting to school has declined over time, and interventions are needed to reverse this trend. The main objective was to investigate the effects of a school-based intervention on active commuting to school and health-related fitness in school-age children of Southern Spain. Methods: A total of 494 children aged 8 to 11 years were invited to participate in the study. The schools were non-randomly allocated (i.e., school level allocation) into the experimental group (EG) or the control group (CG). The EG received an intervention program for 6 months (a monthly activity) focused on increasing the level of active commuting to school and mainly targeting children’s perceptions and attitudes. Active commuting to school and health-related fitness (i.e., cardiorespiratory fitness, muscular fitness and speed-agility), were measured at baseline and at the end of the intervention. Children with valid data on commuting to school at baseline and follow-up, sex, age and distance from home to school were included in the final analysis (n = 251). Data was analyzed through a factorial ANOVA and the Bonferroni post-hoc test. Results: At follow up, the EG had higher rates of cycling to school than CG for boys only (p = 0.04), but not for walking to school for boys or girls. The EG avoided increases in the rates of passive commuting at follow up, which increased in the CG among girls for car (MD = 1.77; SE = 0.714; p = 0.010) and bus (MD = 1.77; SE = 0.714; p = 0.010) modes. Moreover, we observed significant interactions and main effects between independent variables (study group, sex and assessment time point) on health-related fitness (p < 0.05) over the 6-month period between groups, with higher values in the control group (mainly in boys). Conclusion: A school-based intervention focused on increasing active commuting to school was associated with increases in rates of cycling to school among boys, but not for walking to school or health-related fitness. However, the school-based intervention avoided increases in rates of passive commuting in the experimental group, which were significantly increased in girls of the control group

Substrate translocation involves specific lysine residues of the central channel of the conjugative coupling protein TrwB

Conjugative transfer of plasmid R388 requires the coupling protein TrwB for protein and DNA transport, but their molecular role in transport has not been deciphered. We investigated the role of residues protruding into the central channel of the TrwB hexamer by a mutational analysis. Mutations affecting lysine residues K275, K398, and K421, and residue S441, all facing the internal channel, affected transport of both DNA and the relaxase protein in vivo. The ATPase activity of the purified soluble variants was affected significantly in the presence of accessory protein TrwA or DNA, correlating with their behaviour in vivo. Alteration of residues located at the cytoplasmic or the inner membrane interface resulted in lower activity in vivo and in vitro, while variants affecting residues in the central region of the channel showed increased DNA and protein transfer efficiency and higher ATPase activity, especially in the absence of TrwA. In fact, these variants could catalyze DNA transfer in the absence of TrwA under conditions in which the wild-type system was transfer deficient. Our results suggest that protein and DNA molecules have the same molecular requirements for translocation by Type IV secretion systems, with residues at both ends of the TrwB channel controlling the opening?closing mechanism, while residues embedded in the channel would set the pace for substrate translocation (both protein and DNA) in concert with TrwA

A school-based physical activity promotion intervention in children: rationale and study protocol for the PREVIENE Project

The lack of physical activity and increasing time spent in sedentary behaviours during childhood place importance on developing low cost, easy-toimplement school-based interventions to increase physical activity among children. The PREVIENE Project will evaluate the effectiveness of five innovative, simple, and feasible interventions (active commuting to/from school, active Physical Education lessons, active school recess, sleep health promotion, and an integrated program incorporating all 4 interventions) to improve physical activity, fitness, anthropometry, sleep health, academic achievement, and health-related quality of life in primary school children. The PREVIENE Project will provide the information about the effectiveness and implementation of different school-based interventions for physical activity promotion in primary school children.The PREVIENE Project was funded by the Spanish Ministry of Economy and Competitiveness (DEP2015-63988-R, MINECO-FEDER). MAG is supported by grants from the Spanish Ministry of Economy and Competitivenes

PEDIA: prioritization of exome data by image analysis

Purpose Phenotype information is crucial for the interpretation of genomic variants. So far it has only been accessible for bioinformatics workflows after encoding into clinical terms by expert dysmorphologists. Methods Here, we introduce an approach driven by artificial intelligence that uses portrait photographs for the interpretation of clinical exome data. We measured the value added by computer-assisted image analysis to the diagnostic yield on a cohort consisting of 679 individuals with 105 different monogenic disorders. For each case in the cohort we compiled frontal photos, clinical features, and the disease-causing variants, and simulated multiple exomes of different ethnic backgrounds. Results The additional use of similarity scores from computer-assisted analysis of frontal photos improved the top 1 accuracy rate by more than 20–89% and the top 10 accuracy rate by more than 5–99% for the disease-causing gene. Conclusion Image analysis by deep-learning algorithms can be used to quantify the phenotypic similarity (PP4 criterion of the American College of Medical Genetics and Genomics guidelines) and to advance the performance of bioinformatics pipelines for exome analysis