Choose where you live carefully: built environment differences in children’s cardiorespiratory fitness and cardiometabolic risk

© 2021 The Authors. Published by MDPI. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.3390/sports9020031Information regarding urban-rural differences in health indicators are scarce in Brazil. This study sought to identify rural-urban differences in cardiorespiratory fitness (CRF) and car-diometabolic risk (CMR) in Brazilian children and adolescents whilst controlling for the important confounding variables including social economic status (SES). This is a cross-sectional study developed with children and adolescents (n = 2250, age 11.54 ± 2.76) selected from a city in the south of Brazil. CRF was estimated using a 6-minute run/walk test. CMR scores were calculated by summing different cardiometabolic risk indicators. CRF was analysed assuming a multiplicative model with allometric body-size components. CMR differences in residential locations was assessed using Analysis of caovariance (ANCOVA) adopting SES, Body Mass Index (BMI), waist circumference (WC), age and fitness as covariates. Results indicated a main effect of location (p< 0.001) with children living a rural environment having the highest CRF, and children living in the periphery of towns having the lowest. Analysis also revealed significant main effects of location (p< 0.001) with children living a rural environment having the lowest CMR and children living in the centre of towns having the highest. Therefore, Brazilian children living in a rural environment appear to have superior health benefits.Published versio

Choice of activity-intensity classification thresholds impacts upon accelerometer-assessed physical activity-health relationships in children

It is unknown whether using different published thresholds (PTs) for classifying physical activity (PA) impacts upon activity-health relationships. This study explored whether relationships between PA (sedentary [SED], light PA [LPA], moderate PA [MPA], moderate-to-vigorous PA, vigorous PA [VPA]) and health markers differed in children when classified using three different PTs

Cardiorespiratory fitness is associated with hard and light intensity physical activity but not time spent sedentary in 10–14 year old schoolchildren: the HAPPY study

Sedentary behaviour is a major risk factor for developing chronic diseases and is associated with low cardiorespiratory fitness in adults. It remains unclear how sedentary behaviour and different physical activity subcomponents are related to cardiorespiratory fitness in children. The purpose of this study was to assess how sedentary behaviour and different physical activity subcomponents are associated with 10–14 year-old schoolchildren's cardiorespiratory fitness

The genetic parameters of feed efficiency and its component traits in the turkey (Meleagris gallopavo)

Residual feed intake (RFI) and feed conversion ratio (FCR) can be incorporated into a breeding program as traits to select for feed efficiency. Alternatively, the direct measures used to calculate RFI and FCR can be analyzed to determine the underlying variation in the traits that impact overall efficiency. These constituent traits can then be appropriately weighted in an index to achieve genetic gain. To investigate feed efficiency in the turkey, feed intake and weight gain were measured on male primary breeder line turkeys housed in individual feeding cages from 15 to 19 weeks of age. The FCR and RFI showed moderate heritability values of 0.16 and 0.21, respectively. Feed intake, body weight, and weight gain were also moderately heritable (0.25, 0.35, and 0.18, respectively). Weight gain was negatively correlated to feed conversion ratio and was not genetically correlated to RFI. Body weight had a small and positive genetic correlation to RFI (0.09) and FCR (0.12). Feed intake was positively genetically correlated to RFI (0.62); however, there was no genetic correlation between feed intake and FCR. These estimates of heritability and the genetic correlations can be used in the development of an index to improve feed efficiency and reduce the cost of production

Relationship between human tumour angiogenic profile and combretastatin-induced vascular shutdown: an exploratory study

Combretastatin-A4-phosphate (CA4P) acts most effectively against immature tumour vasculature. We investigated whether histological angiogenic profile can explain the differential sensitivity of human tumours to CA4P, by correlating the kinetic changes demonstrated by dynamic MRI (DCE-MRI) in response to CA4P, with tumour immunohistochemical angiogenic markers. Tissue was received from 24 patients (mean age 59, range 32–73, 18 women, 6 men). An angiogenic profile was performed using standard immunohistochemical techniques. Dynamic MRI data were obtained for the same patients before and 4 h after CA4P. Three patients showed a statistically significant fall in Ktrans following CA4P, and one a statistically significant fall in IAUGC60. No statistically significant correlations were seen between the continuous or categorical variables and the DCE-MRI kinetic parameters other than between ang-2 and Ktrans (P=0.044). In conclusion, we found no strong relationships between changes in DCE-MRI kinetic variables following CA4P and the immunohistochemical angiogenic profile

Use and optimization of different sources of information for genomic prediction

Abstract Background Molecular data is now commonly used to predict breeding values (BV). Various methods to calculate genomic relationship matrices (GRM) have been developed, with some studies proposing regression of coefficients back to the reference matrix of pedigree-based relationship coefficients (A). The objective was to compare the utility of two GRM: a matrix based on linkage analysis (LA) and anchored to the pedigree, i.e. $${\mathbf{G}}_{{{\mathbf{LA}}}} ,$$ G LA , and a matrix based on linkage disequilibrium (LD), i.e. $${\mathbf{G}}_{{{\mathbf{LD}}}}$$ G LD , using genomic and phenotypic data collected on 5416 broiler chickens. Furthermore, the effects of regressing the coefficients of $${\mathbf{G}}_{{{\mathbf{LD}}}}$$ G LD back to A (LDA) and to $${\mathbf{G}}_{{{\mathbf{LA}}}}$$ G LA (LDLA) were evaluated, using a range of weighting factors. The performance of the matrices and their composite products was assessed by the fit of the models to the data, and the empirical accuracy and bias of the BV that they predicted. The sensitivity to marker choice was examined by using two chips of equal density but including different single nucleotide polymorphisms (SNPs). Results The likelihood of models using GRM and composite matrices exceeded the likelihood of models based on pedigree alone and was highest with intermediate weighting factors for both the LDA and LDLA approaches. For these data, empirical accuracies were not strongly affected by the weighting factors, although they were highest when different sources of information were combined. The optimum weighting factors depended on the type of matrices used, as well as on the choice of SNPs from which the GRM were constructed. Prediction bias was strongly affected by the chip used and less by the form of the GRM. Conclusions Our findings provide an empirical comparison of the efficacy of pedigree and genomic predictions in broiler chickens and examine the effects of fitting GRM with coefficients regressed back to a reference anchored to the pedigree, either A or $${\mathbf{G}}_{{{\mathbf{LA}}}}$$ G LA . For the analysed dataset, the best results were obtained when $${\mathbf{G}}_{{{\mathbf{LD}}}}$$ G LD was combined with relationships in A or $${\mathbf{G}}_{{{\mathbf{LA}}}}$$ G LA , with optimum weighting factors that depended on the choice of SNPs used. The optimum weighting factor for broiler body weight differed from weighting factors that were based on the density of SNPs and theoretically derived using generalised assumptions