Canadian 24-hour movement guidelines for adults aged 18-64 years and adults aged 65 years or older: an integration of physical activity, sedentary behaviour, and sleep

The Canadian Society for Exercise Physiology assembled a Consensus Panel representing national organizations, content experts, methodologists, stakeholders, and end-users and followed an established guideline development procedure to create the Canadian 24-Hour Movement Guidelines for Adults aged 18-64 years and Adults aged 65 years or older: An Integration of Physical Activity, Sedentary Behaviour, and Sleep. These guidelines underscore the importance of movement behaviours across the whole 24-h day. The development process followed the strategy outlined in the Appraisal of Guidelines for Research and Evaluation (AGREE) II instrument. A large body of evidence was used to inform the guidelines including 2 de novo systematic reviews and 4 overviews of reviews examining the relationships among movement behaviours (physical activity, sedentary behaviour, sleep, and all behaviours together) and several health outcomes. Draft guideline recommendations were discussed at a 4-day in-person Consensus Panel meeting. Feedback from stakeholders was obtained by survey (n = 877) and the draft guidelines were revised accordingly. The final guidelines provide evidence-based recommendations for a healthy day (24-h), comprising a combination of sleep, sedentary behaviours, and light-intensity and moderate-to-vigorous-intensity physical activity. Dissemination and implementation efforts with corresponding evaluation plans are in place to help ensure that guideline awareness and use are optimized. Novelty First ever 24-Hour Movement Guidelines for Adults aged 18-64 years and Adults aged 65 years or older with consideration of a balanced approach to physical activity, sedentary behaviour, and sleep Finalizes the suite of 24-Hour Movement Guidelines for Canadians across the lifespa

Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

Background Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. Methods We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. Results Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. Conclusions Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.Peer reviewe

La memoria de los libros. Estudios sobre la historia del escrito y de la lectura en Europa y América. Vol. I

Numerosos artículos sobre aspectos variados de historia del libro y de la lectura, bibliotecas, manuscritos, iluminación e ilustración, etc

Impact of Optimized Breastfeeding on the Costs of Necrotizing Enterocolitis in Extremely Low Birthweight Infants

To estimate risk of NEC for ELBW infants as a function of preterm formula and maternal milk (MM) intake and calculate the impact of suboptimal feeding on NEC incidence and costs

El museo de todos: el Victoria and Albert Museum de Londres en los albores del siglo XXI

El artículo presenta una breve historia de la fundación y desarrollo del Victoria and Albert Museum, y esboza algunos de los proyectos más notables que se están realizando bajo el programa actual de renovación de salas, denominado «FuturePlan». Se centra en las ideas y objetivos presentes en la reforma de las salas de arte medieval y renacentista, y sitúa este análisis en el contexto general del papel del museo para demostrar cómo la institución moderna de hoy sigue fiel a los ideales que impulsaron su fundación hace más de siglo y medio

Alfonso X el Sabio : Astromagia ed. Alfonso D'Agostino

Sin resume

Alfonso X el Sabio: Astromagia, ed. Alfonso D'Agostino.

Sin resume

Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data

Abstract: Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural networks (NN). The main score used to compare the methods was the Area Under the ROC Curve (AUC) statistics. The impact of quality control (QC), imputing and coding methods on LR results showed that QC methods and imputation of missing genotypes may artificially increase the scores. At the opposite, neither the patient/control ratio nor marker preselection or coding strategies significantly affected the results. LR methods, including Lasso, Ridge and ElasticNet provided similar results with a maximum AUC of 0.80. GBT methods like XGBoost, LightGBM and CatBoost, together with dense NN with one or more hidden layers, provided similar AUC values, suggesting limited epistatic effects in the genetic architecture of the trait. ML methods detected near all the genetic variants previously identified by GWAS among the best predictors plus additional predictors with lower effects. The robustness and complementarity of the different methods are also studied. Compared to LR, non-linear models such as GBT or NN may provide robust complementary approaches to identify and classify genetic markers