An article in BMCGeriatr discusses a study protocol to evaluate the effect of including 50g of raisins in the daily diet for six months on cognitive performance, cardiovascular risk factors and inflammation in older adults without cognitive impairment.
], height with the Seca 213 portable stadiometer with integrated leveler, and hip and waist circumference with a flexible tape measure.All participants , before random assignment is made, and after the baseline visit, will receive brief nutritional advice from one of the principal investigators, aimed at maintaining a balanced diet.Instructions will be given for the daily intake, in addition to the usual diet, of 50 g of raisins. The duration of this intervention will be 6 months.
In this project, it is intended to contribute, with preventive strategies, to minimize the problems derived from cognitive deterioration in older people.
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Automatic disease prediction from human gut metagenomic data using boosting GraphSAGE - BMC BioinformaticsBackground The human microbiome plays a critical role in maintaining human health. Due to the recent advances in high-throughput sequencing technologies, the microbiome profiles present in the human body have become publicly available. Hence, many works have been done to analyze human microbiome profiles. These works have identified that different microbiome profiles are present in healthy and sick individuals for different diseases. Recently, several computational methods have utilized the microbiome profiles to automatically diagnose and classify the host phenotype. Results In this work, a novel deep learning framework based on boosting GraphSAGE is proposed for automatic prediction of diseases from metagenomic data. The proposed framework has two main components, (a). Metagenomic Disease graph (MD-graph) construction module, (b). Disease prediction Network (DP-Net) module. The graph construction module constructs a graph by considering each metagenomic sample as a node in the graph. The graph captures the relationship between the samples using a proximity measure. The DP-Net consists of a boosting GraphSAGE model which predicts the status of a sample as sick or healthy. The effectiveness of the proposed method is verified using real and synthetic datasets corresponding to diseases like inflammatory bowel disease and colorectal cancer. The proposed model achieved a highest AUC of 93%, Accuracy of 95%, F1-score of 95%, AUPRC of 95% for the real inflammatory bowel disease dataset and a best AUC of 90%, Accuracy of 91%, F1-score of 87% and AUPRC of 93% for the real colorectal cancer dataset. Conclusion The proposed framework outperforms other machine learning and deep learning models in terms of classification accuracy, AUC, F1-score and AUPRC for both synthetic and real metagenomic data.
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Meta-analysis of the relationship between bullying and depressive symptoms in children and adolescents - BMC PsychiatryChildhood and adolescence are critical periods for physical and mental development; thus, they are high-risk periods for the occurrence of mental disorders. The purpose of this study was to systematically evaluate the association between bullying and depressive symptoms in children and adolescents. We searched the PubMed, MEDLINE and other databases to identify studies related to bullying behavior and depressive symptoms in children and adolescents. A total of 31 studies were included, with a total sample size of 133,688 people. The results of the meta-analysis showed that the risk of depression in children and adolescents who were bullied was 2.77 times higher than that of those who were not bullied; the risk of depression in bullying individuals was 1.73 times higher than that in nonbullying individuals; and the risk of depression in individuals who bullied and experienced bullying was 3.19 times higher than that in nonbullying-bullied individuals. This study confirmed that depression in children and adolescents was significantly associated with being bullied, bullying, and bullying-bullied behavior. However, these findings are limited by the quantity and quality of the included studies and need to be confirmed by future studies.
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Ethnic minority representation in UK COVID-19 trials: systematic review and meta-analysis - BMC MedicineBackground The COVID-19 pandemic has highlighted health disparities affecting ethnic minority communities. There is growing concern about the lack of diversity in clinical trials. This study aimed to assess the representation of ethnic groups in UK-based COVID-19 randomised controlled trials (RCTs). Methods A systematic review and meta-analysis were undertaken. A search strategy was developed for MEDLINE (Ovid) and Google Scholar (1st January 2020–4th May 2022). Prospective COVID-19 RCTs for vaccines or therapeutics that reported UK data separately with a minimum of 50 participants were eligible. Search results were independently screened, and data extracted into proforma. Percentage of ethnic groups at all trial stages was mapped against Office of National Statistics (ONS) statistics. Post hoc DerSimonian-Laird random-effects meta-analysis of percentages and a meta-regression assessing recruitment over time were conducted. Due to the nature of the review question, risk of bias was not assessed. Data analysis was conducted in Stata v17.0. A protocol was registered (PROSPERO CRD42021244185). Results In total, 5319 articles were identified; 30 studies were included, with 118,912 participants. Enrolment to trials was the only stage consistently reported (17 trials). Meta-analysis showed significant heterogeneity across studies, in relation to census-expected proportions at study enrolment. All ethnic groups, apart from Other (1.7% [95% CI 1.1–2.8%] vs ONS 1%) were represented to a lesser extent than ONS statistics, most marked in Black (1% [0.6–1.5%] vs 3.3%) and Asian (5.8% [4.4–7.6%] vs 7.5%) groups, but also apparent in White (84.8% [81.6–87.5%] vs 86%) and Mixed 1.6% [1.2–2.1%] vs 2.2%) groups. Meta-regression showed recruitment of Black participants increased over time (p = 0.009). Conclusions Asian, Black and Mixed ethnic groups are under-represented or incorrectly classified in UK COVID-19 RCTs. Reporting by ethnicity lacks consistency and transparency. Under-re
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Social media has no significant impact on teenagers' mental health, study suggestsA new study suggests the so-called damaging effect of Facebook and other social media sites are overblown and have little effect on teenagers’ wellbeing 🔴 Exclusive from BawdenTom
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Domenicali: there's more to it than the Drive to Survive effectFormulaNerds.com — Latest News — Drive to Survive has undoubtedly contributed to the growing success of Formula 1. But Formula 1 CEO and President Stefano Domenicali explains the other reasons behind the sport's positive development.
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Effect of the Communities That Care Prevention System on Adolescent Handgun CarryingThis cluster-randomized trial evaluates the effect of universal school-, family-, and community-based programs on adolescent handgun carrying.
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