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The polygenic risk score (PRS) allows for quantification of the relative contributions of genes and environment in population-based studies of mental health. We analyzed the impact of transdiagnostic schizophrenia PRS and measures of familial and environmental risk on the level of and change in general mental health (Short-Form-36 mental health) in the Netherlands Mental Health Survey and Incidence Study-2 general population sample, interviewed 4 times over a period of 9 years, yielding 8901 observations in 2380 individuals. Schizophrenia PRS, family history, somatic pain, and a range of environmental risks and social circumstances were included in the regression model of level of and change in mental health. We calculated the relative contribution of each (group of) risk factor(s) to the variance in (change in) mental health. In the combined model, familial and environmental factors explained around 17% of the variance in mental health, of which around 5% was explained by age and sex, 30% by social circumstances, 16% by pain, 22% by environmental risk factors, 24% by family history, and 3% by PRS for schizophrenia (PRS-SZ). Results were similar, but attenuated, for the model of mental health change over time. Childhood trauma and gap between actual and desired social status explained most of the variance. PRS for bipolar disorder, cross-disorder, and depression explained less variance in mental health than PRS-SZ. Polygenic risk for mental suffering, derived from significance-testing in massive samples, lacks impact in analyses focusing on prediction in a general population epidemiological setting. Social-environmental circumstances, particularly childhood trauma and perceived status gap, drive most of the attributable variation in population mental health.<br /><br /> Synthetic antioxidants have toxigenic effects, there is therefore growing interest in substituting them with natural antioxidants. Attention is being focused on extracting them from agricultural industry residuals to minimize costs. Legume seed hulls could be cheap sources of such natural antioxidants.<br /><br /> This study aims to unravel potential free radical scavenging activity, antioxidant activity, and total phenolic and flavonoid contents of some legumes' hulls extracted by different solvents and evaluate their efficacy to enhance sunflower oil stability.<br /><br /> Legume hulls extracted by different solvents were evaluated for their antioxidant activity coefficient (AAC), free radical scavenging activity [by 2,2-diphenyl-1- picrylhydrazyl (DPPH)], and phenolic and flavonoids contents. [https://www.selleckchem.com/products/gilteritinib-asp2215.html see more] The protection factor and induction periods (rancimat test) of the highest activity extracts were evaluated.<br /><br /> Sunflower seed hull ethyl acetate extract, lupine seed hull ethanol extract, and mung bean hull petroleum ether extract exhinduction periods and protection factors of sunflower oil.The human lifespan and quality of life depend on complex interactions among genetic, environmental, and lifestyle factors. Aging research has been remarkably advanced by the development of high-throughput "omics" technologies. Differences between chronological and biological ages, and identification of factors (eg, nutrition) that modulate the rate of aging can now be assessed at the individual level on the basis of telomere length, the epigenome, and the metabolome. Nevertheless, the understanding of the different responses of people to dietary factors, which is the focus of precision nutrition research, remains incomplete. The lack of reliable dietary assessment methods constitutes a significant challenge in nutrition research, especially in elderly populations. For practical and successful personalized diet advice, big data techniques are needed to analyze and integrate the relevant omics (ie, genomic, epigenomic, metabolomics) with an objective and longitudinal capture of individual nutritional and environmental information. Application of such techniques will provide the scientific evidence and knowledge needed to offer actionable, personalized health recommendations to transform the promise of personalized nutrition into reality.The Japanese people have enjoyed longevity for several decades, and Japanese dietary habits are considered to contribute to this longevity. The scientific definition of the Japanese diet, however, is not yet fully established. The Working Group 1 of the Healthy Diet Research Committee of the International Life Sciences Institute Japan reviewed the literature to collect definitions of the Japanese diet appearing in articles in the fields of diet, nutrition, foods, and human health. This report addresses the definitions and the questions raised by these definitions. Among 283 relevant articles identified, 116 were carefully screened and included in the analysis. In most of the articles, the authors self-defined the Japanese diet; some studies used a government-proposed definition. This review revealed no systematic approach to define the Japanese diet from the viewpoints of nutrition and health. Before conducting studies to determine whether the Japanese diet is healthy, it is important to address the question of what the Japanese diet is from the viewpoint of human nutrition rather than culinary culture.Precision health care plays a crucial role in an elderly society by providing personalized health care plans for improving an individual's health conditions and preventing disease. To realize precision health care, data science is key; it allows for analyses of health-related big data. In this article, an actual analysis of time-series health check-up data is presented and as is a discussion of how personalized simulation models of health conditions are constructed and used to modify individual behavior. Future directions for precision health care based on the integration of genetic variations and the microbiome are also discussed.This narrative review discusses how to preserve or increase health through personalized nutritional products and services using microbiome data. In contrast to other reviews, which discuss this subject in the light of metabolic disorders and/or with a nutrition-affects-the-microbiota view, this review takes the perspective that the gut microbiota (GM) affects nutrition. Gut microbes affect host nutritional status through their role in energy harvest and nutrient availability. Consequently, GM modulation could contribute to fulfil nutritional requirements and in this way conquer malnutrition and disease. This review provides an overview of microbiota modulation methods that could be used to improve nutritional status as well as the personalization of these approaches. While some of these methods are immediately applicable, others require more development to assess their feasibility and safety.