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The oral lipid tolerance test (OLTT) has been known to assess intestinal fat metabolism and whole-body lipid metabolism, but rodent models for OLTT are not yet established. Differences in OLTT methodology preclude the generation of definitive results, which may cause some confusion about the anti-hypertriglyceridemia effects of the test materials. selleck compound To standardize and generate more appropriate methodology for the OLTT, we examined the effects of mice strain, dietary lipid sources, fasting period, and gender on lipid-induced hypertriglyceridemia in mice. First, lipid-induced hypertriglyceridemia was more strongly observed in male ddY mice than in C57BL/6N or ICR mice. Second, the administration of olive and soybean oils remarkably represented lipid-induced hypertriglyceridemia. Third, fasting period before the OLTT largely affected the plasma triglyceride elevation. Fasting for 12 h, but less than 48 h, provoked lipid-induced hypertriglyceridemia. Fourth, we explored the suppressive effects of epigallocatechin gallate (EGCG), a green tea polyphenol, on lipid-induced hypertriglyceridemia. The administration of 100 mg/kg of EGCG suppressed lipid-induced hypertriglyceridemia and intestinal lipase activity. Fifth, EGCG-induced suppressive effects were observed after lipid-induced hypertriglyceridemia was observed in male mice, but not in female mice. Lastly, lipid-induced hypertriglyceridemia could be more effectively induced in mice fed a high-fat diet for 1 week before the OLTT. These findings indicate that male ddY mice after 12 h fasting displayed marked lipid-induced hypertriglyceridemia in response to soybean oil. Hence, the defined experiment condition may be a more appropriate OLTT model for evaluating lipid-induced hypertriglyceridemia.

Many health organizations have promoted the importance of the health-related benefits of physical fitness and physical activity. Studies have evaluated effective public health practice aiming to understand the cognition of physical activity among youths and adolescents. However, studies investigating the level of cognition and knowledge of physical fitness among Asian adults are lacking.

This study aimed to investigate the self-awareness level of physical fitness and exercise prescription and the demand for physical fitness assessment among Taiwanese adults.

In January-July 2019, a cross-sectional anonymous survey was conducted using Research Electronic Data Capture to gather data on demographic data, cognition investigation of physical fitness and exercise prescription, cognitive test of physical fitness and exercise prescription, and demand for physical fitness assessment.

The questionnaire was answered by 200 respondents. The rating for cognition investigation of physical fitness was 2.63-3.13 (unc for health organizations and professionals in the development and management of promotion strategies on health-related physical fitness in preventive medicine and health promotion.

This is the first study to report on the demand for cognition, assessment, and promotion of physical fitness among Taiwanese adults. The study shows that the subjects widely lack knowledge in the cognition of physical fitness and exercise prescription. Furthermore, a self-pay service for the physical fitness assessment and individualized exercise prescription were acceptable to most subjects, especially those undergoing regular health examinations. The findings are encouraging and will aid support for health organizations and professionals in the development and management of promotion strategies on health-related physical fitness in preventive medicine and health promotion.The recent literature shows that the type of gambling practiced influences problem gambling. This study was aimed at investigating the factors associated with gambling type, including gambling severity, gambling motives, and cognitive distortions. A total of 291 regular male gamblers (229 skill gamblers and 62 mixed gamblers, i.e., those who play at least one game of chance and one skill game) were recruited online and assessed for gambling severity (South Oaks Gambling Screen), gambling motives (Gambling Motives Questionnaire-Financial), cognitive distortions (Gambling-Related Cognition Scale), and psychological distress (Hospital Anxiety and Depression Scale). After controlling for the number of games played and psychological distress, we found that gambling type was significantly associated with gambling severity. Moreover, controlling for psychological distress showed that gambling type was also significantly associated with coping motives and interpretative bias. First, mixed gamblers had higher severity scores and higher coping motivation than skill gamblers; second, skill gamblers seemed more at risk of developing interpretative bias. Thus, the gamblers presented different psychological, motivational, and cognitive profiles according to gambling type, indicating that different clinical interventions may be relevant. Working on coping motives and anxiety and depression symptoms with an abstinence purpose would be more suitable for mixed gamblers. Indeed, working on these points could lead to the gambler reducing or eventually ceasing gambling, as the need to regulate negative emotions through gambling behavior would fade in parallel. Gambling type, psychological distress, gambling motives, and cognitive distortions should be taken into consideration systematically in clinical interventions of patients with plural and mixed practice of games.The progress of next-generation sequencing has lead to the availability of massive data sets used by a wide range of applications in biology and medicine. This has sparked significant interest in using modern Big Data technologies to process this large amount of information in distributed memory clusters of commodity hardware. Several approaches based on solutions such as Apache Hadoop or Apache Spark, have been proposed. These solutions allow developers to focus on the problem while the need to deal with low level details, such as data distribution schemes or communication patterns among processing nodes, can be ignored. However, performance and scalability are also of high importance when dealing with increasing problems sizes, making in this way the usage of High Performance Computing (HPC) technologies such as the message passing interface (MPI) a promising alternative. Recently, MetaCacheSpark, an Apache Spark based software for detection and quantification of species composition in food samples has been proposed.