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Abstract Background Every year, volunteers of the Belgian Red Cross provide onsite medical care at more than 8000 mass gathering events and other manifestations. Today standardized planning tools for optimal preventive medical resource use during these events are lacking. This study aimed to develop and validate a prediction model of patient presentation rate (PPR) and transfer to hospital rate (TTHR) at mass gatherings in Belgium. Methods More than 200,000 medical interventions from 2006 to 2018 were pooled in a database. We used a subset of 28 different mass gatherings (194 unique events) to develop a nonlinear prediction model. Using regression trees, we identified potential predictors for PPR and TTHR at these mass gatherings. The additional effect of ambient temperature was studied by linear regression analysis. Finally, we validated the prediction models using two other subsets of the database. Results The regression tree for PPR consisted of 7 splits, with mass gathering category as the most important predictor variable. Other predictor variables were attendance, number of days, and age class. Ambient temperature was positively associated with PPR at outdoor events in summer. Calibration of the model revealed an R 2 of 0.68 (95% confidence interval 0.60–0.75). For TTHR, the most determining predictor variables were mass gathering category and predicted PPR (R 2 = 0.48). External validation indicated limited predictive value for other events (R 2 = 0.02 for PPR; R 2 = 0.03 for TTHR). Conclusions Our nonlinear model performed well in predicting PPR at the events used to build the model on, but had poor predictive value for other mass gatherings. The mass gathering categories “outdoor music” and “sports event” warrant further splitting in subcategories, and variables such as attendance, temperature and resource deployment need to be better recorded in the future to optimize prediction of medical usage rates, and hence, of resources needed for onsite emergency medical care.

Objective: As more states legalize cannabis in the US, marketing from the cannabis industry and news coverage of cannabis have increased. Sources of information on cannabis can influence beliefs about risks and benefits. Yet, little is known about how the use and influence of specific sources of information have changed over time., Method: We conducted a longitudinal study of 5053 US adults between 2017 and 2021. Participants were asked about sources of information on cannabis risks and benefits and which sources were most influential using a web-based survey at three different time points (2017, 2020, 2021). We evaluated changes in the use/influence of multiple sources of information from 2017 to 2021 and examined interactions with age, cannabis use and state cannabis legal status., Results: The largest increases in sources of information on cannabis benefits and risks were in use of health professionals (+5.5% for benefits and +17.4% for risks). The largest declines were in use of traditional media (TV, radio, newspapers) (-12.3% and -11.4%). Use of cannabis advertisements and dispensaries/other industry sources also significantly increased. Health professionals were the most influential source of information in all three waves regardless of age, cannabis use or state legal status., Conclusions: Participants sought information from different sources, and increasingly relied on health professionals as a primary source, highlighting the need to train healthcare providers about cannabis risks and benefits. While fewer people used traditional media, use of industry sources increased, underscoring the need for accurate cannabis information sources.

Background: Every year, volunteers of the Belgian Red Cross provide onsite medical care at more than 8000 mass gathering events and other manifestations. Today standardized planning tools for optimal preventive medical resource use during these events are lacking. This study aimed to develop and validate a prediction model of patient presentation rate (PPR) and transfer to hospital rate (TTHR) at mass gatherings in Belgium.Methods: More than 200,000 medical interventions from 2006 to 2018 were pooled in a database. We used a subset of 28 different mass gatherings (194 unique events) to develop a nonlinear prediction model. Using regression trees, we identified potential predictors for PPR and TTHR at these mass gatherings. The additional effect of ambient temperature was studied by linear regression analysis. Finally, we validated the prediction models using two other subsets of the database.Results: The regression tree for PPR consisted of 7 splits, with mass gathering category as the most important predictor variable. Other predictor variables were attendance, number of days, and age class. Ambient temperature was positively associated with PPR at outdoor events in summer. Calibration of the model revealed an R2 of 0.68 (95% confidence interval 0.60-0.75). For TTHR, the most determining predictor variables were mass gathering category and predicted PPR (R2 = 0.48). External validation indicated limited predictive value for other events (R2 = 0.02 for PPR; R2 = 0.03 for TTHR).Conclusions: Our nonlinear model performed well in predicting PPR at the events used to build the model on, but had poor predictive value for other mass gatherings. The mass gathering categories "outdoor music" and "sports event" warrant further splitting in subcategories, and variables such as attendance, temperature and resource deployment need to be better recorded in the future to optimize prediction of medical usage rates, and hence, of resources needed for onsite emergency medical care. [ABSTRACT FROM AUTHOR]

Musk, apart from its other usages, is a kind of animal medicine which is considered as one of the singular drugs. In this study, various widespread usages of this medical substance and its reflection in Persian poetry are dealt with in order to clarify some of verses and describing their images as a model for further researches.

Berry fruits possess many positive effects on human health because of their phytochemical contents like phenolic compounds, antioxidants and anthocyanins, and they have also an important place among the functional foods. From the varieties of Isabella grape and Bursa-2 blackberry cultivated in Duzce and its neighborhood, aging-retardant cream, vinegar (cyme) which aids in the weight loss and alleviates the stomach discomfort, and grape and blackberry juice are produced. Besides, other berry fruits are also used but only in the form of folk medicine. Thus, further studies about the berry fruits grown in the region may increase the potential medical usages of those plants. [ABSTRACT FROM AUTHOR]

The Qinling-Daba Mountains area is the main producing areas of Gynostemma longipes for medicinal usage, and samples of wild whole plants in Pingli, Shaanxi Province and Qingchuan, Sichuan Province were collected. The ultra-high performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry(UHPLC-Q-TOF-MS~E) was used to profile the chemical compositions and analyze the similarities and differences of G. longipes samples in these areas. Based on the accurate molecular weight and fragment information obtained from Q-TOF-MS~E, the structures of the main components were identified by combining with the mass spectra, chromatographic behaviors of reference standards and related literatures. The results showed that the components of wild G. longipes from different places among Qinling-Daba Mountains area were similar. Forty-five chemical components were identified in the whole plant of G. longipes from Pingli, Shaanxi Province, including 43 triterpenoid saponins and 2 flavonoids which contain all main peaks in its fingerprint. The main components are dammarane-type triterpenoid saponins, such asgypenoside ⅩLⅨ, gypenoside A and its malonylated product of glycosyl.