Three-dimensional (3D) printed models represent educational tools of high quality compared with traditional teaching aids. Colored skull models were produced by 3D printing technology. A randomized controlled trial (RCT) was conducted to compare the learning efficiency of 3D printed skulls with that of cadaveric skulls and atlas. Seventy-nine medical students, who never studied anatomy, were randomized into three groups by drawing lots, using 3D printed skulls, cadaveric skulls, and atlas, respectively, to study the anatomical structures in skull through an introductory lecture and small group discussions. All students completed identical tests, which composed of a theory test and a lab test, before and after a lecture. Pre-test scores showed no differences between the three groups. In post-test, the 3D group was better than the other two groups in total score (cadaver: 29.5 [IQR: 25–33], 3D: 31.5 [IQR: 29–36], atlas: 27.75 [IQR: 24.125–32]; p = 0.044) and scores of lab test (cadaver: 14 [IQR: 10.5–18], 3D: 16.5 [IQR: 14.375–21.625], atlas: 14.5 [IQR: 10–18.125]; p = 0.049). Scores involving theory test, however, showed no difference between the three groups. In this RCT, an inexpensive, precise and rapidly-produced skull model had advantages in assisting anatomy study, especially in structure recognition, compared with traditional education materials.

BackgroundSelf-medication with antibiotics (SMA) has been reported among university students in many countries, but little research has been done on this issue in China. The objective of this study was to evaluate knowledge and behaviors of university students and risk factors concerning SMA.Methodology/Principal FindingsUsing a novel questionnaire-based data collection instrument, an anonymous online survey was conducted with the students of Shantou University (STU), a university comprising 8 schools/colleges in eastern Guangdong, China. Of 1,300 respondents (13.8% of total eligible participants), 47.8% had self-treated with antibiotics. Logistic regression analysis identified prior knowledge of antibiotics (PKA), older age, and higher monthly allowance as independent risk factors for SMA. PKA significantly influenced students' knowledge about antibiotics, their uses, and common adverse reactions (all p<0.05). Among self-medicated students, 61.7% used antibiotics at least twice in the previous year. Community pharmacies were the major source of self-prescribed antibiotics. Reported common indications for SMA were sore throat (59.7%), fever (38.2%), cough (37.4%), runny nose (29.3%), and nasal congestion (28.7%). While 74.1% of self-medication episodes were based on students' own experiences, only 31.1% of students claimed to understand the package insert. Alteration of antibiotics and dosage during the course of self-treatment was made by 63.8% and 55.6% of students, respectively. At least two kinds of antibiotics were simultaneously taken by 82.6% of students. The majority of self-medicated students failed to complete the course of antibiotics. Adverse reactions were reported by 16.3% of students. Amoxicillin was the most common antibiotic used for self-medication.ConclusionsHigh prevalence of SMA was noted among STU students. Presence of risk factors and risk-associated behaviors/attitudes in the study population calls for focused educational intervention and stricter governmental legislation and regulation of antibiotic use and sale in pharmacies.

BackgroundAir pollution in Beijing, especially PM2.5, has received increasing attention in the past years. Despite Beijing being one of the most polluted cities in the world, there has still been a lack of quantitative research regarding the health impact of PM2.5 on the impact of diseases in Beijing. In this study, we aimed to characterize temporal pattern of PM2.5 and its potential association with human influenza in Beijing.MethodsBased on the data collected on hourly ambient PM2.5 from year 2008 to 2013 and on monthly human influenza cases from 2008 and 2011, we investigated temporal patterns of PM2.5 over the five-year period and utilized the wavelet approach to exploring the potential association between PM2.5 and influenza.ResultsOur results found that ambient PM2.5 pollution was severe in Beijing with PM2.5 concentrations being significantly higher than the standards of the World Health Organization, the US EPA, and the Chinese EPA in the majority of days during the study period. Furthermore, PM2.5 concentrations in the winter heating seasons were higher than those in non-heating seasons despite high variations. We also found significant association between ambient PM2.5 peak and human influenza case increase with a delayed effect (e.g. delayed effect of PM2.5 on influenza).ConclusionsAmbient PM2.5 concentrations were significantly associated with human influenza cases in Beijing, which have important implications for public health and environmental actions.