Exploring factors associated with deterioration in mental health among foreign technical intern trainees: a 6-month follow-up study.

To investigate factors contributing to the mental health of Vietnamese technical intern trainees in the food manufacturing industry, a questionnaire survey was conducted twice with a six-month interval. A total of 111 technical trainees who participated in two surveys were included in the analysis. We used a mixed-effects model, where items with statistically significant associations in the univariate analysis were fixed effects, factories were random effects, and the outcome was defined as the K6 score at follow-up. The mean K6 score increased from 3.13 (SD 3.5) at baseline to 3.86 (SD 4.1) at follow-up, with 26.1% and 34.2% exhibiting poor mental health (K6≥5) at baseline and follow-up, respectively. Insomnia and years of training experience were significantly associated with the K6 score at follow-up. Those with insomnia had significantly higher K6 score at follow-up. Compared to the first year of training, K6 score at follow-up increased significantly for training in their third year or more. It is important to understand the sleeping conditions of trainees and support them based on their years of training experience.

Development of a Prediction Model for Subjective Physical Symptoms Induced During Systematic Anatomy Practice Among Medical Students.

To prevent unpleasant symptoms in medical students during systematic anatomy practice, we aimed to develop and validate a model that predicts the likelihood of these symptoms occurring during practice based on risk factors prior to the start of practice. A total of 452 medical students enrolled from 2014 to 2018 were surveyed before and during practice, with questions regarding their sex, psychological status, subjective symptoms, and allergies. The sum of the scores concerning three subjective symptoms related to the eyes and three subjective symptoms related to the nose and fatigue were defined as the "eye-score" and "mask-score," respectively, and a total score of 7 or more was considered symptomatic. A prediction model was developed based on a generalized linear mixed model; the outcome variable in the model was symptoms during practice, and the explanatory variables were indoor formaldehyde concentration during practice, sex, and pre-practice status, such as the students' psychological state, eye-score, mask-score, and the presence of allergies. Five-fold cross-validation was used to assess internal validity and the prediction model was applied to 110 medical students enrolled in 2021 to assess external validity. The sensitivity and specificity by five-fold cross-validation were 0.843 and 0.314 for eye symptoms and 0.847 and 0.432 for mask symptoms. In the external validity assessment, the sensitivity and specificity were 0.889 and 0.207 for eye symptoms and 0.879 and 0.532 for mask symptoms. The prediction model developed in this study can be used in future measures aimed at preventing symptoms in students.

Microbial decomposition of biodegradable plastics on the deep-sea floor.

Microbes can decompose biodegradable plastics on land, rivers and seashore. However, it is unclear whether deep-sea microbes can degrade biodegradable plastics in the extreme environmental conditions of the seafloor. Here, we report microbial decomposition of representative biodegradable plastics (polyhydroxyalkanoates, biodegradable polyesters, and polysaccharide esters) at diverse deep-sea floor locations ranging in depth from 757 to 5552 m. The degradation of samples was evaluated in terms of weight loss, reduction in material thickness, and surface morphological changes. Poly(L-lactic acid) did not degrade at either shore or deep-sea sites, while other biodegradable polyesters, polyhydroxyalkanoates, and polysaccharide esters were degraded. The rate of degradation slowed with water depth. We analysed the plastic-associated microbial communities by 16S rRNA gene amplicon sequencing and metagenomics. Several dominant microorganisms carried genes potentially encoding plastic-degrading enzymes such as polyhydroxyalkanoate depolymerases and cutinases/polyesterases. Analysis of available metagenomic datasets indicated that these microorganisms are present in other deep-sea locations. Our results confirm that biodegradable plastics can be degraded by the action of microorganisms on the deep-sea floor, although with much less efficiency than in coastal settings.