Thyroid hormone triiodothyronine (T₃) plays an important role in coordinated endochondral ossification and hypertrophic differentiation of the growth plate, while aberrant thyroid hormone function appears to be related to skeletal malformations, osteoarthritis, and Kashin-Beck disease. The T-2 toxin, present extensively in cereal grains, and one of its main metabolites, HT-2 toxin, are hypothesized to be potential factors associated with hypertrophic chondrocyte-related osteochondropathy, known as the Kashin-Beck disease. In this study, we investigated the effects of T₃ and HT-2 toxin on human chondrocytes. The immortalized human chondrocyte cell line, C-28/I2, was cultured in four different groups: controls, and cultures with T₃, T₃ plus HT-2 and HT-2 alone. Cytotoxicity was assessed using an MTT assay after 24-h-exposure. Quantitative RT-PCR was used to detect gene expression levels of collagen types II and X, aggrecan and runx2, and the differences in runx2 were confirmed with immunoblot analysis. T₃ was only slightly cytotoxic, in contrast to the significant, dose-dependent cytotoxicity of HT-2 alone at concentrations ≥ 50 nM. T₃, together with HT-2, significantly rescued the cytotoxic effect of HT-2. HT-2 induced significant increases in aggrecan and runx2 gene expression, while the hypertrophic differentiation marker, type X collagen, remained unchanged. Thus, T₃ protected against HT-2 induced cytotoxicity, and HT-2 was an inducer of the pre-hypertrophic state of the chondrocytes.

Background: Short video platforms have become important channels for the public to obtain health information, but the quality of health science popularization content varies greatly. Existing studies lack a comprehensive exploration of the determinants of video quality and their interaction mechanisms. Objective: This study aimed to identify the key features influencing the quality of cerebrovascular disease health science popularization short videos and clarify their configurational effects. Methods: Python web-crawling technology was used to collect health science popularization short videos on TikTok related to cerebrovascular diseases over the past year, and the video quality was evaluated using the Grade Quality Score (GQS) tool by two medical professionals. Eight machine learning models were constructed to identify key quality-related features. The joint effect of six features was analyzed for necessity and sufficiency by using the fuzzy set qualitative comparative analysis (fsQCA) method. Finally, the Kruskal-Wallis H test was employed to evaluate differences in quality among videos of varying duration. Results: A total of 541 valid videos were collected. Most videos were posted by medical staff (77.27%), among which high-quality videos (with GQS > 3) accounted for 14.42%. The importance of video duration reached 30.5%, making it the most crucial feature affecting video quality. The fsQCA results indicated that short duration was one of the conditions for high-quality videos, with the optimal duration being 3 to 5 minutes. Conclusions: Video duration was the main determinant of the quality of cerebrovascular disease health science popularization short videos. Improving the short-video communication skills of medical professionals and optimizing video duration are effective ways to enhance the quality of health science popularization content.

Background: Health science popularization short videos have become one of the main sources of acquiring disease-related information. However, the quality of such videos on popular short video platforms varies considerably. This study aims to evaluate the quality of the health science popularization short videos about cerebrovascular diseases on two popular short video platforms (TikTok and Kuaishou) in China. Methods: Using Python web crawler, short videos related to cerebrovascular diseases were collected from TikTok and Kuaishou in China, posted from December 10th, 2023, to December 10th, 2024. Ultimately, 915 valid videos were included. Two clinical experts evaluated the quality of the included videos using GQS, mDISCERN, and PEMAT-A/V independently. The median (IQR) was used to describe the features of the short videos, and the Kruskal-Wallis test was used to evaluate the differences between groups. Correlation analysis and the Random Forest regression model were applied to investigate the correlation between the features and the quality score of short videos. Results: Health science popularization short videos related to cerebrovascular diseases on the TikTok platform showed significantly more likes, favorites, comments, and shares ( p < 0.001). The videos on TikTok had a median score of 3 on mDISCERN, a median score of 3 on GQS, a median Understandability score of 65.38%, and a median Actionability score of 50%, all of which were significantly higher than those on Kuaishou. There were strong correlations between video duration and mDISCERN score ( r = 0.219, p < 0.001), GQS ( r = 0.495, p < 0.001), Understandability score ( r = 0.282, p < 0.001), and Actionability score ( r = 0.361, p < 0.001). The four Random Forest regression models for video quality scores demonstrated favorable fitting performance, with R ² values ranging from 0.862 to 0.903. Conclusion: Health science popularization short videos related to cerebrovascular diseases on TikTok and Kuaishou showed a moderate quality, and the quality of the health science popularization short videos on TikTok was better than those on Kuaishou. Video duration was a key determinant of video quality.