Background: The widespread use of artificial intelligence, such as ChatGPT (OpenAI), is transforming sectors, including health care, while separate advancements of the internet have enabled platforms such as China’s DingXiangYuan to offer remote medical services. Objective: This study evaluates ChatGPT-4’s responses against those of professional health care providers in telemedicine, assessing artificial intelligence’s capability to support the surge in remote medical consultations and its impact on health care delivery. Methods: We sourced remote orthopedic consultations from “Doctor DingXiang,” with responses from its certified physicians as the control and ChatGPT’s responses as the experimental group. In all, 3 blindfolded, experienced orthopedic surgeons assessed responses against 7 criteria: “logical reasoning,” “internal information,” “external information,” “guiding function,” “therapeutic effect,” “medical knowledge popularization education,” and “overall satisfaction.” We used Fleiss κ to measure agreement among multiple raters. Results: Initially, consultation records for a cumulative count of 8 maladies (equivalent to 800 cases) were gathered. We ultimately included 73 consultation records by May 2023, following primary and rescreening, in which no communication records containing private information, images, or voice messages were transmitted. After statistical scoring, we discovered that ChatGPT’s “internal information” score (mean 4.61, SD 0.52 points vs mean 4.66, SD 0.49 points; P=.43) and “therapeutic effect” score (mean 4.43, SD 0.75 points vs mean 4.55, SD 0.62 points; P=.32) were lower than those of the control group, but the differences were not statistically significant. ChatGPT showed better performance with a higher “logical reasoning” score (mean 4.81, SD 0.36 points vs mean 4.75, SD 0.39 points; P=.38), “external information” score (mean 4.06, SD 0.72 points vs mean 3.92, SD 0.77 points; P=.25), and “guiding function” score (mean 4.73, SD 0.51 points vs mean 4.72, SD 0.54 points; P=.96), although the differences were not statistically significant. Meanwhile, the “medical knowledge popularization education” score of ChatGPT was better than that of the control group (mean 4.49, SD 0.67 points vs mean 3.87, SD 1.01 points; P<.001), and the difference was statistically significant. In terms of “overall satisfaction,” the difference was not statistically significant between the groups (mean 8.35, SD 1.38 points vs mean 8.37, SD 1.24 points; P=.92). According to how Fleiss κ values were interpreted, 6 of the control group’s score points were classified as displaying “fair agreement” (P<.001), and 1 was classified as showing “substantial agreement” (P<.001). In the experimental group, 3 points were classified as indicating “fair agreement,” while 4 suggested “moderate agreement” (P<.001). Conclusions: ChatGPT-4 matches the expertise found in DingXiangYuan forums’ paid consultations, excelling particularly in scientific education. It presents a promising alternative for remote health advice. For health care professionals, it could act as an aid in patient education, while patients may use it as a convenient tool for health inquiries.

Tendon‐derived stem cells (TDSCs) play a vital role in repair of rotator cuff tear injuries by secreting paracrine proteins that regulate resident cell functions. Secreted exosomes may play a role in tendon injury repair by mediating intercellular communication; however, the detailed mechanisms by which TDSC‐derived exosomes affect tenocyte development remain unknown. Here, we examined the effects of exosomes isolated from conditioned medium of TDSCs on tenocyte differentiation, migration, and transition to a fibroblastic phenotype in vitro. Successful isolation of exosomes from TDSCs was confirmed by high expression levels of CD81, CD63, CD9, and TSG101. Treatment with TDSC‐derived exosomes promoted the growth and migration of cultured rat tenocytes, and increased the levels of the fibrosis markers collagen I, collagen III, scleraxis, tenascin C, and α‐smooth muscle actin. Furthermore, vascular endothelial growth factor A (VEGFA) expression was higher in TDSC‐derived exosomes than in TDSCs, and genetic knockdown of VEGFA suppressed the stimulatory effect of TDSC‐derived exosomes on tenocyte development. Overall, these results demonstrate that VEGFA‐enriched exosomes isolated from TDSCs promote differentiation and migration of cultured tenocytes and their transition to a fibroblastic phenotype. These data provide a new potential clinical treatment strategy for tendon injury.

Osteosarcoma is one of the most prevalent bone malignancies with a poor prognosis. The N7-methylguanosine (m7G) modification facilitates the modification of RNA structure and function tightly associated with cancer. Nonetheless, there is a lack of joint exploration of the relationship between m7G methylation and immune status in osteosarcoma. With the support of TARGET and GEO databases, we performed consensus clustering to characterize molecular subtypes based on m7G regulators in all osteosarcoma patients. The least absolute shrinkage and selection operator (LASSO) method, Cox regression, and receiver operating characteristic (ROC) curves were employed to construct and validate m7G-related prognostic features and derived risk scores. In addition, GSVA, ssGSEA, CIBERSORT, ESTIMATE, and gene set enrichment analysis were conducted to characterize biological pathways and immune landscapes. We explored the relationship between risk scores and drug sensitivity, immune checkpoints, and human leukocyte antigens by correlation analysis. Finally, the roles of EIF4E3 in cell function were verified through external experiments. Two molecular isoforms based on regulator genes were identified, which presented significant discrepancies in terms of survival and activated pathways. Moreover, the six m7G regulators most associated with prognosis in osteosarcoma patients were identified as independent predictors for the construction of prognostic signature. The model was well stabilized and outperformed traditional clinicopathological features to reliably predict 3-year (AUC = 0.787) and 5-year (AUC = 0.790) survival in osteosarcoma cohorts. Patients with increased risk scores had a poorer prognosis, higher tumor purity, lower checkpoint gene expression, and were in an immunosuppressive microenvironment. Furthermore, enhanced expression of EIF4E3 indicated a favorable prognosis and affected the biological behavior of osteosarcoma cells. We identified six prognostic relevant m7G modulators that may provide valuable indicators for the estimation of overall survival and the corresponding immune landscape in patients with osteosarcoma.

Malignant transformation is concomitant with excessive activation of stress response pathways. Heat shock proteins (HSPs) are stress-inducible proteins that play a role in folding and processing proteins, contributing to the non-oncogene addiction of stressed tumor cells. However, the detailed role of the HSP family in osteosarcoma has not been investigated. Bulk and single-cell transcriptomic data from the GEO and TARGET databases were used to identify HSPs associated with prognosis in osteosarcoma patients. The expression level of HSPD1 was markedly increased in osteosarcoma, correlating with a negative prognosis. Through in vitro and in vivo experiments, we systematically identified HSPD1 as an important contributor to the regulation of proliferation, metastasis, and apoptosis in osteosarcoma by promoting the epithelial-mesenchymal transition (EMT) and activating AKT/mTOR signaling. Subsequently, ATP5A1 was determined as a potential target of HSPD1 using immunoprecipitation followed by mass spectrometry. Mechanistically, HSPD1 may interact with ATP5A1 to reduce the K48-linked ubiquitination and degradation of ATP5A1, which ultimately activates the AKT/mTOR pathway to ensure osteosarcoma progression and EMT process. These findings expand the potential mechanisms by which HSPD1 exerts biological effects and provide strong evidence for its inclusion as a potential therapeutic target in osteosarcoma.