Joint Diseases and Related Surgery (JDRS), the official journal of the Turkish Joint Diseases Foundation, is an international, peer-reviewed, immediate open access journal. All published articles in JDRS has been free for everyone, without embargo, since 1990.

Objective: Patients increasingly seek health-related information through artificial intelligence (AI)-based chatbots. However, the reliability and clinical quality of chatbot-generated patient information remain uncertain. This study aimed to evaluate the quality and reliability of chatbot-generated responses to frequently asked patient questions regarding benign bone tumors using a structured assessment model. Methods: This descriptive and methodological study comprised twenty patient-centered commonly asked questions formulated by three fellowship-trained orthopedic oncology specialists. The inquiries encompassed diagnosis, treatment, complications, follow-up, and lifestyle-related issues pertaining to prevalent benign bone tumors. The responses produced by ChatGPT-5.2 were assessed separately by three independent orthopedic oncology specialists who had no role in formulating the questions. The quality of the response was evaluated using the Quality Analysis of Medical Artificial Intelligence (QAMAI) methodology, encompassing accuracy, clarity, relevance, completeness, citation of sources and references, and utility. Each parameter was evaluated using a five-point Likert scale. The intraclass correlation coefficient (ICC) was employed to assess interobserver reliability. Results: The greatest scores were observed in accuracy (mean score 4.27), but completeness (3.19) and the provision of sources and references (3.03) displayed somewhat lower values. The overall QAMAI score was 21.39 out of 30, reflecting good response quality consistent with the validated scoring range of 18–23 points. Interobserver agreement demonstrated good reliability for total QAMAI scores (ICC = 0.84; 95% CI: 0.74–0.91). The subdomain ICC values ranged from moderate to good agreement. Conclusion: Chatbot-generated responses provide accurate and useful preliminary information on benign bone tumors. However, shortcomings in completeness and reliance on evidence-based citations indicate that chatbot outputs should be employed under the oversight of a physician. AI chatbots can aid in patient education but cannot replace clinical decision-making processes.

Joint Diseases and Related Surgery (JDRS), the official journal of the Turkish Joint Diseases Foundation, is an international, peer-reviewed, immediate open access journal. All published articles in JDRS has been free for everyone, without embargo, since 1990.

Benign and Benign Aggressive Bone Lesions Located in the Femoral Head and Neck: Single-center Experience - European Archives of Medical Research

Central chondrosarcoma is the second most common primary malignant bone tumour, and grade progression markedly worsens prognosis. The contributions of lipid metabolic reprogramming and epigenetic co-dysregulation to grade progression remain poorly characterised. We integrated a bulk RNA-seq discovery cohort of 53 graded central chondrosarcomas (GSE299759) with a single-cell analysis of eight chondrosarcomas (GSE184118). Because the atypical cartilaginous tumour (ACT) and dedifferentiated groups each comprised only three samples, the Grade 3 versus Grade 2 contrast was pre-specified as the primary comparison. Curated panels of 44 lipid metabolism genes and 50 epigenetic regulators were assessed by differential expression and a correlation-based connectivity ranking, evaluated by permutation testing. In the primary Grade 3 versus Grade 2 comparison, SQLE, ACACA, and FASN were upregulated (FDR < 0.05), indicating a grade-associated increase in de novo lipogenesis. In the exploratory Grade 3 versus ACT comparison, additional lipid genes (HMGCR, LDLRAP1) and the epigenetic regulators EHMT2 and SIRT2 showed altered expression, although the small ACT group limits these estimates. A connectivity ranking highlighted FASN, KMT2C, TET2, SETD5, and KDM5B; permutation testing confirmed this co-expression structure was non-random (p < 0.0001). Single-cell analysis showed FASN, SETD5, and KDM5B are expressed predominantly in malignant cells, whereas KMT2C and TET2 are not, indicating cell-type heterogeneity. De novo lipogenesis upregulation is the most consistent lipid alteration in high-grade central chondrosarcoma, nominating SQLE, ACACA, and FASN as candidates for experimental investigation.