Objective:To investigate the inpact of thyroid cancer-derived cancer-associated fibroblasts(CAF) autophagy on papillary thyroid cancer(PTC).Methods:CAF and normal fibroblasts were isolated from cancerous and adjacent normal thyroid tissues from four PTC patients. Expressions of fibroblast activation protein(FAP) and α-smooth muscle actin in cells were assessed. Conditioned medium of CAF and normal fibroblasts were prepared and used to culture PTC cells. The effects of CAF and normal fibroblasts on survival, proliferation, migration, invasion and iodine uptake of PTC cells were evaluated through cell proliferation assay, cell scratch assay, cell invasion assay, and cell iodine uptake assay. The autophagy level of CAF was also evaluated. Autophagy inhibition and activation were used to regulate the autophagy of CAF, and then their effects on PTC cell proliferation, migration and invasion were further evaluated. The in vivo effect of CAF autophagy on PTC xenograft tumor growth was evaluated.Results:CAF exhibited higher FAP expression and basal autophagy levels. PTC cells co-cultured with CAF-conditioned media showed enhanced proliferation, migration, invasion, and reduced iodine uptake. Autophagy inhibition reduced these effects, while autophagy activation further promoted them. In vivo, inhibiting CAF autophagy suppressed tumor growth.Conclusions:CAF promotes PTC cell malignancy through autophagy activation, enhancing proliferation, migration, and invasion while reducing iodine uptake.

Objective To explore the clinical effect of transcranial direct current stimulation(tDCS)treatment strategy based on bi-modal balance model on upper limb dysfunction after ischemic stroke.Methods From October,2023 to December,2024,60 patients with ischemic stroke in General Hospital of Ningxia Medi-cal University were randomly divided into control group(n=30)and experimental group(n=30).Both groups received basic rehabilitation,the control group received tDCS based on the theory of interhemispheric competi-tion model,and the experimental group received tDCS based on the theory of bimodal equilibrium model,for four weeks.Before and after intervention,the effect of both groups was evaluated using Fugl-Meyer Assessment-Upper Extremities(FMA-UE),modified Ashworth Scale(MAS),Action Research Arm Test(ARAT)and modi-fied Barthel Index(MBI).Neurophysiological parameters such as cortical latency(CL)and central motor conduc-tion time(CMCT)were detected and correlated analysis was performed.Results Two cases in the control group and one in the experimental group dropped down.After intervention,the scores of FMA-UE,ARAT and MBI increased in both groups(|t|>13.748,P<0.001),and the above scores were higher in the experimental group than in the control group(|t|>2.321,P<0.05);the MAS grade of the elbow flexor muscle group improved in the experimental group(|Z|=2.095,P<0.05).The CL and CMCT in both groups de-creased(|t|>2.752,P<0.001),and they were better in the experimental group than in the control group(|t|>2.082,P<0.05).There was a correlation between FMA-UE and CMCT(r=-0.433,P<0.05).Conclusion tDCS based on bimodal balance model can improve upper limb dysfunction more effectively in patients with ischemic stroke.

Objective:To explore the application value of problem-based learning (PBL) combined with mini-clinical evaluation exercise (Mini-CEX) in the development of post competency for interns in the Department of Neurology.Methods:A total of 56 interns rotating at the Department of Neurology of The First Affiliated Hospital of Chongqing Medical University from June 2023 to January 2024 were enrolled as the study subjects. They were randomly divided into a control group and an experiment group using the random number table method, with 28 interns in each group. The control group received traditional methods including small lectures and teaching rounds, while the experimental group received the PBL teaching method combined with Mini-CEX. The teaching effectiveness was evaluated through theoretical assessments, practical skill evaluations, teacher and student satisfaction surveys, and Mini-CEX scale assessments conducted at the beginning, middle, and end of the rotation for the experimental group. The data were analyzed using SPSS 23.0 software. For continuous data, the independent-samples t test or Mann-Whitney U test was used for comparison between groups. The chi-square test was used for categorical data and the Kruskal-Wallis H test for repeated-measurement data. Results:The theoretical scores [(45.36±2.67) vs. (42.00±4.29), P<0.01] and practical skill scores [(45.11±2.53) vs. (42.39±4.53), P<0.01] were significantly higher in the experimental group compared to the control group. The Mini-CEX score of the experimental group at the end of the rotation was notably higher than that at the beginning of rotation ( P<0.05), and their abilities improved continuously. The satisfaction rates of teachers and students in the experimental group were 71.43% (20/28) and 67.86% (19/28), respectively, which were significantly higher than those in the control group [39.29% (11/28) and 35.71% (10/28), P<0.05]. Conclusions:The teaching model integrating PBL and Mini-CEX can effectively enhance the post competency of interns in the Department of Neurology, thus offering a new perspective for clinical undergraduate teaching.

Objective:To investigate the inpact of thyroid cancer-derived cancer-associated fibroblasts(CAF) autophagy on papillary thyroid cancer(PTC).Methods:CAF and normal fibroblasts were isolated from cancerous and adjacent normal thyroid tissues from four PTC patients. Expressions of fibroblast activation protein(FAP) and α-smooth muscle actin in cells were assessed. Conditioned medium of CAF and normal fibroblasts were prepared and used to culture PTC cells. The effects of CAF and normal fibroblasts on survival, proliferation, migration, invasion and iodine uptake of PTC cells were evaluated through cell proliferation assay, cell scratch assay, cell invasion assay, and cell iodine uptake assay. The autophagy level of CAF was also evaluated. Autophagy inhibition and activation were used to regulate the autophagy of CAF, and then their effects on PTC cell proliferation, migration and invasion were further evaluated. The in vivo effect of CAF autophagy on PTC xenograft tumor growth was evaluated.Results:CAF exhibited higher FAP expression and basal autophagy levels. PTC cells co-cultured with CAF-conditioned media showed enhanced proliferation, migration, invasion, and reduced iodine uptake. Autophagy inhibition reduced these effects, while autophagy activation further promoted them. In vivo, inhibiting CAF autophagy suppressed tumor growth.Conclusions:CAF promotes PTC cell malignancy through autophagy activation, enhancing proliferation, migration, and invasion while reducing iodine uptake.

Objective To explore the clinical effect of transcranial direct current stimulation(tDCS)treatment strategy based on bi-modal balance model on upper limb dysfunction after ischemic stroke.Methods From October,2023 to December,2024,60 patients with ischemic stroke in General Hospital of Ningxia Medi-cal University were randomly divided into control group(n=30)and experimental group(n=30).Both groups received basic rehabilitation,the control group received tDCS based on the theory of interhemispheric competi-tion model,and the experimental group received tDCS based on the theory of bimodal equilibrium model,for four weeks.Before and after intervention,the effect of both groups was evaluated using Fugl-Meyer Assessment-Upper Extremities(FMA-UE),modified Ashworth Scale(MAS),Action Research Arm Test(ARAT)and modi-fied Barthel Index(MBI).Neurophysiological parameters such as cortical latency(CL)and central motor conduc-tion time(CMCT)were detected and correlated analysis was performed.Results Two cases in the control group and one in the experimental group dropped down.After intervention,the scores of FMA-UE,ARAT and MBI increased in both groups(|t|>13.748,P<0.001),and the above scores were higher in the experimental group than in the control group(|t|>2.321,P<0.05);the MAS grade of the elbow flexor muscle group improved in the experimental group(|Z|=2.095,P<0.05).The CL and CMCT in both groups de-creased(|t|>2.752,P<0.001),and they were better in the experimental group than in the control group(|t|>2.082,P<0.05).There was a correlation between FMA-UE and CMCT(r=-0.433,P<0.05).Conclusion tDCS based on bimodal balance model can improve upper limb dysfunction more effectively in patients with ischemic stroke.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.