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.

In recent years, China has been facing the dual challenges of declining fertility rates and births, with male reproductive health issues, especially the decline in semen quality, identified as a pivotal contributor to this phenomenon. Meanwhile, accumulating evidence indicates that air pollutants, an increasingly severe environmental problem, can damage semen quality not only directly through their biological toxicity but also indirectly by disrupting the composition of microbial communities in the gut and semen, thereby dysregulating immune function, endocrine homeostasis, and oxidative stress responses. The gut microbiota and semen microbiota, as important components of the human microecosystem, play crucial roles in maintaining reproductive health. This article comprehensively reviewed the research progress on the potential effects of air pollutants (particulate matter and gaseous pollutants), gut microbiota, and semen microbiota on semen quality. Specifically, it elucidated the mechanisms of interaction between these factors and explored how they affect male fertility.

Cancer multidrug resistance (MDR) impairs the therapeutic efficacy of various chemotherapeutics. Novel approaches, particularly the development of MDR reversal agents, are critically needed to address this challenge. This study demonstrates that tenacissoside I (TI), a compound isolated from Marsdenia tenacissima (Roxb.) Wight et Arn, traditionally used in clinical practice as an ethnic medicine for cancer treatment, exhibits significant MDR reversal effects in ABCB1-mediated MDR cancer cells. TI reversed the resistance of SW620/AD300 and KBV200 cells to doxorubicin (DOX) and paclitaxel (PAC) by downregulating ABCB1 expression and reducing ABCB1 drug transport function. Mechanistically, protein arginine methyltransferase 1 (PRMT1), whose expression correlates with poor prognosis and shows positive association with both ABCB1 and EGFR expressions in tumor tissues, was differentially expressed in TI-treated SW620/AD300 cells. SW620/AD300 and KBV200 cells exhibited elevated levels of EGFR asymmetric dimethylarginine (aDMA) and enhanced PRMT1-EGFR interaction compared to their parental cells. Moreover, TI-induced PRMT1 downregulation impaired PRMT1-mediated aDMA of EGFR, PRMT1-EGFR interaction, and EGFR downstream signaling in SW620/AD300 and KBV200 cells. These effects were significantly reversed by PRMT1 overexpression. Additionally, TI demonstrated resistance reversal to PAC in xenograft models without detectable toxicities. This study establishes TI's MDR reversal effect in ABCB1-mediated MDR human cancer cells through inhibition of PRMT1-mediated aDMA of EGFR, suggesting TI's potential as an MDR modulator for improving chemotherapy outcomes.
Humans ; Protein-Arginine N-Methyltransferases/antagonists & inhibitors* ; Drug Resistance, Neoplasm/drug effects* ; ErbB Receptors/genetics* ; Animals ; Cell Line, Tumor ; Drug Resistance, Multiple/drug effects* ; Methylation/drug effects* ; Saponins/administration & dosage* ; Mice ; Mice, Nude ; Mice, Inbred BALB C ; ATP Binding Cassette Transporter, Subfamily B/genetics* ; Doxorubicin/pharmacology* ; Paclitaxel/pharmacology* ; Female ; Repressor Proteins

Objective To investigate the efficacy of Jianpiwenyang Gel(SSWYG)for treating chronic diarrhea and explore its therapeutic mechanism.Methods Eighty patients with chronic diarrhea of spleen and stomach weakness type were randomized into two groups for interventions with lifestyle adjustment and treatment with bifid triple viable capsules(control group,n=40)or naval application with SSWYG(treatment group,n=40)for one week,after which symptoms of chronic diarrhea were evaluated.The Chinese medicine system pharmacology analysis platform(TCMSP),GeneCards,NCBI,OMIM database and GEO database(GSE14841)were used to obtain the active ingredients and target proteins of SSWYG and chronic diarrhea-related targets.The key targets were obtained by topological analysis for Gene Ontology(GO)and KEGG analyses.The affinity and binding characteristics of SSWYG for specific targets were verified by molecular docking using AutoDock software.Results In both groups,gastrointestinal symptom rating scale(GSRS),Bristol Scale and TCM syndrome scores significantly improved after the treatments(P<0.05),and better effects were observed in the treatment group(P<0.05).Sixty-eight targets of SSWYG in treating chronic diarrhea were obtained,and 33 most probable ones were screened out by topological analysis.GO and KEGG analyses identified several chronic diarrhea-related pathways including the TNF and IL-17 pathways.Molecular docking study showed good affinity of the core components of SSWYG for the key targets CASP3,JNK,IL1B,IL6,and AKT1.JUN and CASP3 had the lowest binding energy and the highest stable binding energy with multiple major active ingredients of SSWYG.Conclusion SSWYG can significantly improve clinical symptoms of chronic diarrhea possibly by regulating the TNF and IL-17 as well as other pathways via CASP3 and JUN,suggesting a complex therapeutic mechanism of SSWYG involving multiple ingredients and targets and coordinated regulation of multiple pathways.

Objective To investigate the efficacy of Jianpiwenyang Gel(SSWYG)for treating chronic diarrhea and explore its therapeutic mechanism.Methods Eighty patients with chronic diarrhea of spleen and stomach weakness type were randomized into two groups for interventions with lifestyle adjustment and treatment with bifid triple viable capsules(control group,n=40)or naval application with SSWYG(treatment group,n=40)for one week,after which symptoms of chronic diarrhea were evaluated.The Chinese medicine system pharmacology analysis platform(TCMSP),GeneCards,NCBI,OMIM database and GEO database(GSE14841)were used to obtain the active ingredients and target proteins of SSWYG and chronic diarrhea-related targets.The key targets were obtained by topological analysis for Gene Ontology(GO)and KEGG analyses.The affinity and binding characteristics of SSWYG for specific targets were verified by molecular docking using AutoDock software.Results In both groups,gastrointestinal symptom rating scale(GSRS),Bristol Scale and TCM syndrome scores significantly improved after the treatments(P<0.05),and better effects were observed in the treatment group(P<0.05).Sixty-eight targets of SSWYG in treating chronic diarrhea were obtained,and 33 most probable ones were screened out by topological analysis.GO and KEGG analyses identified several chronic diarrhea-related pathways including the TNF and IL-17 pathways.Molecular docking study showed good affinity of the core components of SSWYG for the key targets CASP3,JNK,IL1B,IL6,and AKT1.JUN and CASP3 had the lowest binding energy and the highest stable binding energy with multiple major active ingredients of SSWYG.Conclusion SSWYG can significantly improve clinical symptoms of chronic diarrhea possibly by regulating the TNF and IL-17 as well as other pathways via CASP3 and JUN,suggesting a complex therapeutic mechanism of SSWYG involving multiple ingredients and targets and coordinated regulation of multiple pathways.

The ethical dilemma in scientific research exists at all stages of the scientific research activities among medical graduate students,mainly involving conflicts of interest,clinical trials,animal experiments,and the relationship between teachers and students.If medical graduate students are in the ethical dilemma in scientific research for a long time,their research activities will be greatly affected.By discussing the connotation,evaluation tools,current situation,influencing factors,and improvement measures of ethical dilemmas in scientific research,this paper proposed some suggestions,such as comprehensively investigating the influencing factors of ethical dilemmas in scientific research,and formulating targeted improvement measures,with a view to helping medical graduate students identify and get rid of ethical dilemmas in scientific research,and promote the stability of research activities.