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.

ObjectiveAs a second messenger in intracellular signal transduction, Ca²⁺ plays an important role in cell migration. Previous studies have demonstrated that extracellular Ca²⁺ influx can promote electric field-guided cell migration, known as electrotaxis. However, the effect of intracellular Ca²⁺ flow on electrotaxis is unclear. Therefore, in this study, we investigate the effect of Ca²⁺ flux on the electrotaxis of Dictyostelium discoideum. MethodsThe electrotaxis of Dictyostelium discoideum was investigated by applying a direct current (DC) electric field. Cell migration was recorded using a real-time imaging system. Calcium channel inhibitors, the extracellular Ca²⁺ chelator EGTA, Ca²⁺-free DB buffer, and caffeine were applied to investigate the impact of intra- and extracellular Ca²⁺ flow on electrotaxis. The involvement of G proteins and ERK2 in directed cell migration mediated by endoplasmic reticulum Ca²⁺ release was explored using mutants. ResultsDictyostelium discoideum migrated toward the cathode in the electric field in a voltage-dependent manner. The intracellular Ca²⁺ concentration of the cells was significantly increased in the electric field. Inhibition of both extracellular Ca²⁺ influx and intracellular Ca²⁺ release suppressed cell electrotaxis migration. Inhibition of endoplasmic reticulum Ca²⁺ release induced by caffeine significantly impaired the electrotaxis of Dictyostelium discoideum. Deletion of Gα2, Gβ, Gγ, and Erk2 notably reduced the electrotaxis of the cells. Enhancing Ca²⁺ release mediated by caffeine restored the electrotaxis of the Gα2^-, Gβ ^-, and Erk2^- mutant cells partially or completely, but did not restore electrotaxis in the Gγ^- mutant cells. ConclusionCa²⁺ release from the endoplasmic reticulum regulates electrotaxis migration in Dictyostelium discoideum and is involved in the regulation of cell electrotaxis by G proteins and ERK2.

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: To investigate the predictive value of endothelial activation and stress index (EASIX) for the prognosis of patients with mantle cell lymphoma (MCL). METHODS: A retrospective analysis was conducted to assess prognosis and compare the clinical features of patients diagnosed with MCL who were admitted to the Affiliated Hospital of Xuzhou Medical University from January 2010 to June 2023, had therapeutic indications and received standard treatment. RESULTS: A total of 66 patients were included and divided into high EASIX group and low EASIX group, according to a cutoff value of 0.97 determined by the receiver operating characteristic (ROC) curve. Multivariate Cox regression analysis showed that prealbumin <0.2 g/L, high EASIX, and ECOG PS score ≥2 were independent risk factors influencing overall survival (OS) in MCL patients. The median OS of patients in the high and low EASIX group was 13.0 and 37.5 months, and the median progression-free survival was 8.8 and 26.0 months, respectively. The proportions of patients with ECOG PS score ≥2 and prealbumin <0.2 g/L at onset significantly increased in the high EASIX group compared to those in the low EASIX group. CONCLUSION At the time of initial diagnosis, EASIX can serve as an independent prognostic indicator impacting OS in patients with MCL. Furthermore, patients in the high EASIX group experience a poorer prognosis and shorter survival duration compared with those in the low EASIX group.
Humans ; Lymphoma, Mantle-Cell/pathology* ; Prognosis ; Retrospective Studies ; Male ; Female ; Middle Aged ; Aged ; ROC Curve

OBJECTIVE: To investigate the genetic causal relationship of leukocyte telomere length (LTL) with prostatitis, orchitis and epididymitis by two-sample Mendelian randomization (MR). METHODS: Using LTL as the exposure factor and prostatitis, orchitis and epididymitis as outcome factors, we mined the Database of Genome-Wide Association Studies (GWAS). Then, we analyzed the causal relationship of LTL with prostatitis, orchitis and epididymitis by Mendelian randomization using inverse variance weighting (IVW) as the main method and weighted median and MR-Egger regression as auxiliary methods, determined the horizontal multiplicity by MR-Egger intercept test, and conducted sensitivity analysis using the leaving-one-out method. RESULTS: A total of 121 related single nucleotide polymorphisms (SNPs) were identified in this study. IVW showed LTL to be a risk factor for prostatitis (OR = 1.383, 95% CI: 1.044－1.832, P = 0.024), and for orchitis and epididymitis as well (OR = 1.770, 95% CI: 1.275－2.456, P = 0.000 6). CONCLUSION Genetic evidence from Mendelian randomized analysis indicates that shortening of LTL reduces the risk of prostatitis, orchitis and epididymitis.
Humans ; Male ; Mendelian Randomization Analysis ; Epididymitis/genetics* ; Prostatitis/genetics* ; Polymorphism, Single Nucleotide ; Leukocytes ; Orchitis/genetics* ; Genome-Wide Association Study ; Telomere ; Risk Factors

Liver ischemia-reperfusion injury (LIRI) is a pathological process involving multiple injury factors and cell types, with different stages. Currently, protective drugs targeting a single condition are limited in efficacy, and interventions on immune cells will also be accompanied by a series of side effects. In the current bottleneck research stage, the multi-target and obvious clinical efficacy of Chinese medicine (CM) is expected to become a breakthrough point in the research and development of new drugs. In this review, we summarize the roles of reactive oxygen species (ROS) and reactive nitrogen species (RNS) in various stages of hepatic ischemia-reperfusion and on various types of cells. Combined with the current research progress in reducing ROS/RNS with CM, new therapies and mechanisms for the treatment of hepatic ischemia-reperfusion are discussed.
Reperfusion Injury/drug therapy* ; Reactive Oxygen Species/metabolism* ; Reactive Nitrogen Species/metabolism* ; Humans ; Liver/drug effects* ; Animals ; Medicine, Chinese Traditional ; Drugs, Chinese Herbal/pharmacology*