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 effects of Esketamine(S-KET)on the proliferation,migration,invasion,and Wnt/β-catenin signaling pathway of liver cancer cells.Methods Hep G2 liver cancer cells were separated into Control group,low,medium,and high concentration treatment groups(S-KET-L,S-KET-M,S-KET-H groups),and high concentration treatment group(S-KET-H+LiCl group);Edu was applied to detect cell proliferation;scratch experiment was applied to detect cell migration;Transwell experiment was applied to detect cell invasion.Western blot was applied to detect the expression of nuclear proliferation antigen markers(Ki-67),Cyclin D1,matrix metalloproteinase 2(MMP-2),matrix metalloproteinase 9(MMP-9),Wnt1,and β-catenin proteins;nude mouse transplanted tumor was applied to detect the effect of Esketamine on the growth of liver cancer transplanted tumors;immunohistochemistry was applied to detect the expression of Wnt1 and β-catenin proteins.Results Compared with the Control group,the Edu positive rate,Ki-67,Cyclin D1,scratch healing rate,number of cell invasions,the expression of MMP-2,MMP-9,Wnt1,and β-catenin proteins in Hep G2 cells in the S-KET-L,S-KET-M,and S-KET-H groups were obviously reduced(P＜0.05);compared with the S-KET-H group,the Edu positive rate,Ki-67,Cyclin D1,scratch healing rate,number of cell invasions,the expression of MMP-2,MMP-9,Wnt1,and β-catenin proteins in Hep G2 cells in Hep G2 cells in the S-KET-H+LiCl group were significantly increased(P＜0.05);the results of nude mouse tumor transplantation experiment showed that compared with the Control group,the S-KET group mice showed slow tumor growth,reduced tumor mass and volume,and significantly reduced expression of Wnt1 and β-catenin proteins(P＜0.05).Conclusion Esketamine can inhibit the proliferation,migration,and invasion of liver cancer cells by inhibiting the Wnt/β-catenin signaling pathway.

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.

The present study employed UPLC-MS/MS to analyze and identify compounds in the raw powder of Tongluo Shenggu capsules. An HPLC method for the determination of vitexin content was established. The analysis of this drug was performed on a 30 ℃ thermostatic Acquity UPLC® BEH C18 (2.1 mm×100 mm,1.7 μm) column, with the mobile phase comprising 0.2% formic acid-methanol flowing at 0.3 mL /min in a gradient elution manner. Mass spectrometry was detected by ESI sources in both positive and negative ion modes for qualitative identification of chemical constituents. 12 flavonoid and 3 stilbenes compounds in the raw powder of Tongluo Shenggu capsules were successfully identified. Additionally, an HPLC method for the determination of vitexin content was established using a XBridge C18 column (4.6 mm × 250 mm, 5 µm) with a mobile phase of 0.05% glacial acetic acid in methanol for gradient elution, at a column temperature of 30 °C, a flow rate of 1.0 mL/min, and an injection volume of 20 μL. The method demonstrated good linearity in the concentration range of 10 µg/mL to 40 µg/mL (R=1.000) with an average recovery rate of 96.7%. The establishment of these methods provides a scientific basis for the quality control and development of the raw powder of Tongluo Shenggu capsules.

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 effects of Esketamine(S-KET)on the proliferation,migration,invasion,and Wnt/β-catenin signaling pathway of liver cancer cells.Methods Hep G2 liver cancer cells were separated into Control group,low,medium,and high concentration treatment groups(S-KET-L,S-KET-M,S-KET-H groups),and high concentration treatment group(S-KET-H+LiCl group);Edu was applied to detect cell proliferation;scratch experiment was applied to detect cell migration;Transwell experiment was applied to detect cell invasion.Western blot was applied to detect the expression of nuclear proliferation antigen markers(Ki-67),Cyclin D1,matrix metalloproteinase 2(MMP-2),matrix metalloproteinase 9(MMP-9),Wnt1,and β-catenin proteins;nude mouse transplanted tumor was applied to detect the effect of Esketamine on the growth of liver cancer transplanted tumors;immunohistochemistry was applied to detect the expression of Wnt1 and β-catenin proteins.Results Compared with the Control group,the Edu positive rate,Ki-67,Cyclin D1,scratch healing rate,number of cell invasions,the expression of MMP-2,MMP-9,Wnt1,and β-catenin proteins in Hep G2 cells in the S-KET-L,S-KET-M,and S-KET-H groups were obviously reduced(P＜0.05);compared with the S-KET-H group,the Edu positive rate,Ki-67,Cyclin D1,scratch healing rate,number of cell invasions,the expression of MMP-2,MMP-9,Wnt1,and β-catenin proteins in Hep G2 cells in Hep G2 cells in the S-KET-H+LiCl group were significantly increased(P＜0.05);the results of nude mouse tumor transplantation experiment showed that compared with the Control group,the S-KET group mice showed slow tumor growth,reduced tumor mass and volume,and significantly reduced expression of Wnt1 and β-catenin proteins(P＜0.05).Conclusion Esketamine can inhibit the proliferation,migration,and invasion of liver cancer cells by inhibiting the Wnt/β-catenin signaling pathway.

Objective : To investigate the impact of dexmedetomidine on the oncological behavior of hepatocellular carcinoma and explore the role of NF-E2-related factor 2 (Nrf2) at both in vitro and in vivo levels． Methods : In vivo experiment，Male C57BL/6J mice were randomly divided into a control group ( Ctrl group) ，a hepatocellular carcinoma group ( HCC group) ，and a hepatocellular carcinoma + dexmedetomidine group ( HCC + Dex group) . Hepatocellular carcinoma was induced in mice by combining N-Nitrosodiethylamine ( DEN) / carbon tetrachloride ( CCl4 ) ，followed by daily intraperitoneal injection of 10% dexmedetomidine for two weeks．After feeding the mice for one month，the mice were assessed for the quantity and size of liver tumors．The proliferation ability of liver cancer was evaluated using Ki67 immunohistochemistry．Additionally，the expression level of Nrf2 protein in tumor tissue was measured through immunofluorescence．In vitro experiment，Hepa1-6 cells were incubated with different concentrations of dexmedetomidine (0. 1，1，5 nmol /L) for 48 hours to examine their effects．The proliferation， migration and invasion abilities of Hepa1-6 cells were evaluated using the MTT and Transwell methods．The expres- sion level of Nrf2 protein in the Hepa1-6 cells was measured using Western blot and immunofluorescence．Addition- ally，the proliferation ，migration and invasion abilities of cells were assessed after Nrf2 knockdown via si-RNA transfection，in combination with incubation with 1 nmol /L dexmedetomidine for 48 hours. Results : ompared to the HCC group，the anatomical examination results revealed an increase in the number of liver tumors and the lon- gest diameter in the HCC + Dex group (P ＜0. 05) ． Ki67 immunohistochemistry results indicated the number of Ki67 positive cells in liver cancer tissue increased in the HCC + Dex group (P＜0. 01) ．The immunofluorescence assay demonstrated an upregulation of Nrf2 expression level in the HCC + Dex group (P ＜0. 05 ) ． MTT results showed that 1 nmol /L of dexmedetomidine increased the cell viability of Hepa1-6 cells (P＜0. 05) ．Transwell re- sults indicated that 0. 1 ，1 ，and 5 nmol /L of dexmedetomidine enhanced the invasive ability of Hepa1-6 cells， while 0. 1 and 1 nmol /L of dexmedetomidine enhanced the migration ability (P＜0. 05) ．Western blot and immu- nofluorescence results showed an upregulation of Nrf2 expression level in cells after treatment with 1 nmol /L dexme- detomidine (P＜0. 01) ．The Nrf2 expression level of cells was reduced using si-RNA，followed by treatment with 1 nmol /L dexmedetomidine．The results from MTT and Transwell assays revealed a decrease in the viability，invasion and migration ability of Hepa1-6 cells (P＜0. 01) ． Conclusion Dexmedetomidine may enhance the proliferation， invasion and migration capacity of hepatocellular carcinoma by upregulating the expression of Nrf2 .

BACKGROUND: Osteoporosis (OP) has become a major public health issue, threatening the bone health of middle-aged and elderly people from all around the world. Changes in the gut microbiota (GM) are correlated with the maintenance of bone mass and bone quality. However, research results in this field remain highly controversial, and no systematic review or meta-analysis of the relationship between GM and OP has been conducted. This paper addresses this shortcoming, focusing on the difference in the GM abundance between OP patients and healthy controls based on previous 16S ribosomal RNA (rRNA) gene sequencing results, in order to provide new clinical reference information for future customized prevention and treatment options of OP. METHODS: According to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), we comprehensively searched the databases of PubMed, Web of Science, Embase, Cochrane Library, and China National Knowledge Infrastructure (CNKI). In addition, we applied the R programming language version 4.0.3 and Stata 15.1 software for data analysis. We also implemented the Newcastle-Ottawa Scale (NOS), funnel plot analysis, sensitivity analysis, Egger's test, and Begg's test to assess the risk of bias. RESULTS: This research ultimately considered 12 studies, which included the fecal GM data of 2033 people (604 with OP and 1429 healthy controls). In the included research papers, it was observed that the relative abundance of Lactobacillus and Ruminococcus increased in the OP group, while the relative abundance for Bacteroides of Bacteroidetes increased (except for Ireland). Meanwhile, Firmicutes, Blautia, Alistipes, Megamonas, and Anaerostipes showed reduced relative abundance in Chinese studies. In the linear discriminant analysis Effect Size (LEfSe) analysis, certain bacteria showed statistically significant results consistently across different studies. CONCLUSIONS: This observational meta-analysis revealed that changes in the GM were correlated with OP, and variations in some advantageous GM might involve regional differences.
Middle Aged ; Aged ; Humans ; Gastrointestinal Microbiome/genetics* ; RNA, Ribosomal, 16S/genetics* ; Genes, rRNA ; Osteoporosis ; Feces