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.

Background Metals and metalloids in fine particulate matter (PM_2.5) may cause damage to the respiratory and circulatory systems of the human body, and long-term exposure is prone to causing chronic poisoning, cancer, and other adverse effects. Objective To assess the distribution characteristics of metals and metalloids in outdoor PM_2.5 in a southern city of China, conduct source apportionment, and evaluate the associated health risks, thereby providing theoretical support for further pollution control measures. Methods PM_2.5 samples were collected in districts A, B, and C of a southern China city, and the concentrations of 17 metals and metalloids were detected by inductively coupled plasma-mass spectrometry (ICP-MS). Pollution sources were assessed through enrichment factor and principal components analysis, and the main pollution sources were quantified using absolute principal component scores-multivariate linear regression (APCS-MLR). Health risks were evaluated based on the Technical guide for environmental health risk assessment of chemical exposure (WS/T777—2021). Results The ambient air PM_2.5 concentrations in the city were higher in winter and spring, and lower in summer and autumn. The annual average concentrations of ambient PM_2.5 in districts A, B, and C were 36.7, 31.9, and 24.4 μg·m⁻³, respectively. The ambient PM_2.5 levels in districts B and C were below the second-grade limit set by the Ambient air quality standards (GB 3095—2012). The enrichment factors of cadmium (Cd), aluminum (Al), and antimony (Sb) were greater than 10, those of copper (Cu), lead (Pb), arsenic (As), nickel (Ni), mercury (Hg), and molybdenum (Mo) fell between 1 and 10, and those of manganese (Mn), vanadium (V), chromium (Cr), cobalt (Co), barium (Ba), beryllium (Be), and uranium (U) were below or equal to 1. The comprehensive evaluation of source analysis showed that the main pollution sources in districts A and C and the whole city were coal-burning. In district B, the main pollution source was also coal combustion, followed by industrial process sources and dust sources. The carcinogenic risks of As and Cr were between 1×10⁻⁶ and 1×10⁻⁴. However, the hazard quotients for 15 metals and metalloids in terms of non-carcinogenic risk were below 1. Conclusion Cr and As in the atmospheric PM_2.5 of the city present a certain risk of cancer and should be paid attention to. In addition, preventive control measures should be taken against relevant pollution sources such as industrial emission, dust, and coal burning.

Through network pharmacology and molecular docking technology, combined with in vitro experiment verification, we explored the mechanism of action of Porana racemosa Roxb. (PRA) in the treatment of rheumatoid arthritis (RA), and provided a modern pharmacological basis for the treatment of RA by PRA. The potential target of chemical components in the analyzed moth rattan was predicted by Swiss Target Prediction database; OMIM, GeneCards, TTD and Disgenet databases were used to search the disease targets of RA; the protein interaction (PPI) network and medicine-composition-target network were constructed using STRING database and Cytoscape software; GO (gene ontology) functional enrichment and KEGG (kyoto encyclopedia of genes and genomes) pathway analysis were carried out using DAVID database, and molecular docking software was used to dock the potentially active ingredients of PRA and core targets; finally, MH7A cells were selected for cell viability, scratch healing and mRNA expression level analysis of key genes to explore the effects of PRA and their potentially active ingredients on the proliferation, migration and apoptosis of MH7A cells. In this study, a total of 628 potentially active ingredient targets, 1 890 RA targets and 235 intersection targets were identified. It was screened that the potentially active ingredients of RA treatment by PRA were ethylcaffeate, N-p-coumaroyltyramine, 9,12,15-octadecatrienoic acid, methyl ester and so on, and the core targets involved tumor necrosis factor (TNF), matrix metalloproteinase 9 (MMP9), prostaglandin-endoperoxide synthase 2 (PTGS2) and so on. 1 200 GO entries and 166 KEGG pathway entries were obtained from the enrichment analysis; molecular docking results showed that N-p-coumaroyltyramine and ethylcaffeate had good binding activity with TNF, MMP9, cysteine-aspartate protease 3 (CASP3), PTGS2, B-cell lymphoma 2 (BCL2) proteins. In vitro experiments showed that PRA, ethylcaffeate and N-p-coumaroyltyramine could inhibit the proliferation, migration and invasion of MH7A cells, up-regulate the expression of apoptosis-related gene CASP3 mRNA, and down-regulate the expression of MMP9, PTGS2 and BCL2 mRNA, and it can also down-regulate the expression of phosphatidylinositol 3-kinase (PI3K) and protein kinase B (AKT) mRNA and PI3K and p-AKT proteins. This study preliminarily revealed that the treatment of RA by PRA may be related to proliferation, migration, invasion, apoptosis and regulation of PI3K/AKT signaling pathway.

Roxadustat is the world's first small molecule hypoxia-inducible factor prolyl hydroxylase inhibitor. Its adverse effect of causing hypothyroidism with low thyroid-stimulating hormone (TSH) is relatively rare and manifests subtly in elderly patients with multiple coexisting diseases. This article reports a case of an elderly patient with renal anemia who developed reversible low-TSH hypothyroidism after taking roxadustat for 12 days, with a significant decrease in thyroid hormone levels. After discontinuing roxadustat for 15 days, the thyroid hormone levels gradually returned to normal. Due to the worsening of renal anemia, the patient took roxadustat again, and 9 days later, the thyroid function-related indicators decreased upon re-examination, leading to the initiation of levothyroxine replacement therapy. In conjunction with relevant literature, this article analyzes the adverse reactions that occur during the oral administration of roxadustat in elderly patients with chronic kidney disease, aiming to provide reference for drug treatment of such patients.

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 summarize the medication law of TCM in the treatment of chronic bronchitis;To provide reference for clinical medication.Methods Medical records of patients with chronic bronchitis who were hospitalized in the Respiratory Department of the First Affiliated Hospital of Henan University of Chinese Medicine from January 1,2016 to December 31,2021 were extracted based on HIS electronic medical record data.After screening,the TCM prescriptions used by patients with chronic bronchitis were input into Excel 2019 to establish a database.Based on the software Lantern 5.0,the latent structure model was learned,hidden variables and explicit variables were obtained,and the model was interpreted.SPSS Modeler 18.0 was used to establish model points with Apriori algorithm for Chinese materia medica with a frequency greater than 6%,to obtain the association rules between drugs,and to analyze the medication law of TCM in treating chronic bronchitis.Results A total of 3 410 cases were included,involving 423 kinds of Chinese materia medica,with a cumulative frequency of 82 766 times.Among them,109 kinds of Chinese materia medica with a frequency of>6 % had a cumulative frequency of 69 845 times.The top five commonly used medicines were Fritillariae Cirrhosae Bulbus,Poria,Atractyodis Macrocephalae Rhizoma,Asteris Radix et Rhizoma,Citri Reticulatae Pericarpium,mainly with medicines of reducing cough and phlegm,antiasthmatic medicine,tonifying deficiency,clearing heat,relieving superficies,promoting blood circulation and removing blood stasis.The medicinal properties were warming,cold and mild,and the main tastes were bitter,sweet and pungent,and the meridians were mainly lung,spleen,liver and stomach meridians.Through analysis of latent structure,49 hidden variables and 149 hidden classes were obtained.Combined with professional knowledge,10 comprehensive clustering models and 21 core formulas were deduced,such as Sangbaipi Decoction,Xuefu Zhuyu Decoction,Xiaoqinglong Decoction,Erchen Decoction,Shashen Maidong Decoction,Liuwei Dihuang Pills,Yinqiao Powder,Zhisou Powder,Yupingfeng Powder,Xuefu Zhuyu Decoction combined with Daotan Decoction,etc.It was concluded that the chronic bronchitis syndrome included phlegm-heat stagnation lung syndrome,qi stagnation blood stasis syndrome,cold fluid attacking lung syndrome,phlegm-dampness accumulation lung syndrome,lung qi and yin deficiency syndrome,kidney yin deficiency syndrome,wind heat attacking lung syndrome,wind cold attacking lung syndrome,lung qi and spleen deficiency syndrome,phlegm stasis interjunction syndrome.A total of 41 strong association rules were screened in the analysis of association rules,including 5 strong association rules for two and 36 strong association rules for three.The high confidence rules were Saposheikovize Radix + Angelicae Sinensis Radix →Atractyodis Macrocephalae Rhizoma,Saposheikovize Radix + Codonopsis Radix → Atractyodis Macrocephalae Rhizoma,Codonopsis Radix + Citri Reticulatae Pericarpium → Atractyodis Macrocephalae Rhizoma;the higher degree of improvement were Bupleuri Radix + Mori Cortex → Scutellariae Radix,Perillae Fructus + Belamcandae Rhizoma → Fritillariae Cirrhosae Bulbus,Armeniacae Semen Amarum + Pinelliae Rhizoma → Citri Reticulatae Pericarpium,etc.Conclusion In the treatment of chronic bronchitis,TCM is mainly used to reduce phlegm,relieve cough and asthma,and the method of promoting blood circulation and removing blood stasis is commonly used to help eliminate phlegm.In addition,TCM pays attention to the application of methods such as tonifying lung and securing the exterior,invigorating spleen and benefiting qi.

AIM To establish an HPLC method for the simultaneous content determination of gallic acid,protocatechuic acid,morroniside,loganin,sweroside,paeoniflorin,hypericin,astragalin,salvianolic acid B,salvianolic acid A,epimedin C and icariin in Bushen Huoxue Sanjie Capsules.METHODS The analysis was performed on a 30℃thermostatic Agilent 5 TC-C18 column(250 mm×4.6 mm,5 μm),with the mobile phase comprising of acetonitrile-0.1%phosphoric acid flowing at 1.0 mL/min in a gradient elution manner,and the detection wavelength was set at 240 nm.RESULTS Twelve constituents showed good linear relationships within their own ranges(r≥0.999 8),whose average recoveries were 97.11%-101.14%with the RSDs of 0.60%-2.65%.CONCLUSION This simple,accurate and reproducible method can be used for the quality control of Bushen Huoxue Sanjie Capsules.