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.

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.

Objective:To analyze the blood-transition prototype components and metabolites of Fengliaoxing Fengshi Dieda medicinal liquor.Methods:Ultra-high performance liquid chromatographyquadrupole/electrostatic field orbital trap high resolution mass spectrometry (UHPLC-Q Exactive Focus MS/MS) technique was used to compare the chromatogram differences of Fengliaoxing Fengshi Dieda medicinal liquor extract, blank serum and drug-containing serum. According to the retention time, relative molecular weight and the ratio with primary and secondary ion fragments provided by MS, the prototype components and metabolites of Fengliaoxing Fengshi Dieda medicinal liquor extract were analyzed in serum of rats after oral administration. The detection conditions were as follows: the mobile phase of methanol (A)-0.1% formic acid solution (B) for elution gradient (0-5 min, 5%A; 5-60 min, 5%-95%A; 60-65 min, 95%A), the flow rate of 0.3 ml/min, heated electrospray ionization, detection range of m/z 80-1 200, positive and negative ion scanning modes.Results:A total of 31 transitional components were detected in the serum, of which 9 were prototype components and 22 were metabolites. The 9 prototype components were identified as phenylacetaldehyde, baogongteng C/ erycibellin, p-coumaric acid, 5-Hydroxymethylfurfural, quinic acid, paeonol, 3-Hydroxybenzaldehyde, salicylic acid, and isourecumenol. The 22 metabolites mainly consist of 11 organic acid components, 3 indole components, 2 organic phenolic components, 2 alkaloid components, 1 nucleoside component, 1 amino acid component, 1 lactone component, and 1 sulfonic component. The metabolic pathways were mainly glucuronidation, sulfation and others, which by phase Ⅱ metabolism.Conclusion:Organic phenols and organic acids are the main components that enter the body of Fengliaoxing Fengshi Dieda Medicinal Liquor, while alkaloid compounds and organic acid components may be potential active ingredients for its pharmacological effects.

To investigate the impact of mild-to-moderate frailty on the long-term prognosis of hospitalized elderly patients with type 2 diabetes mellitus(T2DM).

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 observe the value of fetal MRI in diagnosis of duodenal obstruction(DO).Methods A total of 35 fetuses with suspected DO according to MRI were retrospectively included.The length and the maximum diameter of the dilated duodenum were measured,so as site(categorized in descending order from proximal to distal as descending segment,horizontal segment and ascending duodenum/proximal jejunum)and the degree of obstruction(complete or incomplete)were assessed.Taken findings of labor induction specimen,postnatal neonatal surgery or follow-up data as standards,the positive predictive value(PPV)of MRI for diagnosing fetal DO was calculated,while the correlations of the measured parameters of dilated duodenum and the confirmed obstruction site/degree were analyzed.Results Among 35 fetuses,DO was confirmed in 34 fetuses,yielding an overall PPV of 97.14％(34/35)for MRI.In 34 fetuses with confirmed DO,there were 23 with descending DO(DDO),4 with horizontal DO(HDO)and 7 with ascending DO/proximal jejunum obstruction(ADO/PJO),including 12 with complete DO and 22 with incomplete DO.PPV of MRI for diagnosing DDO,HDO and ADO/PJO was 87.50％(21/24),50.00％(2/4)and 100％(7/7),respectively,for diagnosing complete and incomplete DO was 90.00％(9/10)and 84.00％(21/25),respectively.Both the length and the maximum diameter of fetal proximal dilated duodenum showed on MRI were positively correlated with the actual obstruction site(from proximal to distal)(rs=0.736,P＜0.001;rs=0.424,P=0.011,respectively),but had no significant rank correlation with the degree of obstruction(rs=-0.216,P=0.212;rs=-0.285,P=0.097,respectively).Conclusion Fetal MRI could effectively evaluate the length and the maximum diameter of dilated duodenum hence indicating the level and degree of DO.