1.Distribution characteristics, source apportionment, and health risk assessment of metals and metalloids in PM2.5 in a southern city in 2019
Yaxin QU ; Suli HUANG ; Chao WANG ; Jie JIANG ; Jiajia JI ; Daokui FANG ; Shaohua XIE ; Xiaoheng LI ; Ning LIU
Journal of Environmental and Occupational Medicine 2025;42(2):196-204
Background Metals and metalloids in fine particulate matter (PM2.5) 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 PM2.5 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 PM2.5 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 PM2.5 concentrations in the city were higher in winter and spring, and lower in summer and autumn. The annual average concentrations of ambient PM2.5 in districts A, B, and C were 36.7, 31.9, and 24.4 μg·m−3, respectively. The ambient PM2.5 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 PM2.5 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.
2.Exploring mechanism of Porana racemosa Roxb. in treating rheumatoid arthritis based on integration of network pharmacology and molecular docking combined with experimental validation
Chen-yu YE ; Ning LI ; Yin-zi CHEN ; Tong QU ; Jing HU ; Zhi-yong CHEN ; Hui REN
Acta Pharmaceutica Sinica 2025;60(1):117-129
Through network pharmacology and molecular docking technology, combined with
3.A Case Report of Hypothyrotropin Hypothyroidism Caused by Roxadustat
Xuelian YAN ; Bingying TANG ; Xuan QU ; Ning ZHANG ; Lin KANG
Medical Journal of Peking Union Medical College Hospital 2025;16(2):519-522
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.
4.Predicting Postoperative Progression of Ossification of the Posterior Longitudinal Ligament in the Cervical Spine Using Interpretable Radiomics Models
Siyuan QIN ; Ruomu QU ; Ke LIU ; Ruixin YAN ; Weili ZHAO ; Jun XU ; Enlong ZHANG ; Feifei ZHOU ; Ning LANG
Neurospine 2025;22(1):144-156
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.
5.Predicting Postoperative Progression of Ossification of the Posterior Longitudinal Ligament in the Cervical Spine Using Interpretable Radiomics Models
Siyuan QIN ; Ruomu QU ; Ke LIU ; Ruixin YAN ; Weili ZHAO ; Jun XU ; Enlong ZHANG ; Feifei ZHOU ; Ning LANG
Neurospine 2025;22(1):144-156
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.
6.Predicting Postoperative Progression of Ossification of the Posterior Longitudinal Ligament in the Cervical Spine Using Interpretable Radiomics Models
Siyuan QIN ; Ruomu QU ; Ke LIU ; Ruixin YAN ; Weili ZHAO ; Jun XU ; Enlong ZHANG ; Feifei ZHOU ; Ning LANG
Neurospine 2025;22(1):144-156
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.
7.Predicting Postoperative Progression of Ossification of the Posterior Longitudinal Ligament in the Cervical Spine Using Interpretable Radiomics Models
Siyuan QIN ; Ruomu QU ; Ke LIU ; Ruixin YAN ; Weili ZHAO ; Jun XU ; Enlong ZHANG ; Feifei ZHOU ; Ning LANG
Neurospine 2025;22(1):144-156
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.
8.Predicting Postoperative Progression of Ossification of the Posterior Longitudinal Ligament in the Cervical Spine Using Interpretable Radiomics Models
Siyuan QIN ; Ruomu QU ; Ke LIU ; Ruixin YAN ; Weili ZHAO ; Jun XU ; Enlong ZHANG ; Feifei ZHOU ; Ning LANG
Neurospine 2025;22(1):144-156
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.
9.Research Advance on Smartphone-based Visual Biosensor in Point-of-Care Testing
Xian-Xin XIANG ; Hua-Yue SUN ; Hui-Ning CHAI ; Kun YU ; Li-Jun QU ; Guang-Yao ZHANG ; Xue-Ji ZHANG
Chinese Journal of Analytical Chemistry 2024;52(2):145-156
Human physiological indicators have become an important standard for assessing health in modern society.Traditional detection methods often require a separate laboratory,complex operation process and long detection time,so it is urgent to develop portable,fast and accurate on-site detection technologies for bioanalysis.Point-of-care testing(POCT),which differs from traditional laboratory testing,can realize the rapid in situ detection of biomarkers without the complicated analytical process of the laboratory.Smartphones,which are an essential tool in our daily life,not only have independent operating systems and built-in storage functions,but also have high-definition cameras,which have great application potential in POCT visualization.The combination of various biosensing technologies and smartphones has developed into a new direction in the field of POCT.This review mainly introduced the research progress of smartphone-based visual biosensors in POCT in recent years,including colorimetric sensors,fluorescence sensors,chemiluminescence sensors and electrochemiluminescence sensors.Finally,the problems faced by smart-phone-based visual biosensors in the application of POCT were summarized,and their future development was prospected.
10.Visualization analysis on research progress and trends of Ziziphi Spinosae Semen from 2000 to 2022
Tong QU ; Ning LI ; Hui REN ; Wenjing LU ; Xiaomin CUI ; Jing HU ; Zhiyong CHEN ; Hong ZHANG
China Pharmacist 2024;27(2):242-254
Objective To explore the research hotspots and development trends of Ziziphi Spinosae Semen in the past 20 years,and to provide reference for related research.Methods Literatures on Ziziphi Spinosae Semen were searched from January 1,2000 to December 31,2022 in CNKI,Web of Science Core Collection Database.VOS viewer software was used to visually analyze the citation frequency,research institutions and keyword hotspots of English literatures.CiteSpace software was used to visually analyze research institutions,authors,emergence keywords and keyword overlap time of Chinese literatures,and Microsoft Excel 2021 software was used to analyze of annual publication trends and publication volume of Chinese and English literatures,and download frequency of Chinese literatures.Results A total of 4 872 Chinese and 128 English literatures were included,with an overall upward trend in the number of annual publications.The research institutions with the highest number of publications in Chinese and English were Shandong University of Traditional Chinese Medicine and Tianjin University of Commerce,and the authors with the highest number of publications were DU Chenhui and XIE Junbo,respectively.The most frequent keywords in Chinese literatures were"Ziziphi Spinosae Semen","composed"and"application of compound therapy",and in English literatures were"performance","oxidative stress".Conclusion From 2000 to 2022,the research hotspots of Ziziphi Spinosae Semen mainly focused on the chemical composition,pharmacological effects and clinical application analysis,compatibility research,formulation and preparation.Quality control and evaluation of Ziziphi Spinosae Semen,and the research on the mechanism of preventing and treating insomnia with Ziziphi Spinosae Semen may become future research directions.

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