1.Research progress of nano drug delivery system based on metal-polyphenol network for the diagnosis and treatment of inflammatory diseases
Meng-jie ZHAO ; Xia-li ZHU ; Yi-jing LI ; Zi-ang WANG ; Yun-long ZHAO ; Gao-jian WEI ; Yu CHEN ; Sheng-nan HUANG
Acta Pharmaceutica Sinica 2025;60(2):323-336
Inflammatory diseases (IDs) are a general term of diseases characterized by chronic inflammation as the primary pathogenetic mechanism, which seriously affect the quality of patient′s life and cause significant social and medical burden. Current drugs for IDs include nonsteroidal anti-inflammatory drugs, corticosteroids, immunomodulators, biologics, and antioxidants, but these drugs may cause gastrointestinal side effects, induce or worsen infections, and cause non-response or intolerance. Given the outstanding performance of metal polyphenol network (MPN) in the fields of drug delivery, biomedical imaging, and catalytic therapy, its application in the diagnosis and treatment of IDs has attracted much attention and significant progress has been made. In this paper, we first provide an overview of the types of IDs and their generating mechanisms, then sort out and summarize the different forms of MPN in recent years, and finally discuss in detail the characteristics of MPN and their latest research progress in the diagnosis and treatment of IDs. This research may provide useful references for scientific research and clinical practice in the related fields.
2.Discriminating Tumor Deposits From Metastatic Lymph Nodes in Rectal Cancer: A Pilot Study Utilizing Dynamic Contrast-Enhanced MRI
Xue-han WU ; Yu-tao QUE ; Xin-yue YANG ; Zi-qiang WEN ; Yu-ru MA ; Zhi-wen ZHANG ; Quan-meng LIU ; Wen-jie FAN ; Li DING ; Yue-jiao LANG ; Yun-zhu WU ; Jian-peng YUAN ; Shen-ping YU ; Yi-yan LIU ; Yan CHEN
Korean Journal of Radiology 2025;26(5):400-410
Objective:
To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer.
Materials and Methods:
A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs.
Results:
All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027).
Conclusion
The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.
3.Discriminating Tumor Deposits From Metastatic Lymph Nodes in Rectal Cancer: A Pilot Study Utilizing Dynamic Contrast-Enhanced MRI
Xue-han WU ; Yu-tao QUE ; Xin-yue YANG ; Zi-qiang WEN ; Yu-ru MA ; Zhi-wen ZHANG ; Quan-meng LIU ; Wen-jie FAN ; Li DING ; Yue-jiao LANG ; Yun-zhu WU ; Jian-peng YUAN ; Shen-ping YU ; Yi-yan LIU ; Yan CHEN
Korean Journal of Radiology 2025;26(5):400-410
Objective:
To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer.
Materials and Methods:
A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs.
Results:
All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027).
Conclusion
The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.
4.Discriminating Tumor Deposits From Metastatic Lymph Nodes in Rectal Cancer: A Pilot Study Utilizing Dynamic Contrast-Enhanced MRI
Xue-han WU ; Yu-tao QUE ; Xin-yue YANG ; Zi-qiang WEN ; Yu-ru MA ; Zhi-wen ZHANG ; Quan-meng LIU ; Wen-jie FAN ; Li DING ; Yue-jiao LANG ; Yun-zhu WU ; Jian-peng YUAN ; Shen-ping YU ; Yi-yan LIU ; Yan CHEN
Korean Journal of Radiology 2025;26(5):400-410
Objective:
To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer.
Materials and Methods:
A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs.
Results:
All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027).
Conclusion
The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.
5.Discriminating Tumor Deposits From Metastatic Lymph Nodes in Rectal Cancer: A Pilot Study Utilizing Dynamic Contrast-Enhanced MRI
Xue-han WU ; Yu-tao QUE ; Xin-yue YANG ; Zi-qiang WEN ; Yu-ru MA ; Zhi-wen ZHANG ; Quan-meng LIU ; Wen-jie FAN ; Li DING ; Yue-jiao LANG ; Yun-zhu WU ; Jian-peng YUAN ; Shen-ping YU ; Yi-yan LIU ; Yan CHEN
Korean Journal of Radiology 2025;26(5):400-410
Objective:
To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer.
Materials and Methods:
A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs.
Results:
All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027).
Conclusion
The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.
6.Comparison of small-sample multi-class machine learning models for plasma concentration prediction of valproic acid
Xi CHEN ; Shen’ao YUAN ; Hailing YUAN ; Jie ZHAO ; Peng CHEN ; Chunyan TIAN ; Yi SU ; Yunsong ZHANG ; Yu ZHANG
China Pharmacy 2025;36(11):1399-1404
OBJECTIVE To construct three-class (insufficient, normal, excessive) and two-class (insufficient, normal) models for predicting plasma concentration of valproic acid (VPA), and compare the performance of these two models, with the aim of providing a reference for formulating clinical medication strategies. METHODS The clinical data of 480 patients who received VPA treatment and underwent blood concentration test at the Xi’an International Medical Center Hospital were collected from November 2022 to September 2024 (a total of 695 sets of data). In this study, predictive models were constructed for target variables of three-class and two-class models. Feature ranking and selection were carried out using XGBoost scores. Twelve different machine learning algorithms were used for training and validation, and the performance of the models was evaluated using three indexes: accuracy, F1 score, and the area under the working characteristic curve of the subject (AUC). RESULTS XGBoost feature importance scores revealed that in the three-class model, the importance ranking of kidney disease and electrolyte disorders was higher. However, in the two-class model, the importance ranking of these features significantly decreased, suggesting a close association with the excessive blood concentration of VPA. In the three-class model, Random Forest method performed best, with F1 score of 0.704 0 and AUC of 0.519 3 on the test set; while in the two-class model, CatBoost method performed optimally, with F1 score of 0.785 7 and AUC of 0.819 5 on the test set. CONCLUSIONS The constructed three-class model has the ability to predict excessive VPA blood concentration, but its prediction and model generalization abilities are poor; the constructed two-class model can only perform classification prediction for insufficient and normal blood concentration cases, but its model performance is stronger.
7.Discriminating Tumor Deposits From Metastatic Lymph Nodes in Rectal Cancer: A Pilot Study Utilizing Dynamic Contrast-Enhanced MRI
Xue-han WU ; Yu-tao QUE ; Xin-yue YANG ; Zi-qiang WEN ; Yu-ru MA ; Zhi-wen ZHANG ; Quan-meng LIU ; Wen-jie FAN ; Li DING ; Yue-jiao LANG ; Yun-zhu WU ; Jian-peng YUAN ; Shen-ping YU ; Yi-yan LIU ; Yan CHEN
Korean Journal of Radiology 2025;26(5):400-410
Objective:
To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer.
Materials and Methods:
A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs.
Results:
All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027).
Conclusion
The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.
8.Subchronic exposure to benzoapyrene results in lung tissue cell damage caused by ferroptosis in mice
Chaoli ZHOU ; Shihan DING ; Hui HE ; Zhirui MA ; Jie CHEN ; Xingdi GUO ; Yi LYU ; Jinping ZHENG
Journal of Environmental and Occupational Medicine 2025;42(8):971-977
Background Exposure to benzo[a]pyrene (BaP) may impair lung function through various mechanisms; however, it remains uncertain whether BaP induces ferroptosis in lung tissue cells, resulting in lung function impairment. Objective To investigate the ferroptosis of lung tissue cells triggered by subchronic BaP exposure in mice and its correlation with lung injury, and to explore the function of ferroptosis in BaP-induced lung tissue damage. Method Seventy-two healthy 3-weeks-old male C57BL/6J mice were acclimatized for 1 week and then randomly divided into six groups: control group (corn oil 10 mL·kg−1), low-dose BaP group (2.5 mg·kg−1), medium-dose BaP group (5 mg·kg−1), high-dose BaP group (10 mg·kg−1), BaP+ferrostatin-1 (Fer-1) group (10 mg·kg−1+1 mg·kg−1), and Fer-1 group (1 mg·kg−1), with 12 mice each group. Corn oil and BaP were administered via gavage every other day, followed by an intraperitoneal injection of Fer-1 the subsequent day, throughout a period of 90 d. Whole-body plethysmography was applied to detect lung function; hematoxylin-eosin staining (HE) and Masson staining were used to observe lung tissue injury and fibrosis; microscopy of alveolar epithelial cells was conducted to reveal mitochondrial morphology; biochemical assays were used to measure the content of tissue iron, malondialdehyde (MDA), and glutathione (GSH), as well as the activity of glutathione peroxidase (GSH-Px); Western blotting and real-time quantitative PCR (RT-qPCR) analyses were performed to reveal the protein and mRNA expression of ferroptosis markers. Results Compared to the control group, the high-dose BaP group showed a significant increase in expiration time (Te) (P<0.01), and a significant decrease in ratio rate of achieving peak expiratory flow (Rpef), tidal volume (TVb), peak inspiratory flow (PIF), minute volume (MVb), and peak expiratory flow (PEF) (P<0.05 or 0.01). Based on the results of HE and Masson staining, partial destruction of alveolar structures, thickening of alveolar walls, infiltration of inflammatory cells, significant thickening of tracheal walls and a large deposition of collagen fibers in lung tissue were observed in the medium- and high-dose BaP groups. By microscopy, the alveolar epithelial cells exposed to low-dose BaP showed condensed chromatin, and the mitochondria exposed to medium and high-dose BaP showed wrinkles, increased mitochondrial membrane density, and diminished mitochondrial cristae. Compared to the control group, in the medium- and high-dose BaP groups, the lung tissue iron content and the expression levels of ACSL4 protein and mRNA significantly elevated (P<0.01 or 0.05), while the mRNA expression level of SLC7A11 significantly decreased (P<0.05); in the high-dose BaP group, the MDA content, COX2 protein, and PTGS2 mRNA expression levels significantly increased (P<0.05 or 0.01), GSH content and GSH-Px activity, GPX4 protein and mRNA expression levels, and the expression level of SLC7A11 protein significantly decreased (P<0.01 or 0.05). The ferroptosis inhibitor Fer-1 markedly reversed respiratory function, morphology, mitochondrial alterations, and the aforementioned ferroptosis-related biochemical indicators. Conclusion Subchronic exposure to BaP can induce ferroptosis in mice lung tissue cells, resulting in compromised lung function.
9.Trends and sex disparities in the burden of urolithiasis in 204 countries and territories, 1990-2021.
Junjiong ZHENG ; Qihang ZHANG ; Jie ZHANG ; Yuhui YAO ; Li CHEN ; Yunfei LIU ; Yi SONG ; Tianxin LIN ; Guohua HE
Chinese Medical Journal 2025;138(16):1973-1983
BACKGROUND:
Urolithiasis is a widespread disease with a high prevalence worldwide. This study aims to evaluate the disease burden of urolithiasis and its trends from 1990 to 2021 globally, based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 database.
METHODS:
The numbers and age-standardized rates (ASRs) of incidence, disability-adjusted life years (DALYs), and mortality of urolithiasis were extracted from GBD 2021 to represent the disease burden. Joinpoint regression analyses were conducted to assess the temporal trends in the burden of urolithiasis. The male-to-female ASR ratio indices were used to evaluate sex disparities. Additionally, we explored the relationship between the ASR ratio and the sociodemographic index (SDI).
RESULTS:
The total numbers of incidence, DALY, and mortality of urolithiasis were 105,983,780 cases (95% uncertainty interval [UI] = 88,349,356-128,645,155 cases), 693,444 cases (95% UI = 567,765-850,490 cases), and 17,672 cases (95% UI = 13,932-21,241 cases), respectively, in 2021. There is an increasing trend in the number of these measures globally, whereas the ASRs have decreased over the past 30 years. The age-standardized incidence rate (ASIR) and age-standardized mortality rate (ASMR) were significantly higher in males than in females in 2021. The sex disparities in the age-standardized DALY rate (ASDR) and ASMR of urolithiasis were negatively correlated with the SDI. In 2021, the ASIR of urolithiasis was 964.70 (95% UI = 801.26-1175.09) per 100,000 people in China, which is much lower than the global average (1242.84 [95% UI = 1034.94-1506.99] per 100,000 people). Compared with the global average, a more pronounced decline in ASIR was observed in China from 1793.16 (1446.0-2235.14) in 1990 to 964.70 (801.26-1175.09) per 100,000 people in 2021.
CONCLUSIONS
Urolithiasis poses a significant healthcare burden worldwide. More robust global and national strategies are warranted to address the prevention and treatment, especially in low SDI countries and regions.
Humans
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Urolithiasis/mortality*
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Male
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Female
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Incidence
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Global Burden of Disease
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Disability-Adjusted Life Years
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Adult
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Middle Aged
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Risk Factors
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Sex Factors
10.Associations between statins and all-cause mortality and cardiovascular events among peritoneal dialysis patients: A multi-center large-scale cohort study.
Shuang GAO ; Lei NAN ; Xinqiu LI ; Shaomei LI ; Huaying PEI ; Jinghong ZHAO ; Ying ZHANG ; Zibo XIONG ; Yumei LIAO ; Ying LI ; Qiongzhen LIN ; Wenbo HU ; Yulin LI ; Liping DUAN ; Zhaoxia ZHENG ; Gang FU ; Shanshan GUO ; Beiru ZHANG ; Rui YU ; Fuyun SUN ; Xiaoying MA ; Li HAO ; Guiling LIU ; Zhanzheng ZHAO ; Jing XIAO ; Yulan SHEN ; Yong ZHANG ; Xuanyi DU ; Tianrong JI ; Yingli YUE ; Shanshan CHEN ; Zhigang MA ; Yingping LI ; Li ZUO ; Huiping ZHAO ; Xianchao ZHANG ; Xuejian WANG ; Yirong LIU ; Xinying GAO ; Xiaoli CHEN ; Hongyi LI ; Shutong DU ; Cui ZHAO ; Zhonggao XU ; Li ZHANG ; Hongyu CHEN ; Li LI ; Lihua WANG ; Yan YAN ; Yingchun MA ; Yuanyuan WEI ; Jingwei ZHOU ; Yan LI ; Caili WANG ; Jie DONG
Chinese Medical Journal 2025;138(21):2856-2858

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