1.Five new triterpenoid saponins from the kernels of Momordica cochinchinensis
Ru DING ; Jia-qi WANG ; Yi-yang LUO ; Yong-long HAN ; Xiao-bo LI ; Meng-yue WANG
Acta Pharmaceutica Sinica 2025;60(2):442-448
Five saponins were isolated from the kernels of
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.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.
7.Correlation between Muscle Tension,Clinical Characteristics, and Traditional Chinese Medicine Syndromes in Patients with Wilson Disease Based on Digital Muscle Function Assessment System Myoton PRO
Yulong YANG ; Wenming YANG ; Han WANG ; Xiang LI ; Taohua WEI ; Wenjie HAO ; Yue YANG ; Yufeng DING ; Yuqi SONG ; Wei HE
Chinese Journal of Experimental Traditional Medical Formulae 2025;31(15):147-154
ObjectiveThis paper aims to use the digital muscle function assessment system Myoton PRO to assess the correlation between muscle tension,clinical characteristics, and traditional Chinese medicine(TCM) syndromes in patients with hepatolenticular degeneration [also known as Wilson disease(WD)]. MethodsA total of 104 patients with WD accompanied by abnormal muscle tension(increased or decreased,hereinafter the same) who were hospitalized in the Brain Disease Centre of the First Affiliated Hospital of Anhui University of Chinese Medicine from April 2021 to November 2023 were selected,all of whom were subjected to TCM syndrome diagnosis and Myoton PRO for the measurement of F value of muscle tension,Goldstein, and UWDRS-N scales. The age of onset of the disease and disease duration were analyzed,and the differences and correlations of the above indexes in different TCM syndromes of WD were analyzed ResultsAmong the 104 patients with WD ,the phlegm and stasis syndrome was the most common(60 patients),followed by the damp-heat syndrome(33 patients),and the least common was the liver-kidney Yin deficiency syndrome(11 patients). The F value of the phlegm and stasis syndrome group was higher than that of the liver-kidney Yin deficiency syndrome group and the damp-heat syndrome group(P<0.01). The F value of the damp-heat syndrome group was higher than that of the liver-kidney Yin deficiency syndrome group(P<0.05),and the F value of the lower limbs of each group was higher than that of the upper limbs(P<0.01). Goldstein and UWDRS-N scores of the patients in the phlegm and stasis syndrome group were higher than those in the damp-heat syndrome group and the liver-kidney Yin deficiency syndrome group(P<0.05). There was no significant difference between the Goldstein and UWDRS-N scores of patients in the liver-kidney Yin deficiency syndrome group and the damp-heat syndrome group. Correlation analysis revealed that the age of onset and duration of the disease were positively correlated with the F values of the lower limbs(r=0.20,P<0.05,r=0.38,P<0.01)and had no significant correlation with those of the upper limbs. The F value levels of muscle tension of all limbs in the three groups of patients were positively correlated with the Goldstein and UWDRS-N scores(muscle tension of the upper limbs in the phlegm and stasis syndrome group,r=0.36,P<0.01,r=0.42,P<0.01. muscle tension of the lower limbs in the phlegm and stasis syndrome group,r=0.70,P<0.01,r=0.60,P<0.01. muscle tension of the upper limbs in the damp-heat syndrome group,r=0.64,P<0.01,r=0.53,P<0.01. muscle tension of the lower limbs in the damp-heat syndrome group,r=0.59,P<0.01,r=0.70,P<0.01. muscle tension of the upper limbs in the liver-kidney Yin deficiency syndrome group,r=0.70,P<0.01,r=0.74,P<0.01. muscle tension of the lower limbs in the liver-kidney Yin deficiency syndrome group,r=0.85,P<0.01,r=0.62,P<0.01).
8.Life's Essential 8 cardiovascular health metrics and long-term risk of cardiovascular disease at different stages: A multi-stage analysis.
Jiangtao LI ; Yulin HUANG ; Zhao YANG ; Yongchen HAO ; Qiuju DENG ; Na YANG ; Lizhen HAN ; Luoxi XIAO ; Haimei WANG ; Yiming HAO ; Yue QI ; Jing LIU
Chinese Medical Journal 2025;138(5):592-594
10.Diagnosis and treatment of colorectal liver metastases: Chinese expert consensus-based multidisciplinary team (2024 edition).
Wen ZHANG ; Xinyu BI ; Yongkun SUN ; Yuan TANG ; Haizhen LU ; Jun JIANG ; Haitao ZHOU ; Yue HAN ; Min YANG ; Xiao CHEN ; Zhen HUANG ; Weihua LI ; Zhiyu LI ; Yufei LU ; Kun WANG ; Xiaobo YANG ; Jianguo ZHOU ; Wenyu ZHANG ; Muxing LI ; Yefan ZHANG ; Jianjun ZHAO ; Aiping ZHOU ; Jianqiang CAI
Chinese Medical Journal 2025;138(15):1765-1768

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