1.Stage-Based Intervention in Atherosclerosis Using the "Attacking,Supplementing,Dispersing,Dissipating" Method Based on the Accumulation Syndrome Theory
Yujie LUAN ; Chenlu YUAN ; Zizhen CHEN ; Yijun LIU ; Yi WEI ; Yuanhui HU
Journal of Traditional Chinese Medicine 2025;66(7):685-689
Atherosclerosis is a complex pathological condition resulting from lipid deposition, chronic inflammatory responses, and fibrosis, with a prolonged disease course and multifactorial etiology. Based on the traditional Chinese medicine (TCM) theory of accumulation syndrome, atherosclerosis can be classified under this category, with its pathogenesis involving phlegm, blood stasis, deficiency, and accumulation. This paper proposed a stage-based intervention strategy using the four therapeutic principles of "attacking, supplementing, dispersing, dissipating", and divided into six stages based on the pathological progression, including the stage of accumulation before formation, the stage of accumulation already formed, the stage of nucleus accumulation, the stage of nucleus accumulation decay, the stage of nucleus accumulation consolidation, and the stage of severe stenosis of nucleus. At different stages, the intervention focuses on reinforcing healthy qi and consolidating the root, tonifying the kidneys and spleen, dispersing and removing turbidity, removing phlegm stagnation, promoting qi circulation, dispersing accumulations and removing stasis, attacking accumulation and expelling stasis, directing the turbid downward and dispersing accumulation, and treatment would be adjusted based on specific symptoms, which provides a theoretical framework for the prevention and treatment of atherosclerosis with TCM.
2.Mitochondria: The Target of Ionizing Radiation Damage
Lian-Chen TIAN ; Ya-Yi YUAN ; Xu-Hong DANG
Progress in Biochemistry and Biophysics 2025;52(4):836-844
In recent years, due to the development of radiotherapy technology and nuclear energy, people have paid more and more attention to the various effects of ionizing radiation on organisms. Ionizing radiation can induce protein, DNA and other biological macromolecules to damage, resulting in apoptosis, senescence, cancer and a series of changes. For a long time, it has been believed that the main target of ionizing radiation damage is DNA in the nucleus. However, it has been reported in recent years that ionizing radiation has both direct and indirect effects, and the theory of ROS damage in the indirect effects believes that ionizing radiation has target uncertainty, so it is not comprehensive enough to evaluate only the DNA damage in the nucleus. It has been reported that ionizing radiation can cause damage to organelles as well as damage to cells. Mitochondria are important damaged organelles because mitochondria occupy as much as 30% of the entire cell volume in the cytoplasm, which contains DNA and related enzymes that are closely related to cellular ATP synthesis, aerobic respiration and other life activities. What is more noteworthy is that mitochondria are the only organelles in which DNA exists in the human body, which makes researchers pay attention to various damage to mitochondrial DNA caused by ionizing radiation (such as double-strand breaks, base mismatching, and fragment loss). Although these damages also occur in the nucleus, mitochondrial DNA is more severely damaged than nuclear DNA due to its lack of histone protection, so mitochondria are important targets of ionizing radiation damage in addition to the nucleus. Mitochondrial DNA is not protected by histones and has little repair ability. When exposed to ionizing radiation, common deletions occur at an increased frequency and are passed on to offspring. For large-scale mitochondrial DNA damage, mitochondria indirectly compensate for the amount of damaged DNA by increasing the number of DNA copies and maintaining the normal function of mitochondrial DNA. Mitochondria are in a state of oxidative stress after exposure to ionizing radiation, and this oxidative stress will promote the change in mitochondrial function. When mitochondria are damaged, the activity of proteins related to aerobic respiration decreases, and oxidative respiration is inhibited to a certain extent. At the same time, a large amount of active superoxide anions are continuously produced to stimulate mitochondrial oxidative stress, and the signal of such damage is transmitted to the surrounding mitochondria, resulting in a cascade of damage reaction, which further activates the signalling pathway between mitochondria and nucleus. The cell nucleus is also in a state of oxidative stress, and finally, the level of free radicals is high, causing secondary damage to the genetic material DNA of mitochondria and nucleus. In this paper, the damage effects of ionizing radiation on mitochondria are reviewed, to provide a new idea for radiation protection.
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.Zinc Finger Protein 639 Expression Is a Novel Prognostic Determinant in Breast Cancer
Fang LEE ; Shih-Ping CHENG ; Ming-Jen CHEN ; Wen-Chien HUANG ; Yi-Min LIU ; Shao-Chiang CHANG ; Yuan-Ching CHANG
Journal of Breast Cancer 2025;28(2):86-98
Purpose:
Zinc finger protein 639 (ZNF639) is often found within the overlapping amplicon of PIK3CA, and previous studies suggest its involvement in the pathogenesis of esophageal and oral squamous cell carcinomas. However, its expression and significance in breast cancer remain uncharacterized.
Methods:
Immunohistochemical analysis of ZNF639 was performed using tissue microarrays.Functional studies, including colony formation, Transwell cell migration, and in vivo metastasis, were conducted on breast tumor cells with ZNF639 knockdown via small interfering RNA transfection.
Results:
Reduced ZNF639 immunoreactivity was observed in 82% of the breast cancer samples, independent of hormone receptor and human epidermal growth factor receptor 2 status. In multivariate Cox regression analyses, ZNF639 expression was associated with favorable survival outcomes, including recurrence-free survival (hazard ratio, 0.35; 95% confidence interval [CI], 0.14–0.89) and overall survival (hazard ratio, 0.41; 95% CI, 0.16– 1.05). ZNF639 knockdown increased clonogenicity, cell motility, and lung metastasis in NOD/ SCID mice. Following the ZNF639 knockdown, the expression of Snail1, vimentin, and C-C chemokine ligand 20 (CCL20) was upregulated, and the changes in cell phenotype mediated by ZNF639 were reversed by the subsequent knockdown of CCL20.
Conclusion
Low ZNF639 expression is a novel prognostic factor for recurrence-free survival in patients with breast cancer.
7.Zinc Finger Protein 639 Expression Is a Novel Prognostic Determinant in Breast Cancer
Fang LEE ; Shih-Ping CHENG ; Ming-Jen CHEN ; Wen-Chien HUANG ; Yi-Min LIU ; Shao-Chiang CHANG ; Yuan-Ching CHANG
Journal of Breast Cancer 2025;28(2):86-98
Purpose:
Zinc finger protein 639 (ZNF639) is often found within the overlapping amplicon of PIK3CA, and previous studies suggest its involvement in the pathogenesis of esophageal and oral squamous cell carcinomas. However, its expression and significance in breast cancer remain uncharacterized.
Methods:
Immunohistochemical analysis of ZNF639 was performed using tissue microarrays.Functional studies, including colony formation, Transwell cell migration, and in vivo metastasis, were conducted on breast tumor cells with ZNF639 knockdown via small interfering RNA transfection.
Results:
Reduced ZNF639 immunoreactivity was observed in 82% of the breast cancer samples, independent of hormone receptor and human epidermal growth factor receptor 2 status. In multivariate Cox regression analyses, ZNF639 expression was associated with favorable survival outcomes, including recurrence-free survival (hazard ratio, 0.35; 95% confidence interval [CI], 0.14–0.89) and overall survival (hazard ratio, 0.41; 95% CI, 0.16– 1.05). ZNF639 knockdown increased clonogenicity, cell motility, and lung metastasis in NOD/ SCID mice. Following the ZNF639 knockdown, the expression of Snail1, vimentin, and C-C chemokine ligand 20 (CCL20) was upregulated, and the changes in cell phenotype mediated by ZNF639 were reversed by the subsequent knockdown of CCL20.
Conclusion
Low ZNF639 expression is a novel prognostic factor for recurrence-free survival in patients with breast cancer.
8.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.
9.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.
10.Zinc Finger Protein 639 Expression Is a Novel Prognostic Determinant in Breast Cancer
Fang LEE ; Shih-Ping CHENG ; Ming-Jen CHEN ; Wen-Chien HUANG ; Yi-Min LIU ; Shao-Chiang CHANG ; Yuan-Ching CHANG
Journal of Breast Cancer 2025;28(2):86-98
Purpose:
Zinc finger protein 639 (ZNF639) is often found within the overlapping amplicon of PIK3CA, and previous studies suggest its involvement in the pathogenesis of esophageal and oral squamous cell carcinomas. However, its expression and significance in breast cancer remain uncharacterized.
Methods:
Immunohistochemical analysis of ZNF639 was performed using tissue microarrays.Functional studies, including colony formation, Transwell cell migration, and in vivo metastasis, were conducted on breast tumor cells with ZNF639 knockdown via small interfering RNA transfection.
Results:
Reduced ZNF639 immunoreactivity was observed in 82% of the breast cancer samples, independent of hormone receptor and human epidermal growth factor receptor 2 status. In multivariate Cox regression analyses, ZNF639 expression was associated with favorable survival outcomes, including recurrence-free survival (hazard ratio, 0.35; 95% confidence interval [CI], 0.14–0.89) and overall survival (hazard ratio, 0.41; 95% CI, 0.16– 1.05). ZNF639 knockdown increased clonogenicity, cell motility, and lung metastasis in NOD/ SCID mice. Following the ZNF639 knockdown, the expression of Snail1, vimentin, and C-C chemokine ligand 20 (CCL20) was upregulated, and the changes in cell phenotype mediated by ZNF639 were reversed by the subsequent knockdown of CCL20.
Conclusion
Low ZNF639 expression is a novel prognostic factor for recurrence-free survival in patients with breast cancer.

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