1.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.
2.Study of adsorption of coated aldehyde oxy-starch on the indexes of renal failure
Qian WU ; Cai-fen WANG ; Ning-ning PENG ; Qin NIE ; Tian-fu LI ; Jian-yu LIU ; Xiang-yi SONG ; Jian LIU ; Su-ping WU ; Ji-wen ZHANG ; Li-xin SUN
Acta Pharmaceutica Sinica 2025;60(2):498-505
The accumulation of uremic toxins such as urea nitrogen, blood creatinine, and uric acid of patients with renal failure
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. Effect Xuefu Zhuyu decoction on endothelial-to-mesenchymal transition of pulmonary artery endothelial cells and its mechanism
Zuo-Mei ZENG ; Xin-Yue WANG ; Lei-Yu TIAN ; Li-Dan CUI ; Jian GUO ; Yu-Cai CHEN
Chinese Pharmacological Bulletin 2024;40(1):155-161
Aim To investigate the effect of Xuefu Zhuyu decoction on transforming growth factor-β1(TGF-β1 ) -induced endothelial-to-mesenchymal transition (EndMT) of pulmonary microvascular endothelial cells ( PMVEC), and further analyze the mechanism related to the TGF-β1/Smad signaling pathway. Method To construct an EndMT cell model, PMVEC was treated with TGF-β1 (5 μg · L
8. Histamine 1 receptor agonist inhibits LPS-induced immune responses in astrocytes via Akt/NF-KB signaling pathway
Jia-Wen XU ; Jia-Hong SHEN ; Yu-Xin WEN ; Jian-Liang SUN
Chinese Pharmacological Bulletin 2024;40(2):317-323
Aim To investigate the effect of histamine H, receptor (HjR) on the immune responses in astrocytes induced by lipopolysaccharide (LPS) and the regulatory mechanism of its signaling pathway. Methods LPS was used to establish an in vitro astrocyte inflammation model. Rat primary astrocytes were divided into the control group, LPS group, LPS + Hj R agonist group (2-pyridylethlamine, Pyri), and HjR agonist group. Astrocytes were treated with Pyri 100 p,mol • L~ for 1 h, then stimulated with LPS at 100 p,g • L~ for 24 h. Cell viability was measured using the CCK-8 assay. The expression of GFAP and HjR was detected by immunofluorescence. Glial morphological changes were observed under a microscope. The levels of proinflammatory mediators (TNF-a and IL-6) were detected by ELISA. The protein expressions of p-Akt, Akt, p-NF-KB p65, and NF-KB p65 were detected by Western blot. Results Compared with the control group, more activated astrocytes with fewer cell processes and branches were observed in the LPS group. Besides, LPS enhanced the GFAP expression level, reduced the H,R expression level and stimulated the production of TNF-a and IL-6 from astrocytes. Pre treatment with Pyri for 1 h ameliorated the glial morphological changes stimulated by LPS, inhibited LPS-induced upregulation of GFAP level and the inflammatory factors secretion. In addition, LPS stimulated astrocytes showed a higher phosphorylation of Akt and NF-KB p65, which was also ameliorated by Pyri. Conclusions H, R agonist can inhibit LPS-induced astrocyte activation and inflammatory factor secretion, and the Akt/NF-KB signaling pathway may be an important pathway for the involvement of H,R in immune regulation.
9.Cloning and gene functional analysis study of dynamin-related protein GeDRP1E gene in Gastrodia elata
Xin FAN ; Jian-hao ZHAO ; Yu-chao CHEN ; Zhong-yi HUA ; Tian-rui LIU ; Yu-yang ZHAO ; Yuan YUAN
Acta Pharmaceutica Sinica 2024;59(2):482-488
The gene
10.Construction and validation of a scoring model for pathogen characteristics and short-term prognosis risk prediction of candidemia
Jian-Xin MA ; Xiao-Qiang LIN ; Ming-Chi CAI ; Yu-Zhen XU ; Jun PENG ; Sheng-Qiang LIANG
Medical Journal of Chinese People's Liberation Army 2024;49(3):280-287
Objective To analyze the pathogenic characteristics and drug sensitivity of candidaemia,and construct a short-term mortality risk prediction scoring model.Methods The clinical data of patients with candidaemia admitted to the 909 Hospital of Joint Logistics Support Force from January 2011 to December 2020 were retrospectively analyzed,and the composition of pathogen composition,drug sensitivity test results and incidence of hospitalized patients were analyzed.324 cases of candidaemia were randomly divided into modeling group(190 cases)and validation group(134 cases),and the risk factors were screened by binary logistic regression.According to the odds ratio(OR)score,the 30 day mortality risk prediction scoring model was constructed,and the predictive performance of the model was verified both in modeling and validation groups.Results 356 strains of Candida including 126 strains of C.albicans(35.39%),79 strains of C.tropicalis(22.19%),74 strains of C.parapsilosis(20.79%),48 strains of C.glabrata(13.48%),14 strains of C.guilliermondii(3.93%),8 strains of C.krusei(2.25%),and 7 strains of other Candida(1.97%)were detected in 336 patients with candidemia.The incidence of candidaemia among hospitalized patients increased from 0.20 ‰ in 2011 to 0.48 ‰ in 2020.The resistance rate of candida to amphotericin B was significantly lower than that of fluconazole,voriconazole and itraconazole(P<0.05).Among the 324 cases included in the model,95 patients died in 30 days after diagnosis,and the mortality rate was 29.32%.The proportion of males,fever,and parenteral nutrition in modeling group was significantly higher than that in validation group(P<0.05),while the proportion of chronic lung disease and surgical history within one month were lower than those in validation group(P<0.05).Logistic regression analysis showed that chronic renal failure,mechanical ventilation,severe neutropenia,failure to receive anti-fungal treatment within 72 hours,and APACHE Ⅱ≥20 were risk factors for short-term death of candidaemia,the OR values were 3.179,1.970,2.979,2.080,and 2.399,and the risk scores were 6,4,6,4,and 5,respectively.The area under the curve(AUC)of the risk scoring model for modeling group was 0.792(95%CI 0.721-0.862),and the result of Hosmer-Lemeshow(H-L)test was P=0.305;The AUC of validation group was 0.796(95%CI 0.735-0.898),and the H-L test result was P=0.329.A risk score≤8 indicated a low risk group for short-term mortality,a score of 9-15 indicated a medium risk group,and a score≥16 indicated a high risk group.Conclusions The incidence of candidemia in hospitalized patients is increasing and the mortality is high.The risk prediction score model can effectively predict the short-term prognosis and facilitate the early identification of the prognosis.

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