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.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.Glutamine signaling specifically activates c-Myc and Mcl-1 to facilitate cancer cell proliferation and survival.
Meng WANG ; Fu-Shen GUO ; Dai-Sen HOU ; Hui-Lu ZHANG ; Xiang-Tian CHEN ; Yan-Xin SHEN ; Zi-Fan GUO ; Zhi-Fang ZHENG ; Yu-Peng HU ; Pei-Zhun DU ; Chen-Ji WANG ; Yan LIN ; Yi-Yuan YUAN ; Shi-Min ZHAO ; Wei XU
Protein & Cell 2025;16(11):968-984
Glutamine provides carbon and nitrogen to support the proliferation of cancer cells. However, the precise reason why cancer cells are particularly dependent on glutamine remains unclear. In this study, we report that glutamine modulates the tumor suppressor F-box and WD repeat domain-containing 7 (FBW7) to promote cancer cell proliferation and survival. Specifically, lysine 604 (K604) in the sixth of the 7 substrate-recruiting WD repeats of FBW7 undergoes glutaminylation (Gln-K604) by glutaminyl tRNA synthetase. Gln-K604 inhibits SCFFBW7-mediated degradation of c-Myc and Mcl-1, enhances glutamine utilization, and stimulates nucleotide and DNA biosynthesis through the activation of c-Myc. Additionally, Gln-K604 promotes resistance to apoptosis by activating Mcl-1. In contrast, SIRT1 deglutaminylates Gln-K604, thereby reversing its effects. Cancer cells lacking Gln-K604 exhibit overexpression of c-Myc and Mcl-1 and display resistance to chemotherapy-induced apoptosis. Silencing both c-MYC and MCL-1 in these cells sensitizes them to chemotherapy. These findings indicate that the glutamine-mediated signal via Gln-K604 is a key driver of cancer progression and suggest potential strategies for targeted cancer therapies based on varying Gln-K604 status.
Glutamine/metabolism*
;
Myeloid Cell Leukemia Sequence 1 Protein/genetics*
;
Humans
;
Proto-Oncogene Proteins c-myc/genetics*
;
Cell Proliferation
;
Signal Transduction
;
Neoplasms/pathology*
;
F-Box-WD Repeat-Containing Protein 7/genetics*
;
Cell Survival
;
Cell Line, Tumor
;
Apoptosis
6.Targeted screening and profiling of massive components of colistimethate sodium by two-dimensional-liquid chromatography-mass spectrometry based on self-constructed compound database.
Xuan LI ; Minwen HUANG ; Yue-Mei ZHAO ; Wenxin LIU ; Nan HU ; Jie ZHOU ; Zi-Yi WANG ; Sheng TANG ; Jian-Bin PAN ; Hian Kee LEE ; Yao-Zuo YUAN ; Taijun HANG ; Hai-Wei SHI ; Hongyuan CHEN
Journal of Pharmaceutical Analysis 2025;15(2):101072-101072
In-depth study of the components of polymyxins is the key to controlling the quality of this class of antibiotics. Similarities and variations of components present significant analytical challenges. A two-dimensional (2D) liquid chromatography-mass spectrometr (LC-MS) method was established for screening and comprehensive profiling of compositions of the antibiotic colistimethate sodium (CMS). A high concentration of phosphate buffer mobile phase was used in the first-dimensional LC system to get the components well separated. For efficient and high-accuracy screening of CMS, a targeted method based on a self-constructed high resolution (HR) mass spectrum database of CMS components was established. The database was built based on the commercial MassHunter Personal Compound Database and Library (PCDL) software and its accuracy of the compound matching result was verified with six known components before being applied to genuine sample screening. On this basis, the unknown peaks in the CMS chromatograms were deduced and assigned. The molecular formula, group composition, and origins of a total of 99 compounds, of which the combined area percentage accounted for more than 95% of CMS components, were deduced by this 2D-LC-MS method combined with the MassHunter PCDL. This profiling method was highly efficient and could distinguish hundreds of components within 3 h, providing reliable results for quality control of this kind of complex drugs.
7.Nogo-A Protein Mediates Oxidative Stress and Synaptic Damage Induced by High-Altitude Hypoxia in the Rat Hippocampus.
Jin Yu FANG ; Huai Cun LIU ; Yan Fei ZHANG ; Quan Cheng CHENG ; Zi Yuan WANG ; Xuan FANG ; Hui Ru DING ; Wei Guang ZHANG ; Chun Hua CHEN
Biomedical and Environmental Sciences 2025;38(1):79-93
OBJECTIVE:
High-altitude hypoxia exposure often damages hippocampus-dependent learning and memory. Nogo-A is an important axonal growth inhibitory factor. However, its function in high-altitude hypoxia and its mechanism of action remain unclear.
METHODS:
In an in vivo study, a low-pressure oxygen chamber was used to simulate high-altitude hypoxia, and genetic or pharmacological intervention was used to block the Nogo-A/NgR1 signaling pathway. Contextual fear conditioning and Morris water maze behavioral tests were used to assess learning and memory in rats, and synaptic damage in the hippocampus and changes in oxidative stress levels were observed. In vitro, SH-SY5Y cells were used to assess oxidative stress and mitochondrial function with or without Nogo-A knockdown in Oxygen Glucose-Deprivation/Reperfusion (OGD/R) models.
RESULTS:
Exposure to acute high-altitude hypoxia for 3 or 7 days impaired learning and memory in rats, triggered oxidative stress in the hippocampal tissue, and reduced the dendritic spine density of hippocampal neurons. Blocking the Nogo-A/NgR1 pathway ameliorated oxidative stress, synaptic damage, and the learning and memory impairment induced by high-altitude exposure.
CONCLUSION:
Our results demonstrate the detrimental role of Nogo-A protein in mediating learning and memory impairment under high-altitude hypoxia and suggest the potential of the Nogo-A/NgR1 signaling pathway as a crucial therapeutic target for alleviating learning and memory dysfunction induced by high-altitude exposure.
GRAPHICAL ABSTRACT
available in www.besjournal.com.
Animals
;
Oxidative Stress
;
Hippocampus/metabolism*
;
Rats
;
Nogo Proteins/genetics*
;
Male
;
Rats, Sprague-Dawley
;
Hypoxia/metabolism*
;
Altitude
;
Synapses
;
Humans
;
Altitude Sickness/metabolism*
8.A Retrospective Study of Pregnancy and Fetal Outcomes in Mothers with Hepatitis C Viremia.
Wen DENG ; Zi Yu ZHANG ; Xin Xin LI ; Ya Qin ZHANG ; Wei Hua CAO ; Shi Yu WANG ; Xin WEI ; Zi Xuan GAO ; Shuo Jie WANG ; Lin Mei YAO ; Lu ZHANG ; Hong Xiao HAO ; Xiao Xue CHEN ; Yuan Jiao GAO ; Wei YI ; Yao XIE ; Ming Hui LI
Biomedical and Environmental Sciences 2025;38(7):829-839
OBJECTIVE:
To investigate chronic hepatitis C virus (HCV) infection's effect on gestational liver function, pregnancy and delivery complications, and neonatal development.
METHODS:
A total of 157 HCV antibody-positive (anti-HCV[+]) and HCV RNA(+) patients (Group C) and 121 anti-HCV(+) and HCV RNA(-) patients (Group B) were included as study participants, while 142 anti-HCV(-) and HCV RNA(-) patients (Group A) were the control group. Data on biochemical indices during pregnancy, pregnancy complications, delivery-related information, and neonatal complications were also collected.
RESULTS:
Elevated alanine aminotransferase (ALT) rates in Group C during early, middle, and late pregnancy were 59.87%, 43.95%, and 42.04%, respectively-significantly higher than Groups B (26.45%, 15.70%, 10.74%) and A (23.94%, 19.01%, 6.34%) ( P < 0.05). Median ALT levels in Group C were significantly higher than in Groups A and B at all pregnancy stages ( P < 0.05). No significant differences were found in neonatal malformation rates across groups ( P > 0.05). However, neonatal jaundice incidence was significantly greater in Group C (75.16%) compared to Groups A (42.25%) and B (57.02%) ( χ 2 = 33.552, P < 0.001). HCV RNA positivity during pregnancy was an independent risk factor for neonatal jaundice ( OR = 2.111, 95% CI 1.242-3.588, P = 0.006).
CONCLUSIONS
Chronic HCV infection can affect the liver function of pregnant women, but does not increase the pregnancy or delivery complication risks. HCV RNA(+) is an independent risk factor for neonatal jaundice.
Humans
;
Female
;
Pregnancy
;
Adult
;
Pregnancy Complications, Infectious/epidemiology*
;
Retrospective Studies
;
Pregnancy Outcome
;
Infant, Newborn
;
Viremia/virology*
;
Hepatitis C
;
Hepacivirus/physiology*
;
Hepatitis C, Chronic/virology*
;
Young Adult
;
Alanine Transaminase/blood*
9.Spatial-temporal Dynamics of Tuberculosis and Its Association with Meteorological Factors and Air Pollution in Shaanxi Province, China.
Heng Liang LYU ; Xi Hao LIU ; Hui CHEN ; Xue Li ZHANG ; Feng LIU ; Zi Tong ZHENG ; Hong Wei ZHANG ; Yuan Yong XU ; Wen Yi ZHANG
Biomedical and Environmental Sciences 2025;38(7):867-872
10.Integrating Internet Search Data and Surveillance Data to Construct Influenza Epidemic Thresholds in Hubei Province: A Moving Epidemic Method Approach.
Cai Xia DANG ; Feng LIU ; Heng Liang LYU ; Zi Qian ZHAO ; Si Jin ZHU ; Yang WANG ; Yuan Yong XU ; Ye Qing TONG ; Hui CHEN
Biomedical and Environmental Sciences 2025;38(9):1150-1154

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