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.Oxidative Stress-related Signaling Pathways and Antioxidant Therapy in Alzheimer’s Disease
Li TANG ; Yun-Long SHEN ; De-Jian PENG ; Tian-Lu RAN ; Zi-Heng PAN ; Xin-Yi ZENG ; Hui LIU
Progress in Biochemistry and Biophysics 2025;52(10):2486-2498
Alzheimer’s disease (AD) is a neurodegenerative disorder characterized by progressive cognitive decline, functional impairment, and neuropsychiatric symptoms. It represents the most prevalent form of dementia among the elderly population. Accumulating evidence indicates that oxidative stress plays a pivotal role in the pathogenesis of AD. Notably, elevated levels of oxidative stress have been observed in the brains of AD patients, where excessive reactive oxygen species (ROS) can cause extensive damage to lipids, proteins, and DNA, ultimately compromising neuronal structure and function. Amyloid β‑protein (Aβ) has been shown to induce mitochondrial dysfunction and calcium overload, thereby promoting the generation of ROS. This, in turn, exacerbates Aβ aggregation and enhances tau phosphorylation, leading to the formation of two pathological features of AD: extracellular Aβ plaque deposition and intracellular neurofibrillary tangles (NFTs). These events ultimately culminate in neuronal death, forming a vicious cycle. The interplay between oxidative stress and these pathological processes constitutes a core link in the pathogenesis of AD. The signaling pathways mediating oxidative stress in AD include Nrf2, RCAN1, PP2A, CREB, Notch1, NF‑κB, ApoE, and ferroptosis. Nrf2 signaling pathway serves as a key regulator of cellular redox homeostasis, exerts important antioxidant capacity and protective effects in AD. RCAN1 signaling pathway, as a calcineurin inhibitor, and modulates AD progression through multiple mechanisms. PP2A signaling pathway is involved in regulating tau phosphorylation and neuroinflammation processes. CREB signaling pathway contributes to neuroplasticity and memory formation; activation of CREB improves cognitive function and reduce oxidative stress. Notch1 signaling pathway regulates neuronal development and memory, participates in modulation of Aβ production, and interacts with Nrf2 toco-regulate antioxidant activity. NF‑κB signaling pathway governs immune and inflammatory responses; sustained activation of this pathway forms “inflammatory memory”, thereby exacerbating AD pathology. ApoE signaling pathway is associated with lipid metabolism; among its isoforms, ApoE-ε4 significantly increases the risk of AD, leading to elevated oxidative stress, abnormal lipid metabolism, and neuroinflammation. The ferroptosis signaling pathway is driven by iron-dependent lipid peroxidation, and the subsequent release of lipid peroxidation products and ROS exacerbate oxidative stress and neuronal damage. These interconnected pathways form a complex regulatory network that regulates the progression of AD through oxidative stress and related pathological cascades. In terms of therapeutic strategies targeting oxidative stress, among the drugs currently used in clinical practice for AD treatment, memantine and donepezil demonstrate significant therapeutic efficacy and can improve the level of oxidative stress in AD patients. Some compounds with antioxidant effects (such asα-lipoic acid and melatonin) have shown certain potential in AD treatment research and can be used as dietary supplements to ameliorate AD symptoms. In addition, non-drug interventions such as calorie restriction and exercise have been proven to exerted neuroprotective effects and have a positive effect on the treatment of AD. By comprehensively utilizing the therapeutic characteristics of different signaling pathways, it is expected that more comprehensive multi-target combination therapy regimens and combined nanomolecular delivery systems will be developed in the future to bypass the blood-brain barrier, providing more effective therapeutic strategies for AD.
8.Perspective of Calcium Imaging Technology Applied to Acupuncture Research.
Sha LI ; Yun LIU ; Nan ZHANG ; Wang LI ; Wen-Jie XU ; Yi-Qian XU ; Yi-Yuan CHEN ; Xiang CUI ; Bing ZHU ; Xin-Yan GAO
Chinese journal of integrative medicine 2024;30(1):3-9
Acupuncture, a therapeutic treatment defined as the insertion of needles into the body at specific points (ie, acupoints), has growing in popularity world-wide to treat various diseases effectively, especially acute and chronic pain. In parallel, interest in the physiological mechanisms underlying acupuncture analgesia, particularly the neural mechanisms have been increasing. Over the past decades, our understanding of how the central nervous system and peripheral nervous system process signals induced by acupuncture has developed rapidly by using electrophysiological methods. However, with the development of neuroscience, electrophysiology is being challenged by calcium imaging in view field, neuron population and visualization in vivo. Owing to the outstanding spatial resolution, the novel imaging approaches provide opportunities to enrich our knowledge about the neurophysiological mechanisms of acupuncture analgesia at subcellular, cellular, and circuit levels in combination with new labeling, genetic and circuit tracing techniques. Therefore, this review will introduce the principle and the method of calcium imaging applied to acupuncture research. We will also review the current findings in pain research using calcium imaging from in vitro to in vivo experiments and discuss the potential methodological considerations in studying acupuncture analgesia.
Calcium
;
Acupuncture Therapy
;
Acupuncture
;
Acupuncture Analgesia/methods*
;
Acupuncture Points
;
Technology
9.Inflammatory and Immunomodulatory Effects of Tripterygium wilfordii Multiglycoside in Mouse Models of Psoriasis Keratinocytes.
Shuo ZHANG ; Hong-Jin LI ; Chun-Mei YANG ; Liu LIU ; Xiao-Ying SUN ; Jiao WANG ; Si-Ting CHEN ; Yi LU ; Man-Qi HU ; Ge YAN ; Ya-Qiong ZHOU ; Xiao MIAO ; Xin LI ; Bin LI
Chinese journal of integrative medicine 2024;30(3):222-229
OBJECTIVE:
To determine the role of Tripterygium wilfordii multiglycoside (TGW) in the treatment of psoriatic dermatitis from a cellular immunological perspective.
METHODS:
Mouse models of psoriatic dermatitis were established by imiquimod (IMQ). Twelve male BALB/c mice were assigned to IMQ or IMQ+TGW groups according to a random number table. Histopathological changes in vivo were assessed by hematoxylin and eosin staining. Ratios of immune cells and cytokines in mice, as well as PAM212 cell proliferation in vitro were assessed by flow cytometry. Pro-inflammatory cytokine expression was determined using reverse transcription quantitative polymerase chain reaction.
RESULTS:
TGW significantly ameliorated the severity of IMQ-induced psoriasis-like mouse skin lesions and restrained the activation of CD45+ cells, neutrophils and T lymphocytes (all P<0.01). Moreover, TGW significantly attenuated keratinocytes (KCs) proliferation and downregulated the mRNA levels of inflammatory cytokines including interleukin (IL)-17A, IL-23, tumor necrosis factor α, and chemokine (C-X-C motif) ligand 1 (P<0.01 or P<0.05). Furthermore, it reduced the number of γ δ T17 cells in skin lesion of mice and draining lymph nodes (P<0.01).
CONCLUSIONS
TGW improved psoriasis-like inflammation by inhibiting KCs proliferation, as well as the associated immune cells and cytokine expression. It inhibited IL-17 secretion from γ δ T cells, which improved the immune-inflammatory microenvironment of psoriasis.
Male
;
Animals
;
Mice
;
Tripterygium
;
Psoriasis/drug therapy*
;
Keratinocytes
;
Skin Diseases/metabolism*
;
Cytokines/metabolism*
;
Imiquimod/metabolism*
;
Dermatitis/pathology*
;
Disease Models, Animal
;
Mice, Inbred BALB C
;
Skin/metabolism*
10.A case-control study on gut microbiota diversity and species composition in obese/overweight children aged 2-6 years in Shanghai
Ping LIAO ; Qin YAN ; Yi ZHANG ; Xin HE ; Peiyun ZHU ; Jian QI ; Chazhen LIU ; Tong LIU ; Yan SHI ; Wenjing WANG
Journal of Environmental and Occupational Medicine 2024;41(3):243-250
Background Multiple studies have shown a close relationship between changes in gut microbiota composition and obesity, and research results are influenced by factors such as race and geographical location, but there are few studies on children. Objective To analyze the diversity of gut microbiota related to obesity in a population of 2-6 years old, observe the distribution characteristics and species differences of gut microbiota between obese/overweight and normal weight groups, and explore the association betweenobese/overweight and gut microbiota diversity. Methods Fecal samples were collected from 74 children aged 2-6 years in Shanghai, including 18 obese/overweight individuals, 6 males and 12 females (male to female ratio of 1∶2), and 56 normal weight individuals, 18 males and 38 females (male to female ratio is nearly 1∶2). The 16S rDNA was extracted from bacteria in fecal samples, followed by PCR amplification, cDNA construction, and high-throughput sequencing. Naive Bayes algorithm was used to perform taxonomic analysis (phylum, class, order, family, genus, species) and community diversity analysis (Sobs index, Shannon index, Shannoneven index, Coverage index, PD index, and principal co-ordinates analysis) on representative sequences and abundance of amplicon sequence variants (ASV). Wilcoxon rank sum test, P-value multiple test correction, and analysis of similarities were used to test differences between the two groups to obtain information on the distribution characteristics and species differences of intestinal microbiota in children. Results Seventy-four fecal samples were sequenced, and the sequencing results were subjected to quality control and filtering. A total of 4905306 optimized sequences were obtained, resulting in 1860 ASVs. The diversity data analysis of ASVs generated 889 species annotation results at 8 taxonomic levels. The alpha diversity analysis showed that the richness (Sobs index), diversity (Shannon index), evenness (Shannoneven index), and phylogenetic diversity (PD index) of fecal community of the obese/overweight children were increased compared to those of the normal weight children, but there were no statistical differences between the two groups (P>0.05). The beta diversity analysis showed that there was little difference in the composition of microbial species between the two groups, and no significant clustering separation was observed. The results of species composition analysis at phylum, order, family, and genus levels of 74 samples showed a consistent core microbiota structure in the two groups of gut microbiota, but there were differences in microbiota composition. The differences in microbial community composition between the two groups were manifested at the taxonomic levels of order, family, and genus, among which phylum Firmicutes, order Erysipelotrichales, family Erysipelatocyclostridiaceae, genus Erysipelotrichaceae_ UCG-003 and genus Catenibacterium were significantly enriched in the obese/overweight group and contributed significantly to the phenotypic difference of obese/overweight [linear discriminant analysis (LDA)=3.72, P<0.01; LDA=3.29, P<0.05). Phylum Proteobacteria, order Enterobacterales, family Enterobacteriaceae, genus unclassified was significantly enriched in the normal weight group and contributed significantly to the phenotypic difference of normal body weight (LDA=3.93, P<0.05). Conclusion The richness and diversity of gut microbiota in obese/overweight children aged 2-6 years in Shanghai are increased, but there is no difference compared to normal weight children. There is a difference in the composition of gut microbiota between the obese/overweight group and the normal weight group.

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