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.

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.

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.

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.

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.

The Wnt signaling pathway includes both classical and non classical pathways,Wnt5a-Frizzled-2 pathway participates in the Wnt/Ca2+signaling pathway in the non-classical pathway,which is activated by the Wnt-related protein Wnt5a and its ligand Frizzled-2.It can regulate some key sites in cells to affect cell signal transduction,and is closely related to cell growth process.Activation of Wnt5a-Fizzled-2 pathway occurs in some tissues with abundant blood supply,such as heart and brain tissues,during ischemia-reperfusion.Activation of the Wnt5a-Frizzled-2 pathway causes these intracellular calcium overload,ultimately promoting apoptosis.This article reviews the abnormal activation of Wnt5a-Frizzled-2 signaling pathway in ischemia-reperfusion injury diseases and the induced calcium overload leading to apoptosis,in order to provide reference for the study of physiological mechanisms of ischemia-reperfusion injury.

Background::Histological healing is closely associated with improved long-term clinical outcomes and lowered relapses in patients with ulcerative colitis (UC). Here, we developed a novel diagnostic criterion for assessing histological healing in UC patients.Methods::We conducted a retrospective cohort study in UC patients, whose treatment was iteratively optimized to achieve mucosal healing at Shanghai Tenth People’s Hospital of Tongji University from January 2017 to May 2022. We identified an inflammatory cell enumeration index (ICEI) for assessing histological healing based on the proportions of eosinophils, CD177 + neutrophils, and CD40L + T cells in the colonic lamina propria under high power field (HPF), and the outcomes (risks of symptomatic relapses) of achieving histological remission vs. persistent histological inflammation using Kaplan-Meier curves. Intrareader reliability and inter-reader reliability were evaluated by each reader. The relationships to the changes in the Nancy index and the Geboes score were also assessed for responsiveness. The ICEI was further validated in a new cohort of UC patients from other nine university hospitals. Results::We developed an ICEI for clinical diagnosis of histological healing, i.e., Y = 1.701X 1 + 0.758X 2 + 1.347X 3 - 7.745 (X 1, X 2, and X 3 represent the proportions of CD177 + neutrophils, eosinophils, and CD40L + T cells, respectively, in the colonic lamina propria under HPF). The receiver operating characteristics curve (ROC) analysis revealed that Y <-0.391 was the cutoff value for the diagnosis of histological healing and that an area under the curve (AUC) was 0.942 (95% confidence interval [CI]: 0.905-0.979) with a sensitivity of 92.5% and a specificity of 83.6% ( P <0.001). The intraclass correlation coefficient (ICC) for the intrareader reliability was 0.855 (95% CI: 0.781-0.909), and ICEI had good inter-reader reliability of 0.832 (95% CI: 0.748-0.894). During an 18-month follow-up, patients with histological healing had a substantially better outcome compared with those with unachieved histological healing ( P <0.001) using ICEI. During a 12-month follow-up from other nine hospitals, patients with histological healing also had a lower risk of relapse than patients with unachieved histological healing. Conclusions::ICEI can be used to predict histological healing and identify patients with a risk of relapse 12 months and 18 months after clinical therapy. Therefore, ICEI provides a promising, simplified approach to monitor histological healing and to predict the prognosis of UC.Registration::Chinese Clinical Trial Registry, No. ChiCTR2300077792.

Objective To develop a prediction tool for post-endoscopic retrograde cholangiopancreatography(ER-CP)early biliary tract infection(PEEBI)in patients with choledocholithiasis,and assist clinical decision-making be-fore ERCP and early personalized intervention after ERCP.Methods An observational bidirectional cohort study was adopted to select inpatients with choledocholithiasis who underwent ERCP in a hospital.Directed acyclic graph(DAGs)and the least absolute shrinkage and selection operator(LASSO)were used to predict PEEBI based on lo-gistic regression,and the models were compared and validated internally and externally.Results From January 1,2020 to September 30,2023,a total of 2 121 patients with choledocholithiasis underwent ERCP were enrolled,of whom 77(3.6％)developed PEEBI,mostly in the first 2 days after surgery(66.2％).The major influencing fac-tors for PEEBI were non-iatrogenic patient-related factors,namely diabetes mellitus(OR=2.43,95％CI:1.14-4.85),bile duct malignancy(OR=3.95,95％CI:1.74-8.31)and duodenal papillary diverticulum(OR=4.39,95％CI:1.86-9.52).Compared with the LASSO model,the DAGs model showed higher ability(3.0％)in com-prehensive discrimination(P=0.007),as well as good differentiation performance(D=0.133,P=0.894)and cal-ibration performance(x2=5.499,P=0.703)in external validation.Conclusion The DAGs model constructed in this study has good predictive performance.With the help of this tool,targeted early preventive measures in clinical practice can be taken to reduce the occurrence of PEEBI.

Objective To investigate the effect of varying ureteral wall thickness(UWT)at the site of ureteral stones on the clinical efficacy of ureteroscopic lithotripsy(URL).Methods The clinical data of 164 patients with ureteral stones in our hospital were retrospectively analyzed.According to different UWT,the patients were divided into the mild thickening group(84 cases,UWT<3.16 mm),the moderate thickening group(31 cases,UWT 3.16 to 3.49 mm),and the severe thickening group(49 cases,UWT>3.49 mm),and the differences of clinical related indicators among the three groups were compared.Results The incidence of postoperative renal colic and leukocyte disorder in the mild thickening group and the moderate thickening group were lower than those in the severe thickening group,and the differences were statistically significant(P<0.05).The postoperative catheterization time in the mild thickening group and the moderate thickening group were shorter than that in the severe thickening group,and the incidences of secondary lithotripsy,residual stones and stone return to kidney in the mild thickening group and the moderate thickening group were lower than those in the severe thickening group,with statistically significant differences(P<0.05).The length of hospital stay and hospitalization cost in the mild thickening group and the moderate thickening group were shorter/less than those in the severe thickening group,with statistically significant differences(P<0.05).Conclusion With the increase of UWT(especially when UWT>3.49 mm),the incidence of postoperative complications and hospitalization cost of URL increase to varying degrees,and the surgical efficacy decreases.In clinical work,UWT measurement holds potential value in predicting the surgical efficacy and complications of URL.

Background: Intrahepatic cholangiocarcinoma (ICC) is a highly desmoplastic tumor with poor prognosis even after curative resection. We investigated the associations between the composition of the ICC stroma and immune cell infiltration and aimed to develop a stromal-immune signature to predict prognosis in surgically treated ICC. Patients and methods: We recruited 359 ICC patients and performed immunohistochemistry to detect α-smooth muscle actin (α-SMA), CD3, CD4, CD8, Foxp3, CD68, and CD66b. Aniline was used to stain collagen deposition. Survival analyses were performed to detect prognostic values of these markers. Recursive partitioning for a discrete-time survival tree was applied to define a stromal-immune signature with distinct prognostic value. We delineated an integrated stromal-immune signature based on immune cell subpopulations and stromal composition to distinguish subgroups with different recurrence-free survival (RFS) and overall survival (OS) time. Results: We defined four major patterns of ICC stroma composition according to the distributions of α-SMA and collagen: dormant (α-SMAlow/collagenhigh), fibrogenic (α-SMAhigh/collagenhigh), inert (α-SMAlow/collagenlow), and fibrolytic (α-SMAhigh/collagenlow). The stroma types were characterized by distinct patterns of infiltration by immune cells. We divided patients into six classes. Class I, characterized by high CD8 expression and dormant stroma, displayed the longest RFS and OS, whereas Class VI, characterized by low CD8 expression and high CD66b expression, displayed the shortest RFS and OS. The integrated stromal-immune signature was consolidated in a validation cohort. Conclusion We developed and validated a stromal-immune signature to predict prognosis in surgically treated ICC. These findings provide new insights into the stromal-immune response to ICC.