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.

Neddylation is a crucial posttranslational modification that involves the attachment of neural precursor cell-expressed developmentally downregulated protein 8 (NEDD8) to a lysine residue in the substrate via the sequential actions of the E1 NEDD8-activating enzyme (NAE) (E1), E2 NEDD8-conjugating enzyme (E2), and E3 NEDD8-ligase (E3). The most extensively studied substrates of neddylation are members of the cullin family, which act as scaffold components for cullin ring E3 ubiquitin ligases (CRLs). Since cullin neddylation activates CRLs, which are frequently overactive in tumors, inhibiting neddylation has emerged as a promising strategy for developing novel antitumor therapies. This review explores the antitumor effects of inhibiting neddylation that leads to the inactivation of CRLs and provides a summary of known inhibitors that target protein-protein interactions (PPIs) within the neddylation enzymatic cascade.

Objective To observe the clinical efficacy and safety of external application of Piyan Formula in treating epidermal growth factor receptor tyrosine kinase inhibitor(EGFR-TKIs)-related rashes.Methods Sixty cases of EGFR-TKIs-related rash patients were randomly allocated into either a treatment group or a control group.The treatment group received external application of Piyan Formula to the rash area twice daily for 14 days.The control group received external application of fucidic acid cream to the rash area twice daily for 14 days.Changes in rash grading,itching grading,quality of life scores and adverse event were observed and recorded in both groups.At the same time,levels of hypersensitive C-reactive protein,interleukin(IL)-6,and IL-1β were measured before treatment and 24 hours after treatment.Results After treatment,the rash severity,itching severity,and quality of life scores were notably lower in the treatment group compared to the control group(P<0.05).The levels of hypersensitive C-reactive protein,IL-6,and IL-1β exhibited a significant decrease compared to their pre-treatment values.(P<0.05).Compared with the control group,the levels of hypersensitive C-reactive protein,IL-6,and IL-1β decreased in the treatment group,with statistically significant differences(P<0.05).No adverse events related to Piyan Formula or fucidic acid cream occurred during the treatment process.Conclusion External application of Piyan Formula in treating EGFR-TKIs-related rashes shows significant clinical efficacy,can effectively reduce the levels of inflammatory factors,and has high safety,thus warranting clinical promotion.

Background/Aims: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. Methods: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. Results: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. Conclusions Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.

Although microsurgical vasoepididymostomy (MVE) is an effective treatment for epididymal obstructive azoospermia, some patients may experience delayed patency or suboptimal semen parameters after patency. However, research into patency time, semen quality postpatency, and associated influencing factors remains limited. This study aimed to address these issues by evaluating 181 patients who underwent at least one-sided MVE employing asingle-armed longitudinal intussusception vasoepididymostomy technique, with a follow-up period of over 12 months for 150 patients. The overall patency rate was 75.3%, with 86.0% of patients achieving patency within 6 months following MVE. Unexpectedly, factors such as age, history of epididymitis, duration of surgery, side of anastomosis, sperm motility in epididymal fluid, and the site of anastomosis showed no correlation with patency time. Nonetheless, our univariate and multivariate linear regression analysis indicated that only the site of anastomosis was positively correlated with and could independently predict postoperative total motile sperm count. Therefore, the site of anastomosis might serve as a predictor for optimal postoperative semen quality following the MVE procedure.
Male ; Humans ; Epididymis/surgery* ; Semen Analysis ; Azoospermia/surgery* ; Microsurgery/methods* ; Adult ; Anastomosis, Surgical/methods* ; Vas Deferens/surgery* ; Sperm Motility ; Sperm Count ; Middle Aged ; Vasovasostomy/methods*

【Objective】 To investigate the predictive value of high preoperative neutrophile-lymphocyte ratio (NLR) for the prognosis of nonurothelial carcinoma of the bladder (NUBC) after radical cystectomy (RC). 【Methods】 Clinical and follow-up data of NUBC patients undergoing RC during Jan.2005 and Dec.2020 were collected. The optimal cut-off value of NLR was determined with the receiver operating characteristic (ROC) curve. The survival curve was drawn with Kaplan-Meier method to compare the differences in cancer specific survival (CSS) and overall survival (OS) between the high-NLR and low-NLR groups. The independent risk factors of CSS and OS were screened with Cox proportional hazard regression model. 【Results】 Of the 62 eligible cases,34 (54.8%) were diagnosed with adenocarcinoma,17 (27.4%) with squamous cell carcinoma, 6 (9.7%) with small cell carcinoma and 5 (8.1%) with sarcoma. Kaplan-Meier analysis results showed high NLR was associated with poor CSS (P=0.001) and OS (P<0.001). Cox regression results indicated that high NLR (HR=2.42, 95%CI: 1.12-5.23, P=0.025) and advanced pathologic tumor stage (HR=3.21, 95%CI:1.53-6.74,P=0.002) were independent risk factors of unfavorable CSS. Similarly, high NLR (HR=2.75, 95%CI: 1.35-5.56, P=0.005) and advanced pathologic tumor stage (HR=2.81, 95%CI:1.43-5.57, P=0.003) were independent risk factors of unfavorable OS. 【Conclusion】 As an independent risk factor of unfavorable CSS and OS in NUBC patients undergoing RC, high preoperative NLR is of great value in the prediction of long-term prognosis and may help to optimize individualized treatment.