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.

Objective:To analyze the role of learning engagement and learning burnout in the relationship between supervisors' guidance and the personal ability of postgraduates in the Professional Master's Program in Clinical Medicine.Methods:A total of 4 016 postgraduates in the Professional Master's Program in Clinical Medicine from 61 colleges were surveyed in 2020. Common method bias was assessed using the Harman's single factor test and total score was determined by the entropy weight method. Causality and mediation effect were analyzed by linear regression, and mediation effect was tested by Bootstrapping.Results:The average scores of supervisors' guidance, learning burnout, learning engagement and personal ability were (4.13±0.87), (2.49±1.11), (3.88±0.83), and (3.71±0.78), respectively. Supervisors' guidance significantly and positively impacted learning engagement ( β=0.689, P<0.001) and personal ability ( β=0.504, P<0.001). Learning engagement played a partial mediating role (89.30% of mediation effect) between supervisors' guidance and personal ability. Learning burnout (interaction term β=0.078, P<0.001) positively regulated the relationship between supervisors' guidance and learning engagement. Conclusions:Learning engagement can mediate the effect of supervisors' guidance on the personal ability of postgraduates in the Professional Master's Program in Clinical Medicine, and learning burnout positively regulates the effect of supervisors' guidance on learning engagement. Strengthened supervisors' guidance, increased attention to students' learning burnout, and enhanced learning engagement can further improve the personal abilities of postgraduates in the Professional Master's Program in Clinical Medicine.

Objective:To investigate the "burnout-engagement continuum" status of postgraduate supervisors of the Professional Master's Program in Clinical Medicine and to identify key populations.Methods:From October to November 2023, an anonymous online questionnaire survey was conducted to determine the "burnout-engagement continuum" status of postgraduate supervisors of the Professional Master's Program in Clinical Medicine. The scores of different dimensions of job burnout are expressed as mean±standard deviation, and the distribution of supervisors of different status is presented in frequency and percentage. All data analyses were performed in R 4.3.1. Distribution of the five profiles among supervisors of different status was compared using the chi-square test and compared pairwise using the Bonferroni method.Results:A total of 2 664 valid questionnaires were collected. The scores of emotional exhaustion, cynicism and personal accomplishment were（2.46±0.95),（1.74±0.89), and（4.23±0.90), respectively. The prevalence of job engagement, inefficacy, overexertion, disengagement, and burnout among the supervisors were 42.76%（1 139/2 664), 43.54%（1 160/2 664), 33.03%（880/2 664), 14.71%（392/2 664), and 13.66%（364/2 664), respectively. In terms of demographics, the distribution of the "burnout-engagement continuum" was significantly different by age, sex, marital status, and highest education level（ P<0.05). In terms of work-related characteristics, the distribution of the "burnout-engagement continuum" was significantly different by income, professional title, administrative position, and working hours on weekdays and holidays（ P<0.05). The distribution of engagement, inefficacy, and overexertion was significantly different between the eastern and western regions（ P<0.05). Conclusions:There is a high percentage of individuals with burnout among postgraduate supervisors of the Professional Master's Program in Clinical Medicine, and inefficacy is a common negative state. Supervisors who work in the western regions, are under 45 years of age, are male, are married, have a doctorate degree, hold associate senior professional title, have lower relative income, are not holding administrative duties, and work more than 10 hours on workdays and more than 4 hours on holidays are key populations that require increased attention. The psychological state of supervisors can be improved by providing them with more resources, work benefits, and incentives.