Prolonged standing work can lead to various lower limb health issues. Footwear, as a convenient and noninvasive intervention, plays a key role in foot protection. The purpose of this review was to evaluate the impact of footwear characteristics on foot comfort among workers engaged in prolonged standing occupations. A systematic search of PubMed, Web of Science, Scopus, and the Cochrane Library was conducted until March 2025 for experimental and observational studies; the review is registered in International Prospective Register of Systematic Reviews (CRD420251003253).Given the diversity of study designs, participant characteristics, and outcome measures, results were synthesized narratively, organizing findings by footwear design factors. The synthesis indicated that soft soles reduce foot impact and fatigue but offer limited support, whereas hard soles enhance stability but may cause localized pressure and discomfort. Sole hardness should balance cushioning and support based on activity: hard soles for standing and soft soles for walking. Insole hardness must be carefully considered as semirigid arch supports can cause discomfort. Most insoles improve pressure distribution by adjusting arch loading, and some enhance intrinsic foot muscles by promoting toe engagement, reducing leg swelling. Custom orthotic insoles outperform standard ones in comfort and balance. Future research should promote interdisciplinary collaboration with footwear designers to explore key design parameters and establish a scientific framework for protective footwear.

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.

Facing of mounting resource constraints and rising demands for personalization in medical education,regional anatomy teaching urgently requires transformation.In this paper,we focus on the regional anatomy of the thoracic wall,in order to explore a novel AI-driven teaching paradigm.Anchored in the core principle of"virtual-real integration with cadaveric dissection as the cornerstone,"the paradigm redefines educational objective and constructs an intelligent,closed-loop teaching model integrating students,computers,and instructors.Leveraging the robust support of digital intelligence(e.g.,DeepSeek),this paradigm incorporates interactive method including group collaboration,branching instruction,and gamified assessments.It achieves a comprehensive intelligent transformation of the entire teaching process-from goal setting and plan customization to activity implementation,task completion,outcome exchange,multidimensional evaluation,and reflective iteration.This new paradigm centers on medical students and leverages digital intelligence to activate deep personalized learning potential.It seamlessly integrates fundamental anatomical knowledge with clinical scenarios(e.g.,key anatomy in breast cancer surgery,flap design in breast reconstruction),and significantly enhances clinical decision-making abilities,scientific research and innovative thinking,as well as medical humanistic literacy,paving a new path for intelligent medical education.

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.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective:To evaluate the safety, and feasibility of transoral robot-assisted retropharyngeal lymph node (RPLN) dissection.Methods:Clinical data of head and neck cancer patients who underwent transoral robot-assisted RPLN dissection at the Department of Otorhinolaryngology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, and Sun Yat-sen University Cancer Centre from December 2017 to March 2024 were retrospectively analyzed. A total of 35 patients(22 males, 13 females, aged 47.4±13.4 years old) with RPLN metastases from head and neck cancer, including 20 cases of nasopharyngeal cancer, 9 cases of thyroid cancer, 2 cases of salivary adenocarcinoma, 2 cases of tonsil cancer, and 2 cases of hypopharyngeal cancer. Operation time, intraoperative bleeding and complications, postoperative nasogastric tube retention time, hospital stay and complications were evaluated. Statistical analysis was performed using SPSS 22.0 software.Results:All patients successfully received transoral robot-assisted RPLN dissection without intermediate open surgery, with removals of 2 (1, 3) RPLNs. The total operation time was 130 (102, 210) minutes. The intraoperative bleeding was 50 (20, 100) ml, and there was no major bleeding or organ damage during the operation. Prophylactic tracheotomy was performed in 8 cases, and postoperatively nasogastric tubes were left in 22 patients, with retention time of 10.5 (7.5, 14.0) days. Postoperative hospital stay was 5 (4, 9) days. Postoperative complications included incision dehiscence in 4 cases and dysphagia in 4 cases. The median postoperative follow-up was 23.4 months, with progression or recurrence in 5 patients, including regional recurrence in 3 patients, lung metastasis in 1 patient, and bone metastasis in 1 patient. The 2-year regional failure-free survival and disease-free survival rates were 91.43% and 85.71%, respectively.Conclusion:Transoral robot-assisted RPLN dissection is a safe and feasible surgical method with less trauma, fewer complications, and higher safety. Patients need to be carefully selected at the initial stage of application.

Objective:To explore the clinical application value of transoral robotic surgery (TORS) in the treatment of tonsil squamous cell carcinoma (TSCC).Methods:A retrospective analysis was conducted. The clinical data of 157 TSCC patients were collected who received TORS at five medical centers, namely, the Sun Yat-sen University Cancer Center, Sun Yat-sen Memorial Hospital, Eye Ear Nose and Throat Hospital of Fudan University, the First Affiliated Hospital of China Medical University, and Tongji Hospital of Tongji Medical College, from January 1 2017 to July 31 2022. There were 130 males and 27 females, aged 24-85 years. All patients were followed-up at least for 2 years (2-year group), among them, 99 patients had a follow-up of 3 years (3-year group). The overall survival (OS), progression-free survival (PFS), clinical stage, human papillomavirus (HPV) infection status were analyzed. SPSS 25.0 and SAS 9.4 were used for statistical analysis.Results:The OS and PFS of the 2-year group were 91.7% and 87.9%, respectively. The OS and PFS of the 3-year group were 85.9% and 82.8%, respectively. The prognosis of patients with locally early-stage was better than that of locally advanced patients, with the OS of 94.4% for T1-2 vs. 78.0% for T3 ( P=0.005) and the PFS of 91.2% for T1-2 vs. 75.0% for T3 ( P=0.011) in the 2-year group; the OS of 91.1% for T1-2 vs. 65.0% for T3 ( P=0.004) and the PFS of 88.6% for T1-2 vs. 60.0% for T3 ( P=0.002) in the 3-year group; and also, the OS of 90.0% for stage Ⅰ-Ⅱ vs. 79.5% for stage Ⅲ-Ⅳ ( P=0.204) and the PFS of 86.7% for stage Ⅰ-Ⅱ vs. 76.9% for stage Ⅲ-Ⅳ ( P=0.188) in the 3-year group. The prognosis of HPV-positive TSCC patients was better than that of HPV-negative patients in the 3-year group, with the OS of 90.9% for HPV-positive vs. 80.5% for HPV-negative ( P=0.045) and the PFS of 90.9% for HPV-positive vs. 75.6% for HPV-negative ( P=0.047). The average time of postoperative tracheal cannula indwelling was 25.1 days. The indwelling rate and average indwelling time of the postoperative nasogastric tube were 94.3% (148/157) and 8.5 days, respectively. Conclusion:TORS has outstanding survival benefits for TSCC patients. HPV-positive TSCC patients have a better prognosis than HPV-negative patients. TORS treatment of TSCC patients has advantages in postoperative recovery and quality of life.

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.