Objective To evaluate the applicability and guideline concordance of the Chinese Society of Clinical Oncology(CSCO)arti-ficial intelligence(AI)system in clinical decision-making for colorectal cancer(CRC)patients,and to explore its feasibility in real-world clinical applications.Methods A total of 972 CRC patients diagnosed and treated at the Second Affiliated Hospital,Zhejiang University School of Medicine,from January 2010 to December 2021,were included.Patient data were analyzed by the CSCO AI system to gener-ate treatment decisions,and decision concordance was assessed by a blinded independent central review(BICR)panel.The applicability and guideline concordance rates of the CSCO AI system were calculated for different treatment stages,and a logistic regression model was used to analyze factors influencing the system's decision discrepancies with actual treatments.Results The overall applicability rate of the CSCO AI system was 96.2%,and the overall guideline concordance rate was 94.9%.In the adjuvant and palliative treatment stages,the system's applicability rates were 95.8%and 96.7%,respectively,and the guideline concordance rates were 95.0%and 94.9%,respective-ly.Multivariate logistic regression analysis showed that age≥65 years and high-risk stage Ⅱ treatment were significant factors affecting guideline concordance in the adjuvant treatment stage(both P<0.05).Conclusions The CSCO AI system demonstrated high applicability and guideline concordance in the adjuvant and palliative treatment stages for CRC.The system's clinical decision-making potential is sig-nificant,and it can be further optimized for specific clinical scenarios and promoted for use across various medical institutions.

Objective:To evaluate the effect of 5th generation mobile communication technology(5G) remote robot-assisted cholecystectomy on postoperative recovery and quality of life in patients with gallstones.Methods:Clinical data of patients who underwent 5G remote robotic cholecystectomy(20 cases) vs traditional robotic cholecystectomy(20 cases) at Gansu Provincial People's Hospital from May to September 2023 were retrospectively analyzed. Intraoperative and postoperative related indexes were compared between the two groups, and changes in pain analog scores before, 12 hours, and 24 hours after surgery, and global quality of life (GIQLI) scores before and 3 months after surgery were evaluated.Results:There was no significant difference between the two groups in terms of intraoperative and postoperative conditions (intraoperative blood loss, operative time, time to exhaustion, and length of hospital stay). Patients' pain analog scores at 12 and 24 hours postoperatively were lower than preoperatively, but the differences were not statistically significant( P>0.05). In addition, there was no significant difference in recovery indicators between the two groups compared to the control group ( P>0.05). Conclusion:The postoperative recovery metrics of 5G tele-robotic-assisted cholecystectomy were consistent with the results of conventional robotic surgery.

The strategy of pelvic lymph node dissection in patients with localized intermediate- and high-risk prostate cancer（PCa）has been one of the research hotspots in recent years. This review synthesizes recent progress in clinical，diagnostic imaging and immunological aspects of pelvic lymph node dissection.It is found that the detection rate of metastatic lymph nodes in patients with localized intermediate-risk PCa is relatively low，and the survival benefit after dissection is not significant. PSMA PET/CT examination can be used instead of lymph node dissection for staging. Extended lymph node dissection in patients with localized high-risk PCa can achieve a higher detection rate of metastatic lymph nodes and possible survival benefits. However，excessive lymph node dissection can weaken the response ability to immunotherapy. The strategy for pelvic lymph node dissection in patients with localized intermediate-high-risk PCa needs further study.

Objective To develop and translate the Chinese listening self-efficacy questionnaire(C-LSEQ)and to test its reliability and validity.Methods A total of 172 subjects aged≥60 years with age-related hearing loss completed the C-LSEQ questionnaire via direct interviews.Pure tone hearing threshold test,Mandarin hearing in noise test,and the hearing handicap inventory for elderly-screening(HHIE-S)were evaluated.Twenty subjects were randomly selected from the original group to complete the C-LSEQ questionnaire in 2 weeks after the initial evaluation.Results ① Reliability:The Cronbach's a coefficients of the three sub-dimensions and the overall ques-tionnaire were all＞0.8,and the test-retest reliability coefficients of the three sub-dimensions and the overall ques-tionnaire were all＞0.9(P＜0.001).② Validity:The experts collectively evaluated the representativeness of the statements with good content validity.The convergent validity test showed that the composite reliability(CR)of the 2 sub-dimensions and the overall questionnaire were all＞0.7,and the average variance extracted(AVE)were all＞0.5.The CR value of the complex listening dimension was 0.655,and the AVE value was 0.937.The criterion validity test showed that the overall questionnaire and the three sub-dimensions of the C-LSEQ were significantly correlated with the pure-tone average,speech recognition thresholds in noise,and HHIE-S(P＜0.001).Conclusion The C-LSEQ exhibits stable structure,with good reliability and validity.It can be used to assess listen-ing self-efficacy in adults with hearing loss,especially in the elderly with age-related hearing loss.

The development of 5G remote robot-assisted gastrointestinal surgery is an important breakthrough in remote surgery in the field of four-level surgery. This paper will review the development history of 5G remote robot assisted gastrointestinal surgery, and share the Gansu province people′s hospital in 5G remote robot assisted gastrointestinal surgery about preoperative preparation, network and equipment connection,“3+2” Trocar layout, safety emergency treatment mechanism of exploratory experience, for 5G remote robot assisted gastrointestinal surgery, and the status and prospect of 5G remote robot assisted gastrointestinal surgery.

Objective The Hybrid Education Competence Instrument(HybridEduCom)was sinicized,and its reliability and validity were tested.Methods The translation,cultural adjustment and pre-investigation of HybridEduCom were followed by the Brislin translation model.The reliability and validity of the HybridEduCom was tested by surveying 553 educators in medical and nursing related fields by convenience sampling from March to April 2024.Results The Chinese version of HybridEduCom consisted of 46 items in 5 dimensions:planning and resourcing competence,technology competence,interaction competence,digital pedagogy competence,and ethical competence in the hybrid education.The confirmatory factor analysis resulted in the second-order five-factor model,with the chi-square and degree of freedom ratio being 1.274,approximate root mean square error being 0.022,goodness of fit index being 0.913,and standard fit index(NFI)being 0.934,and Tucker-Lewis and comparative fit index being 0.985.All main evaluation indexes were within the acceptable range of the judgment criteria.The item-content validity index was 0.833-1.000,and the scale-content validity index was 0.968.The Cronbach's α for the whole scale was 0.982,while varied from 0.892 to 0.936 for each dimension.The test-retest reliability of the scale was 0.978.Conclusion The reliability and validity of the Chinese version of HybridEduCom were satisfactory,and it can serve as a valid assessment instrument for the implementation of hybrid education competence of Chinese higher medical and nursing educators.

Objective: To investigate the distribution characteristics of previous infection of human parvovirus B19(HPV B19) among blood donors in Xi 'an, and to provide data support and theoretical basis for formulating individualized and precise blood screening strategies. Methods: A total of 970 qualified blood samples tested at Shaanxi Blood Center from August to September 2024 were randomly selected. The levels of HPV B19 IgG antibodies in the serum were detected by enzyme-linked immunosorbent assay (ELISA). The distribution characteristics of the samples were analyzed from the perspectives of age, gender, education level, occupation, blood type and region. Results: The positive rate of HPV B19 IgG antibodies among blood donors in Xi 'an was 25.26%(245/970), which increased gradually with age (P<0.05). There was no significant difference in the positive rate of HPV B19 IgG antibodies among blood donors of different genders, education levels, occupations, or blood types (P>0.05). Univariate logistic regression analysis showed that past HPV B19 infection was only related to age (P<0.05). The distribution of positive blood samples in 13 districts and counties of Xi 'an was counted based on the blood collection sites. The results showed that there was no significant global spatial autocorrelation in the distribution of positive samples. Among them, the Weiyang District and Beilin District exhibited a "high-high" cluster (P<0.05), while Chang'an District exhibited a "low-high" cluster (P<0.01). Conclusion: A certain proportion of blood donors in Xi'an showed past infection with HPV B19, which was only correlated with age and demonstrated an upward trend. It is recommended to continue expanding the screening scope and incorporate screening for this virus in blood transfusion processes involving susceptible populations.

Objective:To develop PixelSIFT-UNet, a novel semantic segmentation model that integrates deep learning with scale-invariant feature transform (SIFT) algorithm to improve the segmentation accuracy of oral mucosal lesions.Methods:This investigation utilized 838 standard clinical white light images of oral mucosal diseases acquired from January 2020 to December 2022 at the Stomatology Hospital Zhejiang University School of Medicine. Randomization was achieved through Python′s random.seed function implementation. The random sample function was subsequently applied for sampling distribution. The dataset was stratified into three subsets with a 6∶2∶2 ratio: training ( n=506), validation ( n=166), and testing ( n=166). Lesion boundaries were annotated using Labelme software, and a PixelSIFT-UNet-based deep learning model was developed with VGG-16 and ResNet-50 backbone networks. Model parameters were optimized using the validation set, and performance metrics [including Dice coefficient, mean intersection over union (mIoU), mean pixel accuracy (mPA), and Precision] were assessed on the test set. The model′s performance was benchmarked against conventional semantic segmentation frameworks (U-Net and PSPNet). Results:The developed PixelSIFT-UNet model could achieve precise segmentation of three common oral mucosal lesions: oral lichen planus, oral leukoplakia, and oral submucous fibrosis. Utilizing VGG-16 as the backbone network, the model achieved Dice coefficient, mIoU, mPA, and Precision values of 0.642, 0.699, 0.836, and 0.792, respectively. Implementation with ResNet-50 backbone network yielded metrics of 0.668, 0.733, 0.872 and 0.817, demonstrating significant improvements across all performance indicators compared to conventional U-Net model (relevant metrics: 0.662, 0.717, 0.861 and 0.809) and PSPNet model (relevant metrics: 0.671, 0.721, 0.858 and 0.813).Conclusions:The proposed PixelSIFT-UNet architecture demonstrates superior performance in oral mucosal lesion segmentation tasks, surpassing conventional semantic segmentation models and providing robust quantitative improvements in segmentation accuracy.

Objective To develop and translate the Chinese listening self-efficacy questionnaire(C-LSEQ)and to test its reliability and validity.Methods A total of 172 subjects aged≥60 years with age-related hearing loss completed the C-LSEQ questionnaire via direct interviews.Pure tone hearing threshold test,Mandarin hearing in noise test,and the hearing handicap inventory for elderly-screening(HHIE-S)were evaluated.Twenty subjects were randomly selected from the original group to complete the C-LSEQ questionnaire in 2 weeks after the initial evaluation.Results ① Reliability:The Cronbach's a coefficients of the three sub-dimensions and the overall ques-tionnaire were all＞0.8,and the test-retest reliability coefficients of the three sub-dimensions and the overall ques-tionnaire were all＞0.9(P＜0.001).② Validity:The experts collectively evaluated the representativeness of the statements with good content validity.The convergent validity test showed that the composite reliability(CR)of the 2 sub-dimensions and the overall questionnaire were all＞0.7,and the average variance extracted(AVE)were all＞0.5.The CR value of the complex listening dimension was 0.655,and the AVE value was 0.937.The criterion validity test showed that the overall questionnaire and the three sub-dimensions of the C-LSEQ were significantly correlated with the pure-tone average,speech recognition thresholds in noise,and HHIE-S(P＜0.001).Conclusion The C-LSEQ exhibits stable structure,with good reliability and validity.It can be used to assess listen-ing self-efficacy in adults with hearing loss,especially in the elderly with age-related hearing loss.

Objective:To develop PixelSIFT-UNet, a novel semantic segmentation model that integrates deep learning with scale-invariant feature transform (SIFT) algorithm to improve the segmentation accuracy of oral mucosal lesions.Methods:This investigation utilized 838 standard clinical white light images of oral mucosal diseases acquired from January 2020 to December 2022 at the Stomatology Hospital Zhejiang University School of Medicine. Randomization was achieved through Python′s random.seed function implementation. The random sample function was subsequently applied for sampling distribution. The dataset was stratified into three subsets with a 6∶2∶2 ratio: training ( n=506), validation ( n=166), and testing ( n=166). Lesion boundaries were annotated using Labelme software, and a PixelSIFT-UNet-based deep learning model was developed with VGG-16 and ResNet-50 backbone networks. Model parameters were optimized using the validation set, and performance metrics [including Dice coefficient, mean intersection over union (mIoU), mean pixel accuracy (mPA), and Precision] were assessed on the test set. The model′s performance was benchmarked against conventional semantic segmentation frameworks (U-Net and PSPNet). Results:The developed PixelSIFT-UNet model could achieve precise segmentation of three common oral mucosal lesions: oral lichen planus, oral leukoplakia, and oral submucous fibrosis. Utilizing VGG-16 as the backbone network, the model achieved Dice coefficient, mIoU, mPA, and Precision values of 0.642, 0.699, 0.836, and 0.792, respectively. Implementation with ResNet-50 backbone network yielded metrics of 0.668, 0.733, 0.872 and 0.817, demonstrating significant improvements across all performance indicators compared to conventional U-Net model (relevant metrics: 0.662, 0.717, 0.861 and 0.809) and PSPNet model (relevant metrics: 0.671, 0.721, 0.858 and 0.813).Conclusions:The proposed PixelSIFT-UNet architecture demonstrates superior performance in oral mucosal lesion segmentation tasks, surpassing conventional semantic segmentation models and providing robust quantitative improvements in segmentation accuracy.