The development of diabetic bladder dysfunction(DBD)is closely related to the dysregulation of the microbiotagut-bladder axis. Diabetic conditions significantly alter gut microbiota composition, causing intestinal barrier disruption, endotoxemia, and systemic inflammation. These alterations impair bladder function by activating bladder NOD-like receptor thermal protein domain associated protein 3(NLRP3)inflammasome, inducing oxidative stress, and nerve remodeling. Emerging technologies for microbiota analysis, Mendelian randomization, and targeted marker development have revealed the causal links between specific gut microbiota and DBD. Modulating gut microbiota increases short-chain fatty acids(SCFAs)production and suppresses inflammation; NLRP3 pathway targeting or direct SCFAs delivery are under clinical evaluation. The therapeutic directions for DBD include microbiota regulation therapy, application of probiotics and dietary fiber, as well as clinical translational research on the microbiota-gut-bladder axis. Engineered live bacterial therapies and nanocarrier technologies are emerging research directions. Current controversies focus on the causal role of dysbiosis, safety and long-term efficacy of individualized therapies, and technical bottlenecks. Future efforts require integrating multi-omics, organoid models, and cross-disciplinary collaboration to advance precision diagnostics and therapeutics targeting the microbiota-gut-bladder axis in DBD.

Object:To explore the feasibility of using artificial intelligence for quality control of echocardiographic images.Methods:Retrospectively，5 000 two-dimensional echocardiographic video images within the period from 2021 to 2023 were randomly retrieved from the echocardiography database of Nanjing Drum Tower Hospital，Affiliated Hospital of Medical School，Nanjing University. Among these selected images，1 559 of them were apical views. The physician team formulated the scoring rules，which specifically included four scoring criteria：gain，scaling ratio，cardiac axis angle，and structure. Subsequently，the data were labeled with view classification and image quality scores. The labeled data were further partitioned into the training set（ n = 643），the validation set（ n = 276），and the test set（ n = 640）. The training and validation sets were utilized for constructing the models for view classification and quality assessment，while the test set was employed to verify the models' effectiveness. The view classification module was implemented using the SlowFast model，and the quality assessment module involved algorithms such as ResNet，Video Swin Transformer，SSD，and U-Net. Results:The average accuracy，precision，recall rate and F1 score of the classification model in identifying each apical view were 0.987 1，0.983 0，0.987 1 and 0.984 9 respectively，and the inference time was（333.4 ± 105.4）ms. The average accuracies of the quality assessment module in terms of gain，scaling ratio，cardiac axis angle and display of main structures were 0.915 1，0.928 2，0.938 7 and 0.965 6 respectively，and the overall scoring accuracy was 0.912 7.Conclusions:The echocardiogram quality control system developed in this research can effectively classify and evaluate the quality of two-dimensional images of the apical views in echocardiograms. Moreover，it guarantees the objectivity，timeliness and high-efficiency of quality control，which has reference value for the establishment of the echocardiogram quality control system.

Object:To explore the feasibility of using artificial intelligence for quality control of echocardiographic images.Methods:Retrospectively，5 000 two-dimensional echocardiographic video images within the period from 2021 to 2023 were randomly retrieved from the echocardiography database of Nanjing Drum Tower Hospital，Affiliated Hospital of Medical School，Nanjing University. Among these selected images，1 559 of them were apical views. The physician team formulated the scoring rules，which specifically included four scoring criteria：gain，scaling ratio，cardiac axis angle，and structure. Subsequently，the data were labeled with view classification and image quality scores. The labeled data were further partitioned into the training set（ n = 643），the validation set（ n = 276），and the test set（ n = 640）. The training and validation sets were utilized for constructing the models for view classification and quality assessment，while the test set was employed to verify the models' effectiveness. The view classification module was implemented using the SlowFast model，and the quality assessment module involved algorithms such as ResNet，Video Swin Transformer，SSD，and U-Net. Results:The average accuracy，precision，recall rate and F1 score of the classification model in identifying each apical view were 0.987 1，0.983 0，0.987 1 and 0.984 9 respectively，and the inference time was（333.4 ± 105.4）ms. The average accuracies of the quality assessment module in terms of gain，scaling ratio，cardiac axis angle and display of main structures were 0.915 1，0.928 2，0.938 7 and 0.965 6 respectively，and the overall scoring accuracy was 0.912 7.Conclusions:The echocardiogram quality control system developed in this research can effectively classify and evaluate the quality of two-dimensional images of the apical views in echocardiograms. Moreover，it guarantees the objectivity，timeliness and high-efficiency of quality control，which has reference value for the establishment of the echocardiogram quality control system.

Objective To explore the value of deep learning(DL)models semi-automatic training system for automatic optimization of clinical image quality control of transthoracic echocardiography(TTE).Methods Totally 1 250 TTE videos from 402 patients were retrospectively collected,including 490 apical four chamber(A4C),310 parasternal long axis view of left ventricle(PLAX)and 450 parasternal short axis view of great vessel(PSAXGv).The videos were divided into development set(245 A4C,155 PLAX,225 PSAXGV),semi-automated training set(98 A4C,62 PLAX,90 PSAXGV)and test set(147 A4C,93 PLAX,135 PSAXGV)at the ratio of 5:2:3.Based on development set and semi-automatic training set,DL model of quality control was semi-automatically iteratively optimized,and a semi-automatic training system was constructed,then the efficacy of DL models for recognizing TTE views and assessing imaging quality of TTE were verified in test set.Results After optimization,the overall accuracy,precision,recall,and F1 score of DL models for recognizing TTE views in test set improved from 97.33％,97.26％,97.26％and 97.26％to 99.73％,99.65％,99.77％and 99.71％,respectively,while the overall accuracy for assessing A4C,PLAX and PSAXGV TTE as standard views in test set improved from 89.12％,83.87％and 90.37％to 93.20％,90.32％and 93.33％,respectively.Conclusion The developed DL models semi-automatic training system could improve the efficiency of clinical imaging quality control of TTE and increase iteration speed.

Objective:To develop an occupational internal driving force measurement scale for general practitioners receiving residency training, and to investigate its reliability and validity.Methods:A pool of items was constructed for the scale based on the literature analysis and qualitative interview results of occupational internal driving force and the current development status of general practitioners, and then expert Delphi consultation was conducted to form the initial version of the scale. A questionnaire survey was conducted among 403 general practitioners to test the reliability and validity of the scale.Results:There were 11 items in the occupational internal driving force scale for general practitioners receiving residency training, which were divided into three dimensions. The scale had a Cronbach's α coefficient of 0.945, and each dimension had a Cronbach's α coefficient of above 0.850; the KMO coefficient of the Bartlett's sphericity test was 0.925. The factor analysis showed that all items had a factor load of ≥0.4 and a commonality of >0.2, and thus 11 items were retained. Three common factors were extracted by the factor analysis and the correlation analysis showed a correlation coefficient of >0 between the common factors of the total score of the scale and a significant positive correlation ( P<0.01). Based on the contents, theoretical research, and expert suggestions of each factor, they were named subject affiliation, development expectations, and identification needs, which contained 3 items, 3 items, and 5 items, respectively. Conclusions:The occupational internal driving force scale for general practitioners receiving residency training has a reasonable structure and good reliability and validity and is suitable for evaluating the occupational internal driving force of general practitioners, which provides guidance for the vocational education of residents.

The integration of regional medical centers and community health service centers is an effective way to improve the professional ability of general practitioners in post-practice training. Its major advantage lies in the establishment of a regional general practitioner ability improvement system integrating assessment, practice and teaching under the unified health administrative department. This article introduces the path of general practitioner post-training developed by Shanghai Tongren Hospital in forms of a regional medical center combined with the community health service center under the "integrated dual-drives" model, which was carried out in Shanghai Changning District; and its preliminary accomplishment is also discussed. It may provide reference for regional medical centers to improve the ability of general practitioners through practice-driven and teaching-driven.

Objective:To analyze the clinical knowledge and training needs of general practitioners from subjective perception and objective assessment, and to analyze their relationship.Methods:A survey was conducted among general practitioners from community health service centers in Shanghai Changning district from September to December 2020. Based on the general practitioner competency indicator system designed by the project team, 17 clinical knowledge competency evaluation indicators were developed through expert consultation, and used for subjective perception and objective assessment of clinical knowledge and learning needs among general practitioners. The influencing factors of objective assessment scores were analyzed, and the relationship between subjective perception and objective assessment scores was analyzed using the four quadrant method.Results:A total of 136 general practitioners participated in the study with the mean age of (39.25±5.90) years, most of whom were attending physician (67.65%, 92/136) and had undergraduate education (88.20%, 122/136). The average daily application frequency score was (1.55±0.21), and the training needs score was (1.65±0.09) for 17 clinical knowledge items; the average objective evaluation score was (74.21±14.0) points. The older the age ( OR=1.25, 95% CI:1.14-1.37), the higher the educational level ( OR=2.11, 95% CI:1.57-2.83), and the longer the working years ( OR=1.16, 95% CI:1.04-1.30) were significantly correlated with the higher objective evaluation scores (all P<0.05). The objective evaluation scores of endocrine diseases such as diabetes, cerebrovascular diseases and respiratory diseases are the highest, and the daily application frequency and learning needs are high (the first quadrant); The objective evaluation scores of common orthopedic diseases, common psychological diseases, and planned immunity indicators were relatively low, but their daily application frequency and learning needs were relatively high (second quadrant). The objective evaluation scores of indicators such as common malignant tumors, common dermatology diseases and health problems, and common ENT diseases were low, and the daily application frequency and learning needs were also low (the third quadrant). The objective evaluation scores of indicators such as hospice and palliative care are relatively high, but their daily application frequency and training needs are relatively low (listed in the fourth quadrant). Conclusions:The clinical knowledge levels of general practitioners are correlated with age, education level, and years of practice. There is a certain overlap between the objective evaluation results of clinical knowledge and the frequency of knowledge usage and training needs of general practitioners, and a targeted training mechanism should be established.

Objective:To construct an evaluation scale for post competence of family doctors based on knowledge-skill-management model.Methods:The evaluation dimensions and indicators for post competency of family doctors were preliminarily developed through literature review, internal group meeting and brainstorming, and in-depth interviews of experts. And 16 experts in the fields of general practice and health management were invited for 2 rounds of Delphi consultation from December 2020 to April 2021. A competency evaluation scale for family doctors based on the dimensions of knowledge, skills and management was finally constructed.Results:The age of the experts was (47.9±7.3) years with a working experience of (24.6±7.8) years. The Cronbach′s α of the questionnaires was 0.891 and the KMO was 0.844. The positive coefficients for 2 rounds of expert consultation were 100%; the familiarity level of experts was 0.86 and authority level was 0.89 in the first round consultation, and those were 0.84 and 0.90 in the second round consultation. After 2 rounds of consultation, the coordination coefficient of expert opinions in the knowledge and skill dimensions was>0.5, and that in the management dimension and overall evaluation system was>0.3. After discussion 2 indicators were deleted in the first round of consultation. The finally constructed family doctor post competency evaluation scale included 3 dimensions, 8 secondary indicators and 61 tertiary indicators. Conclusion:Through the Delphi consultation, we have successfully constructed an evaluation scale for post competence of family doctors based on the three dimensions of knowledge, skills and management.

Objective:To collect data on urinary flow rate in the elderly female population across the country and to analyze the range of reference values.Methods:This study enrolled 333 subjects from July 2020 to June 2022.The study implementation process was divided into two steps.In the first step, subjects completed an electronic questionnaire, which included basic information about the subject, a short form for urinary incontinence, and a scoring form for the symptoms of overactive bladder syndrome.In the second step, the staff introduced the use of a mobile uroflowmetric device and distributed the instrument and materials.Uroflow rate data were automatically uploaded to a cloud database via the mobile phone.Subsequently, two or more physicians specializing in urinary control performed Uroflow rate-qualifying screenings and conducted statistical analyses.Results:A total of 333 subjects were enrolled in the study, and the researchers collected 1375 qualified urine flow rate records using a mobile urine flow rate instrument.The age of the subjects ranged from 60 to 84 years, with a mean age of 69 years.The reference ranges for urinary flow rate were found to be 24.8-26.2 s, with a mean urinary flow rate of 12.2-12.9 ml/s, a maximum urinary flow rate of 22.2-23.4 ml/s, and a time to peak of 8.5-9.7 s. The study observed a tendency for both maximal and mean urinary flow rates to decrease in older women as their age increased(Pearson correlation coefficient: -0.1, P<0.001). Conclusions:The uroflow rate of older women decreases with aging.Specifically, the average uroflow rate of women over 80 years old is lower than that of other age groups.This study aims to establish normal uroflow parameters for uroflowmetry in healthy older women in China.

Objective:To evaluate the clinical effect of anterior clinoid process grinding in the treatment of ophthalmic / superior clinoid process aneurysms and sellar tumors.Methods:The clinical data of 16 patients who underwent anterior clinoid process grinding in Sanbo Brain Hospital, Capital Medical University from January 2015 to July 2021 were analyzed retrospectively. There were 1 patient with recurrent craniopharyngioma, 1 patient with recurrent pituitary adenoma, 13 patients with aneurysms, and 1 patient with suprasellar granulosa cell tumor combined with ophthalmic aneurysm of right internal carotid artery. The Modified Rankin Scale (mRS) score was used to evaluate the situation at discharge and in the medium-and-long term.Results:Sixteen patients underwent anterior clinoidprocess grinding. At discharge and the latest follow-up, the mRS scores of the patients were 0-2. A total of 15 aneurysms were treated, and there were no symptoms of visual loss or visual field defect after operation. No cerebrospinal fluid leakage occurred in all patients.Conclusions:The grinding of anterior clinoid process can effectively and fully stretch the optic nerve and internal carotid artery, and can observe the tumor neck at the lower end of pituitary stalk and the ocular segment/superior clinoid process of internal carotid artery under direct vision. It is one of the important auxiliary methods for the treatment of sellar lesions.