Umbilical cord mesenchymal stem cells (UC-MSCs) have been widely used in regenerative medicine, but there is limited research on the stability of UC-MSCs formulation during production. This study aims to assess the stability of the cell stock solution and intermediate product throughout the production process, as well as the final product following reconstitution, in order to offer guidance for the manufacturing process and serve as a reference for formulation reconstitution methods. Three batches of cell formulation were produced and stored under low temperature (2-8 ℃) and room temperature (20-26 ℃) during cell stock solution and intermediate product stages. The storage time intervals for cell stock solution were 0, 2, 4, and 6 h, while for intermediate products, the intervals were 0, 1, 2, and 3 h. The evaluation items included visual inspection, viable cell concentration, cell viability, cell surface markers, lymphocyte proliferation inhibition rate, and sterility. Additionally, dilution and culture stability studies were performed after reconstitution of the cell product. The reconstitution diluents included 0.9% sodium chloride injection, 0.9% sodium chloride injection + 1% human serum albumin, and 0.9% sodium chloride injection + 2% human serum albumin, with dilution ratios of 10-fold and 40-fold. The storage time intervals after dilution were 0, 1, 2, 3, and 4 h. The reconstitution culture media included DMEM medium, DMEM + 2% platelet lysate, 0.9% sodium chloride injection, and 0.9% sodium chloride injection + 1% human serum albumin, and the culture duration was 24 h. The evaluation items were viable cell concentration and cell viability. The results showed that the cell stock solution remained stable for up to 6 h under both low temperature (2-8 ℃) and room temperature (20-26 ℃) conditions, while the intermediate product remained stable for up to 3 h under the same conditions. After formulation reconstitution, using sodium chloride injection diluted with 1% or 2% human serum albumin maintained a viability of over 80% within 4 h. It was observed that different dilution factors had an impact on cell viability. After formulation reconstitution, cultivation in medium with 2% platelet lysate resulted in a cell viability of over 80% after 24 h. In conclusion, the stability of cell stock solution within 6 h and intermediate product within 3 h meets the requirements. The addition of 1% or 2% human serum albumin in the reconstitution diluent can better protect the post-reconstitution cell viability.

Objectives It was a preliminary exploration on rare disease management of comprehensive hospital based on the"Center-Multidisciplinary Team"structure.Methods By applying interrupted time series analysis,the characteristics and related medical service of rare disease patients discharged from sample hospitals from 2021 to 2023 were measured.Results The results showed that the hospital served 19 825 rare disease patients from 2021 to 2023.The proportion of patients whose main diagnosis were rare diseases was approximately 27％.The interrupted time series technique indicated that the expected proportion of rare disease patients increased instantly by 1.89 thousand points.The capability to diagnose has significantly improved,with a growing trend on volume of bioinformatics analysis services for rare diseases patients.Conclusion The rare disease management based on the"Center-Team"structure can increase the attention of medical staff to rare diseases,strengthen the diagnostic capacity of rare diseases,and make patient management more continuous and disciplinary co-operation more efficient without significantly increasing the input burden on hospitals.

Objectives It was a preliminary exploration on rare disease management of comprehensive hospital based on the"Center-Multidisciplinary Team"structure.Methods By applying interrupted time series analysis,the characteristics and related medical service of rare disease patients discharged from sample hospitals from 2021 to 2023 were measured.Results The results showed that the hospital served 19 825 rare disease patients from 2021 to 2023.The proportion of patients whose main diagnosis were rare diseases was approximately 27％.The interrupted time series technique indicated that the expected proportion of rare disease patients increased instantly by 1.89 thousand points.The capability to diagnose has significantly improved,with a growing trend on volume of bioinformatics analysis services for rare diseases patients.Conclusion The rare disease management based on the"Center-Team"structure can increase the attention of medical staff to rare diseases,strengthen the diagnostic capacity of rare diseases,and make patient management more continuous and disciplinary co-operation more efficient without significantly increasing the input burden on hospitals.

Objectives It was a preliminary exploration on rare disease management of comprehensive hospital based on the"Center-Multidisciplinary Team"structure.Methods By applying interrupted time series analysis,the characteristics and related medical service of rare disease patients discharged from sample hospitals from 2021 to 2023 were measured.Results The results showed that the hospital served 19 825 rare disease patients from 2021 to 2023.The proportion of patients whose main diagnosis were rare diseases was approximately 27％.The interrupted time series technique indicated that the expected proportion of rare disease patients increased instantly by 1.89 thousand points.The capability to diagnose has significantly improved,with a growing trend on volume of bioinformatics analysis services for rare diseases patients.Conclusion The rare disease management based on the"Center-Team"structure can increase the attention of medical staff to rare diseases,strengthen the diagnostic capacity of rare diseases,and make patient management more continuous and disciplinary co-operation more efficient without significantly increasing the input burden on hospitals.

Objectives It was a preliminary exploration on rare disease management of comprehensive hospital based on the"Center-Multidisciplinary Team"structure.Methods By applying interrupted time series analysis,the characteristics and related medical service of rare disease patients discharged from sample hospitals from 2021 to 2023 were measured.Results The results showed that the hospital served 19 825 rare disease patients from 2021 to 2023.The proportion of patients whose main diagnosis were rare diseases was approximately 27％.The interrupted time series technique indicated that the expected proportion of rare disease patients increased instantly by 1.89 thousand points.The capability to diagnose has significantly improved,with a growing trend on volume of bioinformatics analysis services for rare diseases patients.Conclusion The rare disease management based on the"Center-Team"structure can increase the attention of medical staff to rare diseases,strengthen the diagnostic capacity of rare diseases,and make patient management more continuous and disciplinary co-operation more efficient without significantly increasing the input burden on hospitals.

Objectives It was a preliminary exploration on rare disease management of comprehensive hospital based on the"Center-Multidisciplinary Team"structure.Methods By applying interrupted time series analysis,the characteristics and related medical service of rare disease patients discharged from sample hospitals from 2021 to 2023 were measured.Results The results showed that the hospital served 19 825 rare disease patients from 2021 to 2023.The proportion of patients whose main diagnosis were rare diseases was approximately 27％.The interrupted time series technique indicated that the expected proportion of rare disease patients increased instantly by 1.89 thousand points.The capability to diagnose has significantly improved,with a growing trend on volume of bioinformatics analysis services for rare diseases patients.Conclusion The rare disease management based on the"Center-Team"structure can increase the attention of medical staff to rare diseases,strengthen the diagnostic capacity of rare diseases,and make patient management more continuous and disciplinary co-operation more efficient without significantly increasing the input burden on hospitals.

Objectives It was a preliminary exploration on rare disease management of comprehensive hospital based on the"Center-Multidisciplinary Team"structure.Methods By applying interrupted time series analysis,the characteristics and related medical service of rare disease patients discharged from sample hospitals from 2021 to 2023 were measured.Results The results showed that the hospital served 19 825 rare disease patients from 2021 to 2023.The proportion of patients whose main diagnosis were rare diseases was approximately 27％.The interrupted time series technique indicated that the expected proportion of rare disease patients increased instantly by 1.89 thousand points.The capability to diagnose has significantly improved,with a growing trend on volume of bioinformatics analysis services for rare diseases patients.Conclusion The rare disease management based on the"Center-Team"structure can increase the attention of medical staff to rare diseases,strengthen the diagnostic capacity of rare diseases,and make patient management more continuous and disciplinary co-operation more efficient without significantly increasing the input burden on hospitals.

Objectives It was a preliminary exploration on rare disease management of comprehensive hospital based on the"Center-Multidisciplinary Team"structure.Methods By applying interrupted time series analysis,the characteristics and related medical service of rare disease patients discharged from sample hospitals from 2021 to 2023 were measured.Results The results showed that the hospital served 19 825 rare disease patients from 2021 to 2023.The proportion of patients whose main diagnosis were rare diseases was approximately 27％.The interrupted time series technique indicated that the expected proportion of rare disease patients increased instantly by 1.89 thousand points.The capability to diagnose has significantly improved,with a growing trend on volume of bioinformatics analysis services for rare diseases patients.Conclusion The rare disease management based on the"Center-Team"structure can increase the attention of medical staff to rare diseases,strengthen the diagnostic capacity of rare diseases,and make patient management more continuous and disciplinary co-operation more efficient without significantly increasing the input burden on hospitals.

Objectives It was a preliminary exploration on rare disease management of comprehensive hospital based on the"Center-Multidisciplinary Team"structure.Methods By applying interrupted time series analysis,the characteristics and related medical service of rare disease patients discharged from sample hospitals from 2021 to 2023 were measured.Results The results showed that the hospital served 19 825 rare disease patients from 2021 to 2023.The proportion of patients whose main diagnosis were rare diseases was approximately 27％.The interrupted time series technique indicated that the expected proportion of rare disease patients increased instantly by 1.89 thousand points.The capability to diagnose has significantly improved,with a growing trend on volume of bioinformatics analysis services for rare diseases patients.Conclusion The rare disease management based on the"Center-Team"structure can increase the attention of medical staff to rare diseases,strengthen the diagnostic capacity of rare diseases,and make patient management more continuous and disciplinary co-operation more efficient without significantly increasing the input burden on hospitals.

Background/Aims: The accuracy of endosonographers in diagnosing gastric subepithelial lesions (SELs) using endoscopic ultrasonography (EUS) is influenced by experience and subjectivity. Artificial intelligence (AI) has achieved remarkable development in this field. This study aimed to develop an AI-based EUS diagnostic model for the diagnosis of SELs, and evaluated its efficacy with external validation. Methods: We developed the EUS-AI model with ResNeSt50 using EUS images from two hospitals to predict the histopathology of the gastric SELs originating from muscularis propria. The diagnostic performance of the model was also validated using EUS images obtained from four other hospitals. Results: A total of 2,057 images from 367 patients (375 SELs) were chosen to build the models, and 914 images from 106 patients (108 SELs) were chosen for external validation. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of the model for differentiating gastrointestinal stromal tumors (GISTs) and non-GISTs in the external validation sets by images were 82.01%, 68.22%, 86.77%, 59.86%, and 78.12%, respectively. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy in the external validation set by tumors were 83.75%, 71.43%, 89.33%, 60.61%, and 80.56%, respectively. The EUS-AI model showed better performance (especially specificity) than some endosonographers.The model helped improve the sensitivity, specificity, and accuracy of certain endosonographers. Conclusions We developed an EUS-AI model to classify gastric SELs originating from muscularis propria into GISTs and non-GISTs with good accuracy. The model may help improve the diagnostic performance of endosonographers. Further work is required to develop a multi-modal EUS-AI system.