As a distinctive resource of Chinese civilization， traditional Chinese medicine （TCM） technology transfer faces significant opportunities under the background of digital and intelligent transformation， while also being constrained by unique challenges such as the complexity of its theoretical system， lengthy industrial chains， and multidimensional policy restrictions， resulting in a "high-value-high-threshold" paradox. At present， TCM technology transfer is deeply trapped in a "threefold reluctance" dilemma， i.e.， unwillingness to transfer， inability to transfer， and lack of capacity to transfer. Specifically， the disconnection between scientific research evaluation systems and market demand leads to low conversion rates of research achievements， unclear ownership and compliance risks suppress innovation incentives， and the absence of professional services intensifies supply-demand mismatches. This article systematically analyzes the specific characteristics of TCM technology transfer and proposes a breakthrough pathway centered on full-chain digital and intelligent transformation. By integrating technologies such as intelligent sorting systems， blockchain-based traceability， and AI diagnostic models， the TCM ecosystem spanning "cultivation-production-service" can be reconstructed. In terms of standardization， promoting the progression from "experience-based data conversion" to "data standardization" and further to "intelligent standardization" is advocated to resolve quality control challenges. For example， a "three-no-one-full" certification system can strengthen quality trust. Policy coordination should focus on optimizing mechanisms for the transformation of scientific and technological achievements， while exploring intellectual property securitization and risk-sharing models to stimulate research momentum. In terms of internationalization， reliance on the Belt and Road Initiative platform to promote the export of geo-authentic medicinal material brands and standards is recommended to build a dual-driven model of "technology plus culture". Looking ahead， through the construction of national-level databases， the cultivation of interdisciplinary talent， and the mutual recognition of international standards， a new paradigm of "scientific intelligent manufacturing" can be formed， providing systematic solutions for the modernization of TCM and global health governance.

To systematically analyzed the reporting status of core elements in publicly available clinical practice guideline(hereafter referred to as "guideline") protocols published domestically and internationally over the past decade, identified existing problems, and provided evidence to inform the standardized writing and publication of future guideline protocols.

Human umbilical cord mesenchymal stem cell （hUC-MSC） as a cell-based therapeutic strategy have demonstrated significant application potential in the field of intervention for neurodegenerative disease （NDD） due to their advantages such as self-renewal， multi-directional differentiation， and low immunogenicity. hUC-MSC effectively intervenes in the pathological features and neurological functions of various disease models such as Alzheimer disease， Parkinson’s disease， amyotrophic lateral sclerosis， and multiple sclerosis primarily through multiple mechanisms such as homing and differentiation， mediating paracrine actions and releasing exosomes， as well as immune regulation and anti-inflammation. Some clinical studies have also preliminarily verified their safety and effectiveness. Currently， its research still faces challenges such as immune rejection reactions requiring further observation， long-term safety needing evaluation， mechanisms of action not being fully elucidated， and slow progress in clinical trials. Future research needs to establish pharmaceutical standards for hUC-MSC， deepen their pharmacological mechanisms and clinical trials， ultimately providing new and effective drug treatment options for patients with NDD.

Objective: To investigate the damaging effects of red blood cell supernatant (RBC-S) stored for different durations (7 d, 14 d, and 28 d) on vascular endothelial cells, and to explore the underlying mechanisms using bioinformatics analysis, so as to provide references for optimizing red blood cell transfusion strategies. Methods: Human umbilical vein endothelial cells (HUVECs) were co-cultured with RBC-S stored for 7, 14 and 28 days, designated as the 7 d group, 14 d group and 28 d group respectively, which were collectively defined as the experimental groups. Cell damage was evaluated by cell proliferation assay (Cell Counting Kit8, CCK8), lactate dehydrogenase (LDH) release assay, 4′, 6diamidino2phenylindole (DAPI) staining, and flow cytometry for apoptosis and reactive oxygen species (ROS) levels. The damage degree of RBC-S on vascular endothelial cells was assessed by statistical analysis of damage data among different groups. Since the damage effect reached a plateau at all time points, the 28 d storage group was selected as the representative for further mechanistic studies. Transcriptomic analysis was performed to explore the role of frizzled class receptor 1 (FZD1) and Wnt signaling pathway in red blood cell storagerelated endothelial dysfunction. Results: Compared with the control group, the storage groups treated with 7 d, 14 d, and 28 d RBC-S showed significantly decreased cell proliferation rates [control group 100%, 7 d group (69.51±2.30)%, 14 d group (74.54±2.89)%, 28 d group (73.59±2.36)%, P<0.05], significantly reduced numbers of DAPI-stained cell nuclei [control group (213±12.5) per field, 7 d group (140.33±17.04) per field, 14 d group (152.00±23.72) per field, 28 d group (144.33±19.09) per field, P<0.05] and significantly increased LDH release [control group (1), 7 d group (8.33±1.41), 14 d group (9.23±0.83), 28 d group (9.16±0.60), P<0.05]. There was no significant difference in the degree of damage caused by RBC-S among different storage groups (P>0.05). With the prolongation of storage time, free hemoglobin (FHb) gradually increased [control group (not detected), 7 d (16.57±6.38) mg/L, 14 d (76.80±22.83) mg/L, 28 d (286.97±29.02) mg/L, P<0.05]. The apoptotic rate (20.53±2.94)% and ROS relative intensity (5.13±0.91) in the 28 d storage group were significantly higher than those in the control group (P<0.05). Transcriptomic analysis showed that FZD1 played a key role in vascular endothelial dysfunction induced by red blood cell storage and was closely related to the Wnt signaling regulatory network. Conclusion: RBC-S stored for 7 d, 14 d, or 28 d can all significantly damage vascular endothelial cells, and the damaging effect reaches a plateau at 7 d of storage. Mechanistic investigation of the 28 d group indicated that the downregulation of the FZD1/Wnt signaling pathway may play a critical role in vascular endothelial dysfunction induced by red blood cell storage, providing a theoretical basis for further optimizing red blood cell storage and transfusion strategies.

Objective:To investigate the predictive value of computed tomography(CT) based radiomics model for the prognosis of patients with pancreatic ductal adenocarcinoma(PDAC).Methods:The retrospective cohort study was conducted. The clinicopathological data of 206 PDAC patients who were admitted to Zhongshan Hospital of Fudan University from August 2018 to December 2020 were collected. There were 115 males and 91 females, aged (64±9)years. All 206 pati-ents underwent enhanced CT examination. Based on radom number table, the 206 patients were randomly divided into a training set of 165 cases and a validation set of 41 cases with a ratio of 4∶1. The training set was used to construct the prediction model, and the test set was used to validate the performance of the prediction model. Observation indicators: (1) follow-up; (2) analysis of prognostic factors of PDAC patients in the training set; (3) construction and evaluation of prediction model for prognosis of PDAC patients. Comparison of measurement data with normal distribution between groups was conducted using the t test. Comparison of measurement data with skewed distribution between groups was conducted using the Wilcoxon W test. Comparison of count data between groups was conducted using the chi-square test or corrected chi-square test. The Kaplan-Meier method was used to calculate the survival rate and Log-rank test was used for survival analysis. Univariate and multivariate analyses were conducted using the COX regression model. The PyCharm software was used for the least absolute shrinkage and selection operator method (LASSO)-COX regression analysis. The receiver operating characteristic curve was plotted to evaluate the performance of radiomics model. Results:(1)Follow-up. Of the 206 patients,205 cases were followed up for 17.1(range, 12.0?40.1)months. The postoperative 1-, 2-, 3-year survival rates were 80.10%, 29.61% and 4.85%. (2) Analysis of prognostic factors for PDAC patients in the training dataset. Results of multivariate analysis showed that pathological N stage was an independent influencing factor for prognosis of PDAC patients in the training set ( hazard ratio=1.476, 95% confidence interval as 1.054?2.067, P<0.05). (3) Construction and evaluation of prediction model for prognosis of PDAC patients. A total of 1 595 radiomics features were finally extracted from the 206 patients. By intra-group feature selection and dimensionality reduction using LASSO-COX regression model, 10 radiomics features were obtained. Combined with 10 radiomics features and 11 clinical features, using the LASSO-COX regression analysis, 15 features were finally extracted to construct the CT based radiomics model for predicting prognosis of PDAC. The areas under receiver operating characteristic curve of the prediction model in predicting 2-year and 3-year overall survival rates of PDAC patients in the training set were 0.834 (95% confidence interval as 0.777?0.891) and 0.883 (95% confidence interval as 0.834?0.932), respectively. The area under curve of the prediction model for patients in the validation set was 0.606 (95% confidence interval as 0.456?0.756) and 0.625 (95% confidence interval as 0.477?0.773). Conclusion:The prediction model constructed on CT based radiomics features and clinical features for predicting the prognosis of PDAC patients shows a promising prediction efficiency.

Objective:To investigate the trajectory of frailty in elderly patients on maintenance hemodialysis(MHD)following SARS-CoV-2 infection and its associated risk factors.Methods:This prospective cohort study focused on elderly patients who underwent baseline frailty assessment(T0)during hemodialysis treatment at Beijing Friendship Hospital for over 3 months between December 1st, 2022, and December 31th, 2022, and were diagnosed with SARS-CoV-2 infection.The Fried Frailty Phenotype was evaluated at 1 month(T1), 3 months(T2), and 6 months(T3)post-infection.Frailty trajectory after infection was analyzed using repeated measurement ANOVA.Patients were divided into stable/improvement or exacerbation groups based on their frailty status at T0 and T3, with logistic regression analysis employed to identify risk factors for different frailty trajectories.Results:A total of 130 elderly maintenance hemodialysis patients, with a median age of 66 years(range: 63-71 years)and 62 males(47.7%), were included in the study.Six months after the infection, a majority of surviving patients saw their frailty scores return to baseline levels.Specifically, 72 patients(55.4%)either maintained or improved to robust or pre-frail states, while 9 patients(6.9%)progressed to a pre-frail state, 18 patients(13.8%)progressed to a frail state, and 31 patients(23.8%)remained in a frail state.Results from multivariate logistic regression analysis indicated that low grip strength( OR: 6.30, 95% CI: 1.48-26.73)and all-cause hospitalization( OR: 5.01, 95% CI: 1.19-21.03)were identified as risk factors for non-frail patients transitioning to frailty( P<0.05). Conclusions:The majority of elderly maintenance hemodialysis patients who survived SARS-CoV-2 infection returned to their baseline level of frailty or showed improvement within 6 months.Non-frail patients with low grip strength or those who were hospitalized were more likely to deteriorate towards frailty.

Objective:To investigate the trajectory of frailty in elderly patients on maintenance hemodialysis(MHD)following SARS-CoV-2 infection and its associated risk factors.Methods:This prospective cohort study focused on elderly patients who underwent baseline frailty assessment(T0)during hemodialysis treatment at Beijing Friendship Hospital for over 3 months between December 1st, 2022, and December 31th, 2022, and were diagnosed with SARS-CoV-2 infection.The Fried Frailty Phenotype was evaluated at 1 month(T1), 3 months(T2), and 6 months(T3)post-infection.Frailty trajectory after infection was analyzed using repeated measurement ANOVA.Patients were divided into stable/improvement or exacerbation groups based on their frailty status at T0 and T3, with logistic regression analysis employed to identify risk factors for different frailty trajectories.Results:A total of 130 elderly maintenance hemodialysis patients, with a median age of 66 years(range: 63-71 years)and 62 males(47.7%), were included in the study.Six months after the infection, a majority of surviving patients saw their frailty scores return to baseline levels.Specifically, 72 patients(55.4%)either maintained or improved to robust or pre-frail states, while 9 patients(6.9%)progressed to a pre-frail state, 18 patients(13.8%)progressed to a frail state, and 31 patients(23.8%)remained in a frail state.Results from multivariate logistic regression analysis indicated that low grip strength( OR: 6.30, 95% CI: 1.48-26.73)and all-cause hospitalization( OR: 5.01, 95% CI: 1.19-21.03)were identified as risk factors for non-frail patients transitioning to frailty( P<0.05). Conclusions:The majority of elderly maintenance hemodialysis patients who survived SARS-CoV-2 infection returned to their baseline level of frailty or showed improvement within 6 months.Non-frail patients with low grip strength or those who were hospitalized were more likely to deteriorate towards frailty.

OBJECTIVE To investigate the distribution and drug resistance of multidrug-resistant bacteria in the neonatal intensive care unit of a three-A children's hospital in Henan Province,and to provide reference for ational drug use in clinical practice.METHODS Clinical specimens from hospitalized newborns in neonatal intensive care unit from a three-A children's hospital from Jan.1,2019 to Dec.31,2023 were subjected to etiological exam-ination and drug sensitivity test,and to analyze the distribution and drug resistance of multidrug-resistant bacteri-a in hospitalized newborns.RESULTS During the 5-year period,1139 strains of multidrug-resistant bacteria were i-solated,including 229 gram-positive bacteria(20.11％)and 910 gram-negative bacteria(79.89％).There were 92 strains of methicillin-resistant Staphylococcus aureus(MRSA)(accounting for 8.08％),57 strains(accounting for 5.00％)of methicillin-resistant coagulase-negative Staphylococcus epidermidis and 28 strains(accounting for 2.46％)of methicillin-resistant coagulase-negative human Staphylococcus.370 strains(accounting for 32.48)of carbapenem-resistant Klebsiella pneumoniae(CRKP),268 strains(accounting for 23.53％)of extenspectrum β-lactamase-producing Escherichia coli and 85 strains(accounting for 7.46％)of K.pneumoniae,there were 767 sputum specimens(67.34％),160 blood specimens from peripheral intravenous puncture and central venous cath-eterization(PICC)(14.05％),63 bronchoalveolar lavage fluid specimens(5.53％),29 secretion specimens(eye and wound secretions)(2.54％),and 120 other specimens(10.54％).K.pneumoniae and E.coli producing su-per-broad spectrum β-lactamase,CRKP and MRSA were the main drug-resistant bacteria.CONCLUSION The sit-uation of drug resistance in neonatal intensive care unit is serious,therefore monitoring bacterial resistance should be strengthened according to the clinical laboratory results,and antibiotics should be applied rationally.

Objective:To investigate the predictive value of computed tomography(CT) based radiomics model for the prognosis of patients with pancreatic ductal adenocarcinoma(PDAC).Methods:The retrospective cohort study was conducted. The clinicopathological data of 206 PDAC patients who were admitted to Zhongshan Hospital of Fudan University from August 2018 to December 2020 were collected. There were 115 males and 91 females, aged (64±9)years. All 206 pati-ents underwent enhanced CT examination. Based on radom number table, the 206 patients were randomly divided into a training set of 165 cases and a validation set of 41 cases with a ratio of 4∶1. The training set was used to construct the prediction model, and the test set was used to validate the performance of the prediction model. Observation indicators: (1) follow-up; (2) analysis of prognostic factors of PDAC patients in the training set; (3) construction and evaluation of prediction model for prognosis of PDAC patients. Comparison of measurement data with normal distribution between groups was conducted using the t test. Comparison of measurement data with skewed distribution between groups was conducted using the Wilcoxon W test. Comparison of count data between groups was conducted using the chi-square test or corrected chi-square test. The Kaplan-Meier method was used to calculate the survival rate and Log-rank test was used for survival analysis. Univariate and multivariate analyses were conducted using the COX regression model. The PyCharm software was used for the least absolute shrinkage and selection operator method (LASSO)-COX regression analysis. The receiver operating characteristic curve was plotted to evaluate the performance of radiomics model. Results:(1)Follow-up. Of the 206 patients,205 cases were followed up for 17.1(range, 12.0?40.1)months. The postoperative 1-, 2-, 3-year survival rates were 80.10%, 29.61% and 4.85%. (2) Analysis of prognostic factors for PDAC patients in the training dataset. Results of multivariate analysis showed that pathological N stage was an independent influencing factor for prognosis of PDAC patients in the training set ( hazard ratio=1.476, 95% confidence interval as 1.054?2.067, P<0.05). (3) Construction and evaluation of prediction model for prognosis of PDAC patients. A total of 1 595 radiomics features were finally extracted from the 206 patients. By intra-group feature selection and dimensionality reduction using LASSO-COX regression model, 10 radiomics features were obtained. Combined with 10 radiomics features and 11 clinical features, using the LASSO-COX regression analysis, 15 features were finally extracted to construct the CT based radiomics model for predicting prognosis of PDAC. The areas under receiver operating characteristic curve of the prediction model in predicting 2-year and 3-year overall survival rates of PDAC patients in the training set were 0.834 (95% confidence interval as 0.777?0.891) and 0.883 (95% confidence interval as 0.834?0.932), respectively. The area under curve of the prediction model for patients in the validation set was 0.606 (95% confidence interval as 0.456?0.756) and 0.625 (95% confidence interval as 0.477?0.773). Conclusion:The prediction model constructed on CT based radiomics features and clinical features for predicting the prognosis of PDAC patients shows a promising prediction efficiency.

[Objective] To explore the feasibility of using whole blood as a source of NK cells for allogeneic CAR NK cell therapy and activated NK cell reinfusion therapy, and initially construct a technical system for the separation and purification of NK cells from whole blood. [Methods] All peripheral blood mononuclear cells (PBMCs) were enriched from 400 mL of whole blood by manual separation and machine separation, respectively. The erythrocyte loss rate, PBMCs number, NK cell purity of the two methods were compared. NK cells were sorted from PBMCs by three separation and enrichment methods as immunomagnetic bead negative selection method, platelet lysate culture expansion and PERCOLL density gradient separation method, and the purity and yield of NK cells, the activity of NK cells and the tumor-killing ability of the three separation and enrichment methods were compared. [Results] The proportion of NK cells in the lymphocyte population was higher in the manual separation method than in the machine separation method[(13.16±5.16)% vs (8.56±3.92)%, P<0.05]; the number PBMCs was lower in the manual separation method than in the machine separation method[(4.09±1.80)×10⁸vs (6.49±2.16)×10⁸, P<0.05], and there was no difference in the red blood cell loss between the two methods (P>0.05). The purity of NK cells isolated and enriched from PBMCs by manual separation method using immunomagnetic was (96.77±2.31)%; the yield was (56.27±10.47)%; the inhibition of tumor proliferation was (38.67±14.05)%; and the tumor killing rate was (19.90±8.05)%. The purity of NK cells isolated and enriched from PBMCs by manual separation method using platelet lysis culture expansion method was the highest at day 7, which was (54.84±15.80)%; the cell expansion multiple could reach 16.92±6.28 at day 7; the in vitro tumor killing rate of NK cells was (15.83±5.5)%; the tumor inhibition rate was (44.33±13.5)%; and there was no difference in the toxicity and activity of NK cells between the two methods (P>0.05). The purity of NK cells isolated and enriched by PERCOLL density gradient separation method was (15.83±5.82)%, and the yield was (14±6.25)%, which was significantly lower than the other two methods. [Conclusion] PBMCs isolated from whole blood by manual separation and NK cells enriched by negative selection with immunomagnetic beads have the potential to provide NK cell materials for CAR-NK cell therapy, and NK cells enriched by platelet lysate-conditioned medium have the potential to provide NK cells for large-scale NK cell activation reinfusion therapy.