ObjectiveTo systematically collate the randomized controlled trials （RCTs） on the intervention of traditional Chinese medicine （TCM） in chronic kidney disease （CKD） and analyze the characteristics of clinical trials and the current situation of outcome indicators， thus providing references for constructing a core outcome set （COS） for CKD. MethodsThe RCTs on the intervention of TCM in CKD were retrieved from CNKI， Wanfang Data， VIP， SinoMed， PubMed， Cochrane Library， EMbase， and Web of Science with the time interval from January 2022 to December 2024. The risk of bias was evaluated， and the outcome indicators were qualitatively analyzed. ResultsA total of 242 RCTs were included， which reported 238 outcome indicators， with the cumulative frequency of 2 724 times. These outcome indicators can be classified into seven domains： TCM syndromes and diseases （270 times， accounting for 9.90%）， symptoms and signs （218 times， 8.00%）， physical and chemical examinations （1 609 times， 59.07%）， quality of life （29 times， 1.06%）， long-term prognosis （6 times， 0.22%）， economic evaluation （0 times）， and safety events （535 times， 19.64%）. The results demonstrated that the RCTs of TCM intervention for CKD had several shortcomings such as the lack of a basis for sample size estimation， lack of standardization in TCM syndrome differentiation and classification， room for improvement in methodological quality， flaws in the design of the timing of efficacy measurement， absence of long-term prognosis evaluation， imbalance in the selection of surrogate and endpoint indicators， disconnection between overall evaluation and individualized assessment， lack of TCM characteristic indicators， and insufficient reporting of safety indicators. ConclusionAt present， the design of outcome indicators in the RCTs for TCM intervention in CKD is still not standardized. It is recommended that future research endeavors to enhance methodological quality， establish a standardized COS for TCM intervention in CKD， and thereby propel the high-quality development of TCM.

Hypertrophic scar is a fibrous hyperplastic disorder that arises from skin injuries. The current therapeutic modalities are constrained by the dense and rigid scar tissue which impedes effective drug delivery. Additionally, insufficient autophagic activity in fibroblasts hinders their apoptosis, leading to excessive matrix deposition. Here, we developed an active microneedle (MN) system to overcome these challenges by integrating micromotor-driven drug delivery with autophagy regulation to remodel the scar microenvironment. Specifically, sodium bicarbonate and citric acid were introduced into the MNs as a built-in engine to generate CO₂ bubbles, thereby enabling enhanced lateral and vertical drug diffusion into dense scar tissue. The system concurrently encapsulated curcumin (Cur), an autophagy activator, and triamcinolone acetonide (TA), synergistically inducing fibroblast apoptosis by upregulating autophagic activity. In vitro studies demonstrated that active MNs achieved efficient drug penetration within isolated scar tissue. The rabbit hypertrophic scar model revealed that TA-Cur MNs significantly reduced the scar elevation index, suppressed collagen I and transforming growth factor-β1 (TGF-β1) expression, and elevated LC3 protein levels. These findings highlight the potential of the active MN system as an efficacious platform for autonomous augmented drug delivery and autophagy-targeted therapy in fibrotic disorder treatments.

Objective:To design a system for digital procurement management of medical consumables through backpropagation algorithm,and explore the optimal effect of intelligent management mode on the whole process management for medical consumables in hospitals.Methods:Based on the backpropagation algorithm,a management system for digital procurement of medical consumables was designed to carry out intelligent management for medical consumables,including procurement module,information classification module and database module.A total of 300 medical consumables that were used at Beijing Jishuitan Hospital,Capital Medical University,from January 2021 to January 2023 were selected.The 150 consumables that were used during January 2021 and January 2022 were managed by using the conventional management mode,while the 150 consumables that were used during February 2022 and January 2023 were managed by using a management system for digital procurement based on the backpropagation algorithm(management mode with backpropagation algorithm).The scores of management effectiveness,management efficiency,incidence of adverse events,and delivery duration of medical consumables were compared between the two management modes.Result:The scores of delivery timeliness,work efficiency,management standardization and recycling consumables waste of medical consumables under the management mode with backpropagation algorithm were respectively(92.66±6.33)points,(93.55±7.69)points,(94.33±8.33)points and(94.31±8.44)points,which were all higher than those under the conventional mode,and the differences were statistically significant(t=15.665,11.955,10.241,10.440,P<0.05).The values of time consuming of each day and each month of checking medical consumables,as well as the backlog number of monthly inventory,were all significantly less than those under the conventional management mode(t=19.419,15.468,22.079,P<0.05).The incidences of unregistered consumables after were used,unrecorded items in the computer,and the lost consumables were also significantly lower than those under the conventional management mode(x2=9.840,10.227,9.870,P<0.05).Additionally,the required durations from the departments'application to sending orders,from sending orders to consumables storage,and from consumables storage to delivering them to the department were all significantly shorter than those under the conventional management mode(t=17.056,27.474,12.387,P<0.05).Conclusion:The management system for digital procurement of medical consumables based on backpropagation algorithm can realize the rational management for medical consumables,and improve the management effect for medical consumables,and reduce the incidence of adverse conditions,and shorten the delivery duration for medical consumables.

With the widespread promotion of patient-centered care models,narrative medicine,as a medical practice that emphasizes patients'personal stories and experiences,has garnered increasing attention in the medical field.Through a systematic literature review and field observations,this paper analyzed the ethical challenges faced by narrative medicine in reconstructing doctor-patient relationships,which mainly include information asymmetry and uneven distribution of medical resources,insufficient informed consent and privacy protection of patients,and difficulties in ensuring the authenticity and completeness of narrative content.In response,this paper proposed strategies such as enhancing patients'understanding of their rights and narrative medicine,promoting continuous ethical evaluations of narrative medicine practices,and exploring interdisciplinary collaborations to foster harmonious doctor-patient relationships.It also emphasized the importance of establishing multidisciplinary cooperation mechanisms and strengthening ethical training for medical personnel,as well as the necessity of ensuring information security through technological means,aiming to promote harmonious doctor-patient relationships,better realize the ethical practices of narrative medicine,optimize doctor-patient relationships,and improve the quality of medical services.

OBJECTIVE To observe the effect of early warning mechanisms based on nosocomial infection surveil-lance system on precise prevention and control of spread of multidrug-resistant organisms(MDROs)infections in intensive care unit of neurosurgery department.METHODS The dynamic monitoring was performed in the ICU of neurosurgery department of a three-A general hospital by using real-time surveillance system of nosocomial infec-tion from Jan.2023 to Dec.2023.The warning information was sent to the doctor' station immediately once the MDROs infections were detected,the detection of drug-resistant bacteria was carried out for the relevant personnel and their surroundings,and the precise prevention and control measures were implemented.The impact on the iso-lation rate of MDROs,isolation rate of MDROs from the relevant personnel and surroundings,incidence of noso-comial MDROs infections and incidence of surgical site infection was observed after the measures were taken.RESULTS The carrying rate of MDROs was decreased from 21.80％to 5.74％among the relevant personnel after the precise prevention and control measures were taken(P＜0.05),which was improved remarkably among the doctors(decreasing from 21.43％to 6.07％),nurses(decreasing from 23.68％to 3.98％),nursing workers(decreasing from 25.15％to 8.65％),and cleaning staff(decreasing from 25.49％to 5.05％)(P＜0.001).The isolation rate of MDROs was decreased from 20.77％to 7.12％among the surroundings(P＜0.05),which was decreased most remarkably among head cushions(decreasing from 32.28％to 12.13％),bed rails(decreasing from 16.70％to 3.27％),ventilator panels(decreasing from 23.00％to 6.95％)and bedside floors(decreasing from 31.99％to 9.96％)(P＜0.001).The incidence of nosocomial MDROs infections declined from 3.84％to 1.71％(P＜0.05),with incidence of incision infections decreasing from 4.00％to 1.45％(P＜0.05),the inci-dence of intracranial infections decreasing from 2.38％to 0.56％(P＜0.05).CONCLUSION The detection of drug-resistant bacteria is carried out immediately and precisely for the patients with MDROs infection,relevant personnel and their surroundings by using the real-time surveillance system of nosocomial infection,which achieve remarkable effect on prevention of transmission of MDROs and reduction of incidence of hospital-associated infec-tions and surgical site infections.

OBJECTIVE To observe the effect of early warning mechanisms based on nosocomial infection surveil-lance system on precise prevention and control of spread of multidrug-resistant organisms(MDROs)infections in intensive care unit of neurosurgery department.METHODS The dynamic monitoring was performed in the ICU of neurosurgery department of a three-A general hospital by using real-time surveillance system of nosocomial infec-tion from Jan.2023 to Dec.2023.The warning information was sent to the doctor' station immediately once the MDROs infections were detected,the detection of drug-resistant bacteria was carried out for the relevant personnel and their surroundings,and the precise prevention and control measures were implemented.The impact on the iso-lation rate of MDROs,isolation rate of MDROs from the relevant personnel and surroundings,incidence of noso-comial MDROs infections and incidence of surgical site infection was observed after the measures were taken.RESULTS The carrying rate of MDROs was decreased from 21.80％to 5.74％among the relevant personnel after the precise prevention and control measures were taken(P＜0.05),which was improved remarkably among the doctors(decreasing from 21.43％to 6.07％),nurses(decreasing from 23.68％to 3.98％),nursing workers(decreasing from 25.15％to 8.65％),and cleaning staff(decreasing from 25.49％to 5.05％)(P＜0.001).The isolation rate of MDROs was decreased from 20.77％to 7.12％among the surroundings(P＜0.05),which was decreased most remarkably among head cushions(decreasing from 32.28％to 12.13％),bed rails(decreasing from 16.70％to 3.27％),ventilator panels(decreasing from 23.00％to 6.95％)and bedside floors(decreasing from 31.99％to 9.96％)(P＜0.001).The incidence of nosocomial MDROs infections declined from 3.84％to 1.71％(P＜0.05),with incidence of incision infections decreasing from 4.00％to 1.45％(P＜0.05),the inci-dence of intracranial infections decreasing from 2.38％to 0.56％(P＜0.05).CONCLUSION The detection of drug-resistant bacteria is carried out immediately and precisely for the patients with MDROs infection,relevant personnel and their surroundings by using the real-time surveillance system of nosocomial infection,which achieve remarkable effect on prevention of transmission of MDROs and reduction of incidence of hospital-associated infec-tions and surgical site infections.

Objective:To construct and validate a prognostic model of colon cancer based on differentially expressed anoikis-related genes, and to preliminarily investigate the relationship between anoikis-related genes and the tumor immune microenvironment of colon cancer.Methods:A total of 472 cancer tissues samples of patients with colon cancer, RNA sequencing data and clinical data of 41 normal tissues samples were downloaded from the Cancer Genome Atlas (TCGA) database between the establishment time and July in 2024. A total of 919 genes related to anoikis were screened out from GeneCards database, and the common genes were selected from the RNA sequencing gene datasets of colon cancer and normal colon tissues in the TCGA database, among which the differentially expressed anoikis-related genes of colon cancer and normal colon tissues were screened out based on P < 0.05. Furthermore, genes related to the prognosis of 446 colon cancer patients with prognostic data in the TCGA database were screened by using univariate Cox proportional risk model; the genes with P < 0.05 were further screened out and a colon cancer prognosis model was constructed by using LASSO-Cox proportional risk model. The risk score of the above 446 colon cancer patients in the TCGA database was calculated according to the prognostic model, and the patients were divided into high-risk (≥ median value) group and low-risk (< median value) group according to the median risk score, and the overall survival of the 2 groups was analyzed by using the Kaplan-Meier method. The risk score based on R software-based time ROC program package was used to predict 1-year, 2-year, 3-year overall survival therapeutic efficacy of colon cancer patients in the TCGA database. According to the median risk score of colon cancer patients in the TCGA database, the patients in the International Cancer Genome Consortium (ICGC) database were divided into high-risk group and low-risk group. Kaplan-Meier method and receiver operating characteristic (ROC) curve were used to verify the predictive effect of the prognostic model. The differentially expressed genes between low-risk group and high-risk group stratified by prognostic model risk score in the TCGA database were used to perform single sample gene set enrichment analysis (ssGESA) of immune cells and immune function by using R software related programs. The differences in risk scores of patients with different immunophenotypes (including inflammator response type, wound healing type, interferon gamma dominant type and lymphocyte depletion type) were compared; and correlation analysis of infiltration and risk scores between immune cells and stromal cells in tumor microenvironment was made. Based on the tumor immune function and rejection (TIDE) database, the relationship between the prognostic model risk score and programmed death receptor ligand 1 (PD-L1) gene expression level was analyzed. Results:Based on anoikis-related genes in the GeneCards database, 236 differentially expressed anoikis-related genes between colon cancer tissues and normal tissues were obtained from the TCGA database. LASSO Cox regression was applied to establish a prognostic model constructed by 7 differentially expressed anoikis-related genes in cancer tissues and normal colon tissues related to the prognosis of colon cancer. Risk score = 0.366×TIMP1-0.404×NAT1+0.207×LTB4R2+0.075×INHBB+0.140×CD36-0.109×MMP3+2.994×OFCC1. The median risk score of 446 colon cancer patients in the TCGA database was 1.754 719 545. Survival analysis showed that the overall survival of colon cancer patients in high-risk group of the TCGA database was worse than that in low-risk group ( P < 0.001); ROC curve analysis showed that the area under the curve for predicting 1-year, 2-year and 3-year overall survival of patients in the TCGA database based on the prognostic model risk score was 0.705, 0.731 and 0.723, respectively. Kaplan-Meier method analysis showed that in the ICGC database, the overall survival of colon cancer patients in high-risk group was worse than that in low-risk group ( P = 0.041); ROC curve analysis showed that the area under the curve of prognostic model risk score for predicting 1-year and 2-year overall survival of colon cancer patients in the ICGC database was 0.663 and 0.966, respectively. ssGESA analysis showed that macrophage level in high-risk group was higher than that in low-risk group, helper T (Th) 1 cell and Th2 cell levels in high-risk group were lower than those in low-risk group (all P < 0.01). In terms of immune function, the cell killing activity and histocompatibility complex Ⅰ level in high-risk group were lower than those in low-risk group, and type Ⅱ interferon response score in high-risk group was higher than that in low-risk group (all P < 0.05). The analysis of immunophenotype showed that the risk score of inflammatory response type was higher than that of wound healing type ( P < 0.05), and there was no statistically significant difference in risk score between the other 2 types (all P > 0.05). Risk score was positively correlated with stromal cell infiltration score ( R = 0.340, P < 0.001) and immune cell infiltration score ( R = 0.148, P < 0.05); the expression level of PD-L1 in high-risk group was higher than that in low-risk group in the TCGA database ( P = 0.048), and the expression level of PD-L1 was positively correlated with risk score ( R = 0.130, P = 0.009). Conclusions:A prognostic model of colon cancer constructed by anoikis-related genes can better predict the prognosis of colon cancer patients, and anoikis-related genes may play an important role in tumor immunity of colon cancer.

Objective:To design a system for digital procurement management of medical consumables through backpropagation algorithm,and explore the optimal effect of intelligent management mode on the whole process management for medical consumables in hospitals.Methods:Based on the backpropagation algorithm,a management system for digital procurement of medical consumables was designed to carry out intelligent management for medical consumables,including procurement module,information classification module and database module.A total of 300 medical consumables that were used at Beijing Jishuitan Hospital,Capital Medical University,from January 2021 to January 2023 were selected.The 150 consumables that were used during January 2021 and January 2022 were managed by using the conventional management mode,while the 150 consumables that were used during February 2022 and January 2023 were managed by using a management system for digital procurement based on the backpropagation algorithm(management mode with backpropagation algorithm).The scores of management effectiveness,management efficiency,incidence of adverse events,and delivery duration of medical consumables were compared between the two management modes.Result:The scores of delivery timeliness,work efficiency,management standardization and recycling consumables waste of medical consumables under the management mode with backpropagation algorithm were respectively(92.66±6.33)points,(93.55±7.69)points,(94.33±8.33)points and(94.31±8.44)points,which were all higher than those under the conventional mode,and the differences were statistically significant(t=15.665,11.955,10.241,10.440,P<0.05).The values of time consuming of each day and each month of checking medical consumables,as well as the backlog number of monthly inventory,were all significantly less than those under the conventional management mode(t=19.419,15.468,22.079,P<0.05).The incidences of unregistered consumables after were used,unrecorded items in the computer,and the lost consumables were also significantly lower than those under the conventional management mode(x2=9.840,10.227,9.870,P<0.05).Additionally,the required durations from the departments'application to sending orders,from sending orders to consumables storage,and from consumables storage to delivering them to the department were all significantly shorter than those under the conventional management mode(t=17.056,27.474,12.387,P<0.05).Conclusion:The management system for digital procurement of medical consumables based on backpropagation algorithm can realize the rational management for medical consumables,and improve the management effect for medical consumables,and reduce the incidence of adverse conditions,and shorten the delivery duration for medical consumables.

With the widespread promotion of patient-centered care models,narrative medicine,as a medical practice that emphasizes patients'personal stories and experiences,has garnered increasing attention in the medical field.Through a systematic literature review and field observations,this paper analyzed the ethical challenges faced by narrative medicine in reconstructing doctor-patient relationships,which mainly include information asymmetry and uneven distribution of medical resources,insufficient informed consent and privacy protection of patients,and difficulties in ensuring the authenticity and completeness of narrative content.In response,this paper proposed strategies such as enhancing patients'understanding of their rights and narrative medicine,promoting continuous ethical evaluations of narrative medicine practices,and exploring interdisciplinary collaborations to foster harmonious doctor-patient relationships.It also emphasized the importance of establishing multidisciplinary cooperation mechanisms and strengthening ethical training for medical personnel,as well as the necessity of ensuring information security through technological means,aiming to promote harmonious doctor-patient relationships,better realize the ethical practices of narrative medicine,optimize doctor-patient relationships,and improve the quality of medical services.

Objective:To construct and validate a prognostic model of colon cancer based on differentially expressed anoikis-related genes, and to preliminarily investigate the relationship between anoikis-related genes and the tumor immune microenvironment of colon cancer.Methods:A total of 472 cancer tissues samples of patients with colon cancer, RNA sequencing data and clinical data of 41 normal tissues samples were downloaded from the Cancer Genome Atlas (TCGA) database between the establishment time and July in 2024. A total of 919 genes related to anoikis were screened out from GeneCards database, and the common genes were selected from the RNA sequencing gene datasets of colon cancer and normal colon tissues in the TCGA database, among which the differentially expressed anoikis-related genes of colon cancer and normal colon tissues were screened out based on P < 0.05. Furthermore, genes related to the prognosis of 446 colon cancer patients with prognostic data in the TCGA database were screened by using univariate Cox proportional risk model; the genes with P < 0.05 were further screened out and a colon cancer prognosis model was constructed by using LASSO-Cox proportional risk model. The risk score of the above 446 colon cancer patients in the TCGA database was calculated according to the prognostic model, and the patients were divided into high-risk (≥ median value) group and low-risk (< median value) group according to the median risk score, and the overall survival of the 2 groups was analyzed by using the Kaplan-Meier method. The risk score based on R software-based time ROC program package was used to predict 1-year, 2-year, 3-year overall survival therapeutic efficacy of colon cancer patients in the TCGA database. According to the median risk score of colon cancer patients in the TCGA database, the patients in the International Cancer Genome Consortium (ICGC) database were divided into high-risk group and low-risk group. Kaplan-Meier method and receiver operating characteristic (ROC) curve were used to verify the predictive effect of the prognostic model. The differentially expressed genes between low-risk group and high-risk group stratified by prognostic model risk score in the TCGA database were used to perform single sample gene set enrichment analysis (ssGESA) of immune cells and immune function by using R software related programs. The differences in risk scores of patients with different immunophenotypes (including inflammator response type, wound healing type, interferon gamma dominant type and lymphocyte depletion type) were compared; and correlation analysis of infiltration and risk scores between immune cells and stromal cells in tumor microenvironment was made. Based on the tumor immune function and rejection (TIDE) database, the relationship between the prognostic model risk score and programmed death receptor ligand 1 (PD-L1) gene expression level was analyzed. Results:Based on anoikis-related genes in the GeneCards database, 236 differentially expressed anoikis-related genes between colon cancer tissues and normal tissues were obtained from the TCGA database. LASSO Cox regression was applied to establish a prognostic model constructed by 7 differentially expressed anoikis-related genes in cancer tissues and normal colon tissues related to the prognosis of colon cancer. Risk score = 0.366×TIMP1-0.404×NAT1+0.207×LTB4R2+0.075×INHBB+0.140×CD36-0.109×MMP3+2.994×OFCC1. The median risk score of 446 colon cancer patients in the TCGA database was 1.754 719 545. Survival analysis showed that the overall survival of colon cancer patients in high-risk group of the TCGA database was worse than that in low-risk group ( P < 0.001); ROC curve analysis showed that the area under the curve for predicting 1-year, 2-year and 3-year overall survival of patients in the TCGA database based on the prognostic model risk score was 0.705, 0.731 and 0.723, respectively. Kaplan-Meier method analysis showed that in the ICGC database, the overall survival of colon cancer patients in high-risk group was worse than that in low-risk group ( P = 0.041); ROC curve analysis showed that the area under the curve of prognostic model risk score for predicting 1-year and 2-year overall survival of colon cancer patients in the ICGC database was 0.663 and 0.966, respectively. ssGESA analysis showed that macrophage level in high-risk group was higher than that in low-risk group, helper T (Th) 1 cell and Th2 cell levels in high-risk group were lower than those in low-risk group (all P < 0.01). In terms of immune function, the cell killing activity and histocompatibility complex Ⅰ level in high-risk group were lower than those in low-risk group, and type Ⅱ interferon response score in high-risk group was higher than that in low-risk group (all P < 0.05). The analysis of immunophenotype showed that the risk score of inflammatory response type was higher than that of wound healing type ( P < 0.05), and there was no statistically significant difference in risk score between the other 2 types (all P > 0.05). Risk score was positively correlated with stromal cell infiltration score ( R = 0.340, P < 0.001) and immune cell infiltration score ( R = 0.148, P < 0.05); the expression level of PD-L1 in high-risk group was higher than that in low-risk group in the TCGA database ( P = 0.048), and the expression level of PD-L1 was positively correlated with risk score ( R = 0.130, P = 0.009). Conclusions:A prognostic model of colon cancer constructed by anoikis-related genes can better predict the prognosis of colon cancer patients, and anoikis-related genes may play an important role in tumor immunity of colon cancer.