ObjectiveTo investigate the recurrence of ischemic stroke (IS) and to analyze the association between four indices of total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides (TG) and the risk of IS recurrence by analyzing the follow-up data related to IS in the community-based natural population of Songjiang District, Shanghai, so as to provide a scientific basis for improving the prognosis of stroke patients in the community and controlling IS recurrence. MethodsA prospective follow-up study was conducted among the IS patients in the community-based cohort population, collecting data about patient’s age, gender, disease history, biochemical indicators, and etc. Cox regression model and restricted cubic spline model were used to analyze the relationship between different levels of plasma lipids and the recurrence of IS in these patients. ResultsA total of 1 368 patients with IS were included. The total follow-up duration was 7 171.46 person-years, with a median follow-up time of 6.24 years. There were 420 cases of IS recurrence, resulting in a cumulative recurrence rate of 30.70%. The results of multivariate Cox regression analysis showed that the recurrence risk of IS was reduced when the baseline TC and LDL-C levels of IS patients were in the ranges of 4.65‒5.67 mmol·L^-1 and 2.52‒3.46 mmol·L^-1, respectively. The results of restricted cubic spline analysis showed a U-shaped relationship between baseline TC and LDL-C levels and the recurrence risk in IS patients. ConclusionThe cumulative recurrence rate of patients with IS in the community of Songjiang District in Shanghai is high, and the levels of TC and LDL-C at baseline survey are correlated with the recurrence of IS in these patients. It is suggested to pay more attention to the levels of LDL-C and TC in patients with IS, so as to improve the prognosis.

Objective To explore the relationship between NANOS3 and P-bodies in oocytes and the mechanism of their interaction during early oogenesis.Methods The co-localization of NANOS3 and dead box helicase 6(DDX6)in day post postnatal 1(1dpp)mouse oocytes was observed by immunofluorescence,and the interaction between NANOS3 and DDX6 was detected by immunoprecipitation.NANOS3 and DDX6 full-length plasmids were constructed to transfect HEK293T cells,and the mechanism of their interaction was investigated by immunofluorescence and immunoprecipitation.NANOS3 transfected HeLa cells to investigate whether NANOS3 had the ability of liquid-liquid phase separation(LLPS)by live-cell imaging.The proteins recruited by P-bodies in early oogenesis were identified by DDX6-immunoprecipitation-mass spectrometry(DDX6-IP-MS).Results NANOS3 and DDX6 colocalized and interacted with each other in 1dpp mouse oocytes.However,the co-localization of NANOS3 and DDX6 was not observed in HEK293T cells that had been transfected,but co-immunoprecipitation still demonstrated an interaction between these two proteins.Besides,live-cell imaging revealed that NANOS3 exhibited dynamic fluid-like properties within cells,which may promote the formation of P-bodies through LLPS.Finally,DDX6-IP-MS revealed that DDX6 might recruit NANOS3 into P-bodies by binding to the NANOS3 interacting protein Pumilio.Conclusion NANOS3 serves as a specific component of P-bodies in neonatal oocytes and may be involved in the regulation of early oogenesis.

BACKGROUND:silencing information regulatory 1(SIRT1)regulates the function of related proteins in chondrocytes in a deacetylated manner and participates in chondrocyte proliferation and differentiation,thereby promoting cartilage defect repair. OBJECTIVE:To screen for signaling pathways with unclear action status after SIRT1 gene knockdown in chondrocytes,as well as diseases or functions that produce changes using high-throughput technology. METHODS:ATDC5 chondrocytes from mice in logarithmic growth phase were divided into two groups:the cells were transfected with SIRT1 gene knockdown negative control lentivirus in control group and SIRT1 gene knockdown lentivirus in experimental group.GeneChip? Mouse Genome 430 2.0 Array was used to detect the mRNA expression at 72 hours after transfection.Applied bioinformatics technology was also used to screen for unclear activation or inhibition signaling pathways and their related factors.Moreover,enrichment of disease or function modules was analyzed. RESULTS AND CONCLUSION:After knocking down the SIRT1 gene,there were 245 signaling pathways with unclear activation or inhibition status in the mouse ATDC5 chondrocytes.According to the ranking of-Log(P-value),we reported the factors in the top 20 signaling pathways with unclear activation or inhibition status,including IGFBP4,TGFBR1,CTGF,COL4A5,LHX2,IL1RL1,and KLF6.According to the ranking of-Log(P-value),there were significant changes in 14 disease or function modules,including cellular growth and proliferation,organism survival,cell death and survival.According to the number of differentially expressed genes,there were significant changes in three disease or function modules,including organismal injury and abnormalities,cancer,and cell death and survival.According to the comprehensive ranking of-Log(P-value)and the number of differentially expressed genes,the disease or function module related to intrinsic immune response was significantly activated.

OBJECTIVE To establish a performance index evaluation system for pharmacists in inpatient pharmacy to encourage and guide pharmacists to achieve self-professional growth and reshape their own values. METHODS According to the evaluation criteria for the construction of provincial-level clinical specialties in Jiangsu province, the key success factors(KSF) method was used to set the key indicators for the discipline construction of the department, and the key process indicator(KPI) method was used for the daily work of the department. Based on the combination of KSF and KPI, an inpatient pharmacy performance management system was established, employee and clinical satisfaction, ward complaints, error occurrence rate, dispensing efficiency, and scientific research output were taken as indicators to evaluate the effect after the implementation of the performance management system. RESULTS Before and after the construction and implementation of the "KSF + KPI" performance system, the average employee satisfaction had increased from 57.75% to 77.81%(P<0.05), the number of complaints in the ward had decreased from (26.33±6.75) per month to (7.17±3.61) per month, and the number of errors had decreased from (30.33±5.50) per month to (12.58±2.75) per month, the differences were statistically significant(P<0.05). Overall clinical satisfaction reached 81.13%; the PIVAS blending efficiency had been improved to a certain extent, with an average increase of 17%. Innovation related indicators such as article writing, recruitment, project application, and employee research participation had significantly improved after implementation of the indicator performance system. CONCLUSION The inpatient pharmacy performance management system establishes based on "KSF and KPI" provides a good performance evaluation scheme for the transformation and development of the dispensing department of the pharmaceutical department. It has made positive exploration in the aspects of self-motivation and professional development of hospital pharmacists, high-efficiency operation, improvement of clinical service level and development of pharmaceutical discipline, and has achieved good results.

Aim To predict the mechanism of Fufang Congrong Yizhi Capsules (FCYC) in the treatment of mild cognitive impairment (MCI) by network pharmacology method, and further validate it in combination with cellular experiments. Methods TCMSP, Gene-Cards, OMIM and TTD databases, Chinese Pharmacopoeia and related literature were used to screen the active ingredients of FCYC and the targets of MCI treatment. The TCM-compound-target-disease network and PPI of intersection targets were constructed, and the GO and KEGG analysis were performed by the Ehamb bioinformation platform. GO and KEGG analysis were performed through Yihanbo biological information platform. Cell model of MCI was established by PC-12 injury induced by Aβ

Objective To explore the prediction of hospital indoor microbial concentration in air based on real-time indoor air environment monitoring data and machine learning algorithms.Methods Four locations in a hospital were selected as monitoring sampling points from May 23 to June 5,2022.The"internet of things"sensor was used to monitor a variety of real-time air environment data.Air microbial concentration data collected at each point were matched,and the gradient boosting decision tree(GBDT)was used to predict real-time indoor microbial concentra-tion in air.Five other common machine learning models were selected for comparison,including random forest(RF),decision tree(DT),k-nearest neighbor(KNN),linear regression(LR)and artificial neural network(ANN).The validity of the model was verified by the mean absolute error(MAE),root mean square error(RMSE)and mean absolute percentage error(MAPE).Results The MAPE value of GBDT model in the outpa-tient elevator room(point A),bronchoscopy room(point B),CT waiting area(point C),and nurses'station in the supply room(point D)were 22.49％,36.28％,29.34％,and 26.43％,respectively.The mean performance of the GBDT model was higher than that of other machine learning models at three sampling points and slightly lower than that of the ANN model at only one sampling point.The mean MAPE value of GBDT model at four sampling points was 28.64％,that is,the predicted value deviated from the actual value by 28.64％,indicating that GBDT model has good prediction results and the predicted value was within the available range.Conclusion The GBDT machine learning model based on real-time indoor air environment monitoring data can improve the prediction accuracy of in-door air microbial concentration in hospitals.

Objective To compare the dosimetric effects of volume modulated arc therapy(VMAT)and intensity modulated radiation therapy(I M RT)on the anal sphincter(AS)and its sub-structures in neoadjuvant radiotherapy for rectal cancer to facilitate the selection of radiotherapy techniques.Methods Fifty rectal cancer patients receiving neoadjuvant radiotherapy were selected,and 2 types of radiotherapy plans,including coplanar double full-arc VMAT and coplanar seven-field homo-geneous IMRT,were designed based on the CT images of the patients,respectively.Under the premise of ensuring that the irradiated doses to the target area and the major organs at risk reached the standard and met the clinical requirements,AS and its substructures were added as the organs at risk for dosimetric evaluation.The absolute dose parameters and relative dose parameters of AS and its substructures were counted by dose-volume histograms.Statistical analysis was performed using IBM SPSS 22.0 software.Results The VMAT plan had the relative dose parameters V20,V30,and V40 of AS and its substructures lower those of the IMRT plan,the differences were statistically significant(P＜0.05),while the differences in V5 and V 10 were not statistically significant(P＞0.05).The VMAT plan had the absolute dose parameterDmeanlower while the D2％slightly higher than those of the IMRT plan,the differences were statistically significant(P＜0.05).The difference in D98％between the two plans was not statistically significant(P＞0.05).Conclusion During rectal cancer radiotherapy VMAT generally behaves better than IMRT in protecting AS and its sub-structures and decreasing injuries of AS and its sub-structures dosimetrically.[Chinese Medical Equipment Journal,2024,45(8):63-67]

Objective:To explore the surveillance and management method of adverse events of medical consumables based on the capability target hierarchical model,and to analyze its monitoring and management effect.Methods:A four-level medical consumables adverse events monitoring and managing target was set up for each department monitoring level,monitoring expert level,multi department comprehensive office level and monitoring leadership level of the hospital.The monitoring layer of each department collected and summarized the information on medical consumables adverse events,and the monitoring expert layer analyzed the cause and effect of medical consumables adverse events based on the collected information.The support vector machine(SVM)in the machine learning model was used to determine the type of adverse event,and the adverse events of medical consumables were reported through the multi-department comprehensive office layer,and the reported problems were analyzed in detail through the fishbone diagram,and the final management decision was made at the monitoring leadership level.Statistics were conducted on the adverse event data of the top 10 medical consumables in Shanxi Provincial People's Hospital from 2021 to 2022.The changes in data,severity of hazard,distribution of causes and reporting qualification of medical consumables adverse events before and after the application of the medical consumables adverse event monitoring and management method based on the capability target hierarchical model were compared.Results:From 2021 to 2022,a total of 442 adverse events occurred in the top 10 medical consumables of medical consumables,of which 346 occurred in 2021 before the application of the medical consumables adverse event monitoring and management method based on the capability target hierarchical model,and 96 occurred in 2022 after the application.Compared with before the application,the proportion of different medical consumables(0～25%),the proportion of hazard severity(0～79%)and the different causes of adverse events(3-23%)in the top 10 medical consumables adverse events after the application of capability target hierarchical model,the difference was statistically significant(x2=7.92,7.83,7.52,P<0.05);the qualified rate of adverse event reports of medical consumables increased from 60.70%(210/346)before application to 83.30%(80/96),the difference was statistically significant(x2=17.071,P<0.001).Conclusion:The medical consumables adverse event monitoring and management method based on the capability target hierarchical model can ensure that adverse events of medical consumables are monitored and reported in a timely and accurate manner,promptly discover and resolve existing problems,reduce the risks of medical consumables use,and ensure medical quality.

China prospective multicenter birth cohort (Prospective Omics Health Atlas birth cohort, POHA birth cohort) study was officially launched in 2022. This study, in collaboration with 12 participating units, aims to establish a high-quality, multidimensional cohort comprising 20 000 naturally conceived families and assisted reproductive families. The study involves long-term follow-up of parents and offspring, with corresponding biological samples collected at key time points. Through multi-omics testing and analysis, the study aims to conduct multi-omics big data research across the entire maternal and infant life cycle. The goal is to identify new biomarkers for maternal and infant diseases and provide scientific evidence for risk prediction related to maternal diseases and neonatal health.