Objective:To analyze application effect of trend analysis for safe risk in management and control for infection of medical devices,so as to optimize the management path for medical devices.Methods:Focusing on the main factors affecting the safety risks of medical devices,the least squares method of linear regression was applied for trend analysis to optimize the device management path and strengthen management.A total of 70 clinically used medical devices in the First Affiliated Hospital of Xi'an Jiaotong University from January to December 2024 were selected.These devices were managed using two models:the conventional management model and the trend analysis management model,with 35 devices under each model.The infection risk rate of medical equipment and the equipment management quality score were compared between the two management models.Additionally,160 patients managed under the two models(80 patients per model)were included to compare the patient infection rate.Results:In the 450 diagnostic and treated records of sampling inspection and consultation for medical devices from treatment equipment,diagnosis equipment,auxiliary imaging equipment and surgical equipment,the rate of infectious risk of using management mode with trend analysis were respectively 1.78%(8/450),2.22%(10/450),2.22%(10/450)and 2.44%(11/450),all of which were significantly lower than these of using conventional management mode,and the differences were significant(x2=9.904,8.902,10.465,10.770,P＜0.05).The scores of cleaning quality,the quality of disinfection and sterilization,the quality of distribution,and the retrieving quality of the management mode with trend analysis for medical devices were significantly higher than those of the conventional management mode,and the differences were statistically significant(t=15.889,13.172,15.872,17.399,P＜0.05).The infection rate of patients in the trend analysis management mode was 6.25%(5/80),which was significantly lower than that in the conventional management mode[22.50(18/80)],and the difference was statistically significant(x2=11.006,P＜0.05).Conclusion:The trend analysis for safe risk can analyze the risk factors in use and operation for medical devices from multiple perspectives,and mining main factors and conduct intervention for the devices,and reduce the incidence of safe risks of medical devices and the patients'infection rate,and improve the quality of clinical services.

Objective·To identify and evaluate novel and reliable non-invasive serological biomarkers for detecting pancreatic ductal adenocarcinoma(PDAC).Methods·Sixty-seven PDAC patients(Ruijin cohort Ⅰ)were recruited at Pancreatic Center,Ruijin Hospital,Shanghai Jiao Tong University School of Medicine,from May 2018 to December 2019.Global proteome profiling of 67 PDAC tumor tissues and 67 matched adjacent normal tissues was performed using mass spectrum.Bioinformatics analysis on the proteomics data was conducted to identify new biomarkers,and receiver operating characteristic(ROC)curves and the area under the curve(AUC)were used to evaluate their value of detecting PDAC.The proteomic and mRNA sequencing data were further downloaded and analysed from the Clinical Proteomic Tumor Analysis Consortium(CPTAC)cohort for validation.In addition,the Ruijin Cohort Ⅱ,consisting of 47 PDAC patients and 75 healthy individuals,was recruited for a case-control study from June 2021 to June 2022.Enzyme-linked immunosorbent assay(ELISA)was used to detect the expression level of new biomarkers in the serum of patients and healthy individuals to evaluate the serological diagnostic values of them.Results·Collagen type Ⅻ α1 chain(COL12A1)was identified as a candidate biomarker for PDAC diagnosis based on differential expression analysis on the proteomic data and was validated to be higher in tumor tissues than in adjacent normal tissues in the CPTAC cohort.In addition,COL12A1 protein levels were significantly higher in the sera of PDAC patients than in those of healthy controls,showing good diagnostic performance with an AUC of 0.82,a sensitivity of 81%,and a specificity of 83%.ROC analysis revealed that COL12A1 improved the performance of carbohydrate antigen 199(CA199)in distinguishing PDAC patients from healthy individuals(AUCCA199=0.91 vs AUCCA199+COL12A1=0.95,P<0.05).Furthermore,COL12A1 also showed excellent ability to distinguish early-stage PDAC patients(stage Ⅰ?Ⅱ)from healthy individuals(AUCCOL12A1=0.83),and significantly improved the AUC of CA199 in early-stage PDAC patients(AUCCA199=0.92 vs AUCCA199+COL12A1=0.97,P<0.05).Conclusion·COL12A1 is a potential serological diagnostic marker that complements CA199 in detecting early-stage PDAC.

Objective·To identify and evaluate novel and reliable non-invasive serological biomarkers for detecting pancreatic ductal adenocarcinoma(PDAC).Methods·Sixty-seven PDAC patients(Ruijin cohort Ⅰ)were recruited at Pancreatic Center,Ruijin Hospital,Shanghai Jiao Tong University School of Medicine,from May 2018 to December 2019.Global proteome profiling of 67 PDAC tumor tissues and 67 matched adjacent normal tissues was performed using mass spectrum.Bioinformatics analysis on the proteomics data was conducted to identify new biomarkers,and receiver operating characteristic(ROC)curves and the area under the curve(AUC)were used to evaluate their value of detecting PDAC.The proteomic and mRNA sequencing data were further downloaded and analysed from the Clinical Proteomic Tumor Analysis Consortium(CPTAC)cohort for validation.In addition,the Ruijin Cohort Ⅱ,consisting of 47 PDAC patients and 75 healthy individuals,was recruited for a case-control study from June 2021 to June 2022.Enzyme-linked immunosorbent assay(ELISA)was used to detect the expression level of new biomarkers in the serum of patients and healthy individuals to evaluate the serological diagnostic values of them.Results·Collagen type Ⅻ α1 chain(COL12A1)was identified as a candidate biomarker for PDAC diagnosis based on differential expression analysis on the proteomic data and was validated to be higher in tumor tissues than in adjacent normal tissues in the CPTAC cohort.In addition,COL12A1 protein levels were significantly higher in the sera of PDAC patients than in those of healthy controls,showing good diagnostic performance with an AUC of 0.82,a sensitivity of 81%,and a specificity of 83%.ROC analysis revealed that COL12A1 improved the performance of carbohydrate antigen 199(CA199)in distinguishing PDAC patients from healthy individuals(AUCCA199=0.91 vs AUCCA199+COL12A1=0.95,P<0.05).Furthermore,COL12A1 also showed excellent ability to distinguish early-stage PDAC patients(stage Ⅰ?Ⅱ)from healthy individuals(AUCCOL12A1=0.83),and significantly improved the AUC of CA199 in early-stage PDAC patients(AUCCA199=0.92 vs AUCCA199+COL12A1=0.97,P<0.05).Conclusion·COL12A1 is a potential serological diagnostic marker that complements CA199 in detecting early-stage PDAC.

Objective:To analyze application effect of trend analysis for safe risk in management and control for infection of medical devices,so as to optimize the management path for medical devices.Methods:Focusing on the main factors affecting the safety risks of medical devices,the least squares method of linear regression was applied for trend analysis to optimize the device management path and strengthen management.A total of 70 clinically used medical devices in the First Affiliated Hospital of Xi'an Jiaotong University from January to December 2024 were selected.These devices were managed using two models:the conventional management model and the trend analysis management model,with 35 devices under each model.The infection risk rate of medical equipment and the equipment management quality score were compared between the two management models.Additionally,160 patients managed under the two models(80 patients per model)were included to compare the patient infection rate.Results:In the 450 diagnostic and treated records of sampling inspection and consultation for medical devices from treatment equipment,diagnosis equipment,auxiliary imaging equipment and surgical equipment,the rate of infectious risk of using management mode with trend analysis were respectively 1.78%(8/450),2.22%(10/450),2.22%(10/450)and 2.44%(11/450),all of which were significantly lower than these of using conventional management mode,and the differences were significant(x2=9.904,8.902,10.465,10.770,P＜0.05).The scores of cleaning quality,the quality of disinfection and sterilization,the quality of distribution,and the retrieving quality of the management mode with trend analysis for medical devices were significantly higher than those of the conventional management mode,and the differences were statistically significant(t=15.889,13.172,15.872,17.399,P＜0.05).The infection rate of patients in the trend analysis management mode was 6.25%(5/80),which was significantly lower than that in the conventional management mode[22.50(18/80)],and the difference was statistically significant(x2=11.006,P＜0.05).Conclusion:The trend analysis for safe risk can analyze the risk factors in use and operation for medical devices from multiple perspectives,and mining main factors and conduct intervention for the devices,and reduce the incidence of safe risks of medical devices and the patients'infection rate,and improve the quality of clinical services.

The purpose of this study is to provide a culture for mouse bone marrow-derived macrophages (BMDM) and peritoneal macrophages (PM) and to characterize their molecular and cellular biology. The cell number and purity from the primary culture were assessed by cell counter and flow cytometry, respectively. Morphological features were evaluated by inverted microscope. Phagocytosis by macrophages was detected by the neutral red dye uptake assay. Phenotypic markers were analyzed by real-time fluorescent quantitative PCR. Our results show that the cell number was much higher from culture of BMDM than PM, while there was no significant difference regarding the percentage of F4/80+CD11b+ cells (98.30%±0.53% vs. 94.83%±1.42%; P>0.05). The proliferation rate of BMDM was significantly higher than PM in the presence of L929 cell conditioned medium, by using CCK-8 assay. However, PM appeared to adhere to the flask wall and extend earlier than BMDM. The phagocytosis capability of un-stimulated BMDM was significantly higher than PM, as well as lipopolysaccharide (LPS)-stimulated BMDM, except the BMDM stimulated by low dose LPS (0.1 μg/mL). Furthermore, Tnfα expression was significantly higher in un-stimulated BMDM than PM, while Arg1 and Ym1 mRNA expression were significantly lower than PM. The expression difference was persistent if stimulated by LPS+IFN-γ or IL-4. Our data indicate that bone marrow can get larger amounts of macrophages than peritoneal cavity. However, it should be aware that the molecular and cellular characteristics were different between these two culture systems.
Animals ; Bone Marrow Cells ; physiology ; Cells, Cultured ; Culture Media, Conditioned ; Lipopolysaccharides ; metabolism ; Macrophages ; classification ; physiology ; Mice ; Phagocytosis