Objective To study the damage effect of high-voltage electric shock on skin based on metabolomics,analyze its metabolic differences,and explore its injury mechanism.Methods A total of 16 SPF C57BL/6J male mice were divided into the electric shock group(head skin received electric shock treatment)and control group(head skin received electric shock acoustic-optical stimulation),and the skin appearance after treatment of mice in the two groups was observed.The histopathological changes caused by electric shock were analyzed by HE staining,EVG staining and Masson staining.GC-MS and LC-MS metabonomics were used to analyze the changes of skin metabolism spectrum and tissue metabolites after electric shock exposure,and the differential metabolites were analyzed.The obtained differential metabolites were combined and KEGG enrichment analysis was conducted.Results After high-voltage electric shock,the skin of mice could be damaged to the dermis,and the epidermis was partially thickened,lifted and separated.The structure of skin appendages in the dermis was destroyed,with a large number of inflammatory cells infiltrating and obvious swelling,accompanied by congestion,which led to severe skin inflammatory reaction and impaired skin barrier function.Metabonomics analysis suggested that the metabolites changed after electric shock exposure.KEGG enrichment analysis showed that electric shock significantly affected the central carbon metabolism pathway of cancer,pentose phosphate pathway,purine metabolism,glycine,serine and threonine metabolism processes,amino acid tRNA biosynthesis mechanism,glycerophospholipid metabolism pathway,pyrimidine metabolism pattern,glycolysis/gluconeogenesis,alanine metabolism process,glucagon signal pathway and so on.Conclusion High voltage electric shock can cause deep skin damage,disturb its energy metabolism and amino acid metabolism,and seriously interfere with its antioxidant and DNA repair system functions.

Objective:To analyze the influencing factors of China′s DRG payment system reform(DRG reform) and its hierarchical relationship, for references for the in-depth promotion of China′s medical insurance payment reform.Methods:Relevant literature on DRG reform in China from databases such as CNKI, Wanfang Database, Pubmed, etc, were obtained. Content analysis method was used to extract the influencing factors of DRG reform. The correlation between each influencing factor was determined through expert discussion. An interpretive structural model(ISM) was constructed to analyze the hierarchical relationship of factors influencing DRG reform.Results:After analysis, the influencing factors(12) of DRG reform in China were included such as medical level, hospital management, and medical staff′s cognition and behavior. Among them, the local situation was the deep-level factor affecting DRG reform, 9 factors such as data quality assurance and policy design/implementation were the middle-level factors, and patients′ interests/needs and disease grouping were the surface-level factors.Conclusions:There were many influencing factors on the reform of China′s DRG payment system. It was suggested that relevant management departments in various regions should focus on the actual situation of the locality, take data quality and policy design and implementation as the key points of reform, formulate a scientific and reasonable DRG grouping scheme, safeguard the interests of patients, so as to promote the deepening of DRG reform.

Objective To investigate the influencing factors of grade 3-4 multiple myeloma bone disease(MBD)in newly diagnosed multiple myeloma(NDMM)patients,and establish a risk prediction model based on a nomogram.Methods A total of 261 patients with NDMM who were treated in Ningbo Medical Center Lihuili Hospital from January 2015 to December 2021 were retrospectively selected.The patients were divided into group A(MBD grade 0-2,110 cases)and group B(MBD grade 3-4,151 cases)according to MBD grade at the time of initial diagnosis.Logistic regression analysis was used to screen the risk factors for grade 3-4 MBD in NDMM patients,and the risk prediction model was constructed.The receiver operating characteristic(ROC)curve was used for comprehensive evaluation.Results Multivariate regression analysis showed that age,serum phosphorus,C-reactive protein(CRP),globulin(GLB)and bone marrow plasma cell percentage(BMPCp)were independent risk factors for grade 3-4 MBD in NDMM patients(P<0.05).Based on this,risk prediction model was constructed as follows:logit(P)=-15.092+0.107(age)+1.150(serum phosphorus)+0.057(CRP)+0.040(GLB)+0.212(BMPCp).There was no significant difference between the predicted probability and the actual incidence by the Hosmer-Lemeshow goodness of fit test(P=0.770).The accuracy of the model in predicting grade 3-4 MBD in NDMM patients was 90.40%,and the area under the curve was 0.957(95%CI:0.932-0.981),indicating a reliable prediction ability.Conclusion Age,serum phosphorus,CRP,GLB and BMPCp were all independent risk factors for grade 3-4 MBD in NDMM patients,and the constructed risk prediction model has a relatively good predictive effect on the occurrence of grade 3-4 MBD in NDMM patients.

Objective:To explore whether a history of cardiovascular disease (CVD) history in the middle-aged and elderly populations in China is an independent risk factor for Parkinson's disease (PD).Methods:Based on China Health and Retirement Longitudinal Study (CHARLS) database, middle-aged and elderly populations aged 45 years and above in China who did not have PD in 2011 were chosen; their demographic characteristics, health status and lifestyle were collected. These individuals were divided into a PD group and a non-PD group based on whether they had been diagnosed as having PD during follow-up survey in 2020. Multivariate Logistic regression was performed to analyze the association between CVD history and PD. Stratified analysis was conducted based on age (whether ≥60 years old), gender, educational attainment, and presences of chronic lung disease history, diabetes and high blood sugar history, and interaction effects of the above factors with CVD history were analyzed to examine the robustness in different populations. PROCESS software was applied to construct a single mediator chain reaction model; with average daily sleep duration and depression score (based on Depression Scale from Center for Epidemiologic Studies) one month before survey as mediator variables, mediating effect was analyzed.Results:A total of 10,465 individuals were ultimately included, including 101 with PD and 10,364 without PD. CVD history ( OR=2.882, 95% CI: 1.610-5.159, P<0.001) was an independent risk factor for PD. For individuals with different gender, with presence of chronic lung diseases history, aged over 60 years, and with educational level of elementary school and above, and without diabetes or high blood sugar history, CVD history was significantly associated with PD onset ( P<0.05). Significant interations weren't revealed between the above factors with CVD history. The average daily sleep duration ( β=1.114, 95% CI: 0.687-1.540) and depression score ( β=1.060, 95% CI: 0.627-1.493) showed partial mediation effects between the two diseases (95% CI for direct effect parameters not including 0). Conclusion:Chinese middle-aged and elderly populations with CVD history are prone to have PD, with average daily sleep duration and depression score serving as potential mediating factors.

Objective To study the damage effect of high-voltage electric shock on skin based on metabolomics,analyze its metabolic differences,and explore its injury mechanism.Methods A total of 16 SPF C57BL/6J male mice were divided into the electric shock group(head skin received electric shock treatment)and control group(head skin received electric shock acoustic-optical stimulation),and the skin appearance after treatment of mice in the two groups was observed.The histopathological changes caused by electric shock were analyzed by HE staining,EVG staining and Masson staining.GC-MS and LC-MS metabonomics were used to analyze the changes of skin metabolism spectrum and tissue metabolites after electric shock exposure,and the differential metabolites were analyzed.The obtained differential metabolites were combined and KEGG enrichment analysis was conducted.Results After high-voltage electric shock,the skin of mice could be damaged to the dermis,and the epidermis was partially thickened,lifted and separated.The structure of skin appendages in the dermis was destroyed,with a large number of inflammatory cells infiltrating and obvious swelling,accompanied by congestion,which led to severe skin inflammatory reaction and impaired skin barrier function.Metabonomics analysis suggested that the metabolites changed after electric shock exposure.KEGG enrichment analysis showed that electric shock significantly affected the central carbon metabolism pathway of cancer,pentose phosphate pathway,purine metabolism,glycine,serine and threonine metabolism processes,amino acid tRNA biosynthesis mechanism,glycerophospholipid metabolism pathway,pyrimidine metabolism pattern,glycolysis/gluconeogenesis,alanine metabolism process,glucagon signal pathway and so on.Conclusion High voltage electric shock can cause deep skin damage,disturb its energy metabolism and amino acid metabolism,and seriously interfere with its antioxidant and DNA repair system functions.

Objective To investigate the influencing factors of grade 3-4 multiple myeloma bone disease(MBD)in newly diagnosed multiple myeloma(NDMM)patients,and establish a risk prediction model based on a nomogram.Methods A total of 261 patients with NDMM who were treated in Ningbo Medical Center Lihuili Hospital from January 2015 to December 2021 were retrospectively selected.The patients were divided into group A(MBD grade 0-2,110 cases)and group B(MBD grade 3-4,151 cases)according to MBD grade at the time of initial diagnosis.Logistic regression analysis was used to screen the risk factors for grade 3-4 MBD in NDMM patients,and the risk prediction model was constructed.The receiver operating characteristic(ROC)curve was used for comprehensive evaluation.Results Multivariate regression analysis showed that age,serum phosphorus,C-reactive protein(CRP),globulin(GLB)and bone marrow plasma cell percentage(BMPCp)were independent risk factors for grade 3-4 MBD in NDMM patients(P<0.05).Based on this,risk prediction model was constructed as follows:logit(P)=-15.092+0.107(age)+1.150(serum phosphorus)+0.057(CRP)+0.040(GLB)+0.212(BMPCp).There was no significant difference between the predicted probability and the actual incidence by the Hosmer-Lemeshow goodness of fit test(P=0.770).The accuracy of the model in predicting grade 3-4 MBD in NDMM patients was 90.40%,and the area under the curve was 0.957(95%CI:0.932-0.981),indicating a reliable prediction ability.Conclusion Age,serum phosphorus,CRP,GLB and BMPCp were all independent risk factors for grade 3-4 MBD in NDMM patients,and the constructed risk prediction model has a relatively good predictive effect on the occurrence of grade 3-4 MBD in NDMM patients.

Objective:To analyze the influencing factors of China′s DRG payment system reform(DRG reform) and its hierarchical relationship, for references for the in-depth promotion of China′s medical insurance payment reform.Methods:Relevant literature on DRG reform in China from databases such as CNKI, Wanfang Database, Pubmed, etc, were obtained. Content analysis method was used to extract the influencing factors of DRG reform. The correlation between each influencing factor was determined through expert discussion. An interpretive structural model(ISM) was constructed to analyze the hierarchical relationship of factors influencing DRG reform.Results:After analysis, the influencing factors(12) of DRG reform in China were included such as medical level, hospital management, and medical staff′s cognition and behavior. Among them, the local situation was the deep-level factor affecting DRG reform, 9 factors such as data quality assurance and policy design/implementation were the middle-level factors, and patients′ interests/needs and disease grouping were the surface-level factors.Conclusions:There were many influencing factors on the reform of China′s DRG payment system. It was suggested that relevant management departments in various regions should focus on the actual situation of the locality, take data quality and policy design and implementation as the key points of reform, formulate a scientific and reasonable DRG grouping scheme, safeguard the interests of patients, so as to promote the deepening of DRG reform.

Objective:To explore whether a history of cardiovascular disease (CVD) history in the middle-aged and elderly populations in China is an independent risk factor for Parkinson's disease (PD).Methods:Based on China Health and Retirement Longitudinal Study (CHARLS) database, middle-aged and elderly populations aged 45 years and above in China who did not have PD in 2011 were chosen; their demographic characteristics, health status and lifestyle were collected. These individuals were divided into a PD group and a non-PD group based on whether they had been diagnosed as having PD during follow-up survey in 2020. Multivariate Logistic regression was performed to analyze the association between CVD history and PD. Stratified analysis was conducted based on age (whether ≥60 years old), gender, educational attainment, and presences of chronic lung disease history, diabetes and high blood sugar history, and interaction effects of the above factors with CVD history were analyzed to examine the robustness in different populations. PROCESS software was applied to construct a single mediator chain reaction model; with average daily sleep duration and depression score (based on Depression Scale from Center for Epidemiologic Studies) one month before survey as mediator variables, mediating effect was analyzed.Results:A total of 10,465 individuals were ultimately included, including 101 with PD and 10,364 without PD. CVD history ( OR=2.882, 95% CI: 1.610-5.159, P<0.001) was an independent risk factor for PD. For individuals with different gender, with presence of chronic lung diseases history, aged over 60 years, and with educational level of elementary school and above, and without diabetes or high blood sugar history, CVD history was significantly associated with PD onset ( P<0.05). Significant interations weren't revealed between the above factors with CVD history. The average daily sleep duration ( β=1.114, 95% CI: 0.687-1.540) and depression score ( β=1.060, 95% CI: 0.627-1.493) showed partial mediation effects between the two diseases (95% CI for direct effect parameters not including 0). Conclusion:Chinese middle-aged and elderly populations with CVD history are prone to have PD, with average daily sleep duration and depression score serving as potential mediating factors.

Objective To deeply explore the principles of drug combinations in the treatment of vitiligo by traditional Chinese medicine master XUAN Guo-Wei by data mining technology,and to analyze the potential mechanism of action of the core drug pairs by network pharmacology.Methods The original case records of Professor XUAN Guo-Wei in treating vitiligo were compiled,and then TCM inheritance Computing Platform was used to analyze the frequency of drugs in the prescriptions,the association rules between drugs,and the core combinations of drugs by the association rule method,and the core drug pairs of Professor XUAN Guo-Wei's treatment of vitiligo were obtained based on the results of the data mining,additionally,the mechanism of the core pairs of drugs was analyzed by using the method of network pharmacology.Results A total of 243 prescriptions were collected,among which the high-frequency drugs were Glycyrrhizae Radix et Rhizoma,Tribuli Fructus,Ecliptae Herba,Cuscutae Semen,Scrophulariae Radix,Angelicae Dahuricae Radix,etc.,and the core pair was Tribuli Fructus-Ecliptae Herba.The main components of Tribuli Fructus-Ecliptae Herba for the treatment of vitiligo were quercetin,kaempferol,etc.,there were 47 targets for the intersection of the active ingredients with the disease,among which TP53,TNF,IL-1β,CASP3,VEGFA,PTGS2,IL10,IL2,IFNG,and IL4 may be the core targets for the treatment of vitiligo by Tribuli Fructus-Ecliptae Herba.The main pathways of Tribuli Fructus-Ecliptae Herba drug pairs against the disease were PI3K-Akt signaling pathway,NF-κB signaling pathway,JAK-STAT signaling pathway and MAPK signaling pathway.Conclusion The core drug pair of Professor XUAN Guo-Wei in the treatment of vitiligo is Tribuli Fructus-Ecliptae Herba,which involves targets such as TP53,TNF,IL-1β,CASP3,VEGFA,PTGS2,IL10,IL2,IFNG,IL4,etc.,Tribuli Fructus-Ecliptae Herba drug pair maybe exert an effect in the treatment of vitiligo through PI3K-Akt signaling pathway,NF-κB signaling pathway,JAK-STAT signaling pathway and MAPK signaling pathway.