Anxiety disorder is a highly prevalent psychological illness, and research has shown that obesity is a significant risk factor for its development. This study explored the ameliorative effects and mechanisms of saponins from Panax japonicus(SPJ) on anxiety disorder in mice fed a high-fat diet(HFD). Fifty C57BL/6J mice were randomly divided into normal control diet(NCD) group, HFD group, and low-and high-dose SPJ groups. At week 12, six mice from the HFD group were further divided into a control group(treated with DMSO) and an exogenous fibroblast growth factor 21(FGF21) group(administered rFGF21). The anxiety-like behavior of the mice was assessed using the open field test and elevated plus maze test. Hematoxylin-eosin(HE) staining and oil red O staining were performed to observe pathological changes in the liver and adipose tissue. Glucose metabolism was evaluated through the glucose tolerance test(GTT) and insulin tolerance test(ITT). Western blot analysis was performed to detect the expression of FGF21 and its downstream-related proteins in the liver and cortex, along with the expression of brain-derived neurotrophic factor(BDNF), disks large homolog 4(DLG4), and synaptophysin(SYP) in the cortex. Real-time quantitative fluorescent PCR(qPCR) was used to detect the expression of FGF21 and its receptor genes in the liver and cortex. Immunofluorescence staining was employed to examine the expression of neuronal activator c-Fos, FGF21, and the FGF21 co-receptor β-klotho in the cerebral cortex. The results showed that SPJ significantly improved the frequency of activity in the open arms of the elevated plus maze and the central area of the open field in HFD mice, up-regulated the expression of BDNF, DLG4, and SYP, and effectively alleviated anxiety-like behaviors in HFD mice. Compared with the NCD group, HFD mice exhibited up-regulated expression of FGF21 in the liver and cerebral cortex, while the expression of fibroblast growth factor receptor 1(FGFR1) and β-klotho was significantly down-regulated, suggesting that HFD mice exhibited FGF21 resistance. SPJ markedly up-regulated the β-klotho levels in HFD mice, reversing FGF21 resistance. Further comparison with exogenously administered FGF21 revealed that SPJ activates brain cortical regions in a consistent manner, and additionally, SPJ promotes the number and colocalization of c-Fos and β-klotho positive cells in the brain cortex. In summary, SPJ effectively alleviates anxiety-like behaviors in HFD mice. Its mechanism is associated with up-regulation of β-klotho expression in the brain, reversal of FGF21 resistance, and subsequent activation of neurons in the cerebral cortex and amygdala.
Animals ; Diet, High-Fat/adverse effects* ; Fibroblast Growth Factors/genetics* ; Mice ; Male ; Panax/chemistry* ; Mice, Inbred C57BL ; Anxiety/etiology* ; Saponins/administration & dosage* ; Brain-Derived Neurotrophic Factor/genetics* ; Humans ; Liver/metabolism* ; Drugs, Chinese Herbal/administration & dosage*

Objective:Exploring the association rules of factors influencing high hospitalization costs for cancer patients, providing references for hospitals to optimize medical cost management measures.Methods:In the inpatient case information system of a tertiary general hospital, the medical record homepages of inpatients in the DRG groups of the oncology department in 2022 were obtained. The upper four scores of hospitalization costs was used as the threshold for patient grouping. Patients with hospitalization costs≥this threshold were the high-cost group, while other patients were control group; 12 factors, including age, gender, and admission condition, etc, were considered as potential influencing factors of high hospitalization costs. FP-Growth and Apriori algorithms were used to excavate the potential association rules between the influencing factors of high hospitalization costs. Logistic regression was used to analyze the independent influencing factors of high hospitalization costs.Results:A total of 5 512 hospitalized patients were included, including 1 378 patients in the high-cost group. Thirteen validated strong association rules for factors influencing high hospitalization costs were obtained, of which the rule antecedents included age (≥70 years), number of days in hospital (≥7 days), other diagnoses (≥5), surgery, planned readmission, use of antibiotics, admission (general/critical), living admission score (61~99), level of care (level 1/level 2), non-day ward, criticality during hospitalisation. Logistic regression results showed that all nine influencing factors except gender, use of antibiotics, and readmission plans were independent influences on high hospitalization costs ( P<0.05). Conclusions:The joint application of FP-Growth and Apriori algorithm could effectively explore the association rules of high hospitalization costs for oncology patients. The early warning information mainly included the number of hospitalization days, the number of other diagnoses, surgeries, and so on. It was suggested that medical institutions can reasonably control the high hospitalization costs through clinical pathway management, diagnosis and treatment process reengineering, admission risk assessment, and multidisciplinary collaborative diagnosis and treatment strategies.

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.

With the widespread implementation of the DRG point method in China,how to deal with the potential risks brought by the punching behavior of medical institutions under the point method is a real problem that needs to be solved.It explains the special characteristics of uncertainty in the distribution of health insurance fund under the DRG point method,and explores the possibility,feasibility and proliferation of the point flushing behavior of medical institutions under the DRG point method at the theoretical level based on the rational economic man perspective,the principal generation theory and the cohort effect.In response to the theoretical model,game theory is used to further construct a model of point-shuffling behavior of medical institutions under the DRG point method,and analyze the reasons for point-shuffling behavior and its potential risks.It is suggested that the potential risks of point-shaving can be prevented by strengthening the communication and cooperation between medical institutions under the medical association and hierarchical diagnosis and treatment system,and by implementing the monitoring mechanism of medical insurance government departments on medical institutions.

With the widespread implementation of the DRG point method in China,how to deal with the potential risks brought by the punching behavior of medical institutions under the point method is a real problem that needs to be solved.It explains the special characteristics of uncertainty in the distribution of health insurance fund under the DRG point method,and explores the possibility,feasibility and proliferation of the point flushing behavior of medical institutions under the DRG point method at the theoretical level based on the rational economic man perspective,the principal generation theory and the cohort effect.In response to the theoretical model,game theory is used to further construct a model of point-shuffling behavior of medical institutions under the DRG point method,and analyze the reasons for point-shuffling behavior and its potential risks.It is suggested that the potential risks of point-shaving can be prevented by strengthening the communication and cooperation between medical institutions under the medical association and hierarchical diagnosis and treatment system,and by implementing the monitoring mechanism of medical insurance government departments on medical institutions.

Objective:Exploring the association rules of factors influencing high hospitalization costs for cancer patients, providing references for hospitals to optimize medical cost management measures.Methods:In the inpatient case information system of a tertiary general hospital, the medical record homepages of inpatients in the DRG groups of the oncology department in 2022 were obtained. The upper four scores of hospitalization costs was used as the threshold for patient grouping. Patients with hospitalization costs≥this threshold were the high-cost group, while other patients were control group; 12 factors, including age, gender, and admission condition, etc, were considered as potential influencing factors of high hospitalization costs. FP-Growth and Apriori algorithms were used to excavate the potential association rules between the influencing factors of high hospitalization costs. Logistic regression was used to analyze the independent influencing factors of high hospitalization costs.Results:A total of 5 512 hospitalized patients were included, including 1 378 patients in the high-cost group. Thirteen validated strong association rules for factors influencing high hospitalization costs were obtained, of which the rule antecedents included age (≥70 years), number of days in hospital (≥7 days), other diagnoses (≥5), surgery, planned readmission, use of antibiotics, admission (general/critical), living admission score (61~99), level of care (level 1/level 2), non-day ward, criticality during hospitalisation. Logistic regression results showed that all nine influencing factors except gender, use of antibiotics, and readmission plans were independent influences on high hospitalization costs ( P<0.05). Conclusions:The joint application of FP-Growth and Apriori algorithm could effectively explore the association rules of high hospitalization costs for oncology patients. The early warning information mainly included the number of hospitalization days, the number of other diagnoses, surgeries, and so on. It was suggested that medical institutions can reasonably control the high hospitalization costs through clinical pathway management, diagnosis and treatment process reengineering, admission risk assessment, and multidisciplinary collaborative diagnosis and treatment strategies.

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 prevalence of tension-type headache(TTH)in children and adolescents aged 0-19 years globally in 1990-2021,and to provide a basis for the prevention and treatment of TTH.Methods Based on the Global Burden of Disease Study data,the age-standardized prevalence distribution of TTH and its changing trend were analyzed among the children and adolescents aged 0-19 years,with different sexes,age groups,sociodemographic index(SDI)regions and countries/territories.Results The age-standardized prevalence rate(ASPR)of TTH in children and adolescents aged 0-19 globally in 2021 was 17 339.89/100 000,which was increased by 1.73%since 1990.The ASPR in females was slightly higher than that in males(1990:17 707.65/100 000 vs 16 403.78/100 000;2021:17 946.29/100 000 vs 16 763.09/100 000).The ASPR in adolescence was significantly higher than that in school-aged and preschool periods(1990:27 672.04/100 000 vs 10 134.16/100 000;2021:28 239.04/100 000 vs 10 059.39/100 000).Regions with high SDI exhibited a higher ASPR than the other regions,with significant differences in prevalence rates across different countries.From 1990 to 2021,there was a slight increase in global ASPR,with an average annual percentage change(AAPC)of 0.06%.Females experienced a smaller increase than males based on AAPC(0.04%vs 0.07%).There was reduction in ASPR in preschool and school-aged groups,with an AAPC of-0.02%,while there was a significant increase in ASPR in adolescence,with an AAPC of 0.07%.ASPR decreased in regions with low-middle and low levels of SDI,with an AAPC of-0.02%and-0.04%,respectively,while it increased in regions with middle SDI,with an AAPC of 0.24%.Conclusions There is a consistent increase in the ASPR of TTH in children and adolescents aged 0-19 years globally,with significant differences across sexes,age groups,SDI regions and countries/territories.

Objective To propose a sperm classification model based on convolutional neural network to enhance the accuracy of sperm morphological classification.Methods A FT-EfficientNet model was constructed using EfficientNetB0 as the base model,which was fine-tuned by data preprocessing enhancement,transfer learning and cosine decay.Classification experi-ments were performed on the sperm public datasets SCIAN-Morpho and HuSHeM,and the datasets were segmented and vali-dated using 5-fold cross-validation.The classification results by the FT-EfficientNet model were compared with those by the cascade ensemble of support vector machines(CE-SVM)model,the adaptive patch-based dictionary learning(APDL)model,fine tuning of visual geometry group(FT-VGG)model,morphological classification of human sperm heads(MH-HSH)model and transfer learning(TL)model.Ablation experiments were performed in the SCIAN-Morpho dataset to verify the effect of different fine-tuning methods on the model.Results The FT-EfficientNet model proposed had the accuracy,precision and F1 score on the SCIAN-Morpho validation set being 64.1％,63.8％and 64.8％,respectively,which were better than CE-SVM,APDL,FT-VGG and MC-HSH models.The recall rate of the model proposed(65.2％)was slightly lower than that of MC-HSH model(68.0％).The accuracy,precision,F1 score and recall rate on the HuSHeM validation set was 95.4％,95.8％,95.4％and 96.0％,respectively,which were slightly lower than those of TL model while better than those of CE-SVM,APDL,FT-VGG and MC-HSH models.Ablation experiments showed the FT-EfficientNet model behaved the best in fine-tuning.Conclusion The sperm classification model based on convolutional neural network facilitates sperm morphology classification with high accuracy and performance.[Chinese Medical Equipment Journal,2024,45(10):7-13]

DRG payment reform is an important means to control the unreasonable growth of medical expenses, improve the quality of medical services and achieve a win-win situation among three sides of hospitals, medical insurance and patients. This study adopted the Smith policy implementation process model to analyze the difficulties in the DRG policy implementation process from four aspects(idealized policies, policy implementation institutions, target groups, and policy environment), including the deviation between policy connotations and actual needs; the interest objectives of all parties were not completely aligned, the target group lacked a sense of identity, and the social impact and technological support needed to be improved. It was suggested that optimization should be carried out from four dimensions: policy supply coordination and precision, performance evaluation and personnel literacy, target group cognitive level and participation willingness, and policy implementation environment and atmosphere, in order to synergistically promote the effective implementation of DRG policies.