Objective:To construct a refined management model based on the Interrupt Time Series(ITS)algorithm model for medical consumables,so as to provide a scientific basis for hospitals in implementing refined management for medical consumables.Methods:The supply,inventory and usage data of medical consumables were collected,and the ITS algorithm was used to analyze the prediction for the usage of medical consumables,and the influence of policy intervention.The outliers and key influencing factors of the full-cycle data of medical consumables were mined,and management countermeasures were formulated from three aspects:early warning for dynamic inventory,feedback of policy effect,and abnormal rectification handling.A total of 10,614 medical consumables that were routinely used at Taizhou People's Hospital from January 2023 to December 2024 were selected.The empirical management method was adopted to manage 4,924 medical consumables during the period from January to December 2023,and the refined management method was adopted to manage 5,690 medical consumables during the period from January to December 2024.The utilization rate of medical consumables,the quality of management decisions and the performance of clinical services of the two management methods were compared.Results:The average inventory turnover rate and usage rate of medical consumables of the refined management method were respectively(91.11±3.02)%and(91.19±2.75)%,which were higher than those of the empirical management method.The proportion of average inventory cost,and loss rate of overstock of the refined management method were respectively(2.53±0.57)%and(2.84±0.44)%,which were lower than those of the empirical management method,and the differences were all statistically significant(t=4.698,5.976,4.518,8.496,P<0.05).The average accuracy rate of prediction,detection rate of abnormity,and the mean of timely handling rate of the refined management method for medical consumables were all higher than those of the empirical management method,and the differences were statistically significant(t=6.423,8.587,6.102,P<0.05).The satisfaction of doctors,nurses,warehouse managers and purchasing managers who used and managed medical consumables for the clinical service performance of adopting the refined management method was higher than that of adopting the empirical management method,and the differences were statistically significant(x2=7.416,12.793,4.267,4.667,P<0.05).Conclusion:The application of the refined management model based on the ITS algorithm model for medical consumables can enhance the predictive ability for the demand of medical staffs for medical consumables,and reduce the pressure for inventory,and management costs of medical consumables,and accurately detect abnormal problems in the use of medical consumables,and improve the level of clinical services.

Objective:To construct a refined management model based on the Interrupt Time Series(ITS)algorithm model for medical consumables,so as to provide a scientific basis for hospitals in implementing refined management for medical consumables.Methods:The supply,inventory and usage data of medical consumables were collected,and the ITS algorithm was used to analyze the prediction for the usage of medical consumables,and the influence of policy intervention.The outliers and key influencing factors of the full-cycle data of medical consumables were mined,and management countermeasures were formulated from three aspects:early warning for dynamic inventory,feedback of policy effect,and abnormal rectification handling.A total of 10,614 medical consumables that were routinely used at Taizhou People's Hospital from January 2023 to December 2024 were selected.The empirical management method was adopted to manage 4,924 medical consumables during the period from January to December 2023,and the refined management method was adopted to manage 5,690 medical consumables during the period from January to December 2024.The utilization rate of medical consumables,the quality of management decisions and the performance of clinical services of the two management methods were compared.Results:The average inventory turnover rate and usage rate of medical consumables of the refined management method were respectively(91.11±3.02)%and(91.19±2.75)%,which were higher than those of the empirical management method.The proportion of average inventory cost,and loss rate of overstock of the refined management method were respectively(2.53±0.57)%and(2.84±0.44)%,which were lower than those of the empirical management method,and the differences were all statistically significant(t=4.698,5.976,4.518,8.496,P<0.05).The average accuracy rate of prediction,detection rate of abnormity,and the mean of timely handling rate of the refined management method for medical consumables were all higher than those of the empirical management method,and the differences were statistically significant(t=6.423,8.587,6.102,P<0.05).The satisfaction of doctors,nurses,warehouse managers and purchasing managers who used and managed medical consumables for the clinical service performance of adopting the refined management method was higher than that of adopting the empirical management method,and the differences were statistically significant(x2=7.416,12.793,4.267,4.667,P<0.05).Conclusion:The application of the refined management model based on the ITS algorithm model for medical consumables can enhance the predictive ability for the demand of medical staffs for medical consumables,and reduce the pressure for inventory,and management costs of medical consumables,and accurately detect abnormal problems in the use of medical consumables,and improve the level of clinical services.

Objective: To examine differences in depressive and anxiety symptoms between boarding and non boarding high school students and their associations with physical activity (PA) patterns, so as to provide evidence to inform adolescent mental health promotion. Methods: From October to December 2024, a convenience sample of 11 782 students aged 15-18 years was recruited from 36 schools in Nanchang, Ganzhou, and Shangrao of Jiangxi Province. Depressive and anxiety symptoms and PA were assessed using the Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), and International Physical Activity Questionary Short Form (IPAQ-SF). Logistic regression model was used to examine associations between PA patterns, depressive and anxiety symptoms among boarding and non boarding students. Results: The detection rates of depressive symptoms were 45.7% and 46.4% among boarding and non boarding students, respectively; for anxiety symptoms, the corresponding rates were 43.0% and 46.7%. Boarding and non boarding students differed significantly in smoking status, screen time, sleep duration, sedentary time, daily vegetable intake, and napping ( χ 2=16.74-664.17, all P <0.01). Across PA pattern groups, the detection rates of depressive and anxiety symptoms differed significantly between boarding and non boarding students ( χ 2 depression = 23.85 , χ 2 anxiety = 22.78, both P <0.01). Adjusted for confounding factors, Logistic regression analysis of high school students showed that compared with the not meeting PA recommendations, both the concentrated and regular PA pattern were associated with lower odds of depressive symptoms [ OR (95% CI )=0.83(0.70-0.98), 0.90(0.83-0.98)]; and the concentrated pattern was also associated with lower odds of anxiety symptoms [ OR (95% CI )=0.78(0.65-0.92)], and the association of anxiety symptoms in concentrated boarding students was consistent with that of the overall group [ OR (95% CI )=0.71(0.52-0.98)] (all P <0.05). Conclusions There is a correlation of different physical activity patterns with depressive and anxiety symptoms among boarding and non boarding high school students. Schools should ensure students engage in regular physical activity and work to increase overall activity volume.

Objective:To assess the diagnostic performance of serum anti-toxocara immunoglobulin G (anti-T-IgG) in ocular toxocariasis (OT) patients.Methods:A diagnostic tests. A total of 109 patients (109 eyes) with clinically-suspected OT who treated in Department of Ophthalmology of Xuzhou First People’s Hospital from June 2015 to December 2022 were included. Patients were divided into two groups, 76 with OT and 33 with non-OT, according to the clinical manifestations and Goldmann-Witmer coefficient. Paired serum and intraocular fluid samples from each patient were collected and analyzed for specific anti-T-IgG using enzyme linked immunosorbent assay. Mann-Whitney test was performed for comparison between groups. The area under the receiver operating characteristic curve (ROC) was used to assess the diagnostic performance of serum anti-T-IgG. Kappa analysis was performed to examine the consistency of serum or intraocular fluid anti-T-IgG positive rate with OT diagnostic result. Spearman’s rank correlation test was performed to assess the association.Results:Compared with the non-OT group, the proportions of children and history of exposure to cats and dogs ( χ2=9.785, 12.026) were significantly higher in OT group, and the differences were statistically significant ( P<0.01). The positive rate ( χ2=24.551) and U value ( Z=-4.379) of serum anti-T-IgG in OT group were higher than those in non-OT group, and the differences were statistically significant ( P<0.000 1). The recommended serum anti-T-IgG cut-off value of 11 U had 0.72 sensitivity, 0.79 specificity, 0.89 positive predictive value, 0.55 negative predictive value, and 0.77 area under the ROC with 95% confidence interval ( CI) 0.669-0.860. Correlation analysis showed that serum anti-T-IgG was positively correlated with intraocular fluid anti-T-IgG ( r s=0.520, 95% CI 0.363-0.648, P<0.000 1). The Kappa values of serum and intraocular fluid anti-T-IgG positive rate with OT diagnosis were 0.457 (95% CI 0.292-0.622) and 0.711 (95% CI 0.582-0.840), respectively. The Kappa value of serum anti-T-IgG positive rate with OT diagnosis was lower than that of intraocular fluid. Conclusion:The sensitivity and specificity of serum anti-T-IgG and the consistency between serum anti-T-IgG positive rate and OT diagnosis are low, suggesting that serum anti-T-IgG level cannot be used as a basis for OT diagnosis.

Cerebral small vessel disease refers to a type of disease that damages the small blood vessels of the brain and causes parenchymal lesions due to various reasons,which is a common health hazard in the elderly population.It has a slow onset and progressive progression,gradually affecting the whole brain,which can cause stroke,cognitive impairment and other diseases,and seriously affect people's life quality.This article reviewed the correlation between the serological marker β2 microglobulin and cerebral small vessel disease in recent years,aiming to provide guidance for the early diagnosis and prevention of cerebral small vessel disease,and to provide new ideas for the clinical treatment of diagnosed patients.

AIM:To investigate whether the expression of perilipin 2(PLIN2)in renal tubular cells could predict a decline in renal function in diabetic kidney disease(DKD)patients,and to explore the potential mechanisms in-volved in renal tubular cell injury induced by PLIN2 during the progression of DKD.METHODS:Control individuals(n=12)and DKD patients(n=51)were enrolled in this retrospective cohort study.Demographic and laboratory data were col-lected.A simplified linear mixed-effects model was applied to assess the estimated glomerular filtration rate(eGFR)slope.The relationship between PLIN2 and renal function decline in DKD patients was predicted by Spearman correlation analysis and a generalized linear model.BKS-db/db diabetic mice and streptozotocin-induced diabetic mice were used.Primary renal tubular cells were treated with glucose and transfected with small interfering RNA or plasmid.Western blot-ting and immunofluorescence staining were used to detect PLIN2 expression.Lipid droplets were stained with oil red O.The oxygen consumption rate(OCR)of mitochondria was measured using an extracellular flux analyser.RESULTS:The expression of PLIN2 was markedly higher in the tubules of DKD patients than in those of control subjects.After 24(12,39)months of follow-up,the eGFR slope of DKD patients was-7.42(-19.77,-2.09)mL/(min·1.73 m2·year).An in-crease in the baseline percentage of PLIN2-positive tubules was significantly associated with the eGFR slope during the fol-low-up period[hazard ratio(HR)=1.90,95%confidence interval(CI):1.00～3.58],indicating that tubular PLIN2 could predict a decrease in renal function in DKD patients.Both the accumulation of lipid droplets and the expression of PLIN2 were markedly greater in the tubules of diabetic mice than in those of control mice.Glucose treatment induced lipid droplet accumulation and PLIN2 expression in renal tubular cells.Knockdown of PLIN2 significantly alleviated glucose-in-duced lipid droplet accumulation,whereas PLIN2 overexpression aggravated glucose-induced lipid droplet accumulation.The decrease in mitochondrial OCR in renal tubular cells induced by glucose treatment was alleviated after PLIN2 knock-down.However,overexpression of PLIN2 directly decreased the mitochondrial OCR.CONCLUSION:The PLIN2 ex-pression in tubules predicts a decline in renal function in patients with DKD.The PLIN2 suppresses mitochondrial aerobic respiration and contributes to the accumulation of lipid droplets in renal tubular cells to promote the progression of DKD.

Objective:To construct a clinical benefit evaluation model of medical equipment based on the combination weighting of game theory with cloud model,so as to improve the clinical service capability and operational quality of medical equipment. Methods:The game theory,combination weighting and cloud model were used to scientifically empower and comprehensively evaluate 13 clinical benefit evaluation indexes from 3 dimensions:direct input,direct output. and indirect benefits of medical equipment,and to develop corresponding equipment management strategies.. 47 large medical equipment in clinical use at Taizhou People's Hospital from 2022 to 2023 were selected,and the large medical equipment used in 2022 was subjected to subjective evaluation management. The equipment used in 2023 adopts a medical device clinical benefit evaluation model (referred to as model evaluation management) of game theory combination weighting and cloud model to carry out clinical benefit evaluation and management of the equipment. The clinical benefit,operation quality and management level of the two management methods were compared. Results:The effective management rate of medical equipment using the model evaluation management method was 63.83％(30/47),which was higher than that using the subjective evaluation management method,and the difference was statistically significant (x2=5.158,P<0.05). The average clinical risk rate,failure rate and detection failure rate of medical equipment using the model evaluation management method were (10.59±3.09)‰,(7.27±3.53)‰ and (12.06±2.43)‰,respectively,all of which were lower than those obtained through the subjective evaluation management method. The differences were statistically significant (Z=3.783,2.748,3.928,P<0.05). The assessment scores of medical equipment use managers on the ability of equipment use,maintenance,repair and planning using the model evaluation management method were (93.38±3.73) points,(94.05±3.14) points,(92.61±3.44) points and (94.88±2.50) points,respectively,which were higher than those obtained through the subjective evaluation management method. The differences were statistically significant (Z=2.718,3.036,3.039,3.929,P<0.05). Conclusion:The application of the clinical benefit evaluation model of medical equipment,which based on the game theory combination weighting and cloud model,can accurately evaluate the clinical benefit level of medical equipment,and improve the operation quality of the equipment,and enhance the management level of equipment.

Objective:To construct a clinical benefit evaluation model of medical equipment based on the combination weighting of game theory with cloud model,so as to improve the clinical service capability and operational quality of medical equipment. Methods:The game theory,combination weighting and cloud model were used to scientifically empower and comprehensively evaluate 13 clinical benefit evaluation indexes from 3 dimensions:direct input,direct output. and indirect benefits of medical equipment,and to develop corresponding equipment management strategies.. 47 large medical equipment in clinical use at Taizhou People's Hospital from 2022 to 2023 were selected,and the large medical equipment used in 2022 was subjected to subjective evaluation management. The equipment used in 2023 adopts a medical device clinical benefit evaluation model (referred to as model evaluation management) of game theory combination weighting and cloud model to carry out clinical benefit evaluation and management of the equipment. The clinical benefit,operation quality and management level of the two management methods were compared. Results:The effective management rate of medical equipment using the model evaluation management method was 63.83％(30/47),which was higher than that using the subjective evaluation management method,and the difference was statistically significant (x2=5.158,P<0.05). The average clinical risk rate,failure rate and detection failure rate of medical equipment using the model evaluation management method were (10.59±3.09)‰,(7.27±3.53)‰ and (12.06±2.43)‰,respectively,all of which were lower than those obtained through the subjective evaluation management method. The differences were statistically significant (Z=3.783,2.748,3.928,P<0.05). The assessment scores of medical equipment use managers on the ability of equipment use,maintenance,repair and planning using the model evaluation management method were (93.38±3.73) points,(94.05±3.14) points,(92.61±3.44) points and (94.88±2.50) points,respectively,which were higher than those obtained through the subjective evaluation management method. The differences were statistically significant (Z=2.718,3.036,3.039,3.929,P<0.05). Conclusion:The application of the clinical benefit evaluation model of medical equipment,which based on the game theory combination weighting and cloud model,can accurately evaluate the clinical benefit level of medical equipment,and improve the operation quality of the equipment,and enhance the management level of equipment.

Chronic diabetic wound remains a critical challenge suffering from the complicated negative microenvironments, such as high-glucose, excessive reactive oxygen species (ROS), hypoxia and malnutrition. Unfortunately, few strategies have been developed to ameliorate the multiple microenvironments simultaneously. In this study, Chlorella sp. (Chlorella) hydrogels were prepared against diabetic wounds. In vitro experiments demonstrated that living Chlorella could produce dissolved oxygen by photosynthesis, actively consume glucose and deplete ROS with the inherent antioxidants, during the daytime. At night, Chlorella was inactivated in situ by chlorine dioxide with human-body harmless concentration to utilize its abundant contents. It was verified in vitro that the inactivated-Chlorella could supply nutrition, relieve inflammation and terminate the oxygen-consumption of Chlorella-respiration. The advantages of living Chlorella and its contents were integrated ingeniously. The abovementioned functions were proven to accelerate cell proliferation, migration and angiogenesis in vitro. Then, streptozotocin-induced diabetic mice were employed for further validation. The in vivo outcomes confirmed that Chlorella could ameliorate the undesirable microenvironments, including hypoxia, high-glucose, excessive-ROS and chronic inflammation, thereby synergistically promoting tissue regeneration. Given the results above, Chlorella is considered as a tailor-made therapeutic strategy for diabetic wound healing.

Objective:To explore the correlation between socioeconomic status (SES) and diabetic kidney disease (DKD) in patients with type 2 diabetes (T2D).Methods:A total of 276 T2D patients admitted to the Second Affiliated Hospital of Nanjing Medical University from January to June 2020 were enrolled in this cross-sectional study. The estimated glomerular filtration rate (eGFR) was calculated according to the urinary albumin/creatinine ratio (UACR) and the chronic kidney disease epidemiology collaboration equation(CKD-EPI formula) based on serum creatinine. The patients were divided into simple T2D group (184 cases) and DKD group (92 cases). Collect demographic and laboratory examination data, record education, income and occupation, and calculate standardized SES scores. According to SES scores, subjects were divided in three levels: SES≤9, SES≥10-≤12, and SES≥13. Student's t test was used for comparison of measurement data with normal distribution between two groups, and one-way ANOVA was used for comparison between multiple groups. Non-normal distribution was represented by M( Q1, Q3), and rank-sum test was used for comparison between groups. Counting data were expressed as frequency or percentage, and chi-square test was used for comparison between groups. Bofferoni test was further used for pairwise comparison of indicators with statistical significance among multiple groups. Spearman correlation analysis was used to analyze the correlation between variables. The risk factors were analyzed by binary Logistic regression. Results:The age of the subjects was (53.37±10.68) years, men accounted for 55.8% (154/276), the duration of diabetes was 60.00 (12.00, 134.00) months, and eGFR was (97.56±21.15) mL/(min·1.73 m 2). In simple T2D group and DKD group, prevalence of hypertension were 39.7% (73/184) and 57.6% (53/92), systolic blood pressure were (129.43±14.92) mmHg and (139.29±17.61) mmHg, diastolic blood pressure were (81.86±10.06) mmHg and (87.74±11.19) mmHg, serum albumin were (45.74±4.15) g/L and (43.99±5.05) g/L, triglycerides were (1.82±1.24) mmol/L and (2.64±2.92) mmol/L, high density lipoprotein cholesterol were (1.17±0.37) mmol/L and (1.07±0.26) mmol/L, serum uric acid were (298.44±90.73) μmol/L and (336.22±94.01) μmol/L, serum creatinine were (62.83±14.45) μmol/L and (87.75±57.37) μmol/L, eGFR were (102.6±14.28) mL/(min·1.73 m 2) and (87.47±28.04) mL/(min·1.73 m 2), UACR were (7.60 (4.63, 13.15)) mg/g and (93.95 (47.25, 310.25)) mg/g. Prevalence of hypertension, systolic blood pressure, diastolic blood pressure, triglycerides, serum uric acid, serum creatinine, UACR in DKD group were higher than those in simple T2D group. Serum albumin, high density lipoprotein cholesterol and eGFR in DKD group were lower than those in simple T2D group. There was significant difference between the two groups ( χ2=7.95, t values were 4.87, 4.40, 3.04, 3.26, 2.30, 3.22, 5.56, 5.95, Z=13.07, P values were 0.005, <0.001, <0.001, 0.003, 0.001, 0.022, 0.001, <0.001, <0.001, and <0.001, respectively). The number of males in the three groups with SES ≥13 group, SES≥10-≤12 group, SES ≤9 group were 61 (81.3%, 61/75), 55 (59.8%, 55/92), 38 (34.9%, 38/109), respectively. The number of cases with smoking history were 42 (56.0%, 42/75), 41 (44.6%, 41/92), 35 (32.1%, 35/109), respectively. The number of cases with drinking history were 38 (50.7%, 38/75), 32 (34.8%, 32/92), 26 (23.9%, 26/109), respectively. The ages were (47.77±10.76), (52.76±11.22), (57.74±7.96) years old, respectively. Body mass index (BMI) were (26.17±3.87), (24.96±3.93), (24.27±4.89) kg/m 2, respectively. High density lipoprotein cholesterol (HDL) were (1.03±1.03), (1.16±0.41), (1.21±0.32) mmol/L, respectively. Serum uric acid were (336.56±82.05), (293.78±94.78), (307.99±96.53) μmol/L, respectively. EGFR were (105.03±19.72), (99.77±19.44), (90.57±21.49) mL/(min·1.73 m 2),respectively.The difference between groups were statistically significant (χ 2=39.79, 10.55, 14.08, F=22.69, 4.03, 6.20, 4.53, 12.02, P values were <0.001, 0.005, 0.001, <0.001, 0.019, 0.002, 0.012, and <0.001, respectively). Pairwise comparison shows that male and eGFR in SES ≤9 group were lower than those in SES ≥13 group and SES≥10-≤12 group, age in SES ≤9 group was higher than that in SES ≥13 group and SES≥10-≤12 group. The difference was statistically significant (all P<0.05). Smoking history, alcohol history and BMI in SES ≤9 group were lower than those in SES ≥13 group, and the high density lipoprotein cholesterol in SES ≤9 were higher than that in SES ≥13 group. The difference was statistically significant (all P<0.05). Male, alcohol history and serum uric acid in SES≥10-≤12 group were lower than those in SES ≥13 group, and age and high density lipoprotein cholesterol in SES≥10-≤12 group were higher than those in SES ≥13 group. The difference was statistically significant (all P<0.05). Spearman correlation analysis showed that SES in T2D was positively correlated with male, smoking history, alcohol history, BMI, serum uric acid and eGFR ( r values were 0.38, 0.20, 0.24, 0.16, 0.13 and 0.31, P values were <0.001, 0.001, <0.001, 0.008, 0.028, and <0.001, respectively), and negatively correlated with age, high density lipoprotein cholesterol and UACR ( r values were -0.35, -0.24 and -0.14, P values were <0.001, <0.001, and 0.017, respectively). Logistic regression analysis showed that SES (OR=2.71,95% CI:1.10-6.68, P=0.031) was associated with T2DM combined with DKD. The risk of developing DKD increased when the SES was ≤9. Conclusion:The SES in patients with type 2 diabetes is closely related to DKD. Low SES may be a new risk factor for DKD in type 2 diabetic patients.