Objective To analyze the disease burden of chronic kidney diseases (CKD) attributed to high body mass index (BMI) in China from 1992 to 2021 and predict the disease burden for the next decade, and to provide evidence for the prevention and treatment of CKD. Methods Using the Global Burden of Disease (GBD) database and the Joinpoint model, the average annual percentage rate change (AAPC) of the mortality rate and disability-adjusted life year (DALY) rate was calculated to describe and analyze the CKD disease burden attributed to high BMI in China from 1992 to 2021. The ARIMA model was employed to predict and analyze the change trend of the CKD disease burden. Results From 1992 to 2021, the mortality rate and DALY rate attributed to high BMI-induced chronic kidney disease showed an upward trend. Compared to 1992, the attributed number of deaths increased by 324.38%, and DALYs increased by 268.56%; the mortality rate increased by 64.00%, and the DALY rate grew by 51.62%. From 1992 to 2021, the mortality rate and DALY rate for males were lower than those for females, but the growth rate for males exceeded that of females. From 1992 to 2021, the mortality rate and DALY rate of chronic kidney disease attributed to high BMI in China increased with age. The average annual change rate of chronic kidney disease attributed to high BMI in China from 1992 to 2021 (mortality rate: 1.40 per 100,000 (95% CI: 1.04–1.76), DALY rate: 1.43 per 100 000 (95% CI: 1.17–1.70)) was higher than thHuaiyin Normal University, Huai'anher social demographic index (SDI) regions. The ARIMA model predicted that the age-standardized mortality rate increased from 2.91 per 100 000 in 2022 to 3.05 per 100 000 in 2026, and the age-standardized DALY rate increased from 69.65 per 100 000 in 2022 to 73.58 per 100 000 in 2026. Conclusion Chronic kidney disease attributed to high BMI in China is on the rise, and it will continue to grow in the future. The focus of CKD prevention and control should be on males and the elderly, while active measures should be taken to reduce the occurrence and progression of chronic kidney disease.

Objective To construct a nomogram prediction model for predicting hemoglobin A1c(HbA1c)failure in type 2 diabetes mellitus(T2DM)patients.Methods A total of 936 inpatients with T2DM admitted to the Department of Endocrinology of the Affiliated Hospital of Shandong Second Medical University from January 2021 to January 2022 were selected as the research objects and divided into the non-standard group(HbA1c≥7%,n=801)and the standard group(HbA1c<7%,n=135).Univariate analysis was used to screen the related factors of HbA1c failure.Logistic regression multivariate model was used to analyze the influencing factors of HbA1c failure in T2DM patients.The R language was used to construct a nomogram,and the area under the receiver operating characteristic(ROC)curve(AUC)was used to evaluate the predictive ability of the model.The C-index and Hosmer-Lemeshow test were used to evaluate the discrimination and calibration of the model.Results There were statistically significant differences in triglyceride(TG),low-density lipoprotein cholesterol,direct bilirubin,urinary albumin/creatinine ratio(UACR),self-monitoring of blood glucose(SMBG),meat and vegetable pairing,hot pot,whole grain and animal viscera consumption between the two groups(P<0.05).Logistic regression analysis showed that TG(OR 1.699,95%CI 1.298～2.222),UACR(OR 1.003,95%CI 1.001～1.005),SMGB(OR 0.480,95%CI 0.313～0.735),more meat and less vegetables(OR 1.432,95%CI 1.062～1.931)were the influencing factors of HbA1c failure.The AUC of the nomogram prediction model based on the influencing factors was 0.711,with C-index 0.710(95%CI 0.663～0.758)and good calibration(χ2=11.185,P=0.191).Conclusions The nomogram prediction model for HbA1c failure in T2DM patients established based on TG,UACR,SMGB,meat and vegetarian mix has good discrimination and calibration,which can provide certain reference value for warning of poor blood glucose control.

Objective To investigate the knee disorders and risk factors in electromechanical soldiers of a warship,so as to provide a basis for prevention and treatment measures.Methods The knee disorders and treatment data of 200 electromechanical soldiers(study group)and 200 soldiers from other departments(control group)were colected by questionnaire survey and medical records.Results The incidence of knee diseases was 37.5%(75 cases)in the study group,which was significantly higher than that in the control group(16.0%,32 cases,P＜0.05).Traumatic and degenerative diseases were the main types of knee disorders.Age and body mass index were the influencing factors of knee disorders in electromechanical soldiers.Conclusion There is a high incidence of knee disorders in electromechanical soldiers,which is related to a variety of factors.Appropriate prevention and treatment measures are of great significance to reduce the incidence of knee disorders,promote rapid recovery,and reduce non-combat casualty.

Objective To construct a nomogram prediction model for predicting hemoglobin A1c(HbA1c)failure in type 2 diabetes mellitus(T2DM)patients.Methods A total of 936 inpatients with T2DM admitted to the Department of Endocrinology of the Affiliated Hospital of Shandong Second Medical University from January 2021 to January 2022 were selected as the research objects and divided into the non-standard group(HbA1c≥7%,n=801)and the standard group(HbA1c<7%,n=135).Univariate analysis was used to screen the related factors of HbA1c failure.Logistic regression multivariate model was used to analyze the influencing factors of HbA1c failure in T2DM patients.The R language was used to construct a nomogram,and the area under the receiver operating characteristic(ROC)curve(AUC)was used to evaluate the predictive ability of the model.The C-index and Hosmer-Lemeshow test were used to evaluate the discrimination and calibration of the model.Results There were statistically significant differences in triglyceride(TG),low-density lipoprotein cholesterol,direct bilirubin,urinary albumin/creatinine ratio(UACR),self-monitoring of blood glucose(SMBG),meat and vegetable pairing,hot pot,whole grain and animal viscera consumption between the two groups(P<0.05).Logistic regression analysis showed that TG(OR 1.699,95%CI 1.298～2.222),UACR(OR 1.003,95%CI 1.001～1.005),SMGB(OR 0.480,95%CI 0.313～0.735),more meat and less vegetables(OR 1.432,95%CI 1.062～1.931)were the influencing factors of HbA1c failure.The AUC of the nomogram prediction model based on the influencing factors was 0.711,with C-index 0.710(95%CI 0.663～0.758)and good calibration(χ2=11.185,P=0.191).Conclusions The nomogram prediction model for HbA1c failure in T2DM patients established based on TG,UACR,SMGB,meat and vegetarian mix has good discrimination and calibration,which can provide certain reference value for warning of poor blood glucose control.

This study explored the growth-promoting effect and mechanism of the endophytic bacterium Kocuria rosea on Rehmannia glutinosa, aiming to provide a scientific basis for the development of green bacterial fertilizer. R. glutinosa 'Jinjiu' was treated with K. rosea, and the shoot parameters including leaf length, leaf width, plant width, and stem diameter were measured every 15 days. After 120 days, the shoots and roots were harvested. The root indicators(root number, root length, root diameter, root fresh weight, root dry weight, root volume, and root vitality) and secondary metabolites(catalpol, rehmannioside A, rehmannioside D, verbascoside, and leonuride) were determined. The R. glutinosa growth-promoting mechanism of K. rosea was discussed from the effect of K. rosea on the nutrient element content in R. glutinosa and rhizosphere soil and the genome information of this plant. After application of K. rosea, the maximum increases in leaf length, leaf width, plant width, and stem diameter were 35.67%(60 d), 25.39%(45 d), 40.17%(60 d), and 113.85%(45 d), respectively. The root number, root length, root diameter, root volume, root fresh weight, root dry weight, and root viability increased by 41.71%, 45.10%, 48.61%, 94.34%, 101.55%, 147.61%, and 42.08%, respectively. In addition, the content of rehmannioside A and verbascoside in the root of R. glutinosa increased by 76.67% and 69.54%, respectively. K. rosea promoted the transformation of nitrogen(N), phosphorus(P), and potassium(K) in the rhizosphere soil into the available state. Compared with that in the control, the content of available N(54.60 mg·kg~(-1)), available P(1.83 μmol·g~(-1)), and available K(83.75 mg·kg~(-1)) in the treatment with K. rosea increased by 138.78%, 44.89%, and 14.34%, respectively. The content of N, P, and K in the treatment group increased by 293.22%, 202.63%, and 23.80% in the roots and by 23.60%, 107.23%, and 134.53% in the leaves of R. glutinosa, respectively. K. rosea carried the genes related to colonization(rbsB, efp, bcsA, and gmhC), N, P, and K metabolism(narG, narH, narI, nasA, nasB, GDH2, pyk, aceB, ackA, CS, ppa, ppk, ppk2, pstS, pstA, pstB, and pstC), and indole-3-acetic acid and zeatin synthesis(iaaH and miaA). Further studies showed that K. rosea could colonize the roots of R. glutinosa and secrete indole-3-acetic acid(3.85 μg·mL~(-1)) and zeatin(0.10 μg·mL~(-1)). In summary, K. rosea promotes the growth of R.ehmannia glutinosa by enhancing the nutrient uptake, which provides a theoretical basis for the development of plant growth-promoting microbial products.
Rehmannia/metabolism* ; Endophytes/metabolism* ; Plant Roots/growth & development* ; Micrococcaceae/genetics* ; Data Mining ; Plant Leaves/metabolism* ; Genomics ; Rhizosphere

PURPOSE: The combined use of antibiotics and anti-inflammatory medicine to manage bacterial endotoxin-induced inflammation following injuries or diseases is increasing. The cytokine level produced by macrophages plays an important role in this treatment course. Ciprofloxacin and indomethacin, two typical representatives of antibiotics and anti-inflammatory medicine, are cost-effective and has been reported to show satisfactory effect. The current study aims to investigate the effect of ciprofloxacin along with indomethacin on the secretion of inflammatory cytokines by macrophages in vitro. METHODS: Primary murine peritoneal macrophages and RAW 264.7 cells were administrated with lipopolysaccharide (LPS) for 24 h. The related optimal dose and time point of ciprofloxacin or indomethacin in response to macrophage inflammatory response inflammation were determined via macrophage secretion induced by LPS. Then, the effects of ciprofloxacin and indomethacin on the secretory functions and viability of various macrophages were determined by enzyme-linked immunosorbent assay and flow cytometry analysis, especially for the levels of interleukin (IL)-1β, IL-6, IL-10, and tumor necrosis factor (TNF)-α. The optimal dose and time course of ciprofloxacin affecting macrophage inflammatory response were determined by testing the maximum inhibitory effect of the drugs on pro-inflammatory factors at each concentration or time point. RESULTS: According to the levels of cytokines secreted by various macrophages (1.2 × 10⁶ cells/well) after administration of 1 μg/mL LPS, the optimal dose and usage timing for ciprofloxacin alone were 80 μg/mL and 24 h, respectively, and the optimal dose for indomethacin alone was 10 μg/mL. Compared with the LPS-stimulated group, the combination of ciprofloxacin and indomethacin reduced the levels of IL-1β (p < 0.05), IL-6 (p < 0.05), IL-10 (p < 0.01)), and TNF-α (p < 0.01). Furthermore, there was greater stability in the reduction of inflammatory factor levels in the combination group compared with those in which only ciprofloxacin or indomethacin was used. CONCLUSION The combination of ciprofloxacin and indomethacin suppressed the levels of inflammatory cytokines secreted by macrophages in vitro. This study illustrates the regulatory mechanism of drug combinations on innate immune cells that cause inflammatory reactions. In addition, it provides a new potential antibacterial and anti-inflammatory treatment pattern to prevent and cure various complications in the future.
Humans ; Mice ; Animals ; Cytokines ; Lipopolysaccharides/pharmacology* ; Interleukin-10 ; Indomethacin/therapeutic use* ; Interleukin-6/therapeutic use* ; Ciprofloxacin/therapeutic use* ; Macrophages ; Tumor Necrosis Factor-alpha ; Inflammation/drug therapy* ; Anti-Inflammatory Agents/therapeutic use* ; Anti-Bacterial Agents/therapeutic use*

Isotemporal substitution model is a powerful tool to explore the real association between physical behavior and health outcomes, which has the potential of the application in large-scale cohort study. This paper systematically introduces the principle of isotemporal substitution model and its implementation method in specific analysis to provide analytical ideas for the epidemiological research related to physical behavior in China. The baseline data of Regional Ethic Cohort Study in Northwest China conducted in Shaanxi province were used to analyze the relationship between physical behavior and cardiovascular disease with single-factor model, partition model and isotemporal substitution model. The advantages and disadvantages of different models were compared, and the advantages of isotemporal substitution model in quantifying physical activity health risk were introduced. Isotemporal substitution model could qualify physical behavior and health outcomes, which has wide application value in epidemiological research.
Humans ; Cohort Studies ; Epidemiologic Studies ; Cardiovascular Diseases ; China/epidemiology*

Antineoplastic Combined Chemotherapy Protocols ; Bendamustine Hydrochloride/therapeutic use* ; Etoposide ; Hematopoietic Stem Cell Transplantation ; Humans ; Lymphoma/therapy* ; Melphalan ; Transplantation Conditioning ; Transplantation, Autologous

OBJECTIVE: To investigate the risk factors for cow's milk protein allergy (CMPA) among infants through a multicenter clinical study. METHODS: A total of 1 829 infants, aged 1-12 months, who attended the outpatient service of the pediatric department in six hospitals in Shenzhen, China from June 2016 to May 2017 were enrolled as subjects. A questionnaire survey was performed to screen out suspected cases of CMPA. Food avoidance and oral food challenge tests were used to make a confirmed diagnosis of CMPA CMPA. A multivariate logistic regression analysis was used to investigate the risk factors for CMPA. RESULTS: Among the 1 829 infants, 82 (4.48%) were diagnosed with CMPA. The multivariate logistic regression analysis showed that maternal food allergy (OR=4.91, 95%CI: 2.24-10.76, P<0.05), antibiotic exposure during pregnancy (OR=3.18, 95%CI: 1.32-7.65, P<0.05), and the introduction of complementary food at an age of <4 months (OR=3.55, 95%CI: 1.52-8.27, P<0.05) were risk factors for CMPA, while exclusive breastfeeding (OR=0.21, 95%CI: 0.08-0.58, P<0.05) and the introduction of complementary food at an age of >6 months (OR=0.38, 95%CI: 0.17-0.86, P<0.05) were protective factors. CONCLUSIONS The introduction of complementary food at an age of <4 months, maternal food allergy, and antibiotic exposure during pregnancy are risk factors for CMPA in infants.
Animals ; Cattle ; China ; Female ; Humans ; Infant ; Milk Hypersensitivity ; Milk Proteins ; Pregnancy ; Risk Factors ; Surveys and Questionnaires

Objective:To establish autoverification rules for coagulation tests in multicenter cooperative units, in order to reduce workload for manual review of suspected results and shorten turnaround time (TAT) of test reports, while ensure the accuracy of results.Methods:A total of 14 394 blood samples were collected from fourteen hospitals during December 2019 to March 2020. These samples included: Rules Establishment Group 11 230 cases, including 1 182 cases for Delta check rules; Rules Validation Group 3 164 cases, including 487cases for Delta check; Clinical Application Trial Group 77 269 cases. Samples were analyzed for coagulation tests using Sysmex CS series automatic coagulation analyzers, and the clinical information, instrument parameters, test results, clinical diagnosis, medication history of anticoagulant and other relative results such as HCT, TG, TBIL, DBIL were summarized; on the basis of historical data, the 2.5 and 97.5 percentile of all data arranged from low to high were initially accumulated; on the basis of clinical suggestions, critical values and specific drug use as well as relative guidelines, autoverification rules and limits were established.The rules were then input into middleware, in which Stage I/Stage II validation was done. Positive coincidence, negative coincidence, false negative, false positive, autoverification pass rate, passing accuracy (coincidence of autoverification and manual verification) were calculated. Autoverification rules underwent trial application in coagulation results reports.Results:(1) The autoverification algorisms involve 33 rules regarding PT/INR, APTT, FBG, D-dimer, FDP,Delta check, reaction curve and sample abnormalities; (2)Autoverification Establishment Group showed autoverification pass rate was 68.42% (7 684/11 230), the false negative rate was 0%(0/11230), coincidence of autoverification and manual verification was 98.51%(11 063/11 230), in which positive coincidence and negative coincidence were respectively 30.09% (3 379/11 230) and 68.42%(7 684/11 230); Autoverification Validation Group showed autoverification pass rate was 60.37%(1 910/3 164), the false negative rate was 0%(0/11 230), coincidence of autoverification and manual verification was 97.79%(3 094/3 164), in which positive coincidence and negative coincidence were respectively 37.42%(1 184/3 164) and 60.37%(1 910/3 164); (3) Trialed implementation of these autoverification rules on 77 269 coagulation samples showed that the average TAT shortened by 8.5 min-83.1 min.Conclusions:This study established 33 autoverification rules in coagulation tests. Validation showedthese rules could ensure test quality while shortening TAT and lighten manual workload.