Objective To assess the exposure levels of heavy metals,including lead,arsenic,mercury,and cadmium,in the local population in Sichuan and Chongqing,China,to compare and analyze the differences in reference intervals(RIs)obtained from direct and indirect sampling methods,and to explore the interchangeability and limitations of these two sampling methods.Methods RIs were obtained by the direct sampling method and the indirect sampling method.In the direct sample method,the levels of blood arsenic,urinary cadmium,urinary mercury,and blood lead levels of 5562 healthy participants aged 22-50 years in Sichuan and Chongqing,China were measured by atomic absorption spectrometry and inductively coupled plasma-mass spectrometry.Using the human biomonitoring(HBM)data,we established RIs for the population by a nonparametric method.On the other hand,in the indirect sampling method,RIs were established via a nonparametric method based on data from the laboratory information system(LIS)of a local hospital after stratifying healthy individuals using a Gaussian mixture model(GMM).Comparative analysis of the RIs derived from the two sampling methods were then conducted.Results The RI for blood arsenic was 0.11-1.3 μmol/L.The RI for urinary cadmium was 0.51-2.80 μmol/mol creatine for adults aged 22 to under 43 years and 0.66-2.96 μmol/mol creatine for adults aged 43-50 years.The RI for urinary mercury was 0.12-1.10 μmol/mol creatine.The RI for blood lead was 14.00-47.00 pg/L for adults aged 22 to under 41 year,16.00-53.38 pg/L for males aged 41-50 year,and 15.00-51.02 pg/L for females aged 41-50 year.Most of the RIs established by the direct sampling method had a narrower range compared to those established by the indirect sampling method,and the RIs established by both sampling methods were partially biased.Conclusions The RIs for blood arsenic,urine cadmium,urine mercury,and blood lead in healthy individuals aged 22-50 years in Sichuan and Chongqing,China were established using both direct and indirect sampling methods,which contributes to a better understanding of environmental exposure to metals in the general population and provides a reference for metal poisoning.For data from the same lab,the GMM-based indirect sampling method demonstrated relatively consistent performance in establishing RIs compared with the direct sampling method.

The transformation of the efficiency of Party building in public hospitals is a systematic project that requires the establishment of a collaborative mechanism characterized by the leadership of the Party committee,the drive of branch organi-zations,and the participation of all staff.A certain tertiary-level hospital in Fujian has broken free from the path-dependence of the traditional hierarchical Party building model.Based on the"goose formation"pattern,it has optimized the three-level em-powerment governance system of"head goose leading the way,strong goose consolidating the chain,and group goose collabora-ting",which provides an effective path for the transformation of Party building efficiency into governance efficiency and offers a paradigm reference for the innovation of the modern governance system led by Party building in public hospitals.

The transformation of the efficiency of Party building in public hospitals is a systematic project that requires the establishment of a collaborative mechanism characterized by the leadership of the Party committee,the drive of branch organi-zations,and the participation of all staff.A certain tertiary-level hospital in Fujian has broken free from the path-dependence of the traditional hierarchical Party building model.Based on the"goose formation"pattern,it has optimized the three-level em-powerment governance system of"head goose leading the way,strong goose consolidating the chain,and group goose collabora-ting",which provides an effective path for the transformation of Party building efficiency into governance efficiency and offers a paradigm reference for the innovation of the modern governance system led by Party building in public hospitals.

Objective:To investigate the impact of frailty on post-stroke depression (PSD) in patients with acute ischemic stroke and to identify risk factors for PSD in order to construct a risk prediction model.Methods:A convenience sampling method was used to recruit a total of 450 patients with acute ischemic stroke who were treated in the Department of Neurology at the Affiliated Hospital of Jining Medical University from March 2023 to April 2024. Data were collected using the Edmonton Frail Scale, Hamilton Depression Rating Scale, Barthel Index (Activities of Daily Living, ADL), Pittsburgh Sleep Quality Index, and Morse Fall Scale. Binary logistic regression analysis was performed to explore the impact of frailty on PSD and to identify other risk factors. Based on the results, a predictive model was developed.Results:A total of 450 questionnaires were distributed, with 412 valid responses returned, yielding a valid response rate of 91.56%. The incidence of PSD among the 412 patients was 45.63% (188/412). Binary Logistic regression analysis showed that frailty, sleep disturbance, C-reactive protein (CRP), and ADL score were the influencing factors for PSD in patients with acute ischemic stroke ( P<0.05). These factors were incorporated into the predictive model, and a risk nomogram was constructed. The area under the curve of the model was 0.764 [95% CI (0.716, 0.811) ], indicating good discriminative ability. Internal validation of the nomogram using the Hosmer-Lemeshow goodness-of-fit test showed χ 2=5.883, P=0.66 ( P>0.05), suggesting good calibration of the model. Conclusions:Frailty increases the risk of post-stroke depression in patients with acute ischemic stroke. Sleep disturbance, CRP level, and ADL score are important screening indicators for PSD risk. Targeted assessment and early intervention are recommended to reduce the likelihood of PSD.

Objective:To investigate the impact of frailty on post-stroke depression (PSD) in patients with acute ischemic stroke and to identify risk factors for PSD in order to construct a risk prediction model.Methods:A convenience sampling method was used to recruit a total of 450 patients with acute ischemic stroke who were treated in the Department of Neurology at the Affiliated Hospital of Jining Medical University from March 2023 to April 2024. Data were collected using the Edmonton Frail Scale, Hamilton Depression Rating Scale, Barthel Index (Activities of Daily Living, ADL), Pittsburgh Sleep Quality Index, and Morse Fall Scale. Binary logistic regression analysis was performed to explore the impact of frailty on PSD and to identify other risk factors. Based on the results, a predictive model was developed.Results:A total of 450 questionnaires were distributed, with 412 valid responses returned, yielding a valid response rate of 91.56%. The incidence of PSD among the 412 patients was 45.63% (188/412). Binary Logistic regression analysis showed that frailty, sleep disturbance, C-reactive protein (CRP), and ADL score were the influencing factors for PSD in patients with acute ischemic stroke ( P<0.05). These factors were incorporated into the predictive model, and a risk nomogram was constructed. The area under the curve of the model was 0.764 [95% CI (0.716, 0.811) ], indicating good discriminative ability. Internal validation of the nomogram using the Hosmer-Lemeshow goodness-of-fit test showed χ 2=5.883, P=0.66 ( P>0.05), suggesting good calibration of the model. Conclusions:Frailty increases the risk of post-stroke depression in patients with acute ischemic stroke. Sleep disturbance, CRP level, and ADL score are important screening indicators for PSD risk. Targeted assessment and early intervention are recommended to reduce the likelihood of PSD.

Objective:To explore the diagnostic value of whole blood cell parameters logistic regression model for radiation injury on radiation workers by comparing the differences of whole blood cell parameters between occupational radiation injury population and occupational health examination population.Methods:In February 2023, 184 radiation workers who received occupational health examinations in our hospital and occurrenced chromosome aberration from July 2021 to July 2022 were retrospectively selected as the radiation injury group. And other 184 radiation workers encountered in the same period without chromosome aberration occurrence were selected as the control group. Collected whole blood cell parameters from two groups of research subjects, conducted comparative analysis, constructed a logistic regression model, and evaluated the diagnostic value of the logistic regression model for radiation injury on radiation workers by receiver operating characteristic curve (ROC) and area under curve (AUC) . In addition, with the same standard, 60 radiation workers with chromosome aberration and 60 radiation workers without chromosome aberration from August 2022 to January 2023 were included in the validation queue to validate the logistic regression model.Results:Neu_X, Neu_Y, Neu_Z, Lym_X, Lym_Y, Lym_Z, Mon_X, Mon_Y, Mon_Z, Micro, MCHC in the radiation injury group were significantly higher than those in the control group, and the difference was statistically significant ( P<0.05) . And MCV and Macro in the radiation injury group were lower than those in the control group, and the difference was statistically significant ( P<0.05) . Moreover, logistic regression analysis showed that Lym_X, Lym_Y, Lym_Z, MCHC, Micro were all independent risk factors for diagnosing radiation injury on radiation workers ( OR=1.08、1.02、0.99、1.06、51.32, P<0.05) . ROC curve analysis showed that the AUC, sensitivity, specificity, and accuracy of the logistic regression model based by Lym_X, Lym_Y, Lym_Z, MCHC and Micro in diagnosing radiation injury on radiation workers were 0.80, 85.9%, 65.8% and 75.9% respectively. The validation queue verified the logistic regression model and the AUC, sensitivity, specificity, and accuracy of the logistic regression model were 0.80, 81.7%, 71.7% and 76.7% respectively, the model fitted well. Conclusion:Radiation damage can cause changes in multiple whole blood cell parameters of radiation workers. The logistic regression model based by Lym_X, Lym_Y, Lym_Z, MCHC and Micro showed good diagnosis ability and can be used for the screening of radiation injury on radiation workers.

Objective:To explore the diagnostic value of whole blood cell parameters logistic regression model for radiation injury on radiation workers by comparing the differences of whole blood cell parameters between occupational radiation injury population and occupational health examination population.Methods:In February 2023, 184 radiation workers who received occupational health examinations in our hospital and occurrenced chromosome aberration from July 2021 to July 2022 were retrospectively selected as the radiation injury group. And other 184 radiation workers encountered in the same period without chromosome aberration occurrence were selected as the control group. Collected whole blood cell parameters from two groups of research subjects, conducted comparative analysis, constructed a logistic regression model, and evaluated the diagnostic value of the logistic regression model for radiation injury on radiation workers by receiver operating characteristic curve (ROC) and area under curve (AUC) . In addition, with the same standard, 60 radiation workers with chromosome aberration and 60 radiation workers without chromosome aberration from August 2022 to January 2023 were included in the validation queue to validate the logistic regression model.Results:Neu_X, Neu_Y, Neu_Z, Lym_X, Lym_Y, Lym_Z, Mon_X, Mon_Y, Mon_Z, Micro, MCHC in the radiation injury group were significantly higher than those in the control group, and the difference was statistically significant ( P<0.05) . And MCV and Macro in the radiation injury group were lower than those in the control group, and the difference was statistically significant ( P<0.05) . Moreover, logistic regression analysis showed that Lym_X, Lym_Y, Lym_Z, MCHC, Micro were all independent risk factors for diagnosing radiation injury on radiation workers ( OR=1.08、1.02、0.99、1.06、51.32, P<0.05) . ROC curve analysis showed that the AUC, sensitivity, specificity, and accuracy of the logistic regression model based by Lym_X, Lym_Y, Lym_Z, MCHC and Micro in diagnosing radiation injury on radiation workers were 0.80, 85.9%, 65.8% and 75.9% respectively. The validation queue verified the logistic regression model and the AUC, sensitivity, specificity, and accuracy of the logistic regression model were 0.80, 81.7%, 71.7% and 76.7% respectively, the model fitted well. Conclusion:Radiation damage can cause changes in multiple whole blood cell parameters of radiation workers. The logistic regression model based by Lym_X, Lym_Y, Lym_Z, MCHC and Micro showed good diagnosis ability and can be used for the screening of radiation injury on radiation workers.

Objective To analyze the correlation of interferon-induced protein with tetratricopeptide repeats 1(IFIT1)with immune infiltration and prognosis of ovarian cancer(OC).Methods GEO database was employed to select the tumor immune related genes,and Kaplan-Meier and Prognoscan databases were used to identify the genes significantly associated with OC prognosis.The differential expression of IFIT1 between OC tissue and normal tissue were confirmed with GEPIA,Human Protein Atlas,and Timer databases.The expression level of IFIT1 in OC tissues with different grades and stages were analyzed in the UALCAN database.In addition,based on David database,GO enrichment analysis was used to analyze the interacting genes and proteins of IFIT1 in the String and Genemania databases.Timer and Tisidb databases verified the correlation between IFIT1 and immune cells mutually.Finally,after IFIT1 knockdown xenograft model was constructed based on lentiviral vector of IFIT1 shRNA,the tumor growth was observed in the transplanted nude mice,and infiltration of neutrophils was observed with immunohistochemical assay.Results FIT1,a tumor immune gene,selected from the GEO database,Kaplan-Meier and Prognoscan databases,was negatively correlated with the OC prognosis.GEPIA,Human Protein Atlas,Timer database,and UALCAN database indicated that the expression level of IFIT1 was significantly higher in the OC tissues than the normal ovarian tissues,and had no obvious correlation with tumor stage and grade.Analysis in String,Genemania,and David database found the interaction genes and proteins of IFIT1 were enriched in activation of 2'-5'oligonucleotide synthase,virus defense,and innate immunity,and other processes.The Timer database presented that IFIT1 was positively correlated with the infiltration of CD8+T cells,B cells,dendritic cells,neutrophils,and macrophage in OC,with neutrophils having the most significant correlation.Tisidb and GSCA also confirmed the positive correlation between IFIT1 and neutrophil infiltration in OC(P＜0.05).RT-qPCR and Western blotting confirmed that IFIT1 knockdown resulted in suppressed tumor growth in OC cells xenograft nude mice(P＜0.05)and reduced neutrophil infiltration in the xenograft tissues.Conclusion IFIT1 may influence the malignant progression of OC by promoting neutrophil infiltration.

Objective To explore the risk factors for developing chronic pulmonary heart disease in patients with pneumoconiosis.Methods The medical records of pneumoconiosis patients admitted to an occupational disease hospital in Sichuan Province between January 2012 and November 2021 were collected.Kaplan-Meier(K-M)method,or product-limit method,was used to plot the incidence curves of pulmonary heart disease in the pneumoconiosis patients.Cox proportional hazard regression model was used to analyze the influencing factors associated with chronic pulmonary heart disease in patients with pneumoconiosis.Results A total of 885 pneumoconiosis patients were included in this study.The follow-up time was 12 to 115 months and the median follow-up time was 43 months.A total of 138 patients developed chronic pulmonary heart disease and the incidence density of pulmonary heart disease was 38.50/1000 person-years.Multivariate Cox proportional hazard regression analysis showed that the influencing factors of pneumoconiosis inpatients developing chronic pulmonary heart disease included the following,being 50 and older(hazard ratio[HR]=1.85,95%confidence interval[CI]:1.25-2.74),stage Ⅲ pneumoconiosis(HR=2.43,95%CI:1.48-4.01),resting heart rate≥100 beats/min(HR=2.62,95%CI:1.63-4.21),the complication of chronic obstructive pulmonary disease(COPD)(HR=4.52,95%CI:2.12-9.63),underweight(HR=2.40,95%CI:1.48-3.87),overweight and obesity(HR=0.54,95%CI:0.34-0.86),and triacylglycerol(TG)(HR=0.69,95%CI:0.49-0.99).Conclusion Old age,stage Ⅲ pneumoconiosis,high resting heart rate,low BMI,and the complication of COPD are risk factors for chronic pulmonary heart disease in pneumoconiosis patients,while overweight and obesity and TG are protective factors.Early identification of the risk factors and the adoption of the corresponding prevention measures are the key to preventing chronic pulmonary heart disease in patients with pneumoconiosis.

Objective:To screen risk factors for carotid plaque vulnerability in patients with ischemic stroke and construct a risk prediction model.Methods:From November 2019 to January 2021, a total of 164 patients with ischemic stroke hospitalized in the Neurology Department of the Affiliated Hospital of Jining Medical University were selected as the study subjects by convenience sampling method. Color doppler ultrasound was used to measure carotid plaques in patients with ischemic stroke to determine whether they were vulnerable plaques. The patients were surveyed using the General Information Questionnaire and the Type D Personality Scale. Binary Logistic regression analysis was used to explore the risk factors of carotid plaque vulnerability in ischemic stroke patients, and based on this, a risk prediction model for carotid plaque vulnerability in ischemic stroke patients was constructed.Results:A total of 87 patients with ischemic stroke had vulnerable carotid plaques. The results of binary Logistic regression analysis showed that age ( OR=1.136, 95% CI: 1.052-1.226), total score of Type D Personality Scale ( OR=1.170, 95% CI: 1.043-1.312), smoking history ( OR=3.058, 95% CI: 1.054-8.875), homocysteine ( OR=1.400, 95% CI: 1.179-1.664), triglycerides ( OR=2.356, 95% CI: 1.534-3.619) were risk factors for carotid plaque vulnerability in stroke patients ( P<0.05). The results of risk prediction model based on risk factors show that, the area under the receiver operating characteristic of the subjects was 0.935, indicating good clinical predictive ability. Conclusions:Age, total score of Type D Personality Scale, smoking history, homocysteine and triglyceride are risk factors of carotid plaque vulnerability in stroke patients. The risk prediction model can early identify and screen high-risk factors for carotid plaque vulnerability in ischemic stroke patients, and is worthy of clinical promotion and practice.