OBJECTIVE To predict and verify the mechanism of Jiawei qifang weitong granule in ameliorating precancerous lesions of gastric cancer （PLGC）. METHODS Transcriptomic data of PLGC-related were obtained from the GEO database to screen differentially expressed genes and conduct functional enrichment analysis. Targets related to gastric mucosal injury repair were screened via the GeneCards database. The active ingredient targets of Jiawei qifang weitong granule were predicted using the TCMSP and other databases. The intersection of differentially expressed genes， gastric mucosal repair targets and active ingredient targets was extracted. A protein-protein interaction network was constructed based on the STRING database， and the top 6 hub target genes with the highest connectivity were screened. A PLGC rat model was established by combining 1-methyl-3-nitro-1-nitrosoguanidine with alternating fasting and full feeding. Model rats were divided into model group， weifuchun group （positive control， 0.40 g/kg）， low-， medium- and high-dose Jiawei qifang weitong granule groups （9.73， 19.44， 38.90 g/kg）， with 10 rats in each group. Another 10 unmodeled rats were set as control group. Rats in each group were intragastrically administered corresponding liquid medicine or normal saline once a day for 30 consecutive days. After the last administration， pathological morphological changes of rat gastric tissues were observed， and the mRNA expression levels of hub target genes as well as partial protein expression levels in gastric tissues were detected. RESULTS Transcriptomics and network pharmacology analyses revealed that the top 6 hub target genes ranked by connectivity included MMP9 （matrix metalloproteinase 9）， BCL2（B-cell lymphoma 2）， IL10（interleukin 10），ICAM1（intercellular adhesion molecule 1）， PTGS2 （prostaglandin-endoperoxide synthase 2）， and HIF1A （hypoxia-inducible factor 1α subunit）. Animal experiments showed that compared with the model group， gastric mucosal pathological injury was significantly alleviated in medium- and high-dose Jiawei qifang weitong granule groups and weifuchun group. The pathological injury score of gastric mucosa， the mRNA expression levels of MMP9， PTGS2， ICAM1， BCL2 and HIF1A， as well as the protein expression levels of PTGS2 and BCL2 in gastric tissues were significantly decreased （P＜0.05）， while the mRNA expression level of IL10 was significantly increased （P＜0.05）. CONCLUSIONS Jiawei qifang weitong granule may ameliorate PLGC by targeted down-regulating the mRNA expression of MMP9， PTGS2， ICAM1， BCL2 and HIF1A， up-regulating IL10 mRNA expression， and regulating the imbalance between gastric mucosal inflammatory response and injury repair.

Hospital culture is the sum of common values， codes of conduct， and working methods formed by internal employees within the hospital， and it is the spiritual pillar and core of cohesion of the hospital. Party-building leadership plays an important role in promoting hospital culture construction， including strengthening values guidance， enhancing team cohesion， facilitating management system innovation， and shaping social image and brand value. By analyzing the effectiveness of a series of Party-building activities carried out by Xi’an No. 9 Hospital in recent years， this paper explored the effect and significance of Party-building leadership in promoting hospital culture construction in the new era， as well as proposed guiding strategies for strengthening Party-building work in promoting hospital culture construction in the new era， so as to promote high-quality development of the hospital.

To understand the epidemiological and clinical features of patients with non-tuberculous mycobacteria(NTM)lung disease in a hospital for infectious diseases in Xinjiang,and to provide basis for prevention and control of NTM in Xinjiang.The strain distribution,epidemiological features and clinical features of 78 patients with NTM lung disease in the Sixth People′s Hospital of Xinji-ang Uygur Autonomous Region were analysed from June 2021 to June 2024,and a comparative analysis of the clinical features of 156 patients with pulmonary tuberculosis in this hospital during the same period was performed.Among 78 patients with NTM lung disease,the bacteria identified by molecular biology accounted for the top three cases:24 cases of Mycobacterium avium intracellulare complex,16 cases of Mycobacterium Kansaii and 11 cases of Mycobacterium Gordonae.There was no statistically significant difference in gender(χ2=0.009),age(χ2=2.670),smoking history(χ2=0.064),and BMI(χ2=0.896)between the NTM lung disease group and the pulmonary tuberculosis group(P>0.05).However,there were statistically significant differences in the combined bronchiectasis(χ2=19.068),immune-related indicators CD4(Z=-3.498)and CD3(Z=-3.187),and chest CT cavities on imaging(χ2=9.308)be-tween the two groups(P<0.05).There was no statistically significant difference in clinical symptoms such as cough(χ2=0.188)and expectoration(χ2=0.044)between the two groups(P>0.05).The common underlying diseases of NTM lung disease were diabetes mellitus(23.08%),hypertension(21.79%),bronchiectasis(20.51%)and others.The common clinical symptoms of NTM lung disease include cough,sputum,fatigue,poor appetite and others.The common manifestations of chest CT in NTM lung disease were Patchy cord shadows(62.82%),nodule(51.28%),pleural thickening(46.15%),calcification(41.03%)and others.Multivariate Logistic regression analysis showed that bronchiectasis(OR=8.019)is risk factor for NTM lung disease.The dominant strains of NTM in this study were My-cobacterium avium intracellulare complex,Mycobacterium kansasii and Mycobacterium Gordonae.NTM lung disease and pulmonarytuber-culosis have similar clinical manifestations and are difficult to distinguish,especially for patients with bronchiectasis,it is necessary to actively investigate NTM lung disease,provide basis for early diagnosis and treatment of NTM lung disease,and gradually form a system-atic and standardized NTM lung disease diagnosis and treatment system according to local conditions.

AIM:To investigate the impact of recombinant human CC16 protein(rhCC16)on cigarette smoke extract(CSE)-induced senescence-associated secretory phenotype(SASP)in human bronchial epithelial cells(HBECs)and in the lung tissues of chronic obstructive pulmonary disease(COPD)mice,and to explore the underlying mechanism.METHODS:HBECs were induced into cellular senescence using 5%CSE.The senescent HBECs were treated with 250 ng/mL rhCC16,and the levels of reactive oxygen species(ROS)were assessed using the 2',7'-dichlorodihydrofluorescein diacetate(DCFH-DA)method.The levels of trimethylated histone H3 at lysine 9(H3K9me3),a marker of senescence-associated heterochromatic foci(SAHF),were detected using a Western blot assay.RT-qPCR and ELISA were utilized to measure the mRNA expression and protein levels of SASP components including interleukin-1 beta(IL-1β),IL-6,IL-8,chemokine(C-X-C motif)ligand-1(CXCL-1),matrix metalloproteinase 1(MMP1)and MMP3.Passive smoking was con-ducted for six months to induce COPD in mice.RhCC16(2.5 μg/g body weight)or an equal volume of PBS(20 μL)was intranasally administered from the 16th week of smoking in the COPD+rhCC16 group or COPD+PBS group,respectively,with administration 2 hours before smoking.ROS levels in lung tissue cells were investigated using DCFH-DA staining.H3K9me3 levels in lung tissues were tested using Western blot assay.RT-qPCR and ELISA were performed to examine the mRNA expression and protein levels of IL-1β,IL-6,IL-8,CXCL-1,MMP1 and MMP3.RESULTS:DCFH-DA staining results showed that CSE stimulation increased ROS levels in HBECs,while rhCC16 treatment reduced them(P＜0.01).Western blot results indicated that CSE stimulation elevated H3K9me3 levels in HBECs,which were decreased with rhCC16 treatment(P＜0.01).RT-qPCR and ELISA assays demonstrated that CSE stimulation upregulated the mRNA and protein levels of IL-1β,IL-6,IL-8,CXCL-1,MMP1 and MMP3 in HBECs,which were reduced with rhCC16 admin-istration(P＜0.05).DCFH-DA staining results showed an increase in ROS levels in the lung tissues of COPD mice,which were decreased with rhCC16 administration(P＜0.01).Western blot data revealed an increase in H3K9me3 levels in the lung tissues of COPD mice,which were reduced with rhCC16 treatment(P＜0.01).RT-qPCR and ELISA assays demon-strated an upregulation of the mRNA and protein levels of IL-1β,IL-6,IL-8,CXCL-1,MMP1 and MMP3 in the lung tis-sues of COPD mice,which were reduced with rhCC16 treatment(P＜0.05).No statistically significant differences were ob-served in the above-mentioned indicators between the lung tissues of COPD and COPD+PBS mice(P＞0.05).CONCLU-SION:rhCC16 can effectively inhibit CSE-induced SASP in HBECs and in the lung tissues of COPD mice,with its under-lying mechanism potentially related to the inhibition of the ROS-H3K9me3 signaling pathway.

Objective:To analyze the prospective associations between liver biomarkers and mortality among Chinese middle-aged and elderly populations and to evaluate the mortality risk predictive value.Methods:A total of 22 758 participants from the 3 rd resurvey of the China Kadoorie Biobank were included. Cox proportional hazard models were used to analyze the prospective associations of 5 liver biomarkers with mortality. These liver biomarkers included two liver imaging biomarkers (liver fat attenuation parameter, liver stiffness measurement) and three serum liver enzyme biomarkers [gamma-glutamyl transferase (GGT), ALT, and AST]. Restricted cubic spline was used to assess the nonlinear associations between biomarkers and mortality. The area used the receiver operating characteristic curve (AUC) to evaluate the predictive ability of the models after incorporating liver biomarkers into traditional prediction models for mortality. Results:The mean age of the participants was (65.2±9.1) years, with a median follow-up of 1.5 years, during which 307 deaths occurred. Compared to individuals without hepatic steatosis, those with severe hepatic steatosis had a 79% higher risk of mortality, with a HR of 1.79 (95% CI: 1.06-3.03). Compared to individuals without hepatic fibrosis, those with advanced fibrosis and cirrhosis had higher mortality risks of 48% and 91%, respectively (both P<0.05). For each standard deviation increase in GGT, the mortality risk increased by 10% ( HR=1.10, 95% CI: 1.05-1.15), with the positive association plateauing at higher GGT levels. AST exhibited a U-shaped association with mortality risk. The AUC of the prediction model adding liver biomarkers into traditional prediction factors was 0.718 (95% CI: 0.679-0.757), with an increase of 0.030 ( P<0.001) compared with the traditional model. Conclusions:Severe hepatic steatosis, higher levels of hepatic fibrosis, and elevated GGT levels are significantly associated with higher mortality risk. AST shows a U-shaped nonlinear association with mortality risk. Incorporating liver biomarkers into traditional risk prediction models enhance the ability to predict mortality.

Objective:To investigate the prospective associations between plasma metabolites and the risks of all-cause and cause-specific mortality among Chinese adults.Methods:This study analyzed plasma metabolomics data from 2 183 healthy adults in the China Kadoorie Biobank (CKB), measured using targeted mass spectrometry. Cox proportional hazards regression models were used to examine the associations between 630 metabolites and the risk of all-cause mortality. Cause-specific hazard regression models evaluated the associations between metabolites and cardiovascular disease (CVD) risks, cancer, and other-cause mortality. Stepwise regression was used to identify key metabolites independently associated with all-cause mortality, and the area under the receiver operating characteristic curve (AUC) was calculated to assess the improvement in predictive performance when these metabolites were added to traditional risk prediction models.Results:The mean age of the participants was (53.2±9.8) years, 65.1% of whom were female. During a median follow-up of 14.5 years, 231 deaths occurred. A total of 44 metabolites were significantly associated with the risk of all-cause mortality [false discovery rate (FDR)-adjusted P<0.05], primarily including triglycerides, ceramides, and amino acids. Additionally, 29 and 15 metabolites were found to be associated with cancer and other-cause mortality, respectively, but no metabolites were significantly associated with CVD mortality after FDR corrections. Adding 14 metabolites independently associated with all-cause mortality into the traditional prediction model significantly improved its predictive performance. Specifically, incorporating metabolites into the traditional model, which already included laboratory biomarkers, increased the AUC to 0.798 (95% CI: 0.755-0.843), an improvement of 0.088 compared to the traditional model ( P<0.001). Conclusions:Multiple metabolites are significantly associated with mortality risk and can substantially improve the accuracy of mortality risk prediction models. These findings provide new insights into the physiological mechanisms of aging and offer valuable clues for personalized health risk assessment.

Objective To explore the association between plasma fibrinogen(FBG)levels and the risk of in-hospital mortality among patients with septic shock.Methods The clinical data of 563 patients diagnosed with septic shock in the Intensive Care Unit(ICU)of Shenzhen Second People's Hospital from August 1,2018,to December 31,2020,were collected.Patient demographic information,basic vital signs,and blood routine and biochemical indices upon admission were gathered.Moreover,the Acute Physiology and Chronic Health Evaluation Ⅱ(APACHEⅡ)scores were calculated.Binary logistic regression analysis was conducted to explore the correlation between plasma fibrinogen levels and in-hospital mortality in patients with septic shock.Additionally,a generalized additive model(GAM)and smoothed curve fitting were employed to investigate the nonlinear relationship between plasma fibrinogen and in-hospital mortality.Receiver operating characteristic(ROC)curves were constructed for FBG and APACHEⅡ scores to predict in-hospital mortality in septic shock patients.The area under the curve(AUC)was computed to compare the predictive efficacies of the two.Furthermore,a segmented linear regression model was utilized for quantification.Results Binary logistic regression analysis demonstrated a significant negative correlation between plasma fibrinogen levels and in-hospital mortality among patients with septic shock(P<0.05).GAM modeling and smoothed curve fitting disclosed a nonlinear association between plasma fibrinogen levels and in-hospital mortality,with an inflection point at 5.54 g/L.The segmented linear regression model indicated that,to the left of the inflection point(FBG≤5.54 g/L),for every 1 g/L decrease in plasma fibrinogen,the risk of death increased by 24.5%(OR=0.755,P=0.003).Conversely,to the right of the inflection point(FBG>5.54 g/L),the relationship was not statistically significant(OR=1.049,P=0.685).The findings of the subgroup analyses indicated that the characteristics of the subgroups did not alter the relationship between blood fibrinogen levels and in-hospital mortality.Conclusion There is a nonlinear relationship between FBG levels and in-hospital mortality in patients with septic shock,which has predictive value for evaluating the risk of in-hospital mortality in this patient cohort.

Objective:To assess the relationship between basophil levels and mortality in patients with intra-abdominal infection.Methods:Information on patients with intraperitoneal infection admitted to the intensive care unit were extracted from the MIMIC database.A time-dependent Cox regression model was used to adjust for confounders associated with 28-day mortality.Propensity score matching(PSM)was used to balance the baseline differences be-tween groups with different basophil levels,and a restricted cube chart(RCS)was used to show the relationship between basophil count and 28-day mortality in patients with intra-abdominal infection.Results:A total of 4403 patients with intra-abdominal infection were enrolled in the MIMIC database.Patients with high basophil levels have lower mortality than those with low basophil levels.There was an L-shaped curve between basophil level and 28-day mortality,with a cut-off value of 0.47×109/L.Cox regression analysis showed that basophil levels were an independent protective factor for mortal-ity in patients with intra-abdominal infection after adjusting for potential confounders(HR=0.586,95%CI:0.443-0.769).Protective factors for death at basophil levels remained after PSM adjusted for potential confounders(HR=0.628,95%CI:0.470-0.832).Conclusion:Basophil level is an independent protective factor for mortality in patients with intra-abdominal infection,and basophil levels should be dynamically monitored to better evaluate the prognosis of patients.

Objective:To analyze the prospective associations between liver biomarkers and mortality among Chinese middle-aged and elderly populations and to evaluate the mortality risk predictive value.Methods:A total of 22 758 participants from the 3 rd resurvey of the China Kadoorie Biobank were included. Cox proportional hazard models were used to analyze the prospective associations of 5 liver biomarkers with mortality. These liver biomarkers included two liver imaging biomarkers (liver fat attenuation parameter, liver stiffness measurement) and three serum liver enzyme biomarkers [gamma-glutamyl transferase (GGT), ALT, and AST]. Restricted cubic spline was used to assess the nonlinear associations between biomarkers and mortality. The area used the receiver operating characteristic curve (AUC) to evaluate the predictive ability of the models after incorporating liver biomarkers into traditional prediction models for mortality. Results:The mean age of the participants was (65.2±9.1) years, with a median follow-up of 1.5 years, during which 307 deaths occurred. Compared to individuals without hepatic steatosis, those with severe hepatic steatosis had a 79% higher risk of mortality, with a HR of 1.79 (95% CI: 1.06-3.03). Compared to individuals without hepatic fibrosis, those with advanced fibrosis and cirrhosis had higher mortality risks of 48% and 91%, respectively (both P<0.05). For each standard deviation increase in GGT, the mortality risk increased by 10% ( HR=1.10, 95% CI: 1.05-1.15), with the positive association plateauing at higher GGT levels. AST exhibited a U-shaped association with mortality risk. The AUC of the prediction model adding liver biomarkers into traditional prediction factors was 0.718 (95% CI: 0.679-0.757), with an increase of 0.030 ( P<0.001) compared with the traditional model. Conclusions:Severe hepatic steatosis, higher levels of hepatic fibrosis, and elevated GGT levels are significantly associated with higher mortality risk. AST shows a U-shaped nonlinear association with mortality risk. Incorporating liver biomarkers into traditional risk prediction models enhance the ability to predict mortality.

Objective:To investigate the prospective associations between plasma metabolites and the risks of all-cause and cause-specific mortality among Chinese adults.Methods:This study analyzed plasma metabolomics data from 2 183 healthy adults in the China Kadoorie Biobank (CKB), measured using targeted mass spectrometry. Cox proportional hazards regression models were used to examine the associations between 630 metabolites and the risk of all-cause mortality. Cause-specific hazard regression models evaluated the associations between metabolites and cardiovascular disease (CVD) risks, cancer, and other-cause mortality. Stepwise regression was used to identify key metabolites independently associated with all-cause mortality, and the area under the receiver operating characteristic curve (AUC) was calculated to assess the improvement in predictive performance when these metabolites were added to traditional risk prediction models.Results:The mean age of the participants was (53.2±9.8) years, 65.1% of whom were female. During a median follow-up of 14.5 years, 231 deaths occurred. A total of 44 metabolites were significantly associated with the risk of all-cause mortality [false discovery rate (FDR)-adjusted P<0.05], primarily including triglycerides, ceramides, and amino acids. Additionally, 29 and 15 metabolites were found to be associated with cancer and other-cause mortality, respectively, but no metabolites were significantly associated with CVD mortality after FDR corrections. Adding 14 metabolites independently associated with all-cause mortality into the traditional prediction model significantly improved its predictive performance. Specifically, incorporating metabolites into the traditional model, which already included laboratory biomarkers, increased the AUC to 0.798 (95% CI: 0.755-0.843), an improvement of 0.088 compared to the traditional model ( P<0.001). Conclusions:Multiple metabolites are significantly associated with mortality risk and can substantially improve the accuracy of mortality risk prediction models. These findings provide new insights into the physiological mechanisms of aging and offer valuable clues for personalized health risk assessment.