OBJECTIVE To investigate the effect and mechanism of Jingangteng capsules in the treatment of non-alcoholic fatty liver disease （NAFLD）. METHODS Thirty-two SD rats were randomly divided into normal group and modeling group. The modeling group was fed a high-fat diet to establish a NAFLD model. The successfully modeled rats were then randomly divided into model group， atorvastatin group[positive control， 2 mg/（kg·d）]， and Jingangteng capsules low- and high-dose groups [0.63 and 2.52 mg/（kg·d）]， with 6 rats in each group. The pathological changes of the liver were observed by hematoxylin-eosin staining and oil red O staining. Enzyme-linked immunosorbent assay was performed to determine the serum levels of triglycerides （TG）， total cholesterol （TC）， high-density lipoprotein cholesterol （HDL-C）， low-density lipoprotein cholesterol （LDL-C）， alanine transaminase （ALT）， aspartate transaminase （AST）， tumour necrosis factor-α （TNF-α）， interleukin-1β （IL-1β）， IL-6， IL-18. 16S rDNA amplicon sequencing and metabolomics techniques were applied to explore the effects of Jingangteng capsules on gut microbiota and metabolisms in NAFLD rats. Based on the E-mail：591146765@qq.com metabolomics results， Western blot analysis was performed to detect proteins related to the nuclear factor kappa-B （NF-κB）/NOD-like receptor family protein 3 （NLRP3） signaling pathway in the livers of NAFLD rats. RESULTS The experimental results showed that Jingangteng capsules could significantly reduce the serum levels of TG， TC， LDL-C， AST， ALT， TNF-α， IL-1β， IL-6， IL-18， while increased the level of HDL-C， and alleviated the hepatic cellular steatosis and inflammatory infiltration in NAFLD rats. They could regulate the gut microbiota disorders in NAFLD rats， significantly increased the relative abundance of Romboutsia and Oscillospira， and significantly decreased the relative abundance of Blautia （P＜0.05）. They also regulated metabolic disorders primarily by affecting secondary bile acid biosynthesis， fatty acid degradation， O-antigen nucleotide sugar biosynthesis， etc. Results of Western blot assay showed that they significantly reduced the phosphorylation levels of NF-κB p65 and NF-κB inhibitor α， and the protein expression levels of NLRP3， caspase-1 and ASC （P＜0.05 or P＜0.01）. CONCLUSIONS Jingangteng capsules could improve inflammation， lipid accumulation and liver injury in NAFLD rats， regulate the disorders of gut microbiota and metabolisms， and inhibit NF-κB/NLRP3 signaling pathway. Their therapeutic effects against NAFLD are mediated through the inhibition of the NF-κB/NLRP3 signaling pathway.

ObjectiveTo explore the method of optimizing the performance of traditional Chinese medicine （TCM） syndrome diagnostic models using Stacking ensemble learning. MethodsTaking the construction of TCM syndrome diagnostic model for lung cancer as an example， 2598 cases of clinical symptoms and signs from lung cancer patients in 9 hospitals were used as independent variables （i.e.， feature variables）， TCM syndrome information as dependent variables， and the clinical data were divided into training set and testing set in 8：2 ratio according to random number table method using Python 3.7 software. The stable features of TCM syndrome of lung cancer were screened using chi-square test， Spearman's correlation test， and Least Absolute Shrinkage and Selection Operator （LASSO） logistic regression analysis； nine machine learning algorithms are trained， including support vector machines （SVMs）， k-nearest neighbors （KNN） algorithm， Random Forest （RF）， Extremely Randomized Trees， Extreme Gradient Boosting （XGBoost）， Lightweight Gradient Boosting （LightGBM）， Adaptive Boosting （AdaBoost）， Gradient Boosting （GB） and the multi-layer perceptron （MLP）， to obtain 9 basic models. Four models with better performance were screened out from the above basic models and fused to form a fusion model by using the Stacking ensemble learning， and the fusion model was trained twice by the above nine machine learning algorithms and evaluated by accuracy rate， micro-average ROC curves， area under the curve （AUC）， and confusion matrix metrics， to screen the optimal diagnostic model. ResultsAfter data processing， 79 stable features and 13 TCM syndromes were obtained. In the basic model training， the comprehensive performance of RF， ExtraTrees， MLP and SVM basic models were better， so the predicted distributions of the syndromes of these four models were used as the secondary training data， and nine fusion models were obtained based on the Stacking ensemble learning （SVM， KNN， RF， ExtraTree， XGBoost， LightGBM， GB， AdaBoost， MLP）. Among them， the XGBoost fusion model performed the best， with an accuracy of 0.850 and 0.838 in the training set and test set， respectively， an overfitting difference of 0.012， and an area under the micro-average ROC curve of 0.996. All fusion models showed an improvement in accuracy and area under the micro-average ROC curve compared with the base model in the test set. ConclusionTaking the TCM syndrome information of lung cancer as an example， the XGBoost fusion model has significant advantages in improving the diagnostic performance of TCM syndrome information of lung cancer through Stacking ensemble learning. It can be seen that the advantages of Stacking ensemble learning to integrate multiple models and effectively improve the diagnostic efficiency of TCM diagnostic models， which provided a methodological reference for similar studies.

AIM:To investigate the clinical fea-tures of acute exacerbation chronic obstructive pul-monary disease(AECOPD)of complicated with type 2 diabetes mellitus(T2DM),and analyze the relat-ed clinical features and risk factors.METHODS:This was a single-center cross-sectional study.From March 2020 to January 2023,479 hospitalized pa-tients with AECOPD in the department of respirato-ry and critical care medicine,Suining Central Hospi-tal were included.There were 215 patients in AE-COPD group and 60 patients in AECOPD with T2DM group.The collected variables included demograph-ic data,complications,blood routine,infection in-dex,random blood glucose,blood gas analysis and lung function.The adoption rate and constituent ra-tio of the basic description classification data were expressed as mean standard deviation for the nor-mal distribution measurement data and median in-terquartile range for the skew distribution measure-ment data.T-test was used for normal distribution and non-parameter test was used for non-normal distribution.The categorical variables were tested by chi-square test.Rank sum test was used for rank variable data.Binary logistic regression model was used to investigate the independent factors associ-ated with T2DM in patients with AECOPD.Finally,the results of logistic regression were verified and visualized by nomogram,validation curve,ROC curve and DCA curve.P＜0.05 was a significant sta-tistical difference.RESULTS:Univariate analysis showed that there were significant differences in body mass index(BMI),essential hypertension,cor-onary heart disease,atrial fibrillation(AF),pulmo-nary function(GOLD stage),blood neutrophil(NS),blood lymphocyte(LYM),arterial blood gas PaCO2,Alanine transaminase(ALT)and random blood glu-cose(RBG)between the two groups(P＜0.05).The binary logistic regression model(C-index=0.847)was constructed with the above 10 variables,the results showed that BMI(OR=1.309),Af(OR=8.188),LYM counts(OR=0.474),PaCO2(OR=1.082)and RBG(OR=1.434)were independently associat-ed with type 2 diabetes in patients with AECOPD(all P＞0.05).The results of logistic regression were verified and visualized by Nomogram and its-associ-ated ccurves.The MAE and AUC curves were 0.021 and 0.847 respectively,indicating that the model had good prediction consistency and accuracy.The DCA curve showed that Nomogram's risk threshold ranged from 0.01 to 0.99,suggesting that nomo-gram's model had better clinical predictive value.CONCLUSION:Our results showed that increased BMI,PaCO2 and random glucose,decreased blood lymphocyte,and atrial fibrillation is an indepen-dent clinical feature of AECOPD with T2DM.These results suggest that the immune function of pa-tients with AECOPD and T2DM are more severely impaired and more likely to be accompanied by atrial fibrillation,which is a potential cause of poor prognosis in these patients.Meanwhile,this conclu-sion needs to be further verified in multicenter study with large sample size.

With the continuous development of information technology,smart financial systems has gradually become an important tool for financial management in public hospitals.As an important component of the smart financial system,electronic accounting record management is of great practical significance in adapting to the trend of"green and carbon free"economic development,improving the efficiency of financial management in public hospitals,and promoting high-quality development of hospitals.Henan Provincial People's Hospital is taken as an example(hereinafter referred to as the sample hospital)to deeply interpret national policies,explore the difficulties in electronic accounting file management,and combine with the specific situation of the hospital.Guided by the overall strategic goals of the hospital,starting from the top-level design integration,it creates a set of replicable and promotable electronic accounting voucher electronic reimbursement,entry,and archiving progress,so as to provide theoretical and practical experience for the transformation and upgrading of electronic record management in public hospitals,and provide a new template for the development and reform of economic management in public hospitals in China.

AIM: To investigate the clinical features of acute exacerbation chronic obstructive pulmonary disease (AECOPD) of complicated with type 2 diabetes mellitus (T2DM), and analyze the related clinical features and risk factors. METHODS: This was a single-center cross-sectional study. From March 2020 to January 2023, 479 hospitalized patients with AECOPD in the department of respiratory and critical care medicine, Suining Central Hospital were included. There were 215 patients in AECOPD group and 60 patients in AECOPD with T2DM group. The collected variables included demographic data, complications, blood routine, infection index, random blood glucose, blood gas analysis and lung function. The adoption rate and constituent ratio of the basic description classification data were expressed as mean standard deviation for the normal distribution measurement data and median interquartile range for the skew distribution measurement data. T-test was used for normal distribution and non - parameter test was used for non-normal distribution. The categorical variables were tested by chi-square test. Rank sum test was used for rank variable data. Binary logistic regression model was used to investigate the independent factors associated with T2DM in patients with AECOPD. Finally, the results of logistic regression were verified and visualized by nomogram, validation curve, ROC curve and DCA curve. P<0.05 was a significant statistical difference. RESULTS: Univariate analysis showed that there were significant differences in body mass index (BMI), essential hypertension, coronary heart disease, atrial fibrillation (AF), pulmonary function (GOLD stage), blood neutrophil (NS), blood lymphocyte (LYM), arterial blood gas PaCO2, Alanine transaminase (ALT) and random blood glucose (RBG) between the two groups (P<0.05). The binary logistic regression model (C-index=0.847) was constructed with the above 10 variables, the results showed that BMI (OR=1.309), Af (OR= 8.188), LYM counts (OR=0.474), PaCO2 (OR=1.082) and RBG (OR=1.434) were independently associated with type 2 diabetes in patients with AECOPD (all P>0.05). The results of logistic regression were verified and visualized by Nomogram and its-associated ccurves. The MAE and AUC curves were 0.021 and 0.847 respectively, indicating that the model had good prediction consistency and accuracy. The DCA curve showed that Nomogram's risk threshold ranged from 0.01 to 0.99, suggesting that nomogram's model had better clinical predictive value. CONCLUSION: Our results showed that increased BMI, PaCO2 and random glucose, decreased blood lymphocyte, and atrial fibrillation is an independent clinical feature of AECOPD with T2DM. These results suggest that the immune function of patients with AECOPD and T2DM are more severely impaired and more likely to be accompanied by atrial fibrillation, which is a potential cause of poor prognosis in these patients. Meanwhile, this conclusion needs to be further verified in multicenter study with large sample size.

Objective To investigate the effects of different culture conditions(RPMI-1640,DMEM and DMEM/F12 medium)on the passage of MPM cells isolated from the tissues of Malignant pleural mesothelioma(MPM),and to study the effects of CDKN2B on the proliferation,invasion and apoptosis of MPM cells.Methods MPM cells were isolated from MPM tissues and cultured in RPMI-1640,DMEM and DMEM/F12 medium,respectively.Cell proliferation was examined by CCK-8,and the nuclei and chromosomes were observed by Wright-Giemsa staining.Fluorescence intensities of Calretinin,CD141,CK5,EMA and WT-1 were conducted by immunofluorescence assay.The mRNA and protein expression of CDKN2B were detected by RT-qPCR and Western blot,respectively.Transwell was used to detect cell invasion and flow cytometry was used to detect cell apoptosis.Results The established MPM cells showed good viability when passaged to the 10th generation in RPMI-1640,DMEM and DMEM/F12 cultures,and the MPM markers Calretinin,CD141,CK5,EMA and WT-1 were all expressed in the cells.The viability of MPM cells in RPMI-1640 culture medium was relatively stable.CDKN2B was downregulated in MPM cells(P<0.05),and overexpression of CDKN2B significantly suppressed the proliferation(P<0.05),invasion(P<0.05)and epithelial interstitial transformation of MPM cells(P<0.01),and promoted the apoptosis(P<0.01).Conclusion The established MPM cells were stably passaged in RPMI-1640 culture medium,and CDKN2B may be a potential target for the diagnosis and treatment of MPM.

Objective:To explore the efficacy and safety of cryopreservation-free integrated autologous hematopoietic stem cell transplantation (HSCT) model for patients with multiple myeloma.Methods:A total of 96 patients with newly diagnosed multiple myeloma (NDMM) between July 31, 2020, and December 31, 2022, were retrospectively analyzed, of which 41 patients in the observation group received integrated non-cryopreserved transplantation mode. After hematopoietic stem cells were mobilized and collected, melphalan was started immediately for pre-transplant conditioning, and non-cryopreserved grafts from the medical blood transfusion refrigerator were directly injected intravenously into the patient within 24-48 h after the melphalan conditioning. The control group consisted of 55 patients who received traditional transplantation mode. After hematopoietic stem cells were collected, stem cell cryopreservation was performed in liquid nitrogen, and then the transplant plans were started at the right time. All patients received mobilization of autologous hematopoietic stem cells using the G-CSF combined with the plerixafor.Results:① A total of 34 patients (82.9% ) with VGPR plus CR in the observation group were significantly higher than 33 patients (60.0% ) in the control group ( P=0.016). ②Compared with the control group, the incidence of grade 1 oral mucosal inflammation was higher in the observation group ( P<0.001) ; however, the incidence of grades 2 and 3 oral mucosal inflammation was lower ( P=0.004, P=0.048), and neither group experienced grade 4 or above oral mucosal inflammation. The incidence of grade 1 diarrhea was higher in the observation group ( P=0.002), whereas the incidence of grade 3 diarrhea was lower ( P=0.007). No statistically significant difference was observed in the incidence of grade 4 diarrhea ( P=0.506), and neither group experienced grade 5 diarrhea. ③ The incidence of bacterial infection in the observation group was lower than that in the control group (34.1% vs 65.5%, P=0.002), whereas no statistically significant difference was observed in the incidence of fungal infection (29.3% vs 31.4%, P=0.863) and viral infection (4.88% vs 3.64%, P=0.831). ④No statistically significant difference was observed in the implantation time of granulocytes and platelets between the observation and control groups [10 (8-20) days vs 11 (8-17) days, P=0.501; 13 (10-21) days vs 15 (10-20) days, P=0.245]. ⑤ All patients did not receive lenalidomide treatment 100 days post-transplantation. At 30 days post-transplantation, the CTL, NK, and Th cell counts in the observation group were lower than those in the control group ( P<0.001, P=0.002, P=0.049), and the NKT cell counts were higher than those in the control group ( P=0.024). At 100 days post-transplantation, the CTL, NKT, and Th cell counts in the observation group were higher than those in the control group ( P=0.025, P=0.011, P=0.007), and no statistically significant difference in NK cell counts was observed between the two groups ( P=0.396). ⑥ The median follow-up was 18 (4-33) months. The overall 2-year survival rates of the observation and control groups post-transplantation were 91.5% and 78.2%, respectively ( P=0.337). The recurrence-free survival rates were 85.3% and 77.6%, respectively ( P=0.386), and the cumulative recurrence rates were 9.8% and 16.9%, respectively ( P=0.373) . Conclusion:In NDMM, the cryopreservation-free integrated autologous HSCT model can achieve similar therapeutic effects as traditional transplantation models, with lower rates of severe mucosal inflammation and infection compared with traditional transplantation models.

Objective:To assess the impact of exposure to particulate matter with aerodynamic diameter ≤2.5 μm(PM2.5)on non-accidental mortality under different apparent temperature levels and to further explore the modification effect of apparent temperature.Methods:This study used time-series design.Tianjin and Ningbo from China,Bangkok and Chiang Mai from Thailand were selected as the re-search sites,and the apparent temperature was applied as the exposure index.Through the quantitative estimation of the threshold temperature,the corresponding pollutant concentration was divided into high and low levels,and the generalized Poisson additive model was used to evaluate the association between PM2.5 exposure and non-accidental death of residents at different temperature levels.Results:The ave-rage concentrations of PM2.5 in Tianjin,Ningbo,Bangkok,and Chiang Mai during the study period were(73.6±35.6),(48.0±32.1),(33.5±28.4)and(32.6±28.6)μg/m3,respectively;the average daily non-accidental death counts were 148,57,28,and 8.The analysis of the generalized Poisson addi-tive model showed that the daily non-accidental death counts increased by 0.43％(95％CI:0.33％-0.54％)per 10 μg/m3 increase of PM2.5 in lag 0 day in Tianjin of China;0.27％(95％CI:0.08％-0.46％)per 10 μg/m3 increase of PM2.5 in lag 2 days in Ningbo of China.The effect was magnified in high temperature levels in Tianjin and in low temperatures in Ningbo and Bangkok.The mortality effect of PM2 5 in various temperature levels stayed still in co-pollutant regression models.Conclusion:Exposure to fine particulate matter had an adverse effect on non-accidental mortality,which reminded us to give further attention to the pollution control.The findings also indicated that apparent temperature might modify mortality effects of PM2 .5 and the modification effect varied in different regions.Protective policies due to regional differences should be made and more scientific and social attention on mutual effect of air pollution and climate change needs to be appealed.

Subarachnoid hemorrhage (SAH) is the third common type of stroke in the world,and its mortality and disability rates have declined over the past few decades due to the advances in neuroimaging technology and endovascular interventional therapy and promotion of healthy physical examination,but long-term neurological deficits and cognitive impairment of the patients have not significantly improved,which may be related to the white matter injury (WMI) after SAH.Little attention has been paid to WMI after SAH in the past,which may be an important reason for the poor prognosis of the patients with SAH.The neuroin-flammation response is an important pathophysiological process after SAH,and the neuroinflammation after SAH can aggravate WMI.This article reviews the relationship between neuroinflammation and WMI after SAH in order to deepen the understanding of its effects on cognitive function after SAH.

Objective To investigate the risk factors for postoperative pulmonary embolism in patients with spontaneous cerebral hemorrhage,and construct and verify the nomogram model.Methods A retrospective cohort study was conducted on 558 patients admitted in the First Affiliated Hospital of Chongqing Medical University and the Three Gorges Hospital Affiliated to Chongqing University.And 393 of them who hospitalized from January 2015 to January 2021 were assigned into a modeling group,and the other 165 patients from February 2021 to January 2023 into a validation group.Univariate and multivariate stepwise logistic regression analyses were used to screen out the risk factors associated with pulmonary embolism after spontaneous cerebral hemorrhage surgery.Then a nomogram model was build based on these factors and verified.Results Based on age,blood loss,Glasgow coma scale(GCS)score,surgical treatments,levels of fibrin degradation products,D-dimer and hemoglobin,plasma osmolality,and deep vein thrombosis,a risk model of pulmonary embolism was built.Receiver operating characteristic(ROC)curve analysis showed the model had good discriminability for the presence of pulmonary embolism,and the area under the curve(AUC)value was 0.908.Hosmer-Lemeshow goodness-fit test indicated that the model had a good fit to the verification set(Chi-square=14.805,df=8,P=0.063),the correction curve was close to the ideal curve,and the prediction probability of the model was close to the actual occurrence probability,suggesting the model having good accuracy.Decision curve analysis revealed that the established nomogram model can get benefits under a large range of threshold probabilities.Conclusion We develop a prediction model for postoperative pulmonary embolism in patients with spontaneous cerebral hemorrhage after surgical treatment,which shows good prediction performance in both the training and validation groups,and can be used for accurate,prompt and quick identification for the occurrence of pulmonary embolism in clinical practice.