ObjectiveTo establish a regional risk assessment system for hospital-acquired infections in neurosurgery department of general hospital, and to evaluate its prevention and control effectiveness. MethodsFailure mode and effect analysis (FMEA) was used to identify the core risk factors for infections in neurosurgery department. The risk priority number (RPN) of each risk factor was calculated to determine the priority intervention targets. Targeted interventions were developed and continuously refined through the plan-do-check-act (PDCA) cycles. Data from January to June 2023 (control group) and July to December 2023 (intervention group) were collected to compare the differences in environmental hygiene monitoring qualification rate, incidence rate of hospital-acquired infections among inpatients, and detection rate of bacterial antimicrobial resistance. ResultsHigh-risk factors for hospital-acquired infections in neurosurgery department included patient-related risk factors, inadequate implementation of isolation measures for special infections, and poor compliance with surgical site infection (SSI) prevention protocols. After intervention, the environmental hygiene qualification rate significantly increased from 81.55% to 100.00% (χ²=120.49, P<0.001). The overall hospital-acquired infection rate among inpatients decreased from 2.62% to 2.45%, the infection rate of per case declined from 3.12% to 2.84%, and the detection rate of multidrug-resistant organism infections reduced from 43.72% to 36.79%. Additionally, antimicrobial utilization rate decreased from 48.75% to 42.53% (χ²=34.09, P<0.001). ConclusionThe FMEA-based risk assessment system can effectively identify critical infection risks in neurosurgery department, and targeted interventions can significantly improve infection prevention and control performance.

ObjectiveTo evaluate the antitumor activity of Periplaneta americana extract（PAE） against human-derived lung adenocarcinoma organoids（LUAD-PDOs） and to elucidate its potential mechanism based on transcriptomics. MethodsFresh tumor and adjacent normal tissues from patients with LUAD were collected to construct LUAD-PDOs and normal lung organoid（Nor-PDOs） models using 3D organoid culture technology. The effective intervention concentration of PAE was determined using the cell counting kit-8（CCK-8） assay. Experimental groups included the model group（LUAD-PDOs）， normal group， model administration group（LUAD-PDOs+PAE）， and normal administration group（Nor-PDOs+PAE）. Hematoxylin-eosin（HE） staining was used to observe the pathological structures of PDOs， immunohistochemistry（IHC） was performed to detect the expressions of the proliferation marker Ki-67 and lung adenocarcinoma differentiation markers cytokeratin-7（CK-7） and Napsin A， TUNEL staining was applied to detect cell apoptosis. RNA sequencing（RNA-Seq） was conducted to identify differentially expressed genes（DEGs）， followed by Gene Ontology（GO）， Kyoto Encyclopedia of Genes and Genomes（KEGG）， and Gene Set Enrichment Analysis（GSEA）， alongside protein-protein interaction（PPI） network analysis to screen core mechanisms. Finally， key targets were validated by integrating external database analysis with immunofluorescence（IF）. ResultsNor-PDOs and LUAD-PDOs that highly recapitulated the pathological characteristics of the primary tissues were successfully established. The CCK-8 assay determined that the effective intervention concentration of PAE was 16 g·L^-1. Morphological observation showed that Nor-PDOs exhibited lumen-forming structures， whereas LUAD-PDOs displayed dense， solid structures. CCK-8 and TUNEL assays revealed that， compared with the model group， PAE intervention inhibited the proliferation of LUAD-PDOs and promoted apoptosis in LUAD cells， while showing no significant effect on the viability of Nor-PDOs. Transcriptomic analysis identified 719 DEGs that were significantly reversed after PAE intervention（347 up-regulated and 372 down-regulated）（P<0.05）. GO enrichment analysis indicated that DEGs in the model administration group were significantly enriched in biological processes related to cell cycle regulation compared to the model group. KEGG pathway analysis revealed that PAE affected pathways related to proliferation and metabolism， including pathways in cancer and the p53 signaling pathway. GSEA further confirmed that PAE significantly enhanced the activity of the p53 signaling pathway（P<0.05）. PPI network analysis indicated that breast cancer type 1 susceptibility protein（BRCA1） and checkpoint kinase 1（CHEK1） were the core down-regulated targets in the p53 pathway. IF verified the high expression of BRCA1 and CHEK1 in LUAD-PDOs and their significant downregulation after PAE intervention（P<0.05）. Furthermore， survival analysis based on The Cancer Genome Atlas（TCGA） database indicated that low expression of BRCA1 and CHEK1 was significantly associated with prolonged overall survival in patients with LUAD（P<0.05）. ConclusionPAE effectively inhibits proliferation of LUAD-PDOs and promotes their apoptosis， its anti-tumor mechanism is potentially associated with the activation of the p53 signaling pathway， with BRCA1 and CHEK1 genes likely serving as key downstream targets for the effects of PAE.

Objective To explore the recognition capabilities of electronic nose combined with machine learning in identifying the breath odor map of benign and malignant pulmonary nodules and Traditional Chinese Medicine (TCM) syndrome elements. Methods The study design was a single-center observational study. General data and four diagnostic information were collected from 108 patients with pulmonary nodules admitted to the Department of Cardiothoracic Surgery of Hospital of Chengdu University of TCM from April 2023 to March 2024. The patients' TCM disease location and nature distribution characteristics were analyzed using the syndrome differentiation method. The Cyranose 320 electronic nose was used to collect the odor profiles of oral exhalation, and five machine learning algorithms including random forest (RF), K-nearest neighbor (KNN), logistic regression (LR), support vector machine (SVM), and eXtreme gradient boosting (XGBoost) were employed to identify the exhaled breath profiles of benign and malignant pulmonary nodules and different TCM syndromes. Results (1) The common disease locations in pulmonary nodules were ranked in descending order as liver, lung, and kidney; the common disease natures were ranked in descending order as Yin deficiency, phlegm, dampness, Qi stagnation, and blood deficiency. (2) The electronic nose combined with the RF algorithm had the best efficacy in identifying the exhaled breath profiles of benign and malignant pulmonary nodules, with an AUC of 0.91, accuracy of 86.36%, specificity of 75.00%, and sensitivity of 92.85%. (3) The electronic nose combined with RF, LR, or XGBoost algorithms could effectively identify the different TCM disease locations and natures of pulmonary nodules, with classification accuracy, specificity, and sensitivity generally exceeding 80.00%.Conclusion Electronic nose combined with machine learning not only has the potential capabilities to differentiate the benign and malignant pulmonary nodules, but also provides new technologies and methods for the objective diagnosis of TCM syndromes in pulmonary nodules.

Objective To construct and validate a prediction model for urosepsis in patients after upper urinary tract stone surgery using various machine learning algorithms.Methods A total of 7 464 upper urinary tract stone patients who underwent surgery at the Sixth Affiliated Hospital of Guangxi Medical University from Jun.2018 to Jun.2023 were enrolled and randomly assigned to training(5 224 cases)or validation sets(2 240 cases)at a ratio of 7∶3.Among them,622(8.33%)cases developed urosepsis postoperatively.Six machine learning algorithms,including extreme gradient boosting(XGBoost),logistic regression,light gradient boosting machine(LightGBM),random forest(RF),adaptive boosting(AdaBoost),and gradient boosting decision tree(GBDT),were used to construct prediction models for postoperative urosepsis.The model's predictive ability and clinical benefits were evaluated using receiver operating characteristic(ROC)curves,Shapley additive explanation(SHAP)analysis,calibration curves,and decision curve analysis(DCA).Results The clinical features included body mass index(BMI),number of surgeries,heart rate,Barthel index,venous thrombo embolism(VTE)risk assessment,gender,American Society of Anesthesiologists(ASA)grade,urinary nitrite,and urinary leukocyte in the models.In the training set,the XGBoost,LightGBM,and RF models performed excellently,with area under curve(AUC)values of ROC curves reaching 1.00.In the validation set,the logistic regression model performed the best,with an AUC value of ROC curve of 0.76,showing good predictive stability and calibration.The AdaBoost and GBDT models followed with AUC values of 0.74 and 0.75,respectively,while the AUC values of the LightGBM,XGBoost,and RF models were 0.71,0.70,and 0.68.In terms of model interpretability,SHAP analysis showed the contribution of variables in a descending order as:heart rate,urinary leukocytes,gender,BMI,Barthel index,VTE risk assessment,urinary nitrite,number of surgeries,and ASA grade.Conclusion A logistic regression model for early risk prediction of postoperative urosepsis in upper urinary tract stone patients has been successfully constructed.This model has good predictive performance and calibration,and can effectively assist clinical diagnosis.

Objective To explore the expression profile of adenosine A1 receptor in the paraventricular thalamic nucleus(PVT)in wakefulness/sleep state and its role in regulating sleep.Methods Male C57BL/6J mice(6～12 weeks old,weighing 22～28 g)were randomly divided into ZT0,ZT6,ZT10,ZT12,and sleep deprivation and recover0y sleep groups(n=16 or n=4).RT-qPCR and fluorescence in situ hybridization were used to observe the changes of adenosine A1 receptor in PVT.Whole-cell patch-clamp recording was conducted to determine the effects of adenosine on the membrane potential and discharge frequency of PVT neurons.The experimental animals were divided into adenosine A1 receptor interference group(n=8)and interference control group(n=7).After RNA interference,electroencephalography(EEG)and electromyography(EMG)were applied simultaneously to observe the changes in wake and sleep time between the 2 groups during sleep deprivation for 6 h and sleep recovery for 4 h.Results RT-qPCR and fluorescence in situ hybridization confirmed that the expression of adenosine A1 receptor in PVT was affected by wakefulness/sleep state,with the level in the ZT0 group(active stage)significantly higher than that in the ZT12 group(non-active stage,P<0.05).Whole-cell patch clamp recording indicated that adenosine exerted inhibitory effects on PVT neurons through 2 distinct response types(P<0.05),and the inhibition was in a diminishing trend with a decrease in the expression level of adenosine A1 receptor.After sleep deprivation,the expression level of adenosine A1 receptor showed significant intergroup differences:the level was significantly higher in the sleep deprivation group than the recovery sleep group(P<0.05),while that of the recovery sleep group was higher than that of the ZT6 group and that of the ZT10 group(P<0.05).After knocking down adenosine A1 receptor(shRNA-A1R)in the PVT,the wakefulness timing of the shRNA-A1R group was significantly increased,while the sleep timing was significantly decreased within 1 h after sleep recovery when compared with the interference control group(P<0.05).Conclusion The expression of adenosine A1 receptor in the PVT is dynamically regulated by sleep pressure,which was increasing as sleep pressure rises.

Objective To investigate the relationship between serum levels of interferon-inducible protein 10(IP-10)and S100 calcium-binding protein A8(S100A8)and the prognosis of patients with severe pneumo-nia(SP).Methods A total of 315 SP patients admitted to the hospital from January 2021 to December 2023 were selected as the SP group,and 315 non-SP patients admitted to the hospital during the same period were selected as the non-SP group.According to the prognosis of SP patients 28 d after admission,they were divided into good prognosis group(199 cases)and poor prognosis group(116 cases).Enzyme-linked immunosorbent assay was used to detect serum IP-10 and S100A8 levels in SP patients.Pearson correlation analysis was used to analyze the correlation between IP-10,S100A8 levels and infection indicators[high-sensitivity C-reactive protein(hs-CRP),procalcitonin(PCT),interleukin-6(IL-6)].Multivariate Logistic regression was used to analyze the influencing factors of poor prognosis in SP patients.Receiver operating characteristic(ROC)curve was used to analyze the value of hs-CRP,PCT,IP-10 and S100A8 levels in predicting the poor prognosis of SP patients.Results The serum levels of IP-10,S100A8,hs-CRP,PCT and IL-6 in SP group were higher than those in non-SP group(P＜0.05).Paerson correlation analysis showed that serum IP-10 level in SP group was positively correlated with hs-CRP,PCT and IL-6(r=0.744,0.757,0.740,P＜0.05).S100A8 level was posi-tively correlated with hs-CRP,PCT and IL-6(r=0.769,0.718,0.744,P＜0.05).There were significant differences in oxygenation index,acute physiology and chronic health evaluation Ⅱ score,clinical pulmonary in-fection score and levels of hs-CRP,PCT,IP-10 and S100A8 between the poor prognosis group and the good prognosis group(P＜0.05).Multivariate Logistic regression analysis showed that hs-CRP,PCT,IP-10 and S100A8 were risk factors for poor prognosis in SP patients,and oxygenation index was a protective factor(P＜0.05).The ROC curve showed that the area under curve(AUC)of the combination of hs-CRP,PCT,IP-10 and S100A8 in predicting poor prognosis of SP patients was 0.965,which was greater than the AUC of the four alone(Zhs-CRP=4.009,ZPCT=4.022,ZIP-10=3.696,ZS100A8=3.309,P＜0.05).Conclusion The serum lev-els of IP-10 and S100A8 are up-regulated in SP patients.The combination of IP-10 and S100A8 has a high pre-dictive value for poor prognosis in SP patients.

Background and Aims:The incidence of intrahepatic cholangiocarcinoma(ICC)has been increasing in recent years.Due to its insidious onset and low rate of early diagnosis,radical resection remains the only potential curative treatment.Lymph node metastasis is a major adverse prognostic factor in ICC,but the scope and therapeutic value of lymphadenectomy remain controversial.Previous studies suggest that patients with central ICC may derive greater survival benefit from lymphadenectomy than those with peripheral ICC.Preoperative assessment of lymph node status mainly relies on imaging,but its accuracy is limited.This study aimed to investigate the prognostic impact of lymphadenectomy in ICC patients at different anatomical sites to inform surgical decision-making.Methods:A retrospective analysis was conducted on 220 ICC patients who underwent radical resection at the 904th Hospital of the Joint Logistic Support Force of the PLA from May 2016 to May 2021.The cohort included 126 males and 94 females,with a mean age of(56.76±13.15)years.Patients were categorized into peripheral ICC(n=144)and central ICC(n=76)groups.Clinical characteristics,albumin-bilirubin(ALBI)grade,preoperative risk of lymph node metastasis,number of lymph nodes dissected,lymph node metastasis status,and postoperative survival outcomes were compared.Subgroup analyses were conducted to assess the prognostic value of the number of lymph nodes dissected under different risk stratifications.Results:Significant differences were observed between peripheral and central ICC in ALBI grade(x2=9.952,P=0.002),preoperative lymph node metastasis risk(x2=6.166,P=0.014),number of lymph nodes dissected(x2=4.167,P=0.042),and lymph node metastasis rate(x2=7.331,P=0.007).The 3-year overall survival(OS)rate was higher in peripheral ICC(31.94％)than in central ICC(15.79％)(x2=13.890,P＜0.001).Among central ICC patients,those with ≥6 lymph nodes dissected had better 3-year OS than those with＜6(16.89％vs.13.04％,x2=3.894,P=0.048).In the high-risk subgroup of central ICC,≥6 lymph nodes dissected was also associated with improved 3-year OS compared with＜6(15.62％vs.11.11％,x2=3.962,P=0.047).In contrast,the number of lymph node dissections had no significant prognostic impact in peripheral ICC or in patients classified as low risk.Conclusion:Patients with peripheral ICC had a better prognosis than those with central ICC.Adequate lymphadenectomy(≥6 nodes)improved survival and enhanced staging accuracy in central ICC patients at high risk of lymph node metastasis,highlighting the importance of preoperative risk assessment for optimizing surgical strategies.

Objective:To explore the relationship between general demographic characteristics,inflammatory indicators,nutritional indicators,pathological data and lymph node metastasis in endometrial cancer(EC)pa-tients,and to construct and validate a model for preoperative prediction of lymph node status in endometrial canc-er patients.Methods:The preoperative clinical data of 473 patients with EC who underwent surgical treatment in the Zhu Jiang Hospital of Southern Medical University from January 2010 to April 2024 were retrospectively ana-lyzed.The independent risk factors of lymph node metastasis of endometrial cancer were screened by univariate and multivariate Logistic regression analyses,and the nomogram prediction model was constructed by R soft-ware.The performance of the model was evaluated by the receiver operating characteristic(ROC)curve,calibra-tion curve and clinical decision curve.Results:Menopausal status,high grade biopsy pathology,CA125 ≥24.47U/ml,systemic immune inflammatory index(SII)≥710.91,and prognostic nutritional index(PNI)＜52.90 were in-dependent risk factors for lymph node metastasis in endometrial cancer(OR＞1,P＜0.05).The nomogram model constructed based on these five factors had an AUC of 0.853 in the training set and 0.871 in the test set.The cali-bration curve fitted well,and the clinical decision curve shows a positive benefit.Conclusions:The endometrial cancer lymph node metastasis prediction model constructed based on menopausal status,biopsy pathology,CA125,SII,and PNI has good accuracy and fit,with certain clinical application value.

Emerging evidences have indicated the role of ferroptosis in the progression of metabolic-associated fatty liver disease (MAFLD); thus, inhibiting ferroptosis is a promising strategy for the development of MAFLD therapeutics. Recent studies have demonstrated the antioxidative effect of the gut commensal bacterium Akkermansia muciniphila (A. muc); however, whether it can alleviate ferroptosis remains unclear. The current study indicates A. muc intervention efficiently reversed high-fat high-fructose diet (HFHFD)-induced lipid peroxidation and ferroptosis in the liver. These beneficial effects were mediated by activation of the hepatic AMPK/SIRT1/PGC-1α axis, as evidenced by the finding that AMPK deficiency abrogated the amelioration of lipid peroxidation in vitro and in vivo. Furthermore, the short-chain fatty acids (SCFAs) were enriched upon A. muc treatment, and acetate was identified as a key activator of hepatic AMPK signalling. Mechanistically, microbiota-derived acetate was transported to the liver and metabolized to adenosine monophosphate (AMP), which triggered AMPK activation. Furthermore, a colonization assay in germ-free mice confirmed that A. muc mediated antiferroptotic effects in the absence of other microbes. These data indicated that A. muc exerts antiferroptotic effects against MAFLD, at least partially by producing acetate, which activates the hepatic AMPK/SIRT1/PGC-1α axis to alleviate ferroptosis via the inhibition of polyunsaturated fatty acid (PUFA) synthesis.

Objective:To explore the association between circadian syndrome (CircS), metabolic syndrome (MetS) and mild cognitive impairment (MCI) in elderly rural adults in China.Methods:From March to September 2018, totally 5 765 participants aged 60 years or older from 52 villages in Yanlou Town, Yanggu County, Shandong Province were selected. The data included demographic, underlying disease and neuropsychological data were collected by questionaire survey. Having ≥3 of the following components was defined as MetS: elevated waist circumference, high triglycerides, low high-density lipoprotein cholesterol, elevated blood pressure and elevated fasting glucose. Having ≥4 of the following components was defined as CircS: short sleep (<6 h/d), depression and five other components which were used to define MetS, with elevated waist circumference as a mandatory item. MCI was diagnosed according to Petersen's criteria and further classified into amnestic MCI (aMCI) and non-amnestic MCI (naMCI) based on whether the memory domains impaired.Data were analyzed using multivariable Logistic regression and general linear regression models by R statistical software.Results:In the total sample ( n=4 898), 1 280 participants were diagnosed with MCI, of which 1 075 were aMCI and 205 were naMCI.Compared to the normal group, CircS alone was significantly associated with increased risks of MCI ( B=0.695, P=0.039) and aMCI ( B=0.782, P=0.024), as well as lower verbal fluency scores ( B=-0.244, P=0.045). No significant associations were found between MetS alone or both MetS and CircS and cognitive impairment( P>0.05). At the component level, short sleep and depression were associated with increased risks of MCI ( B=0.167, P=0.025; B=0.605, P<0.001) and aMCI ( B=0.185, P=0.020; B=0.600, P<0.001). Conclusion:Individuals with CircS are at a higher risk of cognitive impairment, CircS is more strongly associated with cognitive impairment than MetS, with short sleep duration and depressive symptoms potentially playing key roles.