OBJECTIVE To analyze the reasons for the outbreak of suspected carbapenem-resistant Acinetobacter baumannii(CRAB)infections in the neurosurgical intensive care unit to take comprehensive prevention and con-trol measures to control the spread of infections,and to provide a reference for the control of multidrug-resistant organisms(MDRO)infections in intensive care units.METHODS Epidemiological data were collected from five patients with CRAB infections in the neurosurgical intensive care unit of Gansu Provincial People's Hospital in Mar.2024,and environmental hygiene monitoring and comprehensive infection prevention and control measures were conducted.RESULTS A total of five cases of lower respiratory tract infections occurred,all of which were hospital-acquired infections,and all patients had consistent spatial-temporal distribution.A.baumannii was detec-ted in the sputum cultures of all patients,and all were resistant to carbapenems,aminoglycosides and some β-lac-tam drugs.Before the implementation of comprehensive prevention and control measures,a total of 25 samples from the surfaces and the hands of health workers were collected,with a pass rate of 52.00％;CRAB was detected on the surface of treatment carts and the wall of sputum suction bottles in the treatment room,with a detection rate of 8.00％.After the implementation,a total of 24 samples were collected,with a pass rate of 100.00％,and the difference was statistically significant when compared with the pre-implementation period(χ2=16.987,P<0.001).Through the implementation of comprehensive measures such as isolation,standardization of the ward cleaning and disinfection process,strengthening hand hygiene,standardization of sterile operations and personnel management,the indicators such as hand hygiene compliance rate,the execution rate of multi-drug-resistant bac-terial preventive and control measures and the fluorescent marker removal rate were all improved,and the suspec-ted CRAB infection outbreak was timely controlled.CONCLUSION This suspected CRAB hospital-acquired infec-tion outbreak may be related to a variety of factors,and timely environmental hygiene monitoring and comprehen-sive infection prevention and control measures can effectively control the spread of CRAB infection.

Computational analysis can accurately detect drug-gene interactions(DGIs)cost-effectively.However,transductive learning models are the hotspot to reveal the promising performance for unknown DGIs(both drugs and genes are present in the training model),without special attention to the unseen DGIs(both drugs and genes are absent in the training model).In view of this,this study,for the first time,proposed an inductive learning-based model for the precise identification of unseen DGIs.In our study,by integrating disease nodes to avoid data sparsity,a multi-relational drug-disease-gene(DDG)graph was constructed to achieve effective fusion of data on DDG intro-relationships and inter-actions.Following the extraction of graph features by utilizing graph embedding algorithms,our next step was the retrieval of the attributes of individual gene and drug nodes.In this way,a hybrid feature charac-terization was represented by integrating graph features and node attributes.Machine learning(ML)models were built,enabling the fulfillment of transductive predictions of unknown DGIs.To realize inductive learning,this study generated an innovative idea of transforming known node vectors derived from the DDG graph into representations of unseen nodes using node similarities as weights,enabling inductive predictions for the unseen DGIs.Consequently,the final model was superior to existing models,with significant improvement in predicting both external unknown and unseen DGIs.The practical feasibility of our model was further confirmed through case study and molecular docking.In summary,this study establishes an efficient data-driven approach through the proposed modeling,suggesting its value as a promising tool for accelerating drug discovery and repurposing.

Computational analysis can accurately detect drug-gene interactions (DGIs) cost-effectively. However, transductive learning models are the hotspot to reveal the promising performance for unknown DGIs (both drugs and genes are present in the training model), without special attention to the unseen DGIs (both drugs and genes are absent in the training model). In view of this, this study, for the first time, proposed an inductive learning-based model for the precise identification of unseen DGIs. In our study, by integrating disease nodes to avoid data sparsity, a multi-relational drug-disease-gene (DDG) graph was constructed to achieve effective fusion of data on DDG intro-relationships and inter-actions. Following the extraction of graph features by utilizing graph embedding algorithms, our next step was the retrieval of the attributes of individual gene and drug nodes. In this way, a hybrid feature characterization was represented by integrating graph features and node attributes. Machine learning (ML) models were built, enabling the fulfillment of transductive predictions of unknown DGIs. To realize inductive learning, this study generated an innovative idea of transforming known node vectors derived from the DDG graph into representations of unseen nodes using node similarities as weights, enabling inductive predictions for the unseen DGIs. Consequently, the final model was superior to existing models, with significant improvement in predicting both external unknown and unseen DGIs. The practical feasibility of our model was further confirmed through case study and molecular docking. In summary, this study establishes an efficient data-driven approach through the proposed modeling, suggesting its value as a promising tool for accelerating drug discovery and repurposing.

Objective To explore the global and loci-specific genetic correlations and bidirectional causal relationships between spinal stenosis(SS)and constipation.Methods Utilizing the publicly available genome-wide association study data from the European population,linkage disequilibrium score regression and local analysis of variant association were used for quantifying genetic correlation at both global(genome-wide)and local(genomic regions)levels,and a two-sample Mendelian randomization(TSMR)analysis was conducted:Four distinct methods,namely the inverse variance weighting method,MR-Egger regression method,weighted median method,and weighted mode,were utilized for analysis and evaluation of the results;Cochran's Q test,leave-one-out method,MR-Egger intercept test,Mendelian randomization polymorphic residuals,and outlier tests were applied to examine the stability and reliability of the results.Results The analysis of linkage disequilibrium score regression and local analysis of variant association revealed that a total of 71 regions had at least one pair of traits with local genetic correlations.The TSMR analysis,with SS as the exposure and constipation as the outcome,based on the results of the inverse variance weighting method,suggested a causal relationship between two(OR=1.077,95％CI:1.034-1.122,P=0.000);Cochran's Q test and MR-Egger intercept test indicated the absence of heterogeneity or pleiotropy,and were verified by the analysis of Mendelian randomization polymorphic residuals,and outlier tests,demonstrating that the results of this study did not exhibit horizontal pleiotropy;The sensitivity analysis using the leave-one-out method indicated that the research results were stable.With constipation as the exposure factor and SS as the outcome,no eligible instrumental variables were found.Conclusion There are significant global and loci-specific genetic correlations between SS and constipation,and SS may be a risk factor for the occurrence of constipation.

Objective:To explore genomic features associated with gemcitabine sensitivity, patient-derived organoid models of biliary tract cancer (BTC) were established and characterized.Methods:This is an experimental study. The tissue specimens of BTC were collected from patients who underwent surgical resection at the Department of Hepatobiliary and Pancreatic Surgery,the Second Affiliated Hospital of Zhejiang University School of Medicine between January 2020 and December 2023. The tumor organoids were cultured in vitro and histologically characterized. Drug sensitivity testing was performed using gemcitabine,cisplatin,paclitaxel,fluorouracil,and lenvatinib etc. to evaluate cell viability. The correlation between the drug sensitivity of organoids and clinical therapeutic response was analyzed.Results:Thirty-eight patient-derived organoids (PDO) models were successfully established from 43 biliary tract malignancy patients with complete follow-up data,including gallbladder cancer PDO 14 cases,distal bile duct cancer PDO 16 cases,intrahepatic cholangiocarcinoma PDO 8 cases,achieving an overall success rate of 88.4%. Drug sensitivity testing (DST) was performed on the successfully generated PDO,with 35 models successfully completing DST experiments. The overall consistency rate between drug responses in PDOs and clinical survival outcomes in corresponding patients was 8/14. Transcriptomic analysis of gemcitabine-sensitive vs. gemcitabine-resistant PDO identified 71 differentially expressed genes in the resistant group,the significantly up-regulated genes including GLDC, LINC01595, IL-27, ANGPTL3, CYP7A1,and AKR1C1;the significantly down-regulated genes including P2RY2,LIPC,and ECHDC3. Conclusion:A biobank of patient-derived organoids of BTC has been established,which demonstrates its potential as preclinical models and tools for predicting chemotherapy responses for BTC patients.

Psoriasis is a chronic,inflammatory,recurrent,and systemic disease mediated by immune dysregulation,which is often accompanied by psychological issues such as depression and anxiety.Recent research on the gut microbiota and depression and anxiety has made significant progress,with studies demonstrating that the gut microbiota plays a crucial role in the pathogenesis of psoriasis.Dysbiosis of the gut microbiota may be an important comorbidity mechanism linking psoriasis with depression and anxiety.This article summarizes the changes in the abundance of gut microbiota in patients with psoriasis and those with depression and anxiety,as well as how the gut microbiota influences this comorbidity through neural pathways and immune-endocrine pathways.It aims to provide novel perspectives for the study of the comorbidity mechanisms and clinical treatment of psoriasis and depression and anxiety.In the future,targeting the gut microbiota may enable the development of personalized treatments.

OBJECTIVE To explore the risk factors for hospital-associated infections(HAI)in dead patients so as to provide bases for development of prevention strategies for the hospital-associated infections.METHODS Totally 560 patients who died due to non-SARS-CoV-2 infections and hospitalized in Gansu Provincial People's Hospital for more than 48 hours in 2019 and 2023 were retrospectively analyzed,70 of whom had HAI and were assigned as the HAI group,and the rest of 490 patients were assigned as the non-HAI group.The incidence of HAI,major causes of death,risk factors and economic burden were observed.RESULTS The incidence of HAI was 12.50％a-mong the dead patients,the lower respiratory tract infection was the predominant type of infection,and the re-spiratory failure was the primary and direct cause of death in the HAI group;the total treatment cost of the HAI group was higher than that of the non-HAI group(P＜0.05).Univariate analysis showed that there were signifi-cant differences in the length of hospital stay,multidrug-resistant organisms infections,combined use of antibiot-ics,surgery,hemodialysis/peritoneal dialysis,invasive procedures(drainage,puncture,intubation,tracheoto-my),use of equipment like ventilator or urinary catheter,central venous catheter indwelling,blood transfusion,and use of immunosuppressors/glucocorticoids between the HAI group and the non-HAI group(P＜0.05),while there were no significant differences in the sex,age,underlying diseases,modified early warning score(MEWS)and major diagnosis and chemoradiotherapy between the two groups.Multivariate analysis indicated that the length of hospital stay more than 14 days,history of surgery and combined use of antibiotics were the risk factors for HAI in the dead patients(P＜0.05).CONCLUSION It is necessary for the hospital to identify the high-risk pa-tients as early as possible,pay close attention to the lower respiratory tract infection,reduce the risk of HAI by shortening the length of hospital stay,standardizing the invasive procedures and reasonably using antibiotics so as to improve the prognosis of the patients.

Psoriasis is a chronic,inflammatory,recurrent,and systemic disease mediated by immune dysregulation,which is often accompanied by psychological issues such as depression and anxiety.Recent research on the gut microbiota and depression and anxiety has made significant progress,with studies demonstrating that the gut microbiota plays a crucial role in the pathogenesis of psoriasis.Dysbiosis of the gut microbiota may be an important comorbidity mechanism linking psoriasis with depression and anxiety.This article summarizes the changes in the abundance of gut microbiota in patients with psoriasis and those with depression and anxiety,as well as how the gut microbiota influences this comorbidity through neural pathways and immune-endocrine pathways.It aims to provide novel perspectives for the study of the comorbidity mechanisms and clinical treatment of psoriasis and depression and anxiety.In the future,targeting the gut microbiota may enable the development of personalized treatments.

OBJECTIVE To explore the risk factors for hospital-associated infections(HAI)in dead patients so as to provide bases for development of prevention strategies for the hospital-associated infections.METHODS Totally 560 patients who died due to non-SARS-CoV-2 infections and hospitalized in Gansu Provincial People's Hospital for more than 48 hours in 2019 and 2023 were retrospectively analyzed,70 of whom had HAI and were assigned as the HAI group,and the rest of 490 patients were assigned as the non-HAI group.The incidence of HAI,major causes of death,risk factors and economic burden were observed.RESULTS The incidence of HAI was 12.50％a-mong the dead patients,the lower respiratory tract infection was the predominant type of infection,and the re-spiratory failure was the primary and direct cause of death in the HAI group;the total treatment cost of the HAI group was higher than that of the non-HAI group(P＜0.05).Univariate analysis showed that there were signifi-cant differences in the length of hospital stay,multidrug-resistant organisms infections,combined use of antibiot-ics,surgery,hemodialysis/peritoneal dialysis,invasive procedures(drainage,puncture,intubation,tracheoto-my),use of equipment like ventilator or urinary catheter,central venous catheter indwelling,blood transfusion,and use of immunosuppressors/glucocorticoids between the HAI group and the non-HAI group(P＜0.05),while there were no significant differences in the sex,age,underlying diseases,modified early warning score(MEWS)and major diagnosis and chemoradiotherapy between the two groups.Multivariate analysis indicated that the length of hospital stay more than 14 days,history of surgery and combined use of antibiotics were the risk factors for HAI in the dead patients(P＜0.05).CONCLUSION It is necessary for the hospital to identify the high-risk pa-tients as early as possible,pay close attention to the lower respiratory tract infection,reduce the risk of HAI by shortening the length of hospital stay,standardizing the invasive procedures and reasonably using antibiotics so as to improve the prognosis of the patients.

Objective To explore the global and loci-specific genetic correlations and bidirectional causal relationships between spinal stenosis(SS)and constipation.Methods Utilizing the publicly available genome-wide association study data from the European population,linkage disequilibrium score regression and local analysis of variant association were used for quantifying genetic correlation at both global(genome-wide)and local(genomic regions)levels,and a two-sample Mendelian randomization(TSMR)analysis was conducted:Four distinct methods,namely the inverse variance weighting method,MR-Egger regression method,weighted median method,and weighted mode,were utilized for analysis and evaluation of the results;Cochran's Q test,leave-one-out method,MR-Egger intercept test,Mendelian randomization polymorphic residuals,and outlier tests were applied to examine the stability and reliability of the results.Results The analysis of linkage disequilibrium score regression and local analysis of variant association revealed that a total of 71 regions had at least one pair of traits with local genetic correlations.The TSMR analysis,with SS as the exposure and constipation as the outcome,based on the results of the inverse variance weighting method,suggested a causal relationship between two(OR=1.077,95％CI:1.034-1.122,P=0.000);Cochran's Q test and MR-Egger intercept test indicated the absence of heterogeneity or pleiotropy,and were verified by the analysis of Mendelian randomization polymorphic residuals,and outlier tests,demonstrating that the results of this study did not exhibit horizontal pleiotropy;The sensitivity analysis using the leave-one-out method indicated that the research results were stable.With constipation as the exposure factor and SS as the outcome,no eligible instrumental variables were found.Conclusion There are significant global and loci-specific genetic correlations between SS and constipation,and SS may be a risk factor for the occurrence of constipation.