ObjectiveTo investigate the expression changes of the Endophilin A1 （EPA1）-reactive oxygen species （ROS）-NLR family pyrin domain containing 1 （NLRP1） signaling pathway in chronic unpredictable mild stress （CUMS）-induced depression model mice. Methods50 C57BL/6 mice were randomly divided into control group and CUMS model group（n=25）. The model mice received 42 days of CUMS stress exposure， after which behavioral changes were assessed through monitoring body weight， sucrose preference test， forced swim test， tail suspension test， open field test， and elevated plus-maze test. Hematoxylin-Eosin and Nissl staining were used to observe neuronal damage in hippocampal CA1 and CA3 regions. Calcium ion （Ca²⁺） assay kit was used to detect Ca²⁺ levels in the hippocampus. Immunofluorescence was used to detect colocalization of EPA1 and NLRP1 as well as ROS changes in the hippocampus. Transmission electron microscopy was used to observe mitochondrial structure in hippocampal neurons. The expression levels of calcium-activated neutral protease 1 （Calpain-1）， nicotinamide adenine dinucleotide phosphate oxidase 2 （NOX2）， NLRP1 inflammasome， downstream inflammatory proteins， and synapse-associated proteins in the hippocampus of mice was detected by using Western blot. ResultsCompared with the control group， mice in the CUMS model group exhibited depressive-like behavior and hippocampal neuronal damage. The levels of NLRP1 and EPA1 significantly increased in the hippocampus， and both were co-expressed in the cytoplasm and membrane of hippocampal neurons in the CUMS group mice（P<0.01）. Ca²⁺ concentration was elevated（P<0.01）， and the protein levels of Calpain 1 and NOX2 were upregulated（P<0.01）. The average fluorescence intensity of ROS significantly increased， accompanied by structural damage to neuronal mitochondria（P<0.01）. The levels of NLRP1 and its downstream inflammatory proteins significantly increased （P<0.01）， while the expression levels of synapse-associated proteins significantly decreased （P<0.01）. ConclusionEPA1 exhibits abnormal expression changes in CUMS-induced depression model mice， which may be closely associated with ROS generation， NLRP1 inflammasome activation， and the regulation of synaptic protein expression.

Objective To explore the characteristics of fine motor deficits in the elderly individuals with MCI due to AD through a new wearable inertial motion capture device,and then construct a prediction model for MCI.Methods A total of 260 elderly subjects were recruited in community from November,2022 to April,2023,and based on diagnosis,they were divided into a MCI group(134 cases)and a control group(126 cases).A new wearable inertial motion capture device,which was self-designed and developed based on MEMS inertial sensor,was used to capture the fine mo-tor movements of the hands,and the obtained data were analyzed with a computerized assessment system to make the quantitative evaluation of fine motor.LASSO learning algorithm and logistic regression analysis were employed to identify the predictive factors for MCI,and then a nomo-gram was constructed based on these factors.ROC curve was plotted to evaluate the predictive ability of the model by calculating its AUC value.DC A,CIC,and Bootstrap method were applied to evaluate and validate the clinical utility and stability of the model.Results The total score of MoCA(22.18±2.84 vs 27.60±1.10)and scores of the dimensions were significantly lower in the MCI group than the control group(all P＜0.01).In the five digital assessment tasks,the MCI group showed obviously poorer fine motor performance of both hands than the control group(P＜0.05,P＜0.01).ROC curve analysis showed that the AUC value of our nomogram model in predicting MCI was 0.762(95％CI:0.705-0.819).DCA,CIC,and Bootstrap methods demonstra-ted good and relatively stable discrimination,calibration,and clinical applicability of the model.Conclusion MEMS inertial sensor motion capture technology can make digital evaluation of fine motor.For the elderly,fine motor deficits are significantly associated with risk for MCI.Our no-mogram model based on fine motion parameters shows good predictive efficacy in assessing the risk of MCI.

Objective To explore the application effect of immersive virtual reality(IVR)technology and different viewing content in pediatric patients with general anesthesia during elective surgery,and to provide references for clinical implementation.Methods A total of 180 pediatric patients who underwent elective surgery under general anesthesia in a tertiary hospital in Qingdao from February to October 2023 were selected as study population using convenient sampling method.According to the operation time,60 pediatric patients who underwent surgery from May to July 2023 were included in the immersive panoramic surgical education group,and they could watch the panoramic surgical education video immersively on the basis of routine care.A total of 60 pediatric patients who underwent surgery from August to October 2023 were included in the immersive animation group to watch cartoons immersively on the basis of routine care.A total of 60 pediatric patients who underwent surgery from February to April 2023 were included in the control group and routine preoperative care was implemented.The preoperative anxiety levels,anesthesia induction compliance,and incidence of emergence agitation were compared in the 3 groups by the modified Yale Preoperative Anxiety Scale-Short Form(mYPAS-SF),anesthesia induction cooperation grade,and the Pediatric Anesthesia Emergence Delirium scale(PAED).Results There were statistically significant differences in preoperative anxiety level,anesthesia induced compliance and incidence of emergence agitation during awakening between the 3 groups(P＜0.001).Among them,the preoperative anxiety level of the immersive panoramic surgical education group and the immersive animation group was lower than that of the control group,and the difference was statistically significant(P＜0.001).The anesthesia induced compliance degree of the immersive panoramic surgical education group and the immersive animation group was better than that of the control group,and the difference was statistically significant(P＜0.017),and the incidence of emergence agitation in the immersive panoramic surgical education group was lower than that of the control group,and the difference was statistically significant(P=0.004).Conclusion The use of IVR technology to watch panoramic surgical education videos and cartoons can help reduce the preoperative anxiety level and improve anesthesia induction cooperation degree of pediatric patients with general anesthesia during elective surgery,but the intervention effect of panoramic surgical education videos is better in improving the emergence agitation.

Objective To explore the characteristics of fine motor deficits in the elderly individuals with MCI due to AD through a new wearable inertial motion capture device,and then construct a prediction model for MCI.Methods A total of 260 elderly subjects were recruited in community from November,2022 to April,2023,and based on diagnosis,they were divided into a MCI group(134 cases)and a control group(126 cases).A new wearable inertial motion capture device,which was self-designed and developed based on MEMS inertial sensor,was used to capture the fine mo-tor movements of the hands,and the obtained data were analyzed with a computerized assessment system to make the quantitative evaluation of fine motor.LASSO learning algorithm and logistic regression analysis were employed to identify the predictive factors for MCI,and then a nomo-gram was constructed based on these factors.ROC curve was plotted to evaluate the predictive ability of the model by calculating its AUC value.DC A,CIC,and Bootstrap method were applied to evaluate and validate the clinical utility and stability of the model.Results The total score of MoCA(22.18±2.84 vs 27.60±1.10)and scores of the dimensions were significantly lower in the MCI group than the control group(all P＜0.01).In the five digital assessment tasks,the MCI group showed obviously poorer fine motor performance of both hands than the control group(P＜0.05,P＜0.01).ROC curve analysis showed that the AUC value of our nomogram model in predicting MCI was 0.762(95％CI:0.705-0.819).DCA,CIC,and Bootstrap methods demonstra-ted good and relatively stable discrimination,calibration,and clinical applicability of the model.Conclusion MEMS inertial sensor motion capture technology can make digital evaluation of fine motor.For the elderly,fine motor deficits are significantly associated with risk for MCI.Our no-mogram model based on fine motion parameters shows good predictive efficacy in assessing the risk of MCI.

Objective To investigate the distribution and antimicrobial resistance profiles of clinically isolated Haemophilus influenzae and Moraxella catarrhalis in hospitals across China from 2015 to 2021,and provide evidence for rational use of antimicrobial agents.Methods Data of H.influenzae and M.catarrhalis strains isolated from 2015 to 2021 in CHINET program were collected for analysis,and antimicrobial susceptibility testing was performed by disc diffusion method or automated systems according to the uniform protocol of CHINET.The results were interpreted according to the CLSI breakpoints in 2022.Beta-lactamases was detected by using nitrocefin disk.Results From 2015 to 2021,a total of 43 642 strains of Haemophilus species were isolated,accounting for 2.91％of the total clinical isolates and 4.07％of Gram-negative bacteria in CHINET program.Among the 40 437 strains of H.influenzae,66.89％were isolated from children and 33.11％were isolated from adults.More than 90％of the H.influenzae strains were isolated from respiratory tract specimens.The prevalence of β-lactamase was 53.79％in H.influenzae strains.The H.influenzae strains isolated from children showed higher resistance rate than the strains isolated from adults.Overall,779 strains of H.influenzae did not produce β-lactamase but were resistant to ampicillin(BLNAR).Beta-lactamase-producing strains showed significantly higher resistance rates to these antimicrobial agents than the β-lactamase-nonproducing strains.Of the 16 191 M.catarrhalis strains,80.06％were isolated from children and 19.94％isolated from adults.M.catarrhalis strains were mostly susceptible to both amoxicillin-clavulanic acid and cefuroxime,evidenced by resistance rate lower than 2.0％.Conclusions The emergence of antibiotic-resistant H.influenzae due to β-lactamase production poses a challenge for clinical anti-infective treatment.Therefore,it is very important to implement antibiotic resistance surveillance for H.influenzae and guide rational antibiotic use.All local clinical microbiology laboratories should actively improve antibiotic susceptibility testing and strengthen antibiotic resistance surveillance for H.influenzae.

A scientific and efficient comprehensive operation system for the transformation of clinical research achievements is an important guarantee to fully release the capability of public hospitals of the achievement transformation. A public hospital, focusing on the bottleneck problems faced in the process of transforming scientific and technological achievements, began to explore the construction of a comprehensive operation system for the transformation of clinical research achievements and implemented it throughout the hospital from October 2023. By improving the organizational structure and setting up full-time management positions; formulating supporting policies and perfecting the incentive mechanism; drawing a systematic portrait and creating a standard pathway; expanding the transformation platform and promoting coordinated development; innovating management services and strengthening digital empowerment; and highlighting publicity and education to enhance the capability of transformation, the hospital has effectively promoted the transformation of clinical research achievements. This practice can provide a reference for other hospitals to improve the management of clinical research achievements transformation and promote high-quality hospital development.

Objective:To investigate the value of machine learning models based on CT radiomics for predicting the outcome of neoadjuvant chemotherapy (NAC) in patients with locally advanced gastric cancer (LAGC).Methods:A retrospective case series study was conducted. A total of 279 LAGC patients receiving NAC before surgery in Shanxi Province Cancer Hospital from January 2018 to November 2020 were included. According to a ratio of 7∶3, all patients were randomly divided into the training set (196 cases) and the validation set (83 cases). According to the tumor regression grade (TRG), the pathological grade was divided into the good response of NAC (GR) group (TRG 0-1, 55 cases) and the poor response of NAC (PR) group (TRG 2-3, 224 cases). The clinicopathological data of patients were collected, such as age, gender, differentiation degree, clinical T and N staging, carcinoembryonic antigen (CEA), and carbohydrate antigen 199 (CA199) level. Radiomics features were extracted from the enhanced CT images in the vein phase, and the features were screened by 3-step dimensionality reduction. And then 5 machine learning algorithms including logistic regression (LR), naive bayes (NB), random forest (RF), support vector machine (SVM) and extreme gradient boosting (XGB) were applied to build prediction models based on the CT radiomics. The receiver operating characteristic (ROC) curve and the decision analysis (DCA) curve were drawn to evaluate the predictive performance and clinical benefit of each model on the outcome of NAC in patients with LAGC.Results:Among 196 patients in the training set, there were 39 cases in GR group and 157 cases in PR group; among 83 patients in the validation set, there were 16 cases in GR group and 67 cases in PR group. There were no statistically significant differences in clinicopathological data of patients between the training and validation sets, or between GR and PR groups in the training and validation sets (all P > 0.05). A total of 102 radiomics features were extracted from region of interest of CT images in the vein phase, and 6 key features were finally selected including original_firstorder_10Percentile, original_firstorder_RoubustMeanAbsoluteDeviation, original_glcm_Idmn, original_glcm_MCC, original_ngtdm_Busyness, original_ngtdm_Contrast; and there were statistically significant differences in 6 features between the GR and PR groups (all P < 0.05). LR, NB, RF, SVM and XGB machine learning algorithms were used to construct 5 prediction models based on the CT radiomics. The area under ROC curve for NAC prediction in the training set was 0.553, 0.709, 0.668, 0.772 and 0.790, respectively; in the validation set was 0.662, 0.622, 0.683, 0.752 and 0.784, respectively. The model constructed by XGB showed the best comprehensive performance, and its accuracy, sensitivity and specificity was 0.771, 0.562 and 0.821, respectively. In the DCA of 5 machine learning models in the training set, XGB-based model provided a higher net benefit. Conclusions:Machine learning models based on enhanced CT radiomics in the vein phase have a high predictive efficacy in the outcome of NAC in LAGC patients before surgery and it helps make clinical personalized treatment decisions.

Objective:To evaluate the prevalence, potential risk factors, and correlation between coronary and peripheral microvascular dysfunction in heart failure with non-reduced ejection fraction (nHFrEF) patients.Methods:This was a prospective registry study. nHFrEF patients admitted to Zhongshan Hospital affiliated with Fudan University from December 2021 to December 2023 were enrolled. According to coronary flow reserve (CFR) or reactive congestion index (RHI), enrolled patients were divided into coronary microvascular endothelial dysfunction (CMD) group (CFR<2.5) and no CMD group (CFR≥2.5) or peripheral microvascular endothelial dysfunction (MED) group (RHI<1.67) and no MED group (RHI≥1.67). Patients′ general information, laboratory and auxiliary examination data were collected. Univariate and multivariate logistic regression were used to analyze the influencing factors of CMD and MED in nHFrEF patients, and Spearman correlation analysis was used to evaluate the correlation between MED and CMD.Results:A total of 142 nHFrEF patients were enrolled, aged 69.0 (59.0, 74.0) years, with a male proportion of 66.9% (95/142). The grouping results were as follows: (1) According to CFR, there were 73 cases in the CMD group and 69 cases in the no CMD group; (2) According to RHI, there were 57 cases in the MED group and 85 cases in the no MED group. The prevalence of CMD and MED in this study was 51.4% (73/142) and 40.1% (57/142), respectively. Univariate logistic regression analysis showed that increased heart rate, chronic kidney disease, atrial fibrillation, elevated N-terminal pro-B type natriuretic peptide levels, and increased urinary albumin/creatinine ratio were risk factors for CMD, while increased RHI was a protective factor for CMD; Atrial fibrillation is a risk factor for MED, while increased CFR is a protective factor for MED. Incorporating clinically significant variables from univariate analysis into multivariate analysis, the results showed that increased heart rate and elevated RHI remained risk and protective factors for CMD, respectively; increased CFR remains a protective factor for MED. Spearman correlation analysis showed that CFR was negatively correlated with lg urinary albumin/creatinine ratio, lg cardiac troponin T, lg N-terminal pro-B type natriuretic peptide, and heart rate; RHI is positively correlated with CFR.Conclusions:The prevalence of CMD and MED in nHFrEF patients is high, and the two have a certain positive correlation. Increased heart rate and RHI are risk and protective factors for CMD, respectively, while increased CFR is a protective factor for MED. MED may be a potential therapeutic target for nHFrEF patients.

Objective:To report the nationwide surveillance results of pathogenic profiles and antimicrobial resistance patterns of Gram-positive bloodstream infections in China in 2023.Methods:The clinical isolates of Gram-posttive bacteria from blood cultures were collected in member hospitals of National Bloodstream Infection Bacterial Resistant Investigation Collaborative System（BRICS）during January to December 2023. Antimicrobial susceptibility testing was performed using the dilution method recommended by the Clinical and Laboratory Standards Institute（CLSI）. Statistical analyses were conducted using WHONET 5.6 and SPSS 25.0 software.Results:A total of 4 385 Gram-positive bacterial isolates were obtained from 60 participating center. The top five pathogens were Staphylococcus aureus（ n=1 544，35.2%），coagulase-negative Staphylococci（ n=1 441，32.9%）， Enterococcus faecium（ n=574，13.1%）， Enterococcus faecalis（ n=385，8.8%），and α-hemolytic Streptococci（ n=187，4.3%）. The prevalence of methicillin-resistant Staphylococcus aureus（MRSA）and methicillin-resistant coagulase-negative Staphylococci（MRCNS）was 26.2%（405/1 544）and 69.8%（1 006/1 441），respectively. Notably，all Staphylococci remained susceptible to glycopeptide or daptomycin. Staphylococcus aureus demonstrated excellent susceptibility（>97.0%）to cephalobiol，rifampicin，trimethoprim-sulfamethoxazole，linezolid，minocycline，tigecycline，and eravacycline. No Enterococcus exhibiting resistance to linezolid were detected. Glycopeptide resistance was uncommon but more frequent in Enterococcus faecium（resistance to vancomycin and teicoplanin：both 1.7%）compared to Enterococcus faecalis（both 0.3%）. The detection rates of MRSA and MRCNS exhibited significant regional variations across the country（ χ2=17.674 and 148.650，respectively，both P<0.001）. No vancomycin-resistant Enterococci were detected in central China. Institutional comparison demonstrated higher prevalence of MRSA（ χ2=14.111， P<0.001）and MRCNS（ χ2=4.828， P=0.028）in provincial hospitals than that in municipal hospitals. Socioeconomic analysis identified elevated detection rates of both MRSA（ χ2=18.986， P<0.001）and MRCNS（ χ2=4.477， P=0.034）in less developed regions（per capita GDP

Objective:To report the results of bacterial resistant investigation collaborative system（BRICS）on the distribution and antimicrobial resistance profile of clinical Gram-negative bacteria isolates from bloodstream infections in China in 2023，and provide reference for clinical tretment of bloodstream infections and prevention and control of bacterial resistance.Methods:The clinical isolates of Gram-negative bacteria from blood cultures in member hospitals of BRICS were collected during January 2023 to December 2023. Antibiotic susceptibility tests were conducted by agar dilution or broth dilution methods recommended by Clinical and Laboratory Standards Institute（CLSI）. WHONET 5.6 and SPSS 25.0 were used to analyze the data.Results:During the study period，11 492 strains of Gram-negative bacteria were collected from 60 hospitals，of which 10 098（87.9%）were Enterobacterales and 1 394（12.1%）were non-fermentative bacteria. The top 5 bacterial species were Escherichia coli（50.0%）， Klebsiella pneumoniae（26.1%）， Pseudomonas aeruginosa（5.1%）， Acinetobacter baumannii complex（5.0%）and Enterobacter cloacae complex（4.1%）. The ESBL-producing rates in Escherichia coli， Klebsiella pneumoniae and Proteus mirablilis were 46.8%（2 685/5 741），18.3%（549/2 999）and 44.0%（77/175），respectively. The prevalence of carbapenem-resistant Escherichia coli（CREC）and carbapenem-resistant Klebsiella pneumoniae（CRKP）were 1.3%（76/5 741）and 15.0%（450/2 999）；32.9%（25/76）and 78.0%（351/450）of CREC and CRKP were sensitive to ceftazidime/avibactam combination，respectively. 94.7%（72/76）and 90.2%（406/450）of CREC and CRKP were sensitive to aztreonam/avibactam combination. Furthermore，57.9%（44/76）and 79.1%（356/450）were sensitive to imipenem/relebactam combination. The prevalence of carbapenem-resistant Acinetobacter baumannii（CRAB）complex was 64.6%（370/573），while more than 80.0% of CRAB complex was sensitive to tigecycline，eravacycline and polymyxin B. The prevalence of carbapenem-resistant Pseudomonas aeruginosa（CRPA）was 17.0%（99/581）. There were differences in the composition ratio of Gram-negative bacteria in bloodstream infections and the prevalence of important Gram-negative bacteria resistance among different regions in China，with statistically significant differences in the prevalence of CREC，CRKP，CRPA and CRAB complex（ χ2=10.6，28.6，10.8 and 19.3， P<0.05）. The prevalence of ESBL-producing Escherichia coli， CREC，CRAB complex and CRKP were higher in provincial hospitals than those in municipal hospitals（ χ2=12.5，9.8，12.7 and 57.8，all P<0.01）. Conclusions:Gram-negative bacteria are the main pathogens causing bloodstream infections in China，and Escherichia coli is ranked in the top，while the trend of Klebsiella pneumoniae increases continuously with time. CRKP infection shows a slow upward trend，CREC infecton maintains a low prevalence level，and CRAB complex infection continues to exhibit a high prevalence rate. The composition and resistance patterns of pathogens causing bloodstream infections vary to some extent across different regions and levels of hospitals in China.