Objective:To investigate the predictive value of pre-infarction angina(PIA)combined with serum lipo-protein-associated phospholipase A2(Lp-PLA2)for no-reflow during primary percutaneous coronary interven-tion(PCI)in elderly patients with new-onset acute ST-segment elevation myocardial infarction(STEMI).Meth-ods:A total of 189 patients who hospitalized because of acute STEMI and underwent primary PCI within 12h in De-partment of Cardiology,Cangzhou People's Hospital between January 2018 and December 2022 were enrolled.Ac-cording to their TIMI blood flow during PCI,the patients were divided into no reflow group(n=42)and normal re-flow group(n=147).The baseline data were compared between two groups.Multivariate Logistic regression analy-sis was used to analyze the risk factors of no-reflow during PCI.The receiver operating characteristic(ROC)curve was plotted to evaluate the predictive value of PIA and Lp-PLA2 for no-reflow.Results:PI A occurred in 73 cases(38.6％),and no reflow occurred in 42 cases(22.2％)during primary PCI.Compared with patients in normal re-flow group,those in no reflow group had significant higher Lp-PLA2[(341.33±98.32)ng/ml vs.(261.95±75.21)ng/ml]and onset to reperfusion time[(7.02±1.28)h vs.(5.14±1.48)h],and significant lower incidence of PIA(23.8％ vs.42.9％)(P＜0.05 or＜0.01).Multivariate Logistic regression analysis showed that Lp-PLA2(OR=1.528,95％CI 1.028～2.030,P＜0.001),onset to reperfusion time(OR=2.602,95％CI 1.848～3.665,P＜0.001)were independent risk factors for no reflow during PCI in elderly STEMI patients,while PIA was an inde-pendent protective factor(OR=0.261,95％CI 0.101～0.671,P=0.005).The area under ROC curve of Lp-PLA2 combined PIA was 0.863(95％CI 0.806～0.909),which was significantly higher than those of Lp-PLA2[0.733(95％CI 0.664～0.794),Z=2.690,P=0.007]and PIA alone[0.609(95％CI 0.535～0.679),Z=5.657,P＜0.001].Conclusion:Pre-infarction angina has an important protective effect on no-reflow in STEMI patients.High Lp-PLA2 and absence of pre-infarction angina at admission may be good predictors of no-reflow during primary PCI in elderly patients with newly-onset acute STEMI,and it contributes to risk stratification of high risk patients.

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.

Objective:To investigate the predictive value of pre-infarction angina(PIA)combined with serum lipo-protein-associated phospholipase A2(Lp-PLA2)for no-reflow during primary percutaneous coronary interven-tion(PCI)in elderly patients with new-onset acute ST-segment elevation myocardial infarction(STEMI).Meth-ods:A total of 189 patients who hospitalized because of acute STEMI and underwent primary PCI within 12h in De-partment of Cardiology,Cangzhou People's Hospital between January 2018 and December 2022 were enrolled.Ac-cording to their TIMI blood flow during PCI,the patients were divided into no reflow group(n=42)and normal re-flow group(n=147).The baseline data were compared between two groups.Multivariate Logistic regression analy-sis was used to analyze the risk factors of no-reflow during PCI.The receiver operating characteristic(ROC)curve was plotted to evaluate the predictive value of PIA and Lp-PLA2 for no-reflow.Results:PI A occurred in 73 cases(38.6％),and no reflow occurred in 42 cases(22.2％)during primary PCI.Compared with patients in normal re-flow group,those in no reflow group had significant higher Lp-PLA2[(341.33±98.32)ng/ml vs.(261.95±75.21)ng/ml]and onset to reperfusion time[(7.02±1.28)h vs.(5.14±1.48)h],and significant lower incidence of PIA(23.8％ vs.42.9％)(P＜0.05 or＜0.01).Multivariate Logistic regression analysis showed that Lp-PLA2(OR=1.528,95％CI 1.028～2.030,P＜0.001),onset to reperfusion time(OR=2.602,95％CI 1.848～3.665,P＜0.001)were independent risk factors for no reflow during PCI in elderly STEMI patients,while PIA was an inde-pendent protective factor(OR=0.261,95％CI 0.101～0.671,P=0.005).The area under ROC curve of Lp-PLA2 combined PIA was 0.863(95％CI 0.806～0.909),which was significantly higher than those of Lp-PLA2[0.733(95％CI 0.664～0.794),Z=2.690,P=0.007]and PIA alone[0.609(95％CI 0.535～0.679),Z=5.657,P＜0.001].Conclusion:Pre-infarction angina has an important protective effect on no-reflow in STEMI patients.High Lp-PLA2 and absence of pre-infarction angina at admission may be good predictors of no-reflow during primary PCI in elderly patients with newly-onset acute STEMI,and it contributes to risk stratification of high risk patients.

Objective To propose a novel identification algorithm based on ensemble learning for assessing the severity of acute respiratory distress syndrome(ARDS)to achieve continuous monitoring of the disease severity.Methods Firstly,leve-raging the open-source MIMIC-Ⅳ database,a variety of non-invasive physiological parameters of patients were extracted and subjected to preliminary preprocessing.A multivariate feature selection algorithm was employed to rank these parameters and calculate feature importance scores through weighted computation.Secondly,based on the feature importance scores,a subset search algorithm was utilized to identify the subset of features that could yield optimal performance across four machine learning algorithms:neural networks,logistic regression,AdaBoost and XGBoost.Finally,a soft voting ensemble method was designed using a generalized linear regression model to integrate the results of each single machine learning algorithm,and a multivariate ensemble learning algorithm was proposed by combining the optimal feature subsets.The algorithm proposed when used to identify the severity of ADRS was evaluated with MIMIC-Ⅳ database,and compared with the traditional algorithms.Results The sensitivity,specificity,accuracy and AUC of the algorithm were 87.15％,89.23％,88.34％and 0.923 4,respectively,all of which outperformed those of the traditional algorithms.Conclusion The ARDS severity identification algorithm based on ensemble learning is capable of achieving continuous and real-time monitoring of the severity of ARDS,thereby offering robust support for the early identification and warning of ARDS in patients.[Chinese Medical Equipment Journal,2025,46(2):1-9]

Aim To investigate the effect of Panax no-toginseng saponins(PNS)on the interaction between endometrial cancer cells and macrophages by regulating the epidermal growth factor receptor(EGFR)/heat shock protein 27(HSP27)axis.Methods Ishikawa cells were divided into Control,DDP,PNS-treated,M2-CM,M2-CM+DDP,M2-CM+PNS,M2-CM+PNS+oe-NC,M2-CM+PNS+oe-EGFR,PNS(200 mg·L-1)+oe-NC,PNS(200 mg·L-1)+oe-EG-FR,oe-NC,oe-EGFR,oe-EGFR+si-NC,and oe-EG-FR+si-HSP27 groups.MTT assay was used to detect cell proliferation,Transwell assay for cell invasion,TUNEL assay for cell apoptosis,qRT-PCR for macro-phage polarization markers CD86 and CD163 mRNA levels,ELISA for iNOS and IL-12 levels,and West-ern-blot for EGFR and HSP27 protein expression.A nude mouse xenograft tumor model was established and treated with PNS to evaluate the effect of PNS in vivo.Results Compared with the Control group,PNS and DDP significantly inhibited the proliferation and inva-sion of Ishikawa cells and induced apoptosis.M2-CM treatment inhibited M1 macrophage markers,promoted M2 macrophage markers,and induced Ishikawa cell growth,but this effect was reversed by PNS treatment.EGFR was confirmed as a target of PNS,and compared with the M2-CM+PNS+oe-NC group,EGFR overex-pression promoted M2 macrophage marker levels,in-duced Ishikawa cell proliferation and invasion,and in-hibited apoptosis.Knockdown of HSP27 reversed the effect of EGFR overexpression on the biological behav-ior of Ishikawa cells.Animal experiments showed that PNS could inhibit tumor growth and reduce the positive expression of CD163,EGFR,and HSP27 in tumor tis-sues.Conclusion PNS affects the interaction be-tween macrophages and EC cells by regulating the EG-FR/HSP27 axis,thereby participating in EC progres-sion.

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.

Objective To investigate the effect of loganin(Log)on glutamine metabolism in cervical cancer through the regula-tion of nuclear factor red blood cell 2 related factor 2(NFE2L2)-ferritin heavy chain 1(FTH1)-glutathione peroxidase 4(GPX4).Methods Bioinformatics analysis was conducted to identify common targets of Log,glutamine metabolism,and cervical cancer.Hela cells were divided into Blank,control(Ctrl),Log,cisplatin(DDP),NFE2L2 activator(TBHQ),NFE2L2 inhibitor(ML385),and TBHQ+Log groups to detect cell proliferation,invasion,apoptosis,glutamine metabolism,and the protein expression of NFE2L2,FTH1,and GPX4.A cervical cancer xenograft mouse model was established to investigate the in vivo effects of Log on the progression of cervical cancer.Results Bioinformatics analysis confirmed that NFE2L2 might be a target of Log in the treatment of cervical cancer.Both Log and DDP reduced the proliferation and invasion abilities of Hela cells,increased apoptosis,and decreased the levels of glutamine and glutamic acid,as well as the protein expression of glutaminase(GLS1)and glutamic dehydrogenase(GLUD1,P<0.05).The NFE2L2 activator TBHQ had opposite effects,whereas ML385 had a similar impact on the Log.Additionally,Log treatment inhibited the protein expression of NFE2L2,FTH1,and GPX4(P<0.05).Animal experiments showed that Log significantly inhibited cervical cancer progression(P<0.05).Conclusion Log affects cervical cancer progression via glutamine metabolism by inhibiting the NFE2L2-FTH1-GPX4 signaling pathway.

Objective To propose a novel identification algorithm based on ensemble learning for assessing the severity of acute respiratory distress syndrome(ARDS)to achieve continuous monitoring of the disease severity.Methods Firstly,leve-raging the open-source MIMIC-Ⅳ database,a variety of non-invasive physiological parameters of patients were extracted and subjected to preliminary preprocessing.A multivariate feature selection algorithm was employed to rank these parameters and calculate feature importance scores through weighted computation.Secondly,based on the feature importance scores,a subset search algorithm was utilized to identify the subset of features that could yield optimal performance across four machine learning algorithms:neural networks,logistic regression,AdaBoost and XGBoost.Finally,a soft voting ensemble method was designed using a generalized linear regression model to integrate the results of each single machine learning algorithm,and a multivariate ensemble learning algorithm was proposed by combining the optimal feature subsets.The algorithm proposed when used to identify the severity of ADRS was evaluated with MIMIC-Ⅳ database,and compared with the traditional algorithms.Results The sensitivity,specificity,accuracy and AUC of the algorithm were 87.15％,89.23％,88.34％and 0.923 4,respectively,all of which outperformed those of the traditional algorithms.Conclusion The ARDS severity identification algorithm based on ensemble learning is capable of achieving continuous and real-time monitoring of the severity of ARDS,thereby offering robust support for the early identification and warning of ARDS in patients.[Chinese Medical Equipment Journal,2025,46(2):1-9]

Objective To investigate the effect of loganin(Log)on glutamine metabolism in cervical cancer through the regula-tion of nuclear factor red blood cell 2 related factor 2(NFE2L2)-ferritin heavy chain 1(FTH1)-glutathione peroxidase 4(GPX4).Methods Bioinformatics analysis was conducted to identify common targets of Log,glutamine metabolism,and cervical cancer.Hela cells were divided into Blank,control(Ctrl),Log,cisplatin(DDP),NFE2L2 activator(TBHQ),NFE2L2 inhibitor(ML385),and TBHQ+Log groups to detect cell proliferation,invasion,apoptosis,glutamine metabolism,and the protein expression of NFE2L2,FTH1,and GPX4.A cervical cancer xenograft mouse model was established to investigate the in vivo effects of Log on the progression of cervical cancer.Results Bioinformatics analysis confirmed that NFE2L2 might be a target of Log in the treatment of cervical cancer.Both Log and DDP reduced the proliferation and invasion abilities of Hela cells,increased apoptosis,and decreased the levels of glutamine and glutamic acid,as well as the protein expression of glutaminase(GLS1)and glutamic dehydrogenase(GLUD1,P<0.05).The NFE2L2 activator TBHQ had opposite effects,whereas ML385 had a similar impact on the Log.Additionally,Log treatment inhibited the protein expression of NFE2L2,FTH1,and GPX4(P<0.05).Animal experiments showed that Log significantly inhibited cervical cancer progression(P<0.05).Conclusion Log affects cervical cancer progression via glutamine metabolism by inhibiting the NFE2L2-FTH1-GPX4 signaling pathway.

Lung cancer is the most common malignant tumor worldwide, ranking first in both incidence and mortality rates. According to the latest statistics from the International Agency for Research on Cancer (IARC), approximately 2.5 million new cases and around 1.8 million deaths from lung cancer occurred in 2022, placing a tremendous burden on global healthcare systems. The high mortality rate of lung cancer is closely linked to its subtle early symptoms, which often lead to diagnosis at advanced stages. This not only complicates treatment but also results in substantial economic losses. Current treatment options for lung cancer include surgery, radiotherapy, chemotherapy, targeted drug therapy, and immunotherapy. Among these, immunotherapy has emerged as the most groundbreaking advancement in recent years, owing to its unique antitumor mechanisms and impressive clinical benefits. Unlike traditional therapies such as radiotherapy and chemotherapy, immunotherapy activates or enhances the patient’s immune system to recognize and eliminate tumor cells. It offers advantages such as more durable therapeutic effects and relatively fewer toxic side effects. The main approaches to lung cancer immunotherapy include immune checkpoint inhibitors, tumor-specific antigen-targeted therapies, adoptive cell therapies, cancer vaccines, and oncolytic virus therapies. Among these, immune checkpoint inhibitors and tumor-specific antigen-targeted therapies have received approval from the U.S. Food and Drug Administration (FDA) for clinical use in lung cancer, significantly improving outcomes for patients with advanced non-small cell lung cancer. Although other immunotherapy strategies are still in clinical trials, they show great potential in improving treatment precision and efficacy. This article systematically reviews the latest research progress in lung cancer immunotherapy, including the development of novel immune checkpoint molecules, optimization of treatment strategies, identification of predictive biomarkers, and findings from recent clinical trials. It also discusses the current challenges in the field and outlines future directions, such as the development of next-generation immunotherapeutic agents, exploration of more effective combination regimens, and the establishment of precise efficacy prediction systems. The aim is to provide a valuable reference for the continued advancement of lung cancer immunotherapy.