Objective To investigate whether successful percutaneous coronary intervention(PCI)could improve symptoms and quality of life(QOL)in left main disease and/or 3-vessel disease patients with diabetes.Methods Patients with left main disease and/or 3-vessel disease who underwent PCI in the First Affiliated Hospital of Air Force Medical University from April 2018 to May 2021 were consecutively enrolled and subdivided into 2 groups:diabetes and no diabetes.Detailed baseline characteristics,symptoms,including dyspnea and angina,assessed with the Rose dyspnea scale(RDS),Seattle angina questionnaire(SAQ),the European quality of life-5 dimensions(EQ-5D)and 12-item short-form health survey(SF-12)questionnaire respectively,procedural details,and 1 month and 1 year follow-up data were collected.Results Among 440 left main disease and/or 3-vessel disease patients,disease was present in 176(40.00％),who had more hypertension,peripheral artery disease,and LCX lesion(all P＜0.05).The incidence of major adverse cardiovascular events(MACE)and all-cause mortality were similar between the two groups(both P＞0.05)at 1 month follow-up,while all-cause mortality in diabetes patients was significantly higher than those without diabetes at 1 year follow-up(P=0.013).Low left ventricular ejection fraction was an independent risk factor for MACE and all-cause mortality at 1 month and 1 year follow-up after successful revascularization(all P＜0.05).Most importantly,symptoms,including dyspnea and angina,and QOL were markedly improved regardless of diabetes both at 1 month and 1 year follow-up(all P＜0.05).Diabetes patients showed improved dyspnea and QOL at similar degree to the non-diabetes patients(all P＞0.05)and a more significantly relieved angina(P=0.013).Additionally,the number of chronic total occlusion(CTO)per patient was identified as an independent risk factor of dyspnea(OR 0.723,95％CI 0.525～0.997,P=0.048)and angina relief(OR 0.686,95％CI 0.473～0.995,P=0.047),and the contrast volume(OR 0.995,95％CI 0.992～0.999,P=0.008)as an independent risk factor of QOL improvement in diabetic patients.Conclusions Successful PCI is beneficial for relieving symptoms and improving quality of life in patients with diabetes who have left main disease and/or 3-vessel disease.

Objective·To optimize iSeroSnFR,a genetically encoded 5-hydroxytryptamine(5-HT)fluorescent sensor based on bacterial periplasmic binding proteins(PBPs),to enhance its performance for both in vivo and in vitro 5-HT detection.Methods·iSeroSnFR1.2 was engineered by replacing the circularly permuted superfolder green fluorescence protein(cpsfGFP)sequence in iSeroSnFR1.0 with that from the acetylcholine sensor iAChSnFR using Gibson assembly.The fluorescence response and kinetic properties of iSeroSnFR1.0 and iSeroSnFR1.2 were compared by overexpressing the sensors in HEK293 cells and puffing with exogenous 5-HT.Additionally,to mimic physiological conditions,cultured mouse cortical neurons infected with Sindbis virus carrying each sensor were electrically stimulated to induce endogenous 5-HT release and further evaluate sensor performance.Results·iSeroSnFR1.2 showed significantly improved performance over iSeroSnFR1.0.In HEK293 cells,it exhibited a 1.5-fold increase in fluorescence response(ΔF/F0)to exogenous 5-HT,along with faster kinetics(rise time:36.3 ms vs 44.9 ms;decay time:1 003.6 ms vs 1 730.4 ms).In cortical neurons,it demonstrated a 2.7-fold increase in response to endogenously released 5-HT,with rise and decay times reduced by 44.0%and 26.7%,respectively.Notably,iSeroSnFR1.2 showed increased basal fluorescence,enabling better imaging in high-background environments.Conclusion·The optimized iSeroSnFR1.2 sensor offers a markedly improved fluorescent response and temporal resolution for 5-HT detection,providing an advanced tool for studying 5-HT dynamics in neuroscience and psychiatric research.

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 whether successful percutaneous coronary intervention(PCI)could improve symptoms and quality of life(QOL)in left main disease and/or 3-vessel disease patients with diabetes.Methods Patients with left main disease and/or 3-vessel disease who underwent PCI in the First Affiliated Hospital of Air Force Medical University from April 2018 to May 2021 were consecutively enrolled and subdivided into 2 groups:diabetes and no diabetes.Detailed baseline characteristics,symptoms,including dyspnea and angina,assessed with the Rose dyspnea scale(RDS),Seattle angina questionnaire(SAQ),the European quality of life-5 dimensions(EQ-5D)and 12-item short-form health survey(SF-12)questionnaire respectively,procedural details,and 1 month and 1 year follow-up data were collected.Results Among 440 left main disease and/or 3-vessel disease patients,disease was present in 176(40.00％),who had more hypertension,peripheral artery disease,and LCX lesion(all P＜0.05).The incidence of major adverse cardiovascular events(MACE)and all-cause mortality were similar between the two groups(both P＞0.05)at 1 month follow-up,while all-cause mortality in diabetes patients was significantly higher than those without diabetes at 1 year follow-up(P=0.013).Low left ventricular ejection fraction was an independent risk factor for MACE and all-cause mortality at 1 month and 1 year follow-up after successful revascularization(all P＜0.05).Most importantly,symptoms,including dyspnea and angina,and QOL were markedly improved regardless of diabetes both at 1 month and 1 year follow-up(all P＜0.05).Diabetes patients showed improved dyspnea and QOL at similar degree to the non-diabetes patients(all P＞0.05)and a more significantly relieved angina(P=0.013).Additionally,the number of chronic total occlusion(CTO)per patient was identified as an independent risk factor of dyspnea(OR 0.723,95％CI 0.525～0.997,P=0.048)and angina relief(OR 0.686,95％CI 0.473～0.995,P=0.047),and the contrast volume(OR 0.995,95％CI 0.992～0.999,P=0.008)as an independent risk factor of QOL improvement in diabetic patients.Conclusions Successful PCI is beneficial for relieving symptoms and improving quality of life in patients with diabetes who have left main disease and/or 3-vessel disease.

Objective·To optimize iSeroSnFR,a genetically encoded 5-hydroxytryptamine(5-HT)fluorescent sensor based on bacterial periplasmic binding proteins(PBPs),to enhance its performance for both in vivo and in vitro 5-HT detection.Methods·iSeroSnFR1.2 was engineered by replacing the circularly permuted superfolder green fluorescence protein(cpsfGFP)sequence in iSeroSnFR1.0 with that from the acetylcholine sensor iAChSnFR using Gibson assembly.The fluorescence response and kinetic properties of iSeroSnFR1.0 and iSeroSnFR1.2 were compared by overexpressing the sensors in HEK293 cells and puffing with exogenous 5-HT.Additionally,to mimic physiological conditions,cultured mouse cortical neurons infected with Sindbis virus carrying each sensor were electrically stimulated to induce endogenous 5-HT release and further evaluate sensor performance.Results·iSeroSnFR1.2 showed significantly improved performance over iSeroSnFR1.0.In HEK293 cells,it exhibited a 1.5-fold increase in fluorescence response(ΔF/F0)to exogenous 5-HT,along with faster kinetics(rise time:36.3 ms vs 44.9 ms;decay time:1 003.6 ms vs 1 730.4 ms).In cortical neurons,it demonstrated a 2.7-fold increase in response to endogenously released 5-HT,with rise and decay times reduced by 44.0%and 26.7%,respectively.Notably,iSeroSnFR1.2 showed increased basal fluorescence,enabling better imaging in high-background environments.Conclusion·The optimized iSeroSnFR1.2 sensor offers a markedly improved fluorescent response and temporal resolution for 5-HT detection,providing an advanced tool for studying 5-HT dynamics in neuroscience and psychiatric research.

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]

The functionalized bimetallic organic framework nanozyme (NiFe2-NMOFs) was prepared using solvothermal method for detection of sarcosine content in human urine. The experimental result showed that Fe and Ni were evenly distributed in the material,and Fe existed in the form of Fe2+/Fe3+,Ni existed in the form of Ni2+. Fe2+/Fe3+was the catalytic active center and Ni2+was the adsorption site. The matching of the two elements improved the catalytic activity of the reaction. The successful introduction of amino group induced defects in the structure,formed open accessible sites,and increased water solubility of the material. The NiFe2-NMOFs were proved to have peroxidase-like activity,and the Michaelis-Menten kinetics of NiFe2-NMOFs showd that the material had good kinetic performance and stability. Based on the fact that sarcosine could generate H2O2 under the catalysis of sarcosinase,and the sensing ability of NiFe2-NMOFs to H2O2,a cascade catalytic sensing system of NiFe2-NMOFs-sarcosine oxidase was constructed for detection of sarcosine content in human urine. This sensing system was used to detect sarcosine within the concentration range of 0.2-120μmol/L,with a good linear relationship,and a low detection limit of 0.17μmol/L. This sensing system showed high recoveries (94.1％-99.1％) and lower relative standard deviations (RSDs<5％) when used to detect actual urine samples. As a comparison to the natural peroxidase,this sensing system had better optimum temperature range and other advantages,showing good application prospects in bioanalysis.

Objective We aimed to compare the efficacy and prognosis of percutaneous coronary intervention(PCI)in complex and high-risk patients with coronary heart disease(CHD)treated with extracorporeal membrane oxygenation(ECMO)combined with intra-aortic balloon pump(IABP)assistance,and explore the application value of combined use of mechanical circulatory support(MCS)devices in complex PCI.Methods A total of patients who met the inclusion criteria and underwent selective PCI supported by MCS at the Department of Cardiology,the First Affiliated Hospital of the Air Force Medical University from January 2018 to December 2022 were continuously enrolled.According to the mechanical circulatory support method,the patients were divided into ECMO+IABP group and IABP group.Clinical characteristics,angiographic features,in-hospital outcomes,and complications were collected.The intra-hospital outcomes and major adverse cardiovascular events(MACE)at one month and one year after the procedure were observed.The differences and independent risk factors between the two groups in the above indicators were analyzed.Results A total of 218 patients undergoing elective PCI were included,of which 66 patients were in the ECMO+IABP group and 152 patients were in the IABP group.The baseline characteristics of the two groups of patients were generally comparable,but the ECMO+IABP group had more complex lesion characteristics.The proportion of patients with atrial fibrillation(6.1％vs.0.7％,P=0.030),left main disease(43.9％vs.27.0％,P=0.018),triple vessel disease(90.9％vs.75.5％,P=0.009),and RCA chronic total occlusion disease(60.6％vs.35.5％,P＜0.001)was higher in the ECMO+IABP group compared to the IABP group.The proportion of patients with previous PCI history was higher in the IABP group(32.9％vs.16.7％,P=0.014).There was no statistically significant difference in the incidence of in-hospital complications between the two groups(P=0.176),but the incidence of hypotension after PCI was higher in the ECMO+IABP group(19.7％vs.9.2％,P=0.031).The rates of 1-month MACE(4.5％vs.2.6％,P=0.435)and 1-year MACE(7.6％vs.7.9％,P=0.936)were comparable between the two groups.Multivariate analysis showed that in-hospital cardiac arrest(OR 7.17,95％CI 1.27-40.38,P=0.025)and after procedure hypotension(OR 3.60,95％CI 1.10-11.83,P=0.035)were independent risk factors for the occurrence of 1-year MACE.Conclusions Combination use of ECMO+IABP support can provide complex and high-risk coronary heart disease patients with an opportunity to achieve coronary artery revascularization through PCI,and achieve satisfactory long-term prognosis.

Objective: To observe the characteristics of the evolution of liver indexes in patients with relapsed/refractory multiple myeloma (RRMM) treated with CAR-T-cells based on BCMA. Methods: Retrospective analysis was performed of patients with RRMM who received an infusion of anti-BCMA CAR-T-cells and anti-BCMA combined with anti-CD19 CAR-T-cells at our center between June 1, 2019, and February 28, 2023. Clinical data were collected to observe the characteristics of changes in liver indexes such as alanine aminotransferase (ALT), aspartate aminotransferase (AST), total bilirubin (TBIL), and direct bilirubin (DBIL) in patients, and its relationship with cytokine-release syndrome (CRS) . Results: Ninety-two patients were included in the analysis, including 41 patients (44.6%) in the group receiving a single infusion of anti-BCMA CAR-T-cells, and 51 patients (55.4%) in the group receiving an infusion of anti-BCMA combined with anti-CD19 CAR-T-cells. After infusing CAR-T-cells, 31 patients (33.7%) experienced changes in liver indexes at or above grade 2, which included 20 patients (21.7%) with changes in one index, five patients (5.4%) with changes in two indexes, and six patients (6.5%) with changes in three or more indexes. The median time of peak values of ALT and AST were d17 and d14, respectively, and the median duration of exceeding grade 2 was 5.0 and 3.5 days, respectively. The median time of peak values of TBIL and DBIL was on d19 and d21, respectively, and the median duration of exceeding grade 2 was 4.0 days, respectively. The median time of onset of CRS was d8, and the peak time of fever was d9. The ALT, AST, and TBIL of patients with CRS were higher than those of patients without CRS (P=0.011, 0.002, and 0.015, respectively). CRS is an independent factor that affects ALT and TBIL levels (OR=19.668, 95% CI 18.959-20.173, P=0.001). The evolution of liver indexes can be reversed through anti-CRS and liver-protection treatments, and no patient died of liver injury. Conclusions: In BCMA-based CAR-T-cell therapy for RRMM, CRS is an important factor causing the evolution of liver indexes. The evolution of liver indexes after CAR-T-cell infusion is transient and reversible after treatment.
Humans ; Antigens, CD19 ; B-Cell Maturation Antigen/therapeutic use* ; Bilirubin ; Immunotherapy, Adoptive ; Liver ; Multiple Myeloma/drug therapy* ; Retrospective Studies ; T-Lymphocytes

ObjectiveTo investigate the risk factors and construct a predictive model for severe myelosuppression due to chemotherapy in triple negative breast cancer （TNBC）. MethodsPatients with TNBC who received anthracycline combined with cyclophosphamide sequential paclitaxel chemotherapy regimen at the Second Affiliated Hospital of Nanchang University from September 2， 2016 to September 2， 2021 were selected and assigned to severe myelosuppression group and no/mild myelosuppression group. The χ² test and binary logistic regression were used to analyze the risk factors for severe myelosuppression due to chemotherapy and to develop a prediction model. Hosmer-Lemeshow test and receiver operating characteristic （ROC） curve were used to evaluate the predictive efficiency of the regression model. Kappa consistency test was used to verify the regression model externally. ResultsA total of 207 patients who met the inclusion were enrolled and 106 patients （51%） had severe myelosuppression. Binary logistic regression multivariate analysis showed that age 40 to 60 years （OR = 3.463， 95% CI： 1.144 to 10.486， P = 0.028）， age >60 years （OR = 3.474， 95% CI： 1.004 to 12.020， P = 0.049）， body mass index （BMI） 18.5 to 24.0 （OR = 1.445， 95% CI： 0.686 to 3.087， P = 0.328）， BMI <18.5 （OR = 3.582， 95% CI： 1.260 to 10.182， P = 0.017）， tumor TNM stage Ⅱ （OR = 1.698， 95% CI： 0.831 to 3.468， P = 0.146）， tumor TNM stage Ⅲ （OR = 2.943， 95% CI： 1.199 to 7.227， P = 0.019）， previous diabetes （OR = 2.441， 95% CI： 1.076 to 5.539， P = 0.033）， low pre-treatment albumin level （OR = 2.759， 95% CI： 1.141 to 6.669， P = 0.024） and low pre-treatment lymphocytes （OR = 3.428， 95% CI： 1.689 to 6.958， P = 0.001） were independent risk factors for severe myelosuppression due to chemotherapy. The χ² value for the logistic regression model Hosmer-Lemeshow test was 11.507， P= 0.175， the area under the ROC curve was 0.763， standard error 0.033， 95% CI： 0.698-0.828， P=0.000. External validation showed that the prediction model had a specificity of 88% and a sensitivity of 80%； the kappa value was 0.679， standard error 0.081， P=0.000. conclusionThis logistic regression model had high predictive efficacy and is useful for clinicians to predict whether patients with TNBC develop severe myelosuppression.