Objective To investigate the relationship between four metabolic indices reflecting insulin resistance(IR)and the risk of diabetic kidney disease(DKD)in patients with type 2 diabetes mellitus(T2DM).Methods 157 T2DM patients with DKD(DKD group)and 198 T2DM patients(T2DM group)were included in our study.The general data and clinical indicators were collected.Triglyceride/high density lipoprotein cholesterol ratio(TG/HDL-C),triglyceride glucose(TyG)index,triglyceride glucose-body mass index(TyG-BMI)and metabolic score for IR(METS-IR)were calculated.Results Compared with T2DM group,TG/HDL-C,TyG index,TyG-BMI and METS-IR in DKD group were significantly increased(P<0.05).Logistic regression analysis showed that TyG index(OR=8.303,95%CI 1.787～38.573,P=0.007)was an independent risk factor for DKD.The risk of DKD in the fourth quantile of TyG index group was 5.652 times than the first quantile group(P<0.05).ROC curve analysis showed that when the cutoff value of TyG index was 9.03,its sensitivity and specificity for predicting DKD were 56.7%and 71.7%,respectively.Conclusions Among the four simple IR indicators,TyG index is an independent risk factor for the occurrence of DKD in T2DM patients.Increased TyG index indicates increased UACR level and high risk of DKD.

Chimeric antigen receptor-modified T(CAR-T)cell therapy,as a new type of cellular immunotherapy,has shown good clinical efficacy in the treatment of malignant hematological tumors,especially B-cell acute lympho-blastic leukemia.However,there are problems such as antigen loss and immune evasion in single-target selection,so multi-target therapy strategies are gradually gaining attention.Multi-target CAR-T can effectively avoid antigen escape caused by a single target by targeting multiple tumor-associated antigens at the same time,reduce the risk of recurrence,and is expected to improve the therapeutic effect.This paper primarily discusses the structural types of multi-target CAR-T cell therapy and its clinical trial applications in the treatment of B-cell acute lymphoblastic leu-kemia(B-ALL),aiming to provide future references for the treatment of B-ALL.

OBJECTIVE To investigate a suspected outbreak of carbapenem-resistant Klebsiella pneumoniae(CRKP)infection in the intensive care unit of a traditional Chinese medicine hospital,identify the source of infec-tion and transmission routes,and provide a basis for prevention and control of CRKP infection.METHODS Epide-miological investigations were conducted on five patients with CRKP infections or colonization who were identi-fied in Jul.2024 at Suiyang County Hospital of Traditional Chinese Medicine.Samples were collected from pa-tients,the ward environments,and hand surfaces to detect CRKP.Fourteen CRKP isolates were selected for car-bapenemase gene testing,and homology analysis was performed by enterobacterial repetitive intergenic consensus polymerase chain reaction(ERIC-PCR)and multilocus sequence typing(MLST).RESULTS The median age of the five cases was 73 years,and all had undergone multiple invasive procedures.Environmental monitoring showed a CRKP positive rate of 26.35％,with CRKP isolates detected on the hands of healthcare workers,surfaces in the wards and medical equipment surfaces.Genetic analysis showed that all 14 CRKP strains carried the KPC resist-ance gene;except for case 1,other strains carried the VIM gene.MLST identified CRKP of all strains as sequence type 48(ST48);while ERIC-PCR revealed two distinct genotypes:genotype A for case 1 and genotype B for the other cases and environmental isolates.After strengthening patient isolation and group treatment,strictly cleaning and disinfecting the ward environments and medical equipment,and strictly implementing hand hygiene,the infec-tion was effectively controlled.CONCLUSIONS Inadequate disinfection of the ward environments and medical e-quipment and poor compliance with hand hygiene are the main contributors to the suspected CRKP outbreak.Ho-mology analysis suggests the existence of two independent transmission chains.Timely identification and manage-ment of the infection sources,interruption of transmission routes,protection of susceptible individuals and imple-mentation of comprehensive infection control measures are essential for effective outbreak control.

Objective To investigate the relationship between four metabolic indices reflecting insulin resistance(IR)and the risk of diabetic kidney disease(DKD)in patients with type 2 diabetes mellitus(T2DM).Methods 157 T2DM patients with DKD(DKD group)and 198 T2DM patients(T2DM group)were included in our study.The general data and clinical indicators were collected.Triglyceride/high density lipoprotein cholesterol ratio(TG/HDL-C),triglyceride glucose(TyG)index,triglyceride glucose-body mass index(TyG-BMI)and metabolic score for IR(METS-IR)were calculated.Results Compared with T2DM group,TG/HDL-C,TyG index,TyG-BMI and METS-IR in DKD group were significantly increased(P<0.05).Logistic regression analysis showed that TyG index(OR=8.303,95%CI 1.787～38.573,P=0.007)was an independent risk factor for DKD.The risk of DKD in the fourth quantile of TyG index group was 5.652 times than the first quantile group(P<0.05).ROC curve analysis showed that when the cutoff value of TyG index was 9.03,its sensitivity and specificity for predicting DKD were 56.7%and 71.7%,respectively.Conclusions Among the four simple IR indicators,TyG index is an independent risk factor for the occurrence of DKD in T2DM patients.Increased TyG index indicates increased UACR level and high risk of DKD.

OBJECTIVE To investigate a suspected outbreak of carbapenem-resistant Klebsiella pneumoniae(CRKP)infection in the intensive care unit of a traditional Chinese medicine hospital,identify the source of infec-tion and transmission routes,and provide a basis for prevention and control of CRKP infection.METHODS Epide-miological investigations were conducted on five patients with CRKP infections or colonization who were identi-fied in Jul.2024 at Suiyang County Hospital of Traditional Chinese Medicine.Samples were collected from pa-tients,the ward environments,and hand surfaces to detect CRKP.Fourteen CRKP isolates were selected for car-bapenemase gene testing,and homology analysis was performed by enterobacterial repetitive intergenic consensus polymerase chain reaction(ERIC-PCR)and multilocus sequence typing(MLST).RESULTS The median age of the five cases was 73 years,and all had undergone multiple invasive procedures.Environmental monitoring showed a CRKP positive rate of 26.35％,with CRKP isolates detected on the hands of healthcare workers,surfaces in the wards and medical equipment surfaces.Genetic analysis showed that all 14 CRKP strains carried the KPC resist-ance gene;except for case 1,other strains carried the VIM gene.MLST identified CRKP of all strains as sequence type 48(ST48);while ERIC-PCR revealed two distinct genotypes:genotype A for case 1 and genotype B for the other cases and environmental isolates.After strengthening patient isolation and group treatment,strictly cleaning and disinfecting the ward environments and medical equipment,and strictly implementing hand hygiene,the infec-tion was effectively controlled.CONCLUSIONS Inadequate disinfection of the ward environments and medical e-quipment and poor compliance with hand hygiene are the main contributors to the suspected CRKP outbreak.Ho-mology analysis suggests the existence of two independent transmission chains.Timely identification and manage-ment of the infection sources,interruption of transmission routes,protection of susceptible individuals and imple-mentation of comprehensive infection control measures are essential for effective outbreak control.

Objective To explore the correlation between peripheral blood microRNA-34a(miR-34a),mi-croRNA-431(miR-431),and microRNA-183(miR-183)levels with hemodynamics and hearing prognosis in patients with sudden deafness(SD).Methods A total of 132 patients with SD who visited the First Affiliated Hospital of Air Force Medical University(the hospital)from January 2021 to December 2023 were included as the disease group,132 healthy individuals(without SD)who came to the hospital for physical examination were used as the control group.Real-time fluorescence quantitative PCR(RT-qPCR)was used to detect the levels of miR-34a,miR-431,and miR-183 in peripheral blood.Pearson correlation was applied to analyze the correlation between peripheral blood miR-34a,miR-431,miR-183 levels and hemodynamic indicators.Multiple Logistic regression analysis(stepwise forward method)was applied to screen for factors affecting the hearing prognosis of patients with SD.Receiver operating characteristic(ROC)curve was plotted to obtain the area under the curve(AUC)of the single and combination of peripheral blood miR-34a,miR-431,and miR-183 in predicting hearing prognosis in patients with SD,and the AUC was compared using Z-test.Results The levels of miR-34a and miR-431 in the peripheral blood in the disease group were greatly higher than those in the con-trol group,while the level of miR-183 was greatly lower than that in the control group(P＜0.05).After treatment,the whole blood high shear viscosity(HSV),whole blood low shear viscosity(LSV),plasma vis-cosity(PV)of patients with SD were greatly lower than those before treatment(P＜0.05).The levels of miR-34a and miR-431 in peripheral blood of patients with SD were positively correlated with pre-treatment levels of HSV,LSV,and PV(P＜0.05),while the levels of miR-183 were negatively correlated with pre-treatment levels of HSV,LSV,and PV(P＜0.05).The miR-34a and miR-431 levels in the peripheral blood in the good prognosis group were greatly lower than those in the poor prognosis group,and the miR-183 level was greatly higher than that in the poor prognosis group(P＜0.05).The risk factors affecting the hearing prognosis of patients with SD included miR-34a and miR-431,and miR-183 was a protective factor affecting the hearing prognosis of patients with SD(P＜0.05).The AUC of peripheral blood miR-34a,miR-431,and miR-183 in predicting hearing prognosis in patients with SD was 0.969(95％CI:0.938-1.00),and the pre-dictive value of the the combination of the three was higher than that of miR-34a(Z=2.336,P=0.019),miR-431(Z=2.157,P=0.031),and miR-183(Z=2.351,P=0.019)alone.Conclusion The levels of miR-34a and miR-431 are abnormally elevated in peripheral blood of patients with SD,and are positively correlated with hemodynamic indicators.The level of miR-183 is abnormally reduced and is negatively correlated with hemodynamic indicators.The combination of the three has certain predictive value for the hearing prognosis of patients with SD.

Objective:To explore the differences in gut microbiota and immune factors in fecal lysate of children with different clinical subtypes of Mycoplasma pneumoniae pneumonia (MPP). Methods:Children aged 3-14 years with MPP who visited Shanghai Ninth People′s Hospital from March 2023 to February 2024 were selected and divided into general group (GMPP group) and severe group (SMPP group) based on the severity of the condition. They were also divided into non-refractory group (NRMPP group) and refractory group (RMPP group) based on treatment response. 16S rRNA sequencing was used to analyze the characteristics of gut microbiota, and MSD electrochemiluminescence method was used to determine the levels of immune factors in fecal lysate. Differences in the clinical characteristics, gut microbiota, and fecal immune factors were analyzed. Spearman correlation analysis was performed. Receiver operating characteristic(ROC) curve was used to analyze the evaluation and predictive value of gut microbiota in clinical classification of MPP.Results:Among the 64 children with MPP, there were 34 cases in the GMPP group and 30 cases in the SMPP group. There were statistically significant differences between the two groups in terms of fever duration, presence or absence of hypoxemia, C-reactive protein(CRP), D-Dimer, and chest CT scores ( t=-4.94, P<0.001; χ2=5.33, P=0.021; z=-2.93, P=0.003; z=-3.93, P<0.001; z=-4.10, P<0.001). Among the 64 children with MPP, there were 50 cases in the NRMPP group and 14 cases in the RMPP group. There were statistically significant differences in age, fever duration, and chest CT scores between the two groups ( t=-3.21, P=0.002; t=-5.28, P<0.001; z=-2.95, P=0.003). There was no statistically significant difference in the alpha diversity analysis of gut microbiota between GMPP group and SMPP group( P>0.05). There was a statistically significant difference in beta diversity analysis between the two groups of gut microbiota ( R2=0.06, P=0.001). Species difference analysis showed that the relative abundance of Bifidobacterium in the SMPP group was significantly lower than that in the GMPP group, while the relative abundance of Blautia and Ruminococcus gnavus was significantly higher than that in the GMPP group, with statistical significance ( z=5.21, P<0.001, Q=0.039; z=1.56, P<0.001, Q=0.039; z=2.08, P=0.007, Q=0.700). There was no statistically significant difference in the alpha diversity analysis of gut microbiota between NRMPP and RMPP group( P>0.05). There was a statistically significant difference in beta diversity analysis between the two groups of gut microbiota ( R2=0.05, P=0.001). Analysis of species differences showed that the relative abundance of Bifidobacterium and Subdoligranulum in the RMPP group was significantly lower than that in the NRMPP group, while the relative abundance of Blautia and Ruminococcus gnavus was significantly higher than that in the NRMPP group, with statistical significance( z=3.44, P=0.012, Q=0.638; z=3.64, P=0.040, Q=0.638; z=5.80, P=0.001, Q=0.338; z=5.46, P=0.015, Q=0.638). The level of fecal immune factors IL-10 and IL-1β were statistically significant between GMPP group and SMPP group( z=-1.96, P=0.050; z=-2.46, P=0.014). The level of fecal immune factors IFN-γ, IL-10, IL-1β, IL-8, and TNF-α were statistically significant between NRMPP group and RMPP group ( z=-2.20, P=0.028; z=-2.17, P=0.030; z=-2.00, P=0.046; z=-2.14, P=0.032; z=-2.22, P=0.027). Sperman correlation analysis showed that Bifidobacterium was negatively correlated with fever duration and chest CT score ( r=-0.35, P=0.005; r=-0.30, P=0.017); Blautia was positively correlated with D-Dimer, fever duration, and chest CT score ( r=0.33, P=0.008; r=0.37, P=0.003; r=0.40, P=0.001); Ruminococcus gnavus and TNF-α, IL-10, IL-4, and IL-6 were negatively correlated ( r=-0.34, P=0.001; r=-0.29, P=0.021; r=-0.28, P=0.024; r=-0.28, P=0.027). ROC curve analysis showed that the area under curve(AUC) of Bifidobacterium abundance for assessing the severity of MPP was 0.767 (95% CI: 0.649-0.885, P<0.001). The AUC of Blautia abundance for assessing the severity of MPP was 0.774 (95% CI: 0.658-0.889, P<0.001), and the AUC for predicting treatment response to MPP was 0.787 (95% CI: 0.655-0.919, P=0.001). Conclusions:The levels of fecal immune factors vary among children with different clinical subtypes of MPP. The relative abundance analysis of Bifidobacterium and Blautia in the gut microbiota of children with MPP may have certain clinical value for evaluating the severity of MPP, adopting adjuvant therapy, and predicting treatment response.

Objective:To explore the application of COVID-19-specific IgG antibody in identifying epidemic Omicron BA.5 strain infection.Method:Omicron BF.7/BA.5 naturally infected population, healthy population vaccinated with the COVID-19 vaccine, and Omicron BF.7/BA.5 breakthrough cases were enrolled into this study. The serum WT-S-IgG and BA.5-S-IgG were detected by indirect ELISA, and the serum-specific IgG antibody levels of different populations were compared. The application value of the two antibody titers and the ratio of the two antibodies in identifying Omicron BA.5 epidemic strain infection were explored by the ROC curve, aiming to provide technical support for pathogen diagnosis.Results:The antibody titers of WT-S-IgG and BA.5-S-IgG in the breakthrough cases were higher than those in the naturally infected population and the healthy population ( P<0.05). The area under the curve (AUC) of WT-S-IgG and BA.5-S-IgG in identifying epidemic Omicron BA.5 strain infection was 0.947 and 0.961, respectively. The AUC of BA.5-S-IgG and WT-S-IgG antibody titer ratio was 0.873. When the antibody titer ratio was 0.855, the sensitivity and specificity were 80.00% and 90.00%, respectively. According to the interval since the last infection, the AUC of the ratio of BA.5-S-IgG to WT-S-IgG antibody titer to identify the infection of epidemic strains less than 30 days and more than 30 days was 0.887 and 0.863, respectively, and the sensitivity and specificity were both above 80%. Conclusion:Both BA.5-S-IgG and WT-S-IgG, as well as the combination of these two antibodies, are of high value in the identification of epidemic strains.

Objective:To explore the application of COVID-19-specific IgG antibody in identifying epidemic Omicron BA.5 strain infection.Method:Omicron BF.7/BA.5 naturally infected population, healthy population vaccinated with the COVID-19 vaccine, and Omicron BF.7/BA.5 breakthrough cases were enrolled into this study. The serum WT-S-IgG and BA.5-S-IgG were detected by indirect ELISA, and the serum-specific IgG antibody levels of different populations were compared. The application value of the two antibody titers and the ratio of the two antibodies in identifying Omicron BA.5 epidemic strain infection were explored by the ROC curve, aiming to provide technical support for pathogen diagnosis.Results:The antibody titers of WT-S-IgG and BA.5-S-IgG in the breakthrough cases were higher than those in the naturally infected population and the healthy population ( P<0.05). The area under the curve (AUC) of WT-S-IgG and BA.5-S-IgG in identifying epidemic Omicron BA.5 strain infection was 0.947 and 0.961, respectively. The AUC of BA.5-S-IgG and WT-S-IgG antibody titer ratio was 0.873. When the antibody titer ratio was 0.855, the sensitivity and specificity were 80.00% and 90.00%, respectively. According to the interval since the last infection, the AUC of the ratio of BA.5-S-IgG to WT-S-IgG antibody titer to identify the infection of epidemic strains less than 30 days and more than 30 days was 0.887 and 0.863, respectively, and the sensitivity and specificity were both above 80%. Conclusion:Both BA.5-S-IgG and WT-S-IgG, as well as the combination of these two antibodies, are of high value in the identification of epidemic strains.

Objective:To explore the effectiveness of deep learning image reconstruction (DLIR) algorithm compared to adaptive statistical iterative reconstruction (ASIR-V) algorithm in improving the quality of low-dose brain CT images.Methods:Retrospective inclusion of patients who underwent brain CT examination in the People's Liberation Army General Hospital from November 2021 to August 2022. Four different algorithms were used to reconstruct low-dose CT scans of all patients to obtain 30% intensity ASIR-V (ASIR-V-30%) images, low intensity DLIR (DLIR-L) images, medium intensity DLIR (DLIR-M) images, and high intensity DLIR (DLIR-H) images. The regions of interest were selected from four sets of images, including superficial white matter, superficial gray matter, deep white matter, and deep gray matter, and their CT values and standard deviations were measured for calculating signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR).Subjective evaluation of image quality was conducted by three neuroimaging physicians based on the Likert 5-component scale. The objective and subjective scores of the 4 groups of images were analyzed using ANOVA or Kruskal Wallis. If there are overall differences, pairwise comparisons were conducted within the group.Results:A total of 109 patients were enrolled, including 104 males and 5 females, aged 65-110 years (89.16 ± 9.53) years. The radiation exposure of brain CT low-dose scanning was (0.93 ± 0.01)mSv, significantly lower than that of conventional scanning (2.92 ± 0.01) mSv ( t = 56.15, P < 0.05). The differences in objective image quality analysis of ASIR-V-30%, DLIR-L, DLIR-M, and DLIR-H images of low-dose CT in SNR deep gray matter, SNR deep white matter, SNR superficial gray matter, SNR superficial white matter, CNR deep gray white matter, and CNR superficial gray white matter were statistically significant( F =98.23, 72.95, 68.43, 58.24, 241.13, 289.91, P < 0.05). Among them, DLIR-H images had the lowest noise in deep gray matter, deep white matter, superficial gray matter, and superficial white matter, and had statistically significant differences compared to other image groups ( t = 167.43, 275.46, 182.32, 361.54, P < 0.05). The subjective score of DLIR-H image quality was superior to ASIR-V-30%, DLIR-L, and DLIR-M, with the statistically significant difference ( t = 7.25, 8.32, 9.63, P < 0.05). Conclusions:Compared with ASIR-V, DLIR algorithm can effectively reduce image noise and artifacts in low-dose brain CT, and improve SNR and CNR. The subjective and objective image quality evaluation of DLIR-H is the best.