Aim To explore the impacts of high mobility group box 1 (HMGB1) on the phenotypes, endocy-tosis and extracellular signal-regulated kinase (ERK)/ Jun N-terminal protein kinase (JNK)/P38 mitogen-ac-tivated protein kinase (MAPK) signaling pathway in indoxyl sulfate (IS) -induced dendritic cells (DCs). Methods After treatment with 30, 300 and 600 (xmol · L

Objective To explore the prognostic impact and clinical application value of therapeutic plasma exchange(TPE)intervention timing and liver injury periodization in patients with exertional heat stroke(EHS).Methods Data of 127 EHS patients from the First Medical Center of the General Hospital of the People′s Liberation Army from January 2011 to December 2023 were collected,then divided into the death group and the survival group based on therapeutic outcomes and into 5 stages according to the dynamic changes of ALT,AST,TBIL and DBIL.According to propensity score matching analysis,11 patients in the survival group and 12 patients in the death group were included in the statistical analysis,and 20 of them were treated with TPE.The changes in indicators and clinical outcomes before and after TPE were observed,in order to evaluate the impact of intervention timing on prognosis.Results Among the 23 patients,14 had no liver injury or could progress to the repair phase,resulting in 3 deaths(with the mortality rate of 21.43%),while 9 patients failed to pro-gress to the repair phase,resulting in 9 deaths(with the mortality rate of 100%),with significant differences(P＜0.05).The mortality rate of the first TPE intervention before the third stage of liver injury was 23.08%(3/13),while that of interven-tion after reaching or exceeding the third stage was 85.71%(6/7),and the difference was statistically significant(P＜0.05).Conclusion TPE should be executed actively in EHS patients combined with liver injury before the third phase to lock its pathological and physiological processes,thereby improving prognosis and reducing mortality.

Objective To identify the risk factors of patients with frequent acute exacerbations of chro-nic obstructive pulmonary disease(AECOPD)and construct a prediction model based on the clinical data,provi-ding a theoretical basis for the clinical prevention and treatment.Methods A total of 25 638 COPD patients ad-mitted to the Department of Respiratory and Critical Care Medicine,the Third People's Hospital of Chengdu from January 1,2013 to May 1,2023 were selected.Among them,11 315 patients were included according to the inclusion and exclusion criteria,and their clinical characteristics were analyzed.Multivariate Logistic regression was carried out to identify the risk factors for frequent AECOPD.A nomogram model was utilized to quantify the risk of acute exacerbation,and the performance of the prediction model was assessed based on the area under the receiver operating characteristic(ROC)curve.Results In the patients with frequent AECOPD,male percentage(P＜0.001),age(P＜0.001),urban residence(P＜0.001),smoking(P＜0.001),length of stay(P＜0.001),total cost(P＜0.001),antibiotic cost(P＜0.001),diabetes(P=0.003),respiratory failure(P＜0.001),heart disease(P＜0.001),application of systemic glucocorticoids(P＜0.001),white blood cell count(P＜0.001),neutrophil percentage(P＜0.001),C-reactive protein(P＜0.001),total cholesterol(P＜0.001),and brain natriuretic peptide(BNP)(P＜0.001)were all higher than those in the patients with infre-quent AECOPD.Multivariate Logistic regression analysis revealed that age,urban residence,smoking,diabe-tes,heart disease,Pseudomonas aeruginosa infection,application of systemic glucocorticoids,antibiotics,re-spiratory failure,and elevated white blood cell count,total cholesterol,and BNP were independent risk factors for hospitalization due to frequent AECOPD.A nomogram model of hospitalization due to frequent AECOPD was constructed according to risk factors.The ROC curve was established to evaluate the performance of the model,which showed the area under the ROC curve of 0.899(95％CI=0.892-0.905),the sensitivity of 85.30％,and the specificity of 79.80％.Conclusions Frequent AECOPD is associated with smoking,heart disease,ap-plication of systemic glucocorticoids,Pseudomonas aeruginosa infection,age,low body mass index,and elevat-ed BNP.Predicting the risks of hospitalization due to frequent AECOPD by the established model can provide the-oretical support for the treatment and risk factor management of the patients.

The deubiquitinases (DUBs), as the crucial peptidohydrolases in the ubiquitin system, can reverse and strictly regulate ubiquitination and play key roles in various biological processes, including the regulation of protein stability, cell signal transduction. Ubiquitin-specific protease 28 (USP28) involves multiple cancer-related signaling pathways by enhancing the stability of various cancer-related proteins, and is closely associated with the progression of colorectal, breast cancer, lung carcinomas, and pancreatic cancer. USP28 has been considered as a promising drug target in anticancer therapy, and the development of USP28 inhibitors has made some progress. In this article, we review the structure of USP28 and its interaction with substrates, discuss the research progress of USP28 in cancers and summarize the development of USP28 inhibitors.

Chronic kidney disease （CKD） is a global health problem， and its incidence increases year by year. Studies have revealed that the progression of CKD into end-stage renal disease （ESRD） is related to its inability to effectively eliminate toxins due to decreased renal function. Additionally， intestinal microflora produces a large amount of gut-derived uremic toxins （GDUTs） during protein fermentation. The theory of gut-kidney axis holds that gut and kidney interact with each other， and CKD reduces the ability to remove uremic toxins （UTs）， resulting in the accumulation of UTs in the blood. The accumulation of UTs also accelerates the deterioration of renal function， leading to a vicious circle. This paper focused on the sources of indoxyl sulfate and p-cresol sulfate in GDUTs and their mechanisms against CKD （such as inducing renal tubular cell death， oxidative stress and endothelial injury， promoting renal fibrosis and down-regulating renal protective protein） as well as the sources of trimethylamine oxide and its mechanisms against CKD （such as promoting renal fibrosis and inflammation）. Moreover， starting from gut-kidney axis， this paper summarized the ways of diet and nutrition regulation， toxin adsorption， enhanced dialysis to increase the clearance， inhibiting the sources of gut-derived toxins and traditional Chinese medicine （TCM） therapy （TCM preparations and TCM active ingredients） to regulate intestinal microecology and reduce the generation of GDUTs， aiming to provide new therapeutic ideas for delaying the progression of CKD.

Objective: To evaluate the prognostic value of left ventricular ejection fraction (LVEF) reserve assessed by gated SPECT myocardial perfusion imaging (SPECT G-MPI) for major adverse cardiovascular event (MACE) in patients with coronary artery disease. Methods: This is a retrospective cohort study. From January 2017 to December 2019, patients with coronary artery disease and confirmed myocardial ischemia by stress and rest SPECT G-MPI, and underwent coronary angiography within 3 months were enrolled. The sum stress score (SSS) and sum resting score (SRS) were analyzed by the standard 17-segment model, and the sum difference score (SDS, SDS=SSS-SRS) was calculated. The LVEF at stress and rest were analyzed by 4DM software. The LVEF reserve (ΔLVEF) was calculated (ΔLVEF=stress LVEF-rest LVEF). The primary endpoint was MACE, which was obtained by reviewing the medical record system or by telephone follow-up once every twelve months. Patients were divided into MACE-free and MACE groups. Spearman correlation analysis was used to analyze the correlation between ΔLVEF and all MPI parameters. Cox regression analysis was used to analyze the independent factors of MACE, and the optimal SDS cutoff value for predicting MACE was determined by receiver operating characteristic curve (ROC). Kaplan-Meier survival curves were plotted to compare the difference in the incidence of MACE between different SDS groups and different ΔLVEF groups. Results: A total of 164 patients with coronary artery disease [120 male; age (58.6±10.7) years] were included. The average follow-up time was (26.5±10.4) months, and a total of 30 MACE were recorded during follow-up. Multivariate Cox regression analysis showed that SDS (HR=1.069, 95%CI: 1.005-1.137, P=0.035) and ΔLVEF (HR=0.935, 95%CI: 0.878-0.995, P=0.034) were independent predictors of MACE. According to ROC curve analysis, the optimal cut-off to predict MACE was a SDS of 5.5 with an area under the curve of 0.63 (P=0.022). Survival analysis showed that the incidence of MACE was significantly higher in the SDS≥5.5 group than in the SDS<5.5 group (27.6% vs. 13.2%, P=0.019), but the incidence of MACE was significantly lower in the ΔLVEF≥0 group than in theΔLVEF<0 group (11.0% vs. 25.6%, P=0.022). Conclusions: LVEF reserve (ΔLVEF) assessed by SPECT G-MPI serves as an independent protective factor for MACE, while SDS is an independent risk predictor in patients with coronary artery disease. SPECT G-MPI is valuable for risk stratification by assessing myocardial ischemia and LVEF.
Humans ; Male ; Middle Aged ; Aged ; Coronary Artery Disease/diagnostic imaging* ; Stroke Volume ; Myocardial Perfusion Imaging ; Retrospective Studies ; Ventricular Function, Left ; Myocardial Ischemia

Objective: To construct chimeric antigen receptor (CAR) T cells targeting CD52 (CD52 CAR-T) and validate the effect of CD52 CAR-T cells on CD52-positive leukemia. Methods: A second-generation CD52-targeting CAR bearing 4-1BB costimulatory domain was ligated into a lentiviral vector through molecular cloning. Lentivirus was prepared and packaged by 293 T cells with a four-plasmid system. Fluorescein was used to label cell surface antigens to evaluate the phenotype of CD52 CAR-T cells after infection. Flow cytometry and ELISA were used to evaluate the specific cytotoxicity of CD52 CAR-T cells to CD52-positive cell lines in vitro. Results: ①A pCDH-CD52scFv-CD8α-4-1BB-CD3ζ-GFP expressing plasmid was successfully constructed and used to transduce T cells expressing a novel CD52-targeting CAR. ②On day 6, CD52-positive T cells were almost killed by CD52-targeted CAR-T post lentivirus transduction [CD52 CAR-T (4.48 ± 4.99) %, vs Vector-T (56.58±19.8) %, P=0.011]. ③T cells transduced with the CAR targeting CD52 showed low levels of apoptosis and could be expanded long-term ex vivo. ④The CD52 CAR could promote T cell differentiation into central and effector memory T cells, whereas the proportion of T cells with a CD45RA(+) effector memory phenotype were reduced. ⑤CD52 CAR-T cells could specifically kill CD52-positive HuT78-19t cells but had no killing effect on CD52-negative MOLT4-19t cells. For CD52 CAR-T cells, the percentage of residual of HuT78-19t cells was (2.66±1.60) % at an the E:T ratio of 1∶1 for 24 h, while (56.66±5.74) % of MOLT4-19t cells survived (P<0.001) . ⑥The results of a degranulation experiment confirmed that HuT78-19t cells significantly activated CD52 CAR-T cells but not MOLT4-19t cells[ (57.34±11.25) % vs (13.06± 4.23) %, P<0.001]. ⑦CD52 CAR-T cells released more cytokines when co-cultured with HuT78-19t cells than that of vector-T cells [IFN-γ: (3706±226) pg/ml, P<0.001; TNF-α: (1732±560) pg/ml, P<0.01]. Conclusions: We successfully prepared CD52 CAR-T cells with anti-leukemia effects, which might provide the foundation for further immunotherapy.
CD52 Antigen ; Cell Line, Tumor ; Humans ; Immunotherapy, Adoptive/methods* ; Lentivirus/genetics* ; Leukemia ; Receptors, Antigen, T-Cell ; Receptors, Chimeric Antigen/genetics*

Objective:To investigate the correlation between obstructive sleep apnea (OSA) and triglyceride-glucose (TyG) indexin patients with ischemic stroke.Methods:Patients with ischemic stroke underwent sleep breathing monitoring in Nanjing Stroke Registry Program from August 2020 to August 2021 were retrospectively enrolled. According to apnea-hypopnea index (AHI), the patients were divided into no/mild OSA group (AHI≤15 events/h) and moderate to severe OSA group (AHI>15 events/h). The TyG index was calculated according to triglycerides and fasting blood glucose, and the patients were grouped by quartile. The relationship between moderate to severe OSA and TyG index was determined by ordinal multinomial logistic regression analysis. Pearson correlation analysis was used to evaluate the correlation between TyG index and AHI. Results:A total of 155 patients with ischemic stroke were enrolled in the study, including 66 patients in the no/mild OSA group, 89 in the moderate to severe OSA group; 39 in the Q1 group (TyG index ≤8.46), 39 in the Q2 group (TyG index 8.47-8.78), 39 in the Q3 group (TyG index 8.79-9.17), and 38 in the Q4 group (TyG index >9.17). Ordinal multinomial logistic regression analysis showed that after adjusting for potential confounding factors, higher fasting blood glucose (odds ratio 2.370, 95% confidence interval 1.745-3.222; P<0.001) and moderate to severe OSA (odds ratio 2.377, 95% confidence interval 1.217-4.646; P=0.011) had significant independent positive correlation with TyG index. Pearson correlation analysis showed that AHI was positively correlated with the TyG index in patients with ischemic stroke ( r=0.209, P=0.011). Conclusion:OSA is independently correlated with TyG index in patients with ischemic stroke.

Objective: Whether metabolic redistribution occurs in patients with white matter hyperintensities (WMHs) on magnetic resonance imaging (MRI) is unknown. This study aimed 1) to propose a measure of the brain metabolic network for an individual patient and preliminarily apply it to identify impaired metabolic networks in patients with WMHs, and 2) to explore the clinical and imaging features of metabolic redistribution in patients with WMHs. Materials and Methods: This study included 50 patients with WMHs and 70 healthy controls (HCs) who underwent 18F-fluorodeoxyglucose-positron emission tomography/MRI. Various global property parameters according to graph theory and an individual parameter of brain metabolic network called “individual contribution index” were obtained. Parameter values were compared between the WMH and HC groups. The performance of the parameters in discriminating between the two groups was assessed using the area under the receiver operating characteristic curve (AUC). The correlation between the individual contribution index and Fazekas score was assessed, and the interaction between age and individual contribution index was determined. A generalized linear model was fitted with the individual contribution index as the dependent variable and the mean standardized uptake value (SUVmean) of nodes in the whole-brain network or seven classic functional networks as independent variables to determine their association. Results: The means ± standard deviations of the individual contribution index were (0.697 ± 10.9) x 10-3 and (0.0967 ± 0.0545) x 10-3 in the WMH and HC groups, respectively (p < 0.001). The AUC of the individual contribution index was 0.864 (95% confidence interval, 0.785–0.943). A positive correlation was identified between the individual contribution index and the Fazekas scores in patients with WMHs (r = 0.57, p < 0.001). Age and individual contribution index demonstrated a significant interaction effect on the Fazekas score. A significant direct association was observed between the individual contribution index and the SUVmean of the limbic network (p < 0.001). Conclusion The individual contribution index may demonstrate the redistribution of the brain metabolic network in patients with WMHs.

Objective:To explore the diagnostic value of 18F-deoxyglucose (FDG) PET/CT dual-time-point imaging (DTPI) in the diagnosis of aortic grafts infection (AGI). Methods:Forty-two patients with suspected AGI were prospectively recruited in this DTPI study from October 2014 to October 2021. There were 35(83%) males and 7 females, mean age (54±15) years old, range 22-79 years old. PET/CT image quality was scored as 5 grading scale. Semi-quantitative analysis of DTPI data was performed using maximum standardized uptake value (SUVmax) of suspected AGI lesions. The percentage of SUVmax change between initial and delayed images were recorded as retention index (RI). Management of Aortic Graft Infection Collaboration (MAGIC) criteria were used as the diagnostic reference criteria for AGI.Results:According to the MAGIC criteria, 27 patients (64%) were positive for AGI, and 15 patients (36%) were negative. The mean RI of AGI was higher than that of non-AGI ones[(26.7±18.9)% vs. (6.4 ±18.8)%, P<0.01]. The sensitivity, specificity, and accuracy of initial SUVmax ≥6 with the presence of AGI was 88.9%, 73.3%, and 83.3%, respectively. Delayed SUVmax ≥6 improved the sensitivity (96.3%) and accuracy (88.1%) for diagnosing AGI. DTPI with 15% increment as the optimal cut-off value of RI improved the specificity (93.3%) and accuracy (90.5%) for diagnosing AGI. Fifteen (56%, 15/27) AGI patients had improved image quality grading on the delayed images, leading to more accurately delineating the detailed extent of the infected aortic graft. Conclusion:18F-FDG PET/CT DTPI has better diagnostic performance for AGI than conventional Single-time-point PET/CT imaging by improving image quality as well as enhancing delineation of infected aortic graft extent.