Extensive epigenetic reprogramming involves in memory CD8+ T-cell differentiation. The elaborate epigenetic rewiring underlying the heterogeneous functional states of CD8+ T cells remains hidden. Here, we profile single-cell chromatin accessibility and map enhancer-promoter interactomes to characterize the differentiation trajectory of memory CD8+ T cells. We reveal that under distinct epigenetic regulations, the early activated CD8+ T cells divergently originated for short-lived effector and memory precursor effector cells. We also uncover a defined epigenetic rewiring leading to the conversion from effector memory to central memory cells during memory formation. Additionally, we illustrate chromatin regulatory mechanisms underlying long-lasting versus transient transcription regulation during memory differentiation. Finally, we confirm the essential roles of Sox4 and Nrf2 in developing memory precursor effector and effector memory cells, respectively, and validate cell state-specific enhancers in regulating Il7r using CRISPR-Cas9. Our data pave the way for understanding the mechanism underlying epigenetic memory formation in CD8+ T-cell differentiation.
CD8-Positive T-Lymphocytes/metabolism* ; Cell Differentiation ; Chromatin/immunology* ; Animals ; Mice ; Immunologic Memory ; Epigenesis, Genetic ; SOXC Transcription Factors/immunology* ; NF-E2-Related Factor 2/immunology* ; Mice, Inbred C57BL ; Gene Regulatory Networks ; Enhancer Elements, Genetic

Objective:To explore the relevant factors affecting the accuracy of scanning glucose monitoring (FGM) technology in critically ill patients.Methods:A total of 53 patients who were admitted to the Intensive Care Unit (ICU) of the Second Affiliated Hospital of Soochow University and used FGM glucose monitoring from September 2022 to December 2023 were selected by means of a convenience sampling method. The paired data of arterial blood glucose and FGM glucose were analysed. The accuracy of FGM blood glucose measurement in critically ill patients was evaluated using Bland-Altman analysis. The blood glucose data were divided into two groups: the FGM monitoring accuracy group and the FGM monitoring non-accuracy group.. The t-test and χ2 test were used for the comparison of one-way analysis of arterial versus FGM accuracy among critically ill patients with different demographic characteristics. Logistic regression analysis was used to analyze the factors influencing the accuracy of FGM. Results:The results of Bland-Altman analysis of the 53 patients indicated that the mean bias value of FGM blood glucose was elevated at 1.215 mmol/L in comparison with arterial-blood gas analysis blood glucose values. An incidence of exceeding the upper and lower limits of the range was observed, amounting to 6.349%. The discrepancy between the studies was found to be statistically significant (95% CI:1.0394~1.3908, P<0.001). The effects of the changes in height ( OR=0.877, 95% CI:0.780~0.987, P=0.029), changes in leukocyte counts( OR=0.917, 95% CI:0.868~0.969, P=0.002), changes in C-reactive protein( OR=1.009, 95% CI:1.002~1.017, P=0.016), changes in albumin counts( OR=0.986, 95% CI:0.974~0.999, P=0.031), and whether or not sepsis ( OR=3.937, 95% CI:1.192~13.008, P=0.025) on the accuracy of FGM had a statistically significant. Conclusion:The mean bias value of the accuracy of FGM was relatively higher compared with that of arterial blood gas analysis blood glucose values, and the influencing factors involved height, white blood cells, C-reactive protein, albumin, and whether or not sepsis was present. With the development of science and technology, applying the FGM system to critically ill patients has an absolute advantage in determining the overall glycemic trend, and the application value of FGM technology deserves further study.

Objective:To evaluate the utility of ultrasonographic monitoring of the rectus femoris muscle—specifically, the rates of change in thickness and cross-sectional area (CSA)—in assessing nutritional status and long-term functional outcomes in patients with sepsis.Methods:In this prospective observational study, sepsis patients admitted to the ICU of the Second Affiliated Hospital of Soochow University between October 2023 and October 2024 were classified by nutritional status at discharge using the Global Leadership Initiative on Malnutrition (GLIM) criteria. Differences in serial ultrasound-measured rectus femoris thickness and CSA on days 1, 3, 5, and 7 were compared between malnourished and non-malnourished groups. The predictive value of these ultrasound parameters for malnutrition was analyzed. Functional prognosis was assessed using the Sarcopenia Assessment Scale, Short Physical Performance Battery, and Manual Muscle Testing, with correlations to muscle changes examined.Results:Of the 71 enrolled patients (median age 73.00 [ IQR: 61.00–80.00]; 47.89% female, 52.11% male), those with malnutrition showed significantly greater variation rates in rectus femoris thickness and CSA on days 3, 5, and 7 compared to the non-malnourished group ( P < 0.05). ROC analysis revealed that the day-7 CSA variation rate had the highest predictive value for malnutrition (AUC = 0.817, 95% CI: 0.713-0.930). These muscle variation rates also correlated strongly with conventional nutritional markers such as BMI, albumin, and urea. Similarly, patients with impaired functional outcomes exhibited higher variation rates in muscle parameters on days 3, 5, and 7 ( P < 0.05), with the day-7 CSA variation rate being most predictive of functional prognosis (AUC = 0.749, 95% CI: 0.632-0.867). Conclusions:Ultrasonographic assessment of rectus femoris thickness and CSA variation rates provides a valuable tool for evaluating nutritional status and predicting functional prognosis in sepsis patients, outperforming traditional biomarkers. This method shows promise for guiding individualized nutrition support and rehabilitation strategies to improve long-term outcomes.

Objective:To analyze immune reconstitution and influencing factors in HIV infected men who have sex with men (MSM) with access to antiviral therapy (ART) in Guangxi Zhuang Autonomous Region (Guangxi) during 2005-2021.Methods:The data were collected from Chinese Disease Prevention and Control Information System. The study subjects were HIV infected MSM with access to the initial ART for ≥24 weeks in Guangxi from 2005 to 2021 and HIV RNA lower than the detection limit within 24 months. The proportion of infected MSM who had immune reconstitution after ART was calculated. Cox proportional hazard regression model was used to analyze the influencing factors of immune reconstitution. Software SPSS 24.0 was used for statistical analysis.Results:A total of 3 200 HIV infected MSM were enrolled, in whom 15.56 % (498/3 200) had no immune reconstitution, 14.78% (473/3 200) had moderate immune reconstitution, and the rate of complete immune reconstitution was 69.66% (2 229/3 200). The M ( Q1, Q3) of ART time for immune reconstitution was 12 (5, 27) months. Multivariate Cox proportional risk regression model analysis results showed that compared with those with initial ART at age ≥30 years, WHO clinical stage Ⅲ/Ⅳ illness, baseline BMI <18.50 kg/m 2 and baseline CD4 +T lymphocyte (CD4) counts <200 cells/μl, HIV infected MSM with initial ART at age <30 years, WHO clinical stageⅠ/Ⅱ illness, baseline BMI≥24.00 kg/m 2 and baseline CD4 counts ≥200 cells/μl were more likely to have complete immune reconstitution. Conclusions:In the HIV infected MSM in Guangxi, failures to achieve moderate and complete immune reconstitution were observed. Surveillance and ART regimen should be improved for key populations, such as those with older age and low baseline CD4 counts.

Objectives:To identify the risk factors associated with delirium in intensive care unit (ICU) hospitalization of sepsis patients and construct a clinical prediction model to to provide a reference for the prevention and control of delirium in sepsis patients.Methods:Data were collected of sepsis patients admitted in the Intensive Care Unit in the Second Affiliated Hospital of Soochow University from September 2020 to August 2022.The patients were divided into delirium group and non-delirium group according to whether delirium occurred or not. Comparing of the differences in general and clinical data between the two groups, the independent risk factors for delirium were screened by backward stepwise regression method, and the delirium risk prediction model was constructed and evaluated. An independent risk factor analysis for delirium was conducted using a backward stepwise regression approach to identify significant predictors. A delirium risk prediction model was constructed based on the identified risk factors, followed by a comprehensive evaluation of the model's performance.Results:A total of 381 sepsis patients were included in the study, 114 patients (29.9%) developed delirium during the ICU hospitalization. Univariate analysis revealed statistically significant differences ( P< 0.05) between the delirium and non-delirium groups for several factors including age ≥ 65 years, blood transfusion, use of midazolam, use of adrenaline, APACHEⅡ score>15, SOFA score>4, metabolic acidosis, urea>7.1 mmol/L, coagulation disorders, lactate levels, and platelet count. Multivariate analysis identified age ≥ 65 years, use of midazolam, APACHEⅡ score>15, metabolic acidosis, urea>7.1 mmol/L, and coagulation disorders as independent risk factors for delirium in sepsis patients during ICU hospitalization.The predictive model was evaluated with an area under the ROC curve of 0.813, a non-significant Hosmer-Lemeshow goodness-of-fit test ( P=0.957>0.05), and a Brier score of 0.149 (<0.25), indicating good predictive performance and calibration. Clinical decision and impact curves demonstrated the model's favorable clinical applicability. Conclusions:The occurrence of delirium in ICU sepsis patients closely associate with six factors: age ≥ 65 years, use of midazolam, APACHEⅡ score>15, metabolic acidosis, urea>7.1 mmol/L, and coagulation disorders. This sepsis delirium prediction model has good clinical predictive ability and clinical applicability.

Objective To investigate the efficacy of transcranial direct current stimulation(tDCS)on sleep disorder in patients with Parkinson's disease(PD).Methods From July 2021 to July 2023,patients with PD and sleep disorders in the Department of Neurosurgery of the Second People's Hospital of Guangdong Province were selected.The enrolled patients were divided into sham stimulation group(n=28)and true stimulation group(tDCS)(n=29)according to the inclusion and exclusion criteria.MDS-UPDRS,PDSS and other rating scales were used to evaluate the patients.Before and after tDCS treatment,MS-11 was used for intelligent sleep monitor-ing.The baseline and improvement of sleep disorders in the two groups before and after treatment were analyzed.Results Before tDCS treatment,there was no significant difference in general conditions and scale scores between the two groups(P＞0.05).There was no significant difference in polysomnographic monitoring results between the two groups before treatment(P＞0.05).Compared with pre-treatment,there was no significant difference in sleep monitoring results in the sham stimulation group(P＞0.05),while the sleep duration and sleep efficiency signifi-cantly increased,the nighttime awakening duration,nighttime awakening frequency,MDS-UPDRS-Ⅲ score,and LEDD dose significantly decreased in the true stimulation group,with statistical significance(P＜0.05).Conclusion Pharmacological treatment combined with tDCS treatment is effective for sleep disorders and motor function in patients with PD,which could increase the sleep duration and sleep efficiency of PD patients with sleep disorders to a certain extent,reduce the nighttime awakening duration and frequency,thereby improving the fatigue symp-toms during the daytime,and improving the efficacy of conventional pharmacological treatment for PD.

Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.

Objective:To explore the risk factors for in-hospital mortality in patients with severe trauma and their predictive predictive value.Methods:A retrospective case-control study was used to analyze the data of 509 patients with severe trauma in the trauma database of the Trauma Center of the Second Affiliated Hospital of Soochow University from January 2017 to December 2021, including 377 males and 132 females, aged 18-94 years [53(42, 65)years]. Injury severity score (ISS) was 16-75 points [22(18, 29)points]. Injured parts included the head and neck in 409 patients (80.35%), the chest in 328(64.44%), the abdomen in 193(37.91%), the pelvis in 142(27.90%), the spine in 79(15.52%), and the limb in 247(48.53%). According to the clinical outcome during the hospital stay, the patients were divided into survival group ( n=390) and non-survival group ( n=119). Baseline and clinical data of the two groups were compared, including gender, age, cause of injury (traffic injury, fall from height, sharp instrument injury, etc.), injury site (head and neck, chest, abdomen, pelvis, spine, limb), vital signs on admission (temperature, systolic blood pressure, heart rate, respiratory rate), blood tests on admission [hemoglobin, platelets, prothrombin time (PT), activated partial thromboplastin time (APTT), international normalized ratio (INR), fibrinogen (FIB)], Glasgow coma scale (GCS) upon admission to the emergency room, revised trauma score (RTS) upon admission to the emergency room, ISS after whole-body CT examination, quick sequential organ failure assessment (qSOFA) score upon admission to the emergency room, and INR combined with qSOFA score. The baseline and clinical data of the survival group and the non-survival group were first compared with univariate analysis. Then, the independent risk factors of in-hospital mortality in patients with severe trauma were determined by multivariate Logistic stepwise regression (forward and backward). Based on the above data, receiver operating characteristic (ROC) curves were generated with Medcalc statistical software to analyze the efficacy of each risk factor in assessing in-hospital mortality in patients with severe trauma. Results:Univariate analysis showed that there were significant differences in age, injury site, temperature, systolic blood pressure, hemoglobin, platelet, PT, APTT, INR, FIB, GCS, RTS, ISS, qSOFA score, and INR combined with qSOFA score between the two groups ( P<0.05 or 0.01), while there were no significant differences in gender, cause of injury, heart rate, and respiratory rate between the two groups ( P>0.05). Multivariate Logistic stepwise regression analysis showed that age, systolic blood pressure, APTT, ISS, and INR combined with qSOFA score were significantly correlated with in-hospital mortality in patients with severe trauma ( P<0.01). ROC curve analysis results showed that the area under the curve (AUC) of in-hospital mortality in patients with severe trauma predicted by age, systolic blood pressure, APTT, ISS, and INR combined with qSOFA score were 0.63(95% CI 0.59, 0.68) and 0.60(95% CI 0.55, 0.64), 0.66(95% CI 0.62, 0.70), 0.73(95% CI 0.69, 0.77), and 0.75(95% CI 0.72, 0.80), respectively. Conclusions:Age, systolic blood pressure, APTT, ISS, and INR combined with qSOFA score are the independent risk factors for in-hospital mortality in patients with severe trauma. ISS and INR combined qSOFA score can better predict in-hospital mortality of patients with severe trauma than age, systolic blood pressure and APTT.

Objective:To evaluate the detection performance of left ventricular ejection fraction (LVEF) in patients with chronic renal failure (CRF) by an artificial intelligence (AI) model based on yolox framework integrating left ventricular segmentation and critical point detection.Methods:From January 2019 to June 2023, a total of 4 284 echocardiographic images of 2 000 adults aged 18-80 years without segmental wall motion abnormalities, structural heart disease, cardiac surgery or cardiomyopathy were collected in Henan Provincial People′s Hospital to delineate the endocardial membrane, as a training set, an AI model based on yolox framework integrating left ventricular segmentation and critical point detection was established. The images were divided into the training set( n=1 675) and the test set( n=325) in a ratio of about 5∶1. All 228 echocardiographic images of 100 normal adult volunteers who were treated in Henan Provincial Chest Hospital from May 2020 to May 2021 were collected as external test set validation. All 792 echocardiographic images of 204 patients treated in Henan Provincial People′s Hospital from April 2019 to June 2023 were continuously enrolled to evaluate the measurement efficiency of AI model. Spearman correlation statistical method was used to analyze the consistency of AI model measurement with manual measurement and TomTec software measurement methods of 3 senior echocardiographic professionals. Subjects were divided into clear image group, unclear image group, normal LVEF group and reduced LVEF group, the differences of general data between the two groups were compared. The correlation coefficient(ICC) within the group was calculated to analyze the consistency, so as to evaluate the model performance. Results:LVEF measured by AI model was significantly correlated with both manual measurement and TomTec model measurement ( rs=0.834, 0.826; all P<0.01). ICC values of the clear image group and the unclear image group were 0.96 and 0.97, respectively. ICC values for all subjects, normal LVEF group and reduced LVEF group were 0.96, 0.90 and 0.96, respectively. Conclusions:The AI model based on yolox framework integrating left ventricular segmentation and critical point detection has good diagnostic performance in the automatic measurement of LVEF in patients with CRF.