CAR-T cell immunotherapy,which is derived from T cells and employed in various diseases,particularly blood disorders,involves in vitro gene modification and infusion for treatment.Despite the significant therapeutic effects of CAR-T cells,challenges such as side effects,toxicity,CAR-T cell exhaustion,the immunosuppressive tumor microenvironment,and ge-netic alterations exist.The clinical efficacy of CAR-T cells in solid tumor treatment is limited,often leading to patient re-lapse.Addressing CAR-T-cell exhaustion remains a significant challenge.Scientists are employing diverse technical approaches to prevent CAR-T-cell exhaustion to increase the reliability and utility of CAR-T-cell therapy.This article delves into the mech-anisms of T-cell depletion and CAR-T-cell exhaustion,along with strategies to alleviate or disrupt CAR-T-cell exhaustion.This review of research progress on CAR-T-cell exhaustion aims to identify optimal strategies for reversing CAR-T-cell function and provide a comprehensive theoretical foundation for enhancing CAR-T-cell therapy technology.

OBJECTIVE: To observe the effect of electroacupuncture (EA) on liver protein kinase B (Akt)/forkhead box transcription factor 1 (FoxO1) signaling pathway in Zucker diabetic fatty (ZDF) rats, and to explore the possible mechanism of EA on improving liver insulin resistance of type 2 diabetes mellitus. METHODS: Twelve male 2-month-old ZDF rats were fed with high-fat diet for 4 weeks to establish diabetes model. After modeling, the rats were randomly divided into a model group and an EA group, with 6 rats in each group. In addition, six male Zucker lean (ZL) rats were used as the blank group. The rats in the EA group were treated with EA at bilateral "Zusanli" (ST 36), "Sanyinjiao" (SP 6), "Weiwanxiashu" (EX-B 3), and "Pishu" (BL 20). The ipsilateral "Zusanli" (ST 36) and "Weiwanxiashu" (EX-B 3) were connected to EA device, continuous wave, frequency of 15 Hz, 20 min each time, once a day, six times a week, for a total of 4 weeks. The fasting blood glucose (FBG) in each group was compared before modeling, before intervention and after intervention; the serum levels of insulin (INS) and C-peptide were measured by radioimmunoassay method, and the insulin resistance index (HOMA-IR) was calculated; HE staining method was used to observe the liver tissue morphology; Western blot method was used to detect the protein expression of Akt, FoxO1 and phosphoenolpyruvate carboxykinase (PEPCK) in the liver. RESULTS: Before intervention, compared with the blank group, FBG was increased in the model group and the EA group (P<0.01); after intervention, compared with the model group, FBG in the EA group was decreased (P<0.01). Compared with the blank group, the serum levels of INS and C-peptide, HOMA-IR, and the protein expression of hepatic FoxO1 and PEPCK were increased (P<0.01), while the protein expression of hepatic Akt was decreased (P<0.01) in the model group. Compared with the model group, the serum levels of INS and C-peptide, HOMA-IR, and the protein expression of hepatic FoxO1 and PEPCK were decreased (P<0.01), while the protein expression of hepatic Akt was increased (P<0.01) in the EA group. In the model group, the hepatocytes were structurally disordered and randomly arranged, with a large number of lipid vacuoles in the cytoplasm. In the EA group, the morphology of hepatocytes tended to be normal and lipid vacuoles were decreased. CONCLUSION EA could reduce FBG and HOMA-IR in ZDF rats, improve liver insulin resistance, which may be related to regulating Akt/FoxO1 signaling pathway.
Male ; Animals ; Rats ; Rats, Zucker ; Proto-Oncogene Proteins c-akt/genetics* ; Diabetes Mellitus, Type 2/therapy* ; Insulin Resistance ; C-Peptide ; Electroacupuncture ; Liver ; Signal Transduction ; Insulin ; Lipids

Objective:To investigate the value of a preoperatively MRI-based deep learning (DL) radiomics machine learning model to distinguish low-grade and high-grade soft tissue sarcomas (STS).Methods:From November 2007 to May 2019, 151 patients with STS confirmed by pathology in the Affiliated Hospital of Qingdao University were enrolled as training sets, and 131 patients in the Affiliated Hospital of Shandong First Medical University and the Third Hospital of Hebei Medical University were enrolled as external validation sets. According to the French Federation Nationale des Centres de Lutte Contre le Cancer classification (FNCLCC) system, 161 patients with FNCLCC grades Ⅰ and Ⅱ were defined as low-grade and 121 patients with grade Ⅲ were defined as high-grade. The hand-crafted radiomic (HCR) and DL radiomic features of the lesions were extracted respectively. Based on HCR features, DL features, and HCR-DL combined features, respectively, three machine-learning models were established by decision tree, logistic regression, and support vector machine (SVM) classifiers. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of each machine learning model and choose the best one. The univariate and multivariate logistic regression were used to establish a clinical-imaging factors model based on demographics and MRI findings. The nomogram was established by combining the optimal radiomics model and the clinical-imaging model. The AUC was used to evaluate the performance of each model and the DeLong test was used for comparison of AUC between every two models. The Kaplan-Meier survival curve and log-rank test were used to evaluate the performance of the optimal machine learning model in the risk stratification of progression free survival (PFS) in STS patients.Results:The SVM radiomics model based on HCR-DL combined features had the optimal predicting power with AUC values of 0.931(95%CI 0.889-0.973) in the training set and 0.951 (95%CI 0.904-0.997) in the validation set. The AUC values of the clinical-imaging model were 0.795 (95%CI 0.724-0.867) and 0.615 (95%CI 0.510-0.720), and of the nomogram was 0.875 (95%CI 0.818-0.932) and 0.786 (95%CI 0.701-0.872) in the training and validation sets, respectively. In validation set, the performance of SVM radiomics model was better than those of the nomogram and clinical-imaging models ( Z=3.16, 6.07; P=0.002,<0.001). Using the optimal radiomics model, there was statistically significant in PFS between the high and low risk groups of STS patients (training sets: χ2=43.50, P<0.001; validation sets: χ2=70.50, P<0.001). Conclusion:Preoperative MRI-based DL radiomics machine learning model has accurate prediction performance in differentiating the histopathological grading of STS. The SVM radiomics model based on HCR-DL combined features has the optimal predicting power and was expected to undergo risk stratification of prognosis in STS patients.

Ma-Mu-Ran Antidiarrheal Capsules (MMRAC) is traditional Chinese medicine that has been used to treat diarrhea caused by acute enteritis (AE) and bacillary dysentery in Xinjiang (China) for many years. However, the potential therapeutic mechanism of MMRAC for AE and its regulatory mechanism on host metabolism is unclear. This study used fecal metabolomics profiling with GC/MS and 16S rRNA gene sequencing analysis to explore the potential regulatory mechanisms of MMRAC on a dextran sulfate sodium salt (DSS)-induced mouse model of AE. Fecal metabolomics-based analyses were performed to detect the differentially expressed metabolites and metabolic pathways. The 16S rRNA gene sequencing analysis was used to assess the altered gut microbes at the genus level and for functional prediction. Moreover, Pearson correlation analysis was used to integrate differentially expressed metabolites and altered bacterial genera. The results revealed that six intestinal bacteria and seven metabolites mediated metabolic disorders (i.e., metabolism of amino acid, carbohydrate, cofactors and vitamins, and lipid) in AE mice. Besides, ten altered microbes mediated the differential expression of eight metabolites and regulated these metabolisms after MMRAC administration. Overall, these findings demonstrate that AE is associated with metabolic disorders and microbial dysbiosis. Further, we present that MMRAC exerts protective effects against AE by improving host metabolism through the intestinal flora.
Animals ; Antidiarrheals/pharmacology* ; Capsules ; Enteritis/genetics* ; Feces/microbiology* ; Genes, rRNA ; Metabolomics ; Mice ; RNA, Ribosomal, 16S/genetics*

Background::As a non-invasive and effective diagnostic method for small intestinal bacterial overgrowth (SIBO), wild-use of breath test (BT) has demonstrated a high comorbidity rate in patients with diarrhea-predominant irritable bowel syndrome (IBS-D) and SIBO. Patients overlapping with SIBO respond better to rifaximin therapy than those with IBS-D only. Gut microbiota plays a critical role in both of these two diseases. We aimed to determine the microbial difference between IBS-D overlapping with/without SIBO, and to study the underlying mechanism of its sensitivity to rifaximin.Methods::Patients with IBS-D were categorized as BT-negative (IBSN) and BT-positive (IBSP). Healthy volunteers (BT-negative) were enrolled as healthy control. The patients were clinically evaluated before and after rifaximin treatment (0.4 g bid, 4 weeks). Blood, intestine, and stool samples were collected for cytokine assessment and gut microbial analyses.Results::Clinical complaints and microbial abundance were significantly higher in IBSP than in IBSN. In contrast, severe systemic inflammation and more active bacterial invasion function that were associated with enrichment of opportunistic pathogens were seen in IBSN. The symptoms of IBSP patients were relieved in different degrees after therapy, but the symptoms of IBSN rarely changed. We also found that the presence of IBSN-enriched genera ( Enterobacter and Enterococcus) are unaffected by rifaximin therapy. Conclusions::IBS-D patients overlapping with SIBO showed noticeably different fecal microbial composition and function compared with IBS-D only. The better response to rifaximin in those comorbid patients might associate with their different gut microbiota, which suggests that BT is necessary before IBS-D diagnosis and use of rifaximin.Registration::Chinese Clinical Trial Registry, ChiCTR1800017911.

The antidepressant mechanism of Sini Powder was investigated by metabonomics based on UHPLC-Q-TOF-MS, and the roles of processing and compatibility in the antidepression of Sini Powder were discussed in the present study. The chronic unpredictable mild stress(CUMS) model of depression was induced in the model group, the Bupleuri Radix group, the Paeoniae Radix Alba group, the herb-pair group(Bupleuri Radix-Paeoniae Radix Alba), the Sini Powder group, and the vinegar-processed Sini Powder group(Bupleuri Radix and Paeoniae Radix Alba were vinegar-processed). After the establishment of the model, the rats in each group were continuously administered with corresponding drugs(ig) at a dose of 9.6 g·kg~(-1) for eight days [the rats in the model group and the normal group(without model induction) received the same volume of normal saline at the same time]. Following the last administration, the differential metabolites were identified to analyze metabolic pathways based on the rat plasma samples collected from each group. A total of sixteen potential biomarkers were identified. The metabolites with significant changes were involved in many biological metabolic pathways, such as amino acid metabolism, pentose phosphate pathway, glycerol phospholipid metabolism, sphingolipid metabolism, and purine metabolism. After drug intervention, some biomarkers returned to normal levels. Further comparisons of processing and compatibility revealed that the vinegar-processed Sini Powder group had the most total metabolic pathways where differential metabolites were returned to normal. Compared with the individual herbs, the herb-pair significantly improved the recovery of differential metabolites in the pentose phosphate and purine metabolic pathways. Compared with the Sini Powder, the vinegar-processed Sini Powder facilitated the recovery of differential metabolites in the arginine biosynthesis, and pyrimidine and pentose phosphate metabolic pathways. As indicated by the results, Sini Powder may interfere with depression by regulating lipid and nucleotide metabolisms. The processing and compatibility of Chinese herbal medicines can potentiate the intervention on depression by regulating nucleotide, energy, and amino acid metabolisms to a certain extent.
Animals ; Antidepressive Agents ; Drugs, Chinese Herbal ; Metabolomics ; Paeonia ; Powders ; Rats

OBJECTIVE: To investigate the prevalence rate of hypothyroidism in children with β-thalassemia major (β-TM) and its risk factors. METHODS: A total of 86 children with β-TM treated and followed up in the Department of Pediatrics of the Fifth Affiliated Hospital of Sun Yat-Sen University, Zhuhai Municipal Maternal and Child Health Care Hospital from August 2018 to August 2020 were enrolled. The clinical data of the children were analyzed to investigate the prevalence rate of hypothyroidism in children with β-thalassemia major (β-TM) and its risk factors. RESULTS: The prevalence rate of hypothyroidism in children with β-TM in Zhuhai area was 17.4%. The level of serum ferritin(SF) (4948.27±1225.33 μg/L) in hypothyroidism children was significantly increased(t=10.273，P<0.05). The prevalence rate of hypothyroidism was significantly higher in β-TM children(age ≥10 years old, SF ≥2 500 μg/L and irregular iron removal) (P<0.05). Logistic regression result showed that age ≥10 years old was the independent risk factor affecting the increasing of hypothyroidism rate in the children. The levels of SF(3880.60±1269.17 μg/L), TSH(4.43±1.52 mIU/L) and the prevalence rate of hypothyroidism(37.14%)(P<0.05) were higher for the children in irregular iron removal group. CONCLUSION The prevalence rate of hypothyroidism in children with β-TM in Zhuhai area is high, and it is related to the age ≥10 years old, SF ≥2 500 μg/L and irregular iron removal of the children.
Child ; Humans ; Hypothyroidism/epidemiology* ; Iron Overload ; Prevalence ; Risk Factors ; beta-Thalassemia/epidemiology*

BACKGROUND: Little is known about the effects of environmental cobalt exposure on insulin resistance (IR) in the general adult population. We investigated the association between cobalt concentration and IR. METHODS: A total of 1281 subjects aged more than 20 years with complete blood cobalt data were identified from the National Health and Nutrition Examination Survey (NHANES) 2015-2016 cycle. Blood cobalt levels were analyzed for their association with IR among all populations and subgroups by sex. Regression coefficients and 95% confidence intervals (CIs) of blood cobalt concentrations in association with fasting glucose, insulin and homeostatic model assessment of insulin resistance (HOMA-IR) were estimated using multivariate linear regression after adjusting for age, sex, ethnicity, alcohol consumption, body mass index, education level, and household income. A multivariate generalized linear regression analysis was further carried out to explore the association between cobalt exposure and IR. RESULTS: A negative association between blood cobalt concentration (coefficient = - 0.125, 95% CI - 0.234, - 0.015; P = 0.026) and HOMA-IR in female adults in the age- and sex-adjusted model was observed. However, no associations with HOMA-IR, fasting glucose, or insulin were found in the overall population. In the generalized linear models, participants with the lowest cobalt levels had a 2.74% (95% CI 0.04%, 5.50%) increase in HOMA-IR (P for trend = 0.031) compared with subjects with the highest cobalt levels. Restricted cubic spline regression suggested that a non-linear relationship may exist between blood cobalt and HOMA-IR. CONCLUSIONS These results provide epidemiological evidence that low levels of blood cobalt are negatively associated with HOMA-IR in female adults.
Adult ; Aged ; Aged, 80 and over ; Cobalt/blood* ; Cross-Sectional Studies ; Environmental Pollutants/blood* ; Female ; Homeostasis ; Humans ; Insulin/blood* ; Insulin Resistance ; Male ; Middle Aged ; Nutrition Surveys ; Sex Factors ; United States ; Young Adult

Objective:To investigate the relationships of estrogen receptor-α (ESR1) gene PvuⅡ (rs2234693, C>T) and XbaⅠ (rs9340799, A>G) polymorphisms and susceptibility of type 1 diabetes for female children (T1D) .Methods:From Jan. 2016 to Dec. 2019, 86 female children with newly diagnosed T1D who were admitted to Chongqing Three Gorges Central hospital were selected as the study subjects, and 100 healthy children who underwent physical examination in our hospital during the same period were selected as the healthy control. The height, weight and related metabolic indexes of the subjects were measured. The ESR1 gene was genotyped by capillary electrophoresis and SNaPshot. The mRNA expression of ESR1 gene was detected by real-time fluorescence quantitative polymerase chain reaction (RT-PCR) .Results:Genotyping results showed that PvuII genotype distribution between T1D group and the control group was statistically significant ( χ2=11.672, P=0.003) , but XbaI genotype distribution between T1D patients and controls had no significant difference ( χ2=5.433, P=0.066) . PvuII locus T allele frequency and XbaI locus G allele frequency were significantly in T1D group higher than in the control group (PvuII T vs C: OR=1.909, 95% CI=1.261-2.892, P=0.002; XbaI G vs A: OR=1.815, 95% CI=1.112-2.961, P=0.016) . Glycated hemoglobin (HbA1c) and total cholesterol (TC) levels in T1D patients with PvuII T allele were significantly higher than those with CC genotype (all P<0.05) . Low-density lipoproteins (LDL-C) and total cholesterol (TC) levels in T1D patients with XbaI G allele were significantly higher than those with AA genotypes (both P<0.05) . The relative expression of ESR1 gene mRNA in T1D patients was significantly lower than that in the control group (0.42±0.05 vs 1.04±0.16, t=6.227, P<0.001) . The relative expression of ESR1 gene mRNA in T1D patients with PvuII CC, CT and TT genotypes was statistically different ( F=5.823, P<0.001) , and the relative ESR1 gene mRNA in T1D patients with XbaI AA, AG and GG genotypes was also statistically different ( F=5.415, P<0.001) . Conclusion:PvuII and XbaI olymorphismsof ESR1 genes may be involved in the occurrence and development of T1D in female children by influencing gene expression.

Objective:To analyze the brain function of patients with delirium in intensive care unit (ICU) using resting-state functional magnetic resonance imaging (fMRI), further analyze the structural changes in the brain using diffusion tensor imaging (DTI), and explore the correlations of brain function with structural changes in patients with delirium in ICU from a new perspective of functional imaging, provide visual evidence for the diagnosis of delirium.Methods:Patients with delirium admitted to ICU of the Affiliated Hospital of Zunyi Medical University from January 1st to December 31st in 2017 were enrolled as subjects. During the same period, the healthy volunteers who matched the gender, age and education level of the patients with delirium were enrolled as control group. The intensive care delirium screening checklist (ICDSC) scores within 24 hours after ICU admission were recorded. All the subjects were scanned by fMRI and DTI. The abnormal changes in resting-state brain function of the patients with delirium were evaluated by cerebral regional homogeneity (ReHo) data analysis. The DTI data were processed by the FSL software, and the fractional anisotropy (FA) and mean diffusivity (MD) of the brain were extracted, respectively, to evaluate the damage to brain structure. The values of ReHo, FA and MD were compared between the two groups. The ReHo value of brain region with reduced ReHo value of patients with delirium as compared with the healthy volunteers was extracted for Pearson correlation analysis with ICDSC scores.Results:A total of 22 patients with delirium were included. Seven patients who did not cooperate in the examination, used sedatives or had false images in scanning, were excluded. Finally, 15 patients were enrolled in the delirium group, and 15 healthy volunteers in the healthy control group. ① No statistically significant difference was found in gender, age or education time between the two groups. ICDSC score of the delirium group was significantly higher than that of the healthy control group (6.07±1.28 vs. 1.07±0.88, P < 0.01). ② fMRI scanning and analysis results: compared with the healthy control group, the ReHo values of the cerebellum, right hippocampus, striatum, midbrain and pons in the delirium group were significantly increased (all P < 0.05, AlphaSim correction), while the ReHo values of bilateral superior frontal gyrus, bilateral median frontal gyrus, left inferior frontal gyrus, temporal lobe and parietal lobe were significantly lowered (all P < 0.05, AlphaSim correction). Correlation analysis showed that the ReHo value of the left superior frontal gyrus was negatively correlated with ICDSC score in the patients with delirium ( r = -0.794, P < 0.05), indicating that the changes in the functional area of the medial frontal gyrus was most closely related to delirium. ③ DTI scanning and analysis results: compared with the healthy control group, the FA values of the left cerebellum, bilateral frontal lobes, left temporal lobe, corpus callosum and left hippocampus in the delirium group were decreased significantly (all P < 0.05, AlphaSim correction), while the MD values of the medial frontal gyrus, right superior temporal gyrus, anterior cingulate gyrus, bilateral insular lobes and left caudate nucleus were enhanced significantly (all P < 0.05, AlphaSim correction), suggesting that the structural and functional damage was found in multiple brain regions in patients with delirium. Conclusions:Multiple brain regions of patients with delirium present abnormal resting-state brain function. The abnormal resting-state brain function of the left superior frontal gyrus is closely related to the occurrence of delirium. Structural damage is found in multiple brain regions of patients with delirium. The structural changes in the frontal lobe, temporal lobe, corpus callosum, hippocampus and cerebellum and their abnormal functions can be used as preliminary imaging indexes for the diagnosis of delirium.