Objective To study the clinical significance of CD4 + CD25+ Foxp3 + regulatory T cell (Treg) and interleukin 10 (IL-10),transforming growth factor-β1 (TGF-β 1) in patients with steroidresistant asthma (SRA).Methods Seventy-nine patients with asthma were divided into SRA group (31cases) and steroid-sensitive (SSA) group (48 cases).Forty-five healthy subjects were selected simultaneously as control group.CD4+ CD25+ Foxp3 +Treg level was detected by flow cytometry and serum IL-10 and TGF-β1 levels were detected by enzyme-linked immunosorbent assay.Results The percentage of CD4 + CD25 +Foxp3 +Treg in CD4+ T cell and its absolute value in SRA group and SSA group were 0.0225 ± 0.0063,(1.09 ± 0.23) × 107/L and 0.0345 ± 0.0094,(1.35 ± 0.14) × 107/L,they were significandy lower than those in control group [0.0537 ± 0.0128,(2.06 ± 0.27) × 107/L],and SRA group was significandy lower than SSA group,there were statistical differences (P ＜ 0.05).The levels of serum TGF-β1 in SRA group and SSA group were significantly lower than those in control group [(138.12 ± 23.26),(176.25 ± 40.37) ng/L vs.(281.22 ±47.15) ng/L],there was statistical difference (P ＜0.05).The levels of serum IL-10 in SRA group was significantly lower than that in control group [(516.43 ± 86.33)ng/L vs.(763.02 ± 90.19) ng/L],there was statistical difference (P ＜ 0.05).There was no statistical difference in the level of serum IL-10 between SSA group and control group (P ＞ 0.05).The levels of serum IL-10 and TGF-β 1 in SRA group were significantly lower than those in SSA group,there were statistical differences (P ＜ 0.05).The levels of serum IL-10 and TGF-β1 had positive correlation with CD4 + CD25 + Foxp3 +Treg in SRA group and SSA group (P ＜ 0.01).Conclusion The interaction among CD4+ CD25+ Foxp3 +Treg,IL-10 and TGF-β1 may play an important role in the SRA occurrence and development,while by increasing peripheral blood CD4 + CD25 + Foxp3 +Treg number and stabilizing its function can increase IL-10 and TGF-β1 expression,which may be an important way to treat SRA.

Objective To evaluate the clinical efficacy and safety of ritonavir-boosted danoprevir (DNVr) combined with daclatasvir (DCV) in the treatment of patients with genotype 1b chronic hepatitis C (CHC).Methods Thirty-three patients with genotype 1b CHC admitted in the Department of Infectious Diseases of the First Affiliated Hospital of Nanchang University from August 2018 to February 2019 were enrolled.All the patients received DNVr +DCV antiviral treatment.HCV RNA levels were detected before and 2, 4, 12 weeks after treatment, and after drug withdrawal , respectively.Indicators of liver and kidney function and adverse events were observed.ANOVAV of repeated measurement was used to analyze the data. Results The baseline viral loads of 33 patients ranged from 1.12×104 to 1.76×107 IU／mL.Two weeks after treatment the viral loads of all patients were down to the lowest limit of detection (＜500 IU／mL). Serum ALT, AST and TBil levels returned to norml ( F＝58.26, 14.49 and 20.16, all P＜0.05) and sustained virologic response reached 100%12 weeks after drug withdrawal.Three cases had minor adverse reactions during the treatment.Conclusion DNVr combined with DCV can achieve a rapid and strong virological response in the treatment of patients with genotype 1b CHC with good safety.

Objective To investigate the influencing factors for low-level viremia (LLV) and their dynamic changes in chronic hepatitis B (CHB) patients treated with nucleos(t)ide analogues (NAs) for the first time. Methods A retrospective analysis was performed for 78 CHB patients who attended Department of Infectious Diseases, The First Affiliated Hospital of Nanchang University, from November 2020 to March 2022 and received antiviral therapy with NAs for at least 12 months, and according to HBV DNA level during treatment, they were divided into sustained virologic response (SVR) group with 58 patients and LLV group with 20 patients. The independent samples t -test or the Mann-Whitney U test was used for comparison of continuous data between two groups, and the chi-square test or the Fisher's exact test was used for comparison of categorical data between two groups. The multivariate Logistic regression analysis was used to investigate the independent influencing factors for LLV and establish a predictive model, and the receiver operating characteristic (ROC) curve was used to evaluate the predictive value of this model. The Kaplan-Meier method was used to analyze cumulative HBV DNA negative conversion rate, and the Log-rank test was used for comparison. The analysis of variance with repeated measures was used to analyze the differences in HBV DNA and HBsAg between the two groups or within each group at weeks 0, 12, 24, 36, and 48. Results Compare with the SVR group, the LLV group had significantly higher HBeAg positive rate (90.0% vs 48.3%, χ 2 =10.701, P =0.001), log(HBV DNA) value (7.26±1.46 vs 5.65±1.70, t =-4.178, P < 0.001), and log(HBsAg) value (4.53±0.86 vs 3.44±0.93, t =-4.813, P < 0.001) and significantly lower age [29 (26-34) vs 33 (30-43), Z =-2.751, P =0.009], alanine aminotransferase (ALT) [67.0 (54.0-122.0)U/L vs 111.0 (47.0-406.0)U/L, Z =-2.203, P =0.028], aspartate aminotransferase [43.5 (32.8-62.8) U/L vs 77.5 (35.0-213.0)U/L, Z =-2.466, P =0.014], and liver stiffness measurement [7.7 (6.3-8.5)kPa vs 8.9 (7.2-11.4)kPa, Z =-2.022, P =0.043]. The multivariate logistic regression analysis showed that baseline HBV DNA (odds ratio [ OR ]=2.365, 95% confidence interval [ CI ]: 1.220-4.587, P =0.011), HBsAg ( OR =4.229, 95% CI : 1.098-16.287, P =0.036), and ALT ( OR =0.965, 95% CI : 0.937-0.994, P =0.018) were independent influencing factors for LLV in CHB patients, and the predictive model of Logit(MLLV)=-8.668+1.441×lgHBsAg+0.598×lgHBV DNA-0.016×ALT was established based on these factors, which had a larger area under the ROC curve than HBV DNA, HBsAg, and ALT (0.931 vs 0.774/0.856/0.666), with a sensitivity of 85.00% and a specificity of 93.10% at the optimal cut-off value of 0.44. The CHB patients with baseline HBV DNA > 7.29 lgIU/mL or HBsAg > 4.38 lgIU/mL had a significantly lower DNA negative conversion rate than those with DNA ≤7.29 lgIU/mL or HBsAg ≤4.38 lgIU/mL ( χ 2 =22.52 and 26.35, both P < 0.001). In the CHB patients, the highest reduction rates of HBV DNA and HBsAg were observed at weeks 12 and 24, respectively, and the LLV group had significantly higher levels of HBV DNA and HBsAg than the SVR group at weeks 0, 12, 24, 36, and 48 (HBV DNA: t =-4.084, -4.526, -5.688, -7.123, and -6.266, all P < 0.001; HBsAg: t =-4.652, -4.691, -4.952, -4.804, and -4.407, all P < 0.001). Conclusion For the CHB patients treated with NAs for the first time, those with high HBV DNA load, high HBsAg quantification, and low ALT level at baseline are more likely to develop LLV, and dynamic monitoring of these indices is of great significance to observe the onset of LLV.

OBJECTIVE: To study the difference in age estimation based on quantitative analysis of DNA methylation by MassARRAY and pyrosequencing techniques. METHODS: The methylation levels of 9 CpG sites from two independent whole blood sample sets (containing 65 and 62 samples) were detected using MassARRAY and pyrosequencing techniques. Z-score transformation was used to remove the batch effects of different techniques, and a linear regression model was used for age prediction. RESULTS: For age prediction using the MassARRAY system, the 65 samples showed a mean absolute difference (MAD) of 2.49 years before Z-score transformation of the data and 2.44 years after the transformation, similar to the results in the 62 samples (MAD of 3.36 years before and 3.42 years after Z-score transformation). For data typed from pyrosequencing, the 65 samples showed a MAD of 4.20 years before and 2.76 years after data Z-score transformation, also similar to the results in the 62 samples (MAD of 3.92 years before and 3.63 years after data transformation). CONCLUSIONS Z-score transformation can effectively reduce the system batch effect between MassARRAY and pyrosequencing. Data from the MassARRAY system allows direct age estimation without further data processing, while the pyrosequencing data may increase the error in age estimation, which can be corrected by Z-score transformation of the data.
CpG Islands/genetics* ; DNA Methylation ; High-Throughput Nucleotide Sequencing ; Linear Models ; Sequence Analysis, DNA