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Objective To investigate the ability of combined baseline serum markers, i.e., HBV DNA, HBV RNA, HBsAg, and HBcrAg, to predict HBeAg seroconversion in patients with HBeAg-positive chronic hepatitis B (CHB) treated by nucleos(t)ide analogues. Methods A retrospective analysis was performed for 83 HBeAg-positive patients selected as subjects from the prospective CHB follow-up cohort established by Difficult & Complicated Liver Diseases and Artificial Liver Center, Beijing YouAn Hospital, Capital Medical University, from June 2007 to July 2008, and the baseline serum levels of HBV DNA, HBV RNA, HBsAg, and HBcrAg were analyzed. The t -test or the Mann-Whitney U test was used for comparison of continuous data between two groups, and the chi-square test was used for comparison of categorical data between two groups. The Spearman method was used for correlation analysis. A Cox regression model was established to calculate HBeAg seroconversion prediction score, and the time-dependent receiver operating characteristic curve was used to evaluate the ability of combined markers in predicting HBeAg seroconversion. The Kaplan-Meier method was used to calculate cumulative seroconversion rate in each group, and the Log-rank test was used for comparison between groups. Results For the 83 HBeAg-positive patients, the median follow-up time was 108 months, and 44.58%(37/83) of these patients achieved HBeAg seroconversion. Compared with the non-seroconversion group, the HBeAg seroconversion group had significantly lower baseline serum levels of HBV DNA [6.23(1.99-9.28) log 10 IU/mL vs 7.69(2.05-8.96) log 10 IU/mL, Z =-2.345, P =0.019] and HBV RNA [4.81(1.40-7.53) log 10 copies/mL vs 6.22(2.00-8.49) log 10 copies/mL, Z =-1.702, P =0.010], and there were no significant differences in the levels of HBsAg and HBcrAg between the two groups ( P > 0.05). The Cox regression equation constructed based on the above serum markers showed a median score of 0.95(range 0.37-3.45) for predicting HBeAg seroconversion. In the total population, the combined score was negatively correlated with HBsAg, HBV DNA, HBV RNA, and HBcrAg ( r =-0.697, -0.787, -0.990, and -0.819, all P < 0.001). Based on the median prediction score, the patients were divided into high HBeAg seroconversion group and low HBeAg seroconversion group; as for the prediction of HBeAg seroconversion rate at 36, 60, and 84 months, the high HBeAg seroconversion group had a seroconversion rate of 43.90%, 51.20%, and 63.10%, respectively, while the low HBeAg seroconversion group had a seroconversion rate of 9.60%, 17.00%, and 19.8%, respectively, and there was a significant difference between the two groups ( χ 2 =11.6, P < 0.001). Conclusion The combined prediction score based on baseline serum HBV markers can predict HBeAg seroconversion in CHB patients treated by nucleos(t)ide analogues.
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Objective To investigate the consistency between Shengxiang (S) and Xinbo (X) real-time PCR methods in the quantification of HBV RNA. Methods In the prospective follow-up cohort of 108 chronic hepatitis B (CHB) patients established from July 2007 to August 2008, 20 patients with HBeAg seroconversion were selected, and 20 patients without seroconversion were selected by propensity score matching at a ratio of 1∶ 1. The two quantification methods from S and X companies were used, and a retrospective analysis was performed for HBV RNA in serum samples at baseline and weeks 12, 24, and 48. The paired t -test was used for comparison of normally distributed continuous data between groups, and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between groups; the chi-square test was used for comparison of categorical data. The Pearson correlation coefficient, intraclass correlation coefficient (ICC), and the Bland-Altman method were used to evaluate the consistency of the two quantification methods. Results A total of 132 serum samples were tested by S reagent, and 154 were tested by X reagent; the detection rate of HBV RNA was 100% by both reagents. A total of 131 serum samples were tested by both reagents, with 34 samples at baseline and 29, 35, and 33 samples, respectively, at weeks 12, 24, and 48 of follow-up; at these four time points, the HBV RNA quantification data detected by X reagent were significantly higher than those detected by S reagent (5.75±1.64/5.43±1.73/5.13±1.54/4.76±1.55 log 10 copies/mL vs 4.80±1.48/4.52±1.53/4.10±1.50/3.92± 1.43 log 10 copies/mL, t =8.348, t =5.341, Z =-5.086, Z =-4.762, all P < 0.001). The correlation analysis of the two methods showed a Pearson correlation coefficient of 0.915 (95% confidence interval [ CI ]: 0.836-0.957) and an ICC of 0.771(95% CI : -0.021 to 0.931) at baseline, a Pearson correlation coefficient of 0.849(95% CI : 0.701-0.927) and an ICC of 0.733(95% CI : 0.138-0.902) at week 12, a Pearson correlation coefficient of 0.951(95% CI : 0.905-0.975) and an ICC of 0.776(95% CI : -0.058 to 0.942) at week 24, and a Pearson correlation coefficient of 0.933(95% CI : 0.867-0.967) and an ICC of 0.804(95% CI : -0.014 to 0.944) at week 48 (all P < 0.05). The Bland-Altman analysis showed that the difference of 96.18%(126/131) samples tested by the two methods was within the mean difference±1.96 standard deviation. Conclusion HBV RNA quantification by X reagent is higher than that by S reagent, while the two real-time PCR quantification methods show a good consistency in CHB patients with HBeAg seroconversion and those without seroconversion.
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Objective To investigate the relationship between the composition of vaginal microbiota and the course of cervical precancerous lesion.Methods A total of 64 vaginal swabs were collected from 22 healthy women, 18 CINⅠ patients and 24 CINⅡ/Ⅲ patients who visited Obstetrics and Gynecology of the Second Xiangya Hospital of Central South University during July 2014 and July 2015.The Bacterial genomic DNA was extracted and the V3 and V4 hypervariable regions of 16S rRNA were amplified and high-throughput sequenced.The abundance and composition of vaginal microbiota were analyzed by Uparse, Mothur and LefSe statistical software.Results There was no significant difference in Alpha diversity index between CINⅡ/Ⅲ group(Chao:63±32;ACE:72±38;Simpson:0.70±0.27;Shannon:0.70±0.63) and control group ( Chao:48±24;ACE:54±25;Simpson:0.71±0.27;Shannon:0.65±0.58)(W=192,P=0.11;W=189,P=0.10;W=281,P=0.72;W=241,P=0.62).The ACE(85±37) and Chao(66±25) values of CINⅠgroup were significantly different from those of the control group (ACE:54±25;Chao:48±24)(W=99,P=0.006;W=113,P=0.02).At the phylum level, 78.69%(309 020/392 722) of the vaginal microbiota in the control group was Firmicutes, 16%(62 846/392 722) was Actinobacteria.Firmicutes was reduced to 64.86%(208 422/321 318) and Actinobacteria increased to 27.71%(89 040/321 318) in CINⅠgroup.The composition of vaginal microbiotain in CINⅡ/Ⅲ group was similar to those of control group.At the genus level, the composition of vaginal microbiota were similar between CINⅡ/Ⅲ group and control group, with Lactobacillus as predominant genus[71.81%(307 658/418 424)], Gardnerella[12.91%(55 299/428 424)], others such as Prevotella, atopobium were less.In the CINⅠ group, the abundance of Lactobacillus was decreased to 56.26%(180 787/321 318), Gardnerella was increased to 19.62%(63 057/321 318), and Listeria was increased to 7.7%(24 746/321 318).The composition of vaginal microbiota in the most samples was classified as CSTⅢ and CSTⅠ, with Lactobacillus inersand and Lactobacillus crispatus were dominant respectively.There was no significant difference in the composition of vaginal microbiota between the three groups(χ2=2.72, P=0.949).LEfSe analysis showed that the abundance of bacteria in CIN group and control group were varied.At the genus level, there were significant differences in the abundance of Geobacter, Atopobium and Ureaplasma (P<0.05, P<0.05, P<0.01, respectively).At the species level, there was significant difference in the abundance of Ureaplasma urealyticum serotype 9 (P<0.01).Conclusion The diversity and the composition of vaginal microbiota were similar between CIN patients and healthy women, but the abundances of some bacteria were varied, with Ureaplasma increased in patients with CIN.
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AIM To observe the relationship between dose effect and time effect on hepatoxicity of Gardenia jasminoides Ellis extract in rats.MOTHODS Wistar rats were divided into four groups:low,middle and high (3,10,and 30 g/kg) dose of G.Jasminoides groups (administrated by gavage),and the normal control group were orally given deionized water.All rats were observed daily during the administration period.On the 7th,14th,28th day after the administration,blood samples were collected;serum alanine transaminase (ALT),aspartate transaminase (AST),alkaline phosphatase (ALP),glutamic dehydrogenase (GLDH) activity and total bile acid (TBA) and total bilirubin (TBIL) were determined.The livers were weighed and the liver index was calculated.HE staining and observation of histopathological changes in the structure of liver tissue under light microscopy were performed.RESULTS After the 7th day of administration,the rats in high dose group showed lower food consumption and slowly increased body weight.Serum ALT,AST,ALP,TBA,TBIL and GLDH in rats from high dose group were significantly higher than those in the normal control group.The liver index of rats in the middle and high dose groups was significantly increased than that in the normal control group.After the 14th day of administration,serum ALT,TBA and TBIL in rats from the high dose group were significantly higher than those in the normal group.The liver index of rats in the middle and high dose groups was significantly increased than that in the normal control group.After 28th day of administration,serum ALT and TBA in the rats from the high dose group,TBIL and GLDH in rats from the middle dose group,and GLDH in rats from the low dose group were significantly higher than those in the normal control group.The liver indexes of rats in all dose groups were significantly increased than those in the normal control group.After the 7th,14th or 28th day of the treatment,histopathological changes such as the liver cell hypertrophy,interlobular bile duct hyperplasia,and inflammatory cell infiltration appeared in the middle and high dose groups.CONCLUSION The high dose of G.jasminoides can induce and increase liver toxicity with the increase in dose,but at high dose level,liver toxicity does not increase with time.
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The preclinical safety assessment of hepatotoxicity drugs has a low sensitivity and low specificity. Related tests often generate false negative results and unexpected toxicity,which is one of the major reasons for the cessation of development and withdrawal from the market. Proteomics enjoys advantages of rapidness,high sensitivity and high throughout,and therefore can be used in the search for new biomarkers of hepatotoxicity in preclinical studies,leading to the development of safer drugs and a more efficient drug discovery process. In this review,the current preclinical biomark?ers of liver toxicity and development of proteomic technologies in the discovery and validation of bio?markers of drug-induced liver injury are described,in general the application of proteomics to Chinese medicine-induced liver toxicity in particular. Compared with traditional methods,proteomic technologies show promising results for the discovery of novel hepatotoxic markers. Proteomics,in conjugation with other omics techniques,will play a major role in the early stage of hepatotoxicity screening and will prove to be a good bridge in clinics in the future.