Precore/basal core promoter mutants quantification throughout phases of hepatitis B virus infection by Simpleprobe
Bibliographic record
Abstract
AIM: To investigate precore/basal core promoter (PC/BCP) mutants throughout hepatitis B virus (HBV) infection and to determine their relationship to hepatitis B early antigen (HBeAg) titers. METHODS: We enrolled 191 patients in various stages of HBV infection at the Huashan Hospital and the Taizhou Municipal Hospital from 2010 to 2012. None of the patients received antiviral therapy. HBV DNA from serum, was quantified by real-time PCR. The HBV genotype was determined by direct sequencing of the S gene. We used the Simpleprobe ultrasensitive quantitative method to detect PC/BCP mutants in each patient. We compared the strain number, percentage, and the changes in PC/BCP mutants in different phases, and analyzed the relationship between PC/BCP mutants and HBeAg by multiple linear regression and logistic regression. RESULTS: Patients with HBV infection (n = 191) were assigned to groups by phase: Immune tolerance (IT) = 55, Immune clearance (IC) = 67, Low-replicative (LR) = 49, and HBeAg-negative hepatitis (ENH) = 20. Of the patients (male, 112; female, 79) enrolled, 122 were HBeAg-positive and 69 were HBeAg-negative. The median age was 33 years (range: 18-78 years). PC and BCP mutation detection rates were 84.82% (162/191) and 96.86% (185/191), respectively. In five HBeAg-negative cases, we detected double mutation G1896A/G1899A. The logarithm value of PC mutant quantities (log10 PC) significantly differed in IT, IC, and LR phases, as well as in the ENH phase (F = 49.350, P < 0.001). The logarithm value of BCP mutant quantities (log10 BCP) also differed during the four phases (F = 25.530, P < 0.001). Log10 PC and log10 BCP values were high in the IT and IC phases, decreased in the LR phase, and increased in the ENH phase, although the absolute value at this point remained lower than that in the IT and IC phases. PC mutant quantity per total viral load (PC%) and BCP mutant quantity per total viral load (BCP%) differed between phases (F = 20.040, P < 0.001; F = 10.830, P < 0.001), with PC% and BCP% gradually increasing in successive phases. HBeAg titers negatively correlated with PC% (Spearman's rho = -0.354, P < 0.001) and BCP% (Spearman's rho = -0.395, P < 0.001). The negative correlation between PC% and HBeAg status was significant (B = -5.281, P = 0.001), but there was no such correlation between BCP% and HBeAg status (B = -0.523, P = 0.552). CONCLUSION: PC/BCP mutants become predominant in a dynamic and continuous process. Log10 PC, log10 BCP, PC% and BCP% might be combined to evaluate disease progression. PC% determines HBeAg status.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".