Naturally Occurring Dominant Drug Resistance Mutations Occur Infrequently in the Setting of Recently Acquired Hepatitis C
Bibliographic record
Abstract
BACKGROUND: Direct-acting antivirals (DAAs) are predicted to transform hepatitis C therapy, yet little is known about the prevalence of naturally occurring resistance mutations in recently acquired HCV. This study aimed to determine the prevalence and frequency of drug resistance mutations in the viral quasispecies among HIV-positive and -negative individuals with recent HCV. METHODS: The NS3 protease, NS5A and NS5B polymerase genes were amplified from 50 genotype 1a participants of the Australian Trial in Acute Hepatitis C. Amino acid variations at sites known to be associated with possible drug resistance were analysed by ultra-deep pyrosequencing. RESULTS: A total of 12% of individuals harboured dominant resistance mutations, while 36% demonstrated non-dominant resistant variants below that detectable by bulk sequencing (that is, <20%) but above a threshold of 1%. Resistance variants (<1%) were observed at most sites associated with DAA resistance from all classes, with the exception of sofosbuvir. CONCLUSIONS: Dominant resistant mutations were uncommonly observed in the setting of recent HCV. However, low-level mutations to all DAA classes were observed by deep sequencing at the majority of sites and in most individuals. The significance of these variants and impact on future treatment options remains to be determined. Clinicaltrials.gov NCT00192569.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| 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) | 0.002 | 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".