Do antiviral CD8+ T cells select hepatitis C virus escape mutants? Analysis in diverse epitopes targeted by human intrahepatic CD8+ T lymphocytes
Bibliographic record
Abstract
Hepatitis C virus (HCV) is a variable RNA virus that can readily establish persistent infection. Cellular immune responses are important in the early control of the virus. Evidence from animal models suggests that mutation in epitopes recognized by CD8+ T lymphocytes may play an important role in the establishment of persistence but in human persistent infection, equivalent evidence is lacking. We investigated this by analysing a unique resource: viruses from a set of chronically HCV-infected individuals in whom the CD8+ T-cell responses in liver had previously been accurately mapped. Virus was sequenced in seven individuals at 10 epitopes restricted by 10 human leucocyte antigen (HLA) molecules. Two main patterns emerged: in the majority of epitopes sequenced, no variation was seen. In three epitopes, mutations were identified which were compatible with immune escape as assessed using phylogenetic and/or functional studies. These data suggest that - even where specific intrahepatic T cells are detectable - many epitopes do not undergo mutation in chronic human infection. On the contrary, virus may escape from intrahepatic CD8+ T-cell responses in a 'patchy' manner in certain specific epitopes. Furthermore, longitudinal studies to identify the differences between 'selecting' and 'nonselecting' intrahepatic CD8+ T-cell responses are needed in HCV infection.
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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".