Comment le virus de l’hépatite C détourne la réponse immunitaire adaptative orchestrée par les cellules dendritiques
Bibliographic record
Abstract
Chronic hepatitis C virus (HCV) is a liver-borne infectious disease that remains a major global health threat. The mechanisms whereby HCV evades the host's immune defences and establishes persistent infection remain elusive; but they likely require a complex and coordinated interruption of the interplay between innate and adaptive immune actors. This review discusses the concept that HCV evades the host's immune response to its components partly because of its ability to inactivate the major orchestrator of the adaptive immune response - the DCs. It argues that DCs constitute an immunologically relevant cellular viral host actively targeted by HCV. This targeting disrupts TRIF- and IPS-1-dependent but not MyD88-coupled pathogen recognition receptors (PRR) sensing pathways in these infected cells to foil the networks by which innate immunity to HCV is translated into virus-specific adaptive immune-mediated host resistance. Thus, as a culprit, this cell-specific and numerically restrained DC defect offers a promising field of investigation in which to study and understand the HCV-restricted nature of the deficit in cellular immunity in persistently infected -individuals who have otherwise normal immune functions to unrelated pathogens. In this model, protective immunity is contingent on proper processing and delivery of danger signals by DCs presenting HCV antigens.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".