The paradox of NKp46 <sup>+</sup> natural killer cells: drivers of severe hepatitis C virus-induced pathology but in-vivo resistance to interferon α treatment
Bibliographic record
Abstract
OBJECTIVE: There is evidence that natural killer (NK) cells help control persistent viral infections including hepatitis C virus (HCV). The phenotype and function of blood and intrahepatic NK cells, in steady state and after interferon (IFN) α treatment has not been fully elucidated. DESIGN: We performed a comparison of NK cells derived from blood and intrahepatic compartments in multiple paired samples from patients with a variety of chronic liver diseases. Furthermore, we obtained serial paired samples from an average of five time points in HCV patients treated with IFNα. RESULTS: Liver NK cells demonstrate a distinct activated phenotype compared to blood manifested as downregulation of the NK cell activation receptors CD16, NKG2D, and NKp30; with increased spontaneous degranulation and IFN production. In contrast, NKp46 expression was not downregulated. Indeed, NKp46-rich NK populations were the most activated, correlating closely with the severity of liver inflammation. Following initiation of IFNα treatment there was a significant increase in the proportion of intrahepatic NK cells at days 1 and 3. NKp46-rich NK populations demonstrated no reserve activation capacity with IFNα treatment and were associated with poor viral control on treatment and treatment failure. CONCLUSIONS: NKp46 marks out pathologically activated NK cells, which may result from a loss of homeostatic control of activating receptor expression in HCV. Paradoxically these pathological NK cells do not appear to be involved in viral control in IFNα-treated individuals and, indeed, predict slower rates of viral clearance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
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 teacher head, 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".