<scp>NK</scp> cells in self‐limited <scp>HCV</scp> infection exhibit a more extensively differentiated, but not memory‐like, repertoire
Bibliographic record
Abstract
Summary Natural killer (NK) cells have long been thought of as a purely innate immune cell population, but increasing reports have described developmental and functional qualities of NK cells that are commonly associated with cells of the adaptive immune system. Of these features, the ability of NK cells to acquire functional qualities associated with immunological memory and continuous differentiation resulting in the formation of specific NK cell repertoires has recently been highlighted in viral infection settings. By making use of a unique cohort of monitored, at‐risk intravenous drug users in this study, we were able to dissect the phenotypic and functional parameters associated with NK cell differentiation and NK cell memory in patients 3 years after acute HCV infection and either the subsequent self‐clearance or progression to chronicity. We observed increased expression of cytolytic mediators and markers CD56bright and NKp46+ of NK cells in patients with chronic, but not self‐limited HCV infection. Patients with a self‐limited infection expressed higher levels of differentiation‐associated markers CD57 and KIRs, and lower levels of NKG2A. A more extensively differentiated NK cell phenotype is associated with self‐clearance in HCV patients, while the NK cells of chronic patients exhibited more naïve and effector NK cell phenotypic and functional characteristics. The identification of these distinct NK cell repertoires may shed light on the role NK cells play in determining the outcome of acute HCV infections, and the underlying immunological defects that lead to chronicity.
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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) | 0.002 | 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".