NK cells generate memory‐type responses to human cytomegalovirus‐infected fibroblasts
Bibliographic record
Abstract
Natural killer (NK) cells are cytotoxic lymphocytes that selectively respond against abnormal cells. Human cytomegalovirus (HCMV) infection causes expansion of NKG2C+CD57+ NK cells in vivo and NKG2C+ NK cells proliferate when cultured with HCMV‐infected cells. This raises the possibility of an NK‐cell subset selectively responding against a specific pathogen and accruing memory. To test this possibility, we compared proliferation, natural cytotoxicity and interferon‐γ (IFN‐γ) production of NK cells from HCMV‐seropositive and HCMV‐seronegative individuals co‐cultured with HCMV‐infected or uninfected MRC‐5 cells. There was no significant difference in proliferation of NK cells from HCMV‐seropositive or seronegative individuals against uninfected MRC‐5 cells, but significantly more NK cells from the HCMV‐seropositive group proliferated in response to HCMV‐infected MRC‐5 cells. Natural cytotoxicity of NK cells against K562 cells increased following co‐culture with HCMV‐infected versus uninfected MRC‐5 only for the HCMV‐seropositive group. After co‐culture with HCMV‐infected MRC‐5 cells, proliferating NK cells from HCMV‐seropositive donors selectively produced IFN‐γ when re‐exposed to HCMV‐infected MRC‐5 cells. Both NKG2C+ and NKG2C− NK cells proliferated in co‐culture with HCMV‐infected MRC‐5 cells, with the fraction of proliferating NKG2C+ NK cells directly correlating with the circulating NKG2C+ fraction. These data illustrate an at least partly NKG2C‐independent human NK‐cell memory‐type response against HCMV.
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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) | 0.003 | 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 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".