NK cells require antigen-specific memory CD4+ T cells to mediate superior effector functions during HSV-2 recall responses in vitro
Bibliographic record
Abstract
Abstract Natural killer (NK) cells have an important role in mounting protective innate responses against genital herpes simplex virus type 2 (HSV-2) infections. However their role as effectors in adaptive immune responses against HSV-2 is unclear. Here, we demonstrate that NK cells from C57BL/6 mice in an ex vivo splenocyte culture produce significantly more interferon γ (IFN-γ) upon re-exposure to HSV-2 antigens in a mouse model of genital HSV-2 immunization. We find that naïve NK cells do not require any prior stimulation or priming to be activated to produce IFN-γ. Our results demonstrate that HSV-2–experienced CD4+ T cells have a crucial role in coordinating NK cell activation and that their presence during HSV-2 antigen presentation is required to activate NK cells in this model of secondary immune response. We also examined the requirement of cell-to-cell contacts for both CD4+ T cells and NK cells. NK cells are dependent on direct interactions with other HSV-2–experienced splenocytes, and CD4+ T cells need to be in close proximity to NK cells to activate them. This study revealed that NK cells do not exhibit any memory toward HSV-2 antigens and, in fact, require specific interactions with HSV-2–experienced CD4+ T cells to produce IFN-γ
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".