NK cell recruitment limits tissue damage during an enteric helminth infection
Bibliographic record
Abstract
Parasitic helminths cause significant damage as they migrate through host tissues to complete their life cycle. While chronic helminth infections are characterized by a well-described Type 2 immune response, the early, tissue-invasive stages are not well understood. Here we investigate the immune pathways activated during the early stages of Heligmosomoides polygyrus bakeri (Hpb), a natural parasitic roundworm of mice. In contrast to the Type 2 immune response present at later stages of infection, a robust Type 1 immune signature including IFNg production was dominant at the time of parasite invasion and granuloma formation. This early response was associated with an accumulation of activated Natural Killer (NK) cells, with no increase of other innate lymphoid cell populations. Parabiosis and confocal microscopy studies indicated that NK cells were recruited from circulation to the small intestine, where they surrounded parasitic larvae. NK cell recruitment required IFNγ receptor signaling, but was independent of CXCR3 expression. The depletion of tissue-infiltrating NK cells altered neither worm burden nor parasite fitness, but increased vascular injury, suggesting a role for NK cells in mediating tissue protection. Together, these data identify an unexpected role for NK cells in promoting disease tolerance during the invasive stage of an enteric helminth infection.
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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) | 0.001 | 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".