β1 Integrins Are Required To Mediate NK Cell Killing of <i>Cryptococcus neoformans</i>
Bibliographic record
Abstract
Abstract Cryptococcus neoformans is a fungal pathogen that causes fatal meningitis and pneumonia. During host defense to Cryptococcus, NK cells directly recognize and kill C. neoformans using cytolytic degranulation analogous to killing of tumor cells. This fungal killing requires independent activation of Src family kinase (SFK) and Rac1-mediated pathways. Recognition of C. neoformans requires the natural cytotoxicity receptor, NKp30; however, it is not known whether NKp30 activates both signal transduction pathways or whether a second receptor is involved in activation of one of the pathways. We used primary human NK cells and a human NK cell line and found that NKp30 activates SFK → PI3K but not Rac1 cytotoxic signaling, which led to a search for the receptor leading to Rac1 activation. We found that NK cells require integrin-linked kinase (ILK) to activate Rac1 for effective fungal killing. This observation led to our identification of β1 integrin as an essential anticryptococcal receptor. These findings demonstrate that multiple receptors, including β1 integrins and NKp30 and their proximal signaling pathways, are required for recognition of Cryptococcus, which activates a central cytolytic antimicrobial pathway leading to fungal killing.
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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".