Analysis of the linker for activation of T cells and the linker for activation of B cells in natural killer cells reveals a novel signaling cassette, dual usage in ITAM signaling, and influence on development of the Ly49 repertoire
Bibliographic record
Abstract
The linker for activation of T cells (LAT) and the linker for activation of B cells (LAB/NTAL/LAT2) are integral proteins in receptor coupling to downstream events. Both proteins are expressed in natural killer (NK) cells and LAT is phosphorylated during target cell interactions or ligation of the immunoreceptor tyrosine-based activation motif (ITAM)-coupled CD16. Regardless, Lat(-/-) mice exhibit normal natural and antibody-mediated killing. Here we place both LAT and LAB in the DAP12 pathway of NK cells. Moreover, we unveil a LAT-independent pathway that requires expression of Syk. Mice lacking either LAT or LAB have a skewed Ly49 repertoire, and activated NK cells from Lat(-/-) mice have reduced responses to the ITAM-coupled receptor NK1.1. In contrast, resting Lat(-/-) NK cells show intact NK1.1 responses, whereas NK cells without LAB are hyperactive. Elimination of both adaptors severely reduces NK1.1 signaling under both conditions. Together these data show that NK ITAMs preferentially use a signaling cassette regulated by interplay between LAT and LAB. Activation by interleukin-2 causes a shift to greater dependency on LAT due to suppression of Syk signaling. The overlapping use of multiple adaptors permits fine-tuning of NK-cell ITAM responses over the course of an immune response.
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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".