LFA-1 activates focal adhesion kinases FAK1/PYK2 to generate LAT-GRB2-SKAP1 complexes that terminate T-cell conjugate formation
Bibliographic record
Abstract
Lymphocyte function-associated antigen 1 (LFA-1) affinity and avidity changes have been assumed to mediate adhesion to intercellular adhesion molecule-1 for T-cell conjugation to dendritic cells (DC). Although the T-cell receptor (TCR) and LFA-1 can generate intracellular signals, the immune cell adaptor protein linker for the activation of T cells (LAT) couples the TCR to downstream events. Here, we show that LFA-1 can mediate both adhesion and de-adhesion, dependent on receptor clustering. Although increased affinity mediates adhesion, LFA-1 cross-linking induced the association and activation of the protein-tyrosine kinases FAK1/PYK1 that phosphorylated LAT selectively on a single Y-171 site for the binding to adaptor complex GRB-2-SKAP1. LAT-GRB2-SKAP1 complexes were distinct from canonical LAT-GADs-SLP-76 complexes. LFA-1 cross-linking increased the presence of LAT-GRB2-SKAP1 complexes relative to LAT-GADs-SLP-76 complexes. LFA-1-FAK1 decreased T-cell-dendritic cell (DC) dwell times dependent on LAT-Y171, leading to reduced DO11.10 T cell binding to DCs and proliferation to OVA peptide. Overall, our findings outline a new model for LFA-1 in which the integrin can mediate both adhesion and de-adhesion events dependent on receptor cross-linking.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".