β1/β3 integrin ligation is uncoupled from ERK1/ERK2 activation in cytotoxic T lymphocytes
Bibliographic record
Abstract
beta 3 integrins mediate fibronectin binding and enhanced activation of cytotoxic T lymphocytes (CTL). The intracellular signals initiated by beta 3 integrins in lymphocytes are not well characterized, but in many cell types, beta 1 integrin ligation activates mitogen-activated protein (MAP) kinases. In the present study, we find that fibronectin can synergize with very low levels of CD3 stimulation to activate the extracellular signal-regulated kinase (ERK)1 and ERK2 MAP kinases but that fibronectin alone induces no detectable MAP kinase activation in CTL. Surprisingly, antibodies to beta1 or beta 3 integrins were also unable to stimulate MAP kinase activation, suggesting that although beta 1 integrins are capable of stimulating MAP kinase activation in other cells, they cannot do so in CTL. In CTL, phosphorylation of proline-rich tyrosine kinase 2 downstream of integrin stimulation did not result in recruitment of the adaptor protein Grb2. Additionally, we examined the role of MAP kinases in regulating integrin-mediated adhesion. Anti-CD3-triggered adhesion to fibronectin was largely insensitive to the MAP kinase kinase inhibitor PD98059. Triggered cell-spreading on fibronectin was inhibited by PD98059 but not by U0126. In summary, ligation of beta 3 integrin by antibodies or fibronectin or of beta1 integrin by monoclonal antibodies fails to activate ERK MAP kinases, but integrin ligation synergizes with T cell receptor stimulation upstream of MAP kinases.
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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) | 0.001 | 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".