CD44-initiated Cell Spreading Induces Pyk2 Phosphorylation, Is Mediated by Src Family Kinases, and Is Negatively Regulated by CD45
Bibliographic record
Abstract
CD44 is a cell adhesion molecule implicated in leukocyte adhesion and migration, co-stimulation of T cells, and tumor metastasis. CD45 is a leukocyte-specific protein tyrosine phosphatase that dephosphorylates the Src family kinases, Lck and Fyn, in T cells. Positive regulation of Lck by CD45 is required for its effective participation in T cell receptor signaling events. Here, immobilized CD44 antibody induced a distinctive cell spreading in CD45(-), but not CD45(+), T cells, and this correlated with the induction of tyrosine-phosphorylated proteins. Two focal adhesion family kinases, Pyk2 and, to a lesser extent, FAK were inducibly phosphorylated, as was a potential substrate, Cas. CD44-mediated cell spreading and induced tyrosine phosphorylation were prevented by the Src family kinase inhibitor, PP2. Furthermore, 2-fold more Lck associated with CD44 in the low density sucrose fraction from CD45(-) T cells compared with CD45(+) T cells, suggesting that CD45 may regulate the association of Lck with CD44 in this fraction. Therefore, in CD45(-) T cells, CD44 signaling is mediated by Src family kinases, and this leads to Pyk2 phosphorylation, cytoskeletal changes, and cell spreading. This implicates CD45 in the negative regulation of Src family kinase-mediated CD44 signaling leading to T cell spreading.
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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".