INHIBITION OF FOCAL ADHESION KINASE EXPRESSION CORRELATES WITH CHANGES IN THE CYTOSKELETON BUT NOT APOPTOSIS IN PRIMARY CULTURES OF CHICK EMBRYO CELLS
Bibliographic record
Abstract
Cell adhesion to the extracellular matrix through integrin receptors can activate signaling cascades within the cell. Focal adhesion kinase (FAK) is a protein tyrosine kinase activated by integrin adhesion. The role of FAK within the cell is not clear, although evidence suggests roles in cell motility or the regulation of adhesion-dependent cell survival. We have treated primary cultures of chick embryo cells with antisense oligonucleotides to FAK to reduce the level of FAK protein expression. Levels of the related protein, proline-rich tyrosine kinase 2 (Pyk2) and the FAK substrate paxillin, were unaffected by the addition of oligonucleotides, whereas FAK expression was reduced by 70%. Levels of apoptotic cell death did not significantly increase after the addition of oligonucleotides. However, there was a change in the distribution of focal adhesion sites from a uniformly distributed pattern to a mainly peripheral pattern. This was accompanied by a loss of stress fibers and an increase in the peripheral actin cytoskeleton, as the cells became rounded. These results suggest that in these early embryonic cells, FAK expression regulates the arrangement of focal adhesions and the cytoskeleton that result in a motile phenotype, but that FAK does not appear to regulate apoptosis.
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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) | 0.002 | 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".