p38 mitogen-activated protein kinase interacts with vinculin at focal adhesions during fatty acid-stimulated cell adhesion
Bibliographic record
Abstract
Arachidonic acid stimulates cell adhesion by activating α2β1 integrins in a process that depends on protein kinases, including p38 mitogen activated protein kinase. Here, we describe the interaction of cytoskeletal components with key signaling molecules that contribute to the spreading of, and morphological changes in, arachidonic acid-treated MDA-MB-435 human breast carcinoma cells. Arachidonic acid-treated cells showed increased attachment and spreading on collagen type IV, as measured by electric cell-substrate impedance sensing. Fatty acid-treated cells displayed short cortical actin filaments associated with an increased number of β1 integrin-containing pseudopodia, whereas untreated cells displayed elongated stress fibers and fewer clusters of β1 integrins. Confocal microscopy of arachidonic acid-treated cells showed that vinculin and phospho-p38 both appeared enriched in pseudopodia and at the tips of actin filaments, and fluorescence ratio imaging indicated the increase was specific for the phospho-(active) form of p38. Immunoprecipitates of phospho-p38 from extracts of arachidonic acid-treated cells contained vinculin, and GST-vinculin fusion proteins carrying the central region of vinculin bound phospho-p38, whereas fusion proteins expressing the terminal portions of vinculin did not. These data suggest that phospho-p38 associates with particular domains on critical focal adhesion proteins that are involved in tumor cell adhesion and spreading, and that this association can be regulated by factors in the tumor microenvironment.
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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".