Fibroblast Growth Factor-2 and Remodeled Type I Collagen Control Membrane Protrusion in Human Vascular Smooth Muscle Cells
Bibliographic record
Abstract
Plasma membrane protrusion is fundamental to cell motility, but its regulation by the extracellular environment is not well elucidated. We have quantified lamellipodial protrusion dynamics in human vascular smooth muscle cells exposed to fibroblast growth factor 2 (FGF-2) and type I collagen, two distinct ligands presented to vascular cells during arterial remodeling. Video microscopy revealed that FGF-2 stimulated a modest increase in lamellipodial protrusion rate that peaked within 15 min. This response was associated with immediate but transient activation of Rac1 and was inhibited in cells infected with retrovirus containing cDNA encoding dominant-negative Rac1. A 1-h exposure to FGF-2 also set up a second phase of more striking lamellipodial protrusion evident at 24-36 h. This delayed response was most pronounced when cells were on type 1 collagen and was associated with FGF-2-induced expression of collagenase-1 that localized to the edge of protruding lamellipodia. Moreover, late membrane protrusion was inhibited when cells were on collagenase-resistant type I collagen, implicating degraded collagen as a mediator. For cells on collagen, the immediate activation of Rac1 by FGF-2 was followed by a sustained wave of Rac1 activation that was inhibited when cleavage of the collagen triple helix was prevented and also by blockade of alpha(v)beta(3) integrin. We conclude that lamellipodial protrusion in smooth muscle cells can be regulated by waves of Rac1 activation, corresponding to the sequential presentation of FGF-2 and remodeled collagen. The findings thus reveal a previously unrecognized level of coordination among extracellular input that enables cells to maintain protrusive activity over prolonged periods.
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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".