Flightless anchors IQGAP1 and R-ras to mediate cell extension formation and matrix remodeling
Bibliographic record
Abstract
Tractional remodeling of collagen fibrils by fibroblasts requires long cell extensions that mediate fibril alignment. The formation of these cell extensions involves flightless I (FliI), an actin-binding protein that contains a leucine-rich-repeat (LRR), which binds R-ras and may regulate cdc42. We considered that FliI interacts with small GTPases and their regulators to mediate assembly of cell extensions. Mass spectrometry analyses of FliI immunoprecipitates showed abundant Ras GTPase-activating-like protein (IQGAP1), which in immunostained samples colocalized with FliI at cell adhesions. Knockdown of IQGAP1 reduced the numbers of cell extensions and the alignment of collagen fibrils. In experiments using dominant negative mutants, cdc42 activity was required for the formation of short extensions while R-ras was required for the formation of long extensions. Immunoprecipitation of wild-type and mutant constructs showed that IQGAP1 associated with cdc42 and R-ras; this association required the GAP-related domain (1004-1237 aa) of IQGAP1. In cells transfected with FliI mutants, the LRR of FliI, but not its gelsolin-like domains, mediated association with cdc42, R-ras, and IQGAP1. We conclude that FliI interacts with IQGAP1 and co-ordinates with cdc42 and R-ras to control the formation of cell extensions that enable collagen tractional remodeling.
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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 | 0.001 |
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".