Rhamm−/− fibroblasts are defective in CD44-mediated ERK1,2 motogenic signaling, leading to defective skin wound repair
Bibliographic record
Abstract
Rhamm (receptor for hyaluronan-mediated motility) is an hyaluronan binding protein with limited expression in normal tissues and high expression in advanced cancers. To understand its physiological functions and identify the molecular mechanisms underlying these functions, we created mice with a genetic deletion of Rhamm. We show that Rhamm(-/-) fibroblasts fail to resurface scratch wounds >3 mm or invade hyaluronan-supplemented collagen gels in culture. We identify a requirement for Rhamm in the localization of CD44 to the cell surface, formation of CD44-ERK1,2 (extracellular-regulated kinase 1,2) complexes, and activation/subcellular targeting of ERK1,2 to the cell nucleus. We also show that cell surface Rhamm, restricted to the extracellular compartment by linking recombinant protein to beads, and expression of mutant active mitogen-activated kinase kinase 1 (Mek1) are sufficient to rescue aberrant signaling through CD44-ERK1,2 complexes in Rh(-/-) fibroblasts. ERK1,2 activation and fibroblast migration/differentiation is also defective during repair of Rh(-/-) excisional skin wounds and results in aberrant granulation tissue in vivo. These results identify Rhamm as an essential regulator of CD44-ERK1,2 fibroblast motogenic signaling required for wound repair.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".