Apical expansion of calvarial osteoblasts and suture patency is dependent on graded fibronectin cues
Bibliographic record
Abstract
Summary The skull roof, or calvaria, is comprised of interlocking plates of bone. Premature suture fusion (craniosynostosis, CS) or persistent fontanelles are common defects in calvarial development. Although some of the genetic causes of these disorders are known, we lack an understanding of the instructions directing the growth and migration of progenitors of these bones, which may affect the suture patency. Here, we identify graded expression of Fibronectin (FN1) protein in the mouse embryonic cranial mesenchyme (CM) that precedes the apical expansion of calvarial osteoblasts. Syndromic forms of CS exhibit dysregulated FN1 expression, and we find FN1 expression is altered in a mouse CS model as well. Conditional deletion of Fn1 in CM causes diminished frontal bone expansion by altering cell polarity and shape. To address how osteoprogenitors interact with the observed FN1 prepattern, we conditionally ablate Wasl/N-Wasp to disrupt F-actin junctions in migrating cells, impacting lamellipodia and cell-matrix interaction. Neural crest-targeted deletion of Wasl results in a diminished actin network and reduced expansion of frontal bone primordia similar to conditional Fn1 mutants. Interestingly, defective calvaria formation in both the Fn1 and Wasl mutants occurs without a significant change in proliferation, survival, or osteogenesis. Finally, we find that CM-restricted Fn1 deletion leads to premature fusion of coronal sutures. These data support a model of FN1 as a directional substrate for calvarial osteoblast migration that may be a common mechanism underlying many cranial disorders of disparate genetic etiologies.
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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".