Downstream branches of receptor tyrosine kinase signaling act interdependently to shape the face
Bibliographic record
Abstract
BACKGROUND: Previously we found that increasing fibroblast growth factor (FGF) signaling in the neural crest cells within the frontonasal process (FNP) of the chicken embryo caused dysmorphology that was correlated with reduced proliferation, disrupted cellular orientation, and lower MAPK activation but no change in PLCγ and PI3K activation. This suggests RTK signaling may drive craniofacial morphogenesis through specific downstream effectors that affect cellular activities. In this study we inhibited three downstream branches of RTK signaling to determine their role in regulating cellular activities and how these changes affect morphogenesis of the FNP. RESULTS: Small molecule inhibitors of MEK1/2, PI3K, and PLCγ were delivered individually and in tandem to the right FNP of chicken embryos. All treatments caused asymmetric proximodistal truncation on the treated side and a mild expansion on the untreated side compared to DMSO control treated FNPs. Inhibiting each pathway caused similar decreased proliferation and disrupted cellular orientation, and only mildly increased apoptosis. CONCLUSIONS: Since RTK signaling is a ubiquitous and tightly regulated biochemical system, we conclude that the downstream pathways are robust to developmental perturbation through redundant signaling systems.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".