Fibroblast growth factor signals regulate a wave of Hedgehog activation that is essential for coronary vascular development
Bibliographic record
Abstract
Myocardial infarction and ischemic heart disease are the leading cause of death in the industrial world. Therapies employed for treating these diseases are aimed at promoting increased blood flow to cardiac tissue. Pharmacological induction of new coronary growth has recently been explored, however, clinical trials with known proangiogenic factors have been disappointing. To identify novel therapeutic targets, we have explored signaling pathways that govern embryonic coronary development. Using a combination of genetically engineered mice and an organ culture system, we identified novel roles for fibroblast growth factor (FGF) and Hedgehog (HH) signaling in coronary vascular development. We show that FGF signals promote coronary growth indirectly by signaling to the cardiomyoblast through redundant function of Fgfr1 and Fgfr2. Myocardial FGF signaling triggers a wave of HH activation that is essential for vascular endothelial growth factor (Vegf)-A, Vegf-B, Vegf-C, and angiopoietin-2 (Ang2) expression. We demonstrate that HH is necessary for coronary vascular development and activation of HH signaling is sufficient to promote coronary growth and to rescue coronary defects due to loss of FGF signaling. These studies implicate HH signaling as an essential regulator of coronary vascular development and as a potential therapeutic target for coronary neovascularization. Consistent with this, activation of HH signaling in the adult heart leads to an increase in coronary vessel density.
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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".