Alterations in retinoic acid signaling affect the development of the mouse coronary vasculature
Bibliographic record
Abstract
BACKGROUND: During the final stages of heart development the myocardium grows and becomes vascularized by means of paracrine factors and cell progenitors derived from the epicardium. There is evidence to suggest that retinoic acid (RA), a metabolite of vitamin A, plays an important role in epicardial-based developmental programming. However, the consequences of altered RA-signaling in coronary development have not been systematically investigated. RESULTS: We explored the developmental consequences of altered RA-signaling in late cardiogenic events that involve the epicardium. For this, we used a model of embryonic RA excess based on mouse embryos deficient in the retinaldehyde reductase DHRS3, and a complementary model of embryonic RA deficiency based on pharmacological inhibition of RA synthesis. We found that alterations in embryonic RA signaling led to a thin myocardium and aberrant coronary vessel formation and remodeling. Both excess, and deficient RA-signaling are associated with reductions in ventricular coverage and density of coronary vessels, altered vessel morphology, and impaired recruitment of epicardial-derived mural cells. Using a combined transcriptome and proteome profiling approach, we found that RA treatment of epicardial cells influenced key signaling pathways relevant for cardiac development. CONCLUSIONS: Epicardial RA-signaling plays critical roles in the development of the coronary vasculature needed to support myocardial growth. Developmental Dynamics 247:976-991, 2018. © 2018 Wiley Periodicals, Inc.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".