Sonic Hedgehog signaling regulates the optimal differentiation pace from early‐stage mesoderm to cardiogenic mesoderm in mice
Bibliographic record
Abstract
Abstract Sonic Hedgehog ( Shh ), encoding an extracellular signaling molecule, is vital for heart development. Shh null mutants show congenital heart disease due to left–right asymmetry defects stemming from functional anomaly in the midline structure in mice. Shh signaling is also known to affect cardiomyocyte differentiation, endocardium development, and heart morphogenesis, particularly in second heart field (SHF) cardiac progenitor cells that contribute to the right ventricle, outflow tract, and parts of the atrium. Despite extensive studies, our understanding remains incomplete. Notably, Shh signaling is suggested to promote cardiac differentiation, while paradoxically preventing premature differentiation of SHF progenitors. In this study, we elucidate the role of Shh signaling in the earliest phase of cardiac differentiation. Our meta‐analysis of single‐cell RNA sequencing suggests that cardiogenic nascent mesoderm cells expressing the bHLH transcription factor Mesp1 interact with axial mesoderm via Hh signaling. Activation of Hh signaling using a Smoothened agonist delayed or suppressed the differentiation of primitive streak cells expressing T‐box transcription factor T to Mesp1 + nascent mesoderm cells both in vitro and ex vivo. Conversely, inhibition of Hh signaling by cyclopamine facilitated cardiac differentiation. The reduction of Eomes , an inducer of Mesp1 , by Hh signaling appears to be the underlying mechanism of this phenomenon. Our data suggest that SHH secreted from axial mesoderm inhibits premature differentiation of T + cells to Mesp1 + nascent mesoderm cells, thereby regulating the pace of cardiac differentiation. These findings enhance our comprehension of Shh signaling in cardiac development, underscoring its crucial role in early cardiac differentiation.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".