A dynamic <i>Shh</i> expression pattern, regulated by SHH and BMP signaling, coordinates fusion of primordia in the amniote face
Bibliographic record
Abstract
The mechanisms of morphogenesis are not well understood, yet shaping structures during development is essential for establishing correct organismal form and function. Here, we examine mechanisms that help to shape the developing face during the crucial period of facial primordia fusion. This period of development is a time when the faces of amniote embryos exhibit the greatest degree of similarity, and it probably results from the necessity for fusion to occur to establish the primary palate. Our results show that hierarchical induction mechanisms, consisting of iterative signaling by Sonic hedgehog (SHH) followed by Bone morphogenetic proteins (BMPs), regulate a dynamic expression pattern of Shh in the ectoderm covering the frontonasal (FNP) and maxillary (MxP) processes. Furthermore, this Shh expression domain contributes to the morphogenetic processes that drive the directional growth of the globular process of the FNP toward the lateral nasal process and MxP, in part by regulating cell proliferation in the facial mesenchyme. The nature of the induction mechanism that we discovered suggests that the process of fusion of the facial primordia is intrinsically buffered against producing maladaptive morphologies, such as clefts of the primary palate, because there appears to be little opportunity for variation to occur during expansion of the Shh expression domain in the ectoderm of the facial primordia. Ultimately, these results might explain why this period of development constitutes a phylotypic stage of facial development among amniotes.
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 | 0.000 | 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) | 0.000 | 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".