Nkx2.5 regulates endothelin converting enzyme‐1 during pharyngeal arch patterning
Bibliographic record
Abstract
In gnathostomes, dorsoventral (D-V) patterning of neural crest cells (NCC) within the pharyngeal arches is crucial for the development of hinged jaws. One of the key signals that mediate this process is Endothelin-1 (EDN1). Loss of EDN1 binding to the Endothelin-A receptor (EDNRA) results in loss of EDNRA signaling and subsequent facial birth defects in humans, mice and zebrafish. A rate-limiting step in this crucial signaling pathway is the conversion of immature EDN1 into a mature active form by Endothelin converting enzyme-1 (ECE1). However, surprisingly little is known about how Ece1 transcription is induced or regulated. We show here that Nkx2.5 is required for proper craniofacial development in zebrafish and acts in part by upregulating ece1 expression. Disruption of nkx2.5 in zebrafish embryos results in defects in both ventral and dorsal pharyngeal arch-derived elements, with changes in ventral arch gene expression consistent with a disruption in Ednra signaling. ece1 mRNA rescues the nkx2.5 morphant phenotype, indicating that Nkx2.5 functions through modulating Ece1 expression or function. These studies illustrate a new function for Nkx2.5 in embryonic development and provide new avenues with which to pursue potential mechanisms underlying human facial disorders.
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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".