<scp>NR2F1</scp> regulates a Schwann cell precursor‐vs‐melanocyte cell fate switch in a mouse model of Waardenburg syndrome type <scp>IV</scp>
Bibliographic record
Abstract
Waardenburg syndrome type 4 (WS4) combines abnormal development of neural crest cell (NCC)-derived melanocytes (causing depigmentation and inner ear dysfunction) and enteric nervous system (causing aganglionic megacolon). The full spectrum of WS4 phenotype is present in Spot mice, in which an insertional mutation close to a silencer element leads to NCC-specific upregulation of the transcription factor-coding gene Nr2f1. These mice were previously found to develop aganglionic megacolon because of NR2F1-induced premature differentiation of enteric neural progenitors into enteric glia. Intriguingly, this prior work also showed that inner ear dysfunction in Spot mutants specifically affects balance but not hearing, consistent with the absence of melanocytes in the vestibule only. Here, we report an analysis of the effect of Nr2f1 upregulation on the development of both inner ear and skin melanocytes, also taking in consideration their origin relative to the dorsolateral and ventral NCC migration pathways. In the trunk, we found that NR2F1 overabundance in Spot NCCs forces dorso-laterally migrating melanoblasts to abnormally adopt a Schwann cell precursor (SCP) fate and conversely prevents ventrally migrating SCPs to normally adopt a melanoblast fate. In the head, Nr2f1 upregulation appears not to be uniform, which might explain why SCP-derived melanocytes do colonize the cochlea while non-SCP-derived melanocytes cannot reach the vestibule. Collectively, these data point to a key role for NR2F1 in the control of SCP-vs-melanocyte fate choice and unveil a new pathogenic mechanism for WS4. Moreover, our data argue against the proposed existence of a transit-amplifying compartment of melanocyte precursors in hair follicles.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".