The role of Zic transcription factors in regulating hindbrain retinoic acid signaling
Bibliographic record
Abstract
BACKGROUND: The reiterated architecture of cranial motor neurons aligns with the segmented structure of the embryonic vertebrate hindbrain. Anterior-posterior identity of cranial motor neurons depends, in part, on retinoic acid signaling levels. The early vertebrate embryo maintains a balance between retinoic acid synthetic and degradative zones on the basis of reciprocal expression domains of the retinoic acid synthesis gene aldhehyde dehydrogenase 1a2 (aldh1a2) posteriorly and the oxidative gene cytochrome p450 type 26a1 (cyp26a1) in the forebrain, midbrain, and anterior hindbrain. RESULTS: This manuscript investigates the role of zinc finger of the cerebellum (zic) transcription factors in regulating levels of retinoic acid and differentiation of cranial motor neurons. Depletion of zebrafish Zic2a and Zic2b results in a strong downregulation of aldh1a2 expression and a concomitant reduction in activity of a retinoid-dependent transgene. The vagal motor neuron phenotype caused by loss of Zic2a/2b mimics a depletion of Aldh1a2 and is rescued by exogenously supplied retinoic acid. CONCLUSION: Zic transcription factors function in patterning hindbrain motor neurons through their regulation of embryonic retinoic acid signaling.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".