Zebrafish model of holoprosencephaly demonstrates a key role for TGIF in regulating retinoic acid metabolism
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Bibliographic record
Abstract
Holoprosencephaly (HPE) is the most common human congenital forebrain defect, affecting specification of forebrain tissue and subsequent division of the cerebral hemispheres. The causes of HPE are multivariate and heterogeneous, and include exposure to teratogens, such as retinoic acid (RA), and mutations in forebrain patterning genes. Many of the defects in HPE patients resemble animal models with aberrant RA levels, which also show severe forebrain abnormalities. RA plays an important role in early neural patterning of the vertebrate embryo: expression of RA-synthesizing enzymes initiates high RA levels in the trunk, which are required for proper anterior-posterior patterning of the hindbrain and spinal cord. In the forebrain and midbrain, RA-degrading enzymes are expressed, protecting these regions from the effects of RA. However, the mechanisms that regulate RA-synthesizing and RA-degrading enzymes are poorly understood. Mutations in the gene TGIF are associated with incidence of HPE. We demonstrate in zebrafish that Tgif plays a key role in regulating RA signaling, and is essential to properly pattern the forebrain. Tgif is necessary for normal initiation of genes that control RA synthesis and degradation, resulting in defects in RA-dependent central nervous system patterning in Tgif-depleted embryos. The loss of the forebrain-specific RA-degrading enzyme cyp26a1 causes a forebrain phenotype that mimics tgif morphants. We propose a model in which Tgif controls forebrain patterning by regulating RA degradation. The consequences of abnormal RA levels for forebrain patterning are profound, and imply that in human patients with TGIF deficiencies, increased forebrain RA levels contribute to the development of HPE.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 it