Retinoic acid, midkine, and defects of secondary neurulation
Bibliographic record
Abstract
BACKGROUND: Retinoic acid (RA) is necessary for normal differentiation of the tail bud into the secondary neural tube. Excess RA, however, is teratogenic and causes neural tube defects (NTDs). The way in which RA modulates secondary neurulation is unclear but probably involves RA-regulated downstream genes such midkine (MK), which encodes a growth factor implicated in tail bud mesenchymal-neuroepithelial conversion. Our objective was to determine whether RA-deficiency would produce similar defects and if MK is involved. METHODS: Citral, a drug that blocks endogenous RA formation, as well as a neutralizing antibody, were used to block RA activity in chick embryos. Immunohistochemistry and in situ hybridization were used to localize RA and MK in the tail bud. Competitive RT-PCR was used to examine the effects of excess RA and RA deficiency due to citral on the expression of MK mRNA. RESULTS: Citral-induced NTDs displayed a morphological resemblance to those caused by excess RA. However, citral treatment did not significantly increase embryonic mortality, and RA rescue of citral-treated embryos proved unsuccessful. MK mRNA was detected in the differentiating tail bud by in situ hybridization. Competitive RT-PCR showed that excess RA decreased MK expression by 60%. Doses of citral that caused a comparable incidence of defects, however, caused only a 25% decrease. CONCLUSIONS: The results show that excess RA and RA deficiency both cause defects of secondary neurulation. While excess RA decreased MK expression, RA deficiency had minimal effects. However, whether or not MK is an intermediary in the developmental phenomena regulated physiologically or pathologically by RA remains to be elucidated.
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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 | 0.001 |
| 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".