Dynamic acetylation profile during mammalian neurulation
Bibliographic record
Abstract
BACKGROUND: Neural tube defects (NTDs) result from failure of neural tube closure during embryogenesis. These severe birth defects of the central nervous system include anencephaly and spina bifida, and affect 0.5-2 per 1,000 pregnancies worldwide in humans. It has been demonstrated that acetylation plays a pivotal role during neural tube closure, as animal models for defective histone acetyltransferase proteins display NTDs. Acetylation represents an important component of the complex network of posttranslational regulatory interactions, suggesting a possible fundamental role during primary neurulation events. This study aimed to assess protein acetylation contribution to early patterning of the central nervous system both in human and murine specimens. METHODS: ) samples to analyze the dynamic acetylation of proteins during embryo development through immunohistochemistry, western blot analysis and quantitative polymerase chain reaction. RESULTS: We report the dynamic profile of histone and protein acetylation status during neural tube closure. We also report a rescue effect in an animal model by chemical p53 inhibition. CONCLUSIONS: Our data suggest that the p53-acetylation equilibrium may play a role in primary neurulation in mammals.
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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".