Effects of Ethylene Glycol Monomethyl Ether and Its Metabolite, 2‐Methoxyacetic Acid, on Organogenesis Stage Mouse Limbs In Vitro
Bibliographic record
Abstract
Exposure to ethylene glycol monomethyl ether (EGME), a glycol ether compound found in numerous industrial products, or to its active metabolite, 2-methoxyacetic acid (2-MAA), increases the incidence of developmental defects. Using an in vitro limb bud culture system, we tested the hypothesis that the effects of EGME on limb development are mediated by 2-MAA-induced alterations in acetylation programming. Murine gestation day 12 embryonic forelimbs were exposed to 3, 10, or 30 mM EGME or 2-MAA in culture for 6 days to examine effects on limb morphology; limbs were cultured for 1 to 24 hr to monitor effects on the acetylation of histones (H3K9 and H4K12), a nonhistone protein, p53 (p53K379), and markers for cell cycle arrest (p21) and apoptosis (cleaved caspase-3). EGME had little effect on limb morphology and no significant effects on the acetylation of histones or p53 or on biomarkers for cell cycle arrest or apoptosis. In contrast, 2-MAA exposure resulted in a significant concentration-dependent increase in limb abnormalities. 2-MAA induced the hyperacetylation of histones H3K9Ac and H4K12Ac at all concentrations tested (3, 10, and 30 mM). Exposure to 10 or 30 mM 2-MAA significantly increased acetylation of p53 at K379, p21 expression, and caspase-3 cleavage. Thus, 2-MAA, the proximate metabolite of EGME, disrupts limb development in vitro, modifies acetylation programming, and induces biomarkers of cell cycle arrest and apoptosis.
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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".