Valproic acid increases expression of methylenetetrahydrofolate reductase (MTHFR) and induces lower teratogenicity in MTHFR deficiency
Bibliographic record
Abstract
Valproate (VPA) treatment in pregnancy leads to congenital anomalies, possibly by disrupting folate or homocysteine metabolism. Since methylenetetrahydrofolate reductase (MTHFR) is a key enzyme of folate interconversion and homocysteine metabolism, we addressed the possibility that VPA might have different teratogenicity in Mthfr(+/+) and Mthfr(+/-) mice and that VPA might interfere with folate metabolism through MTHFR modulation. Mthfr(+/+) and Mthfr(+/-) pregnant mice were injected with VPA on gestational day 8.5; resorption rates and occurrence of neural tube defects (NTDs) were examined on gestational day 14.5. We also examined the effects of VPA on MTHFR expression in HepG2 cells and on MTHFR activity and homocysteine levels in mice. Mthfr(+/+) mice had increased resorption rates (36%) after VPA treatment, compared to saline treatment (10%), whereas resorption rates were similar in Mthfr(+/-) mice with the two treatments (25-27%). NTDs were only observed in one group (VPA-treated Mthfr(+/+)). In HepG2 cells, VPA increased MTHFR promoter activity and MTHFR mRNA and protein (2.5- and 3.7-fold, respectively). Consistent with cellular MTHFR upregulation by VPA, brain MTHFR enzyme activity was increased and plasma homocysteine was decreased in VPA-treated pregnant mice compared to saline-treated animals. These results underscore the importance of folate interconversion in VPA-induced teratogenicity, since VPA increases MTHFR expression and has lower teratogenic potential in MTHFR deficiency.
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) | 0.000 | 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".