Folic acid ameliorates neonatal isolation-induced autistic like behaviors in rats: epigenetic modifications of <i>BDNF</i> and <i>GFAP</i> promotors
Bibliographic record
Abstract
The current study investigated the role of epigenetic dysregulation of brain derived neurotrophic factor (BDNF) and glial fibrillary acidic protein (GFAP) genes and oxidative stress as possible mechanisms of autistic-like behaviors in neonatal isolation model in rats and the impact of folic acid administration on these parameters. Forty Wistar albino pups were used as follows: control, folic acid administered, isolated, and isolated folic acid treated groups. Isolated pups were separated from their mothers for 90 min daily from postnatal day (PND) 1 to 11. Pups (isolated or control) received either the vehicle or folic acid (4 mg/kg/day) orally from PND 1 to 29. Behavioral tests were done from PND 30 to 35. Oxidative stress markers and antioxidant defense in the frontal cortex homogenate were determined. DNA methylation of BDNF and GFAP genes was determined by qPCR. Histopathological examination was carried out. Neonatal isolation produced autistic-like behaviors that were associated with BDNF and GFAP hypomethylation, increased oxidative stress, increased inflammatory cell infiltration, and structural changes in the frontal cortex. Folic acid administration concurrently with isolation reduced neonatal isolation-induced autistic-like behaviors, decreased oxidative stress, regained BDNF and GFAP gene methylation, and ameliorated structural changes in the frontal cortices of isolated folic acid treated rats. Novelty: Neonatal isolation induces “autistic-like” behavior and these behaviors are reversed by folic acid supplementation. Neonatal isolation induces DNA hypomethylation of BDNF and GFAP, increased oxidative stress markers, and neuroinflammation. All of these changes were reversed by daily folic acid supplementation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".