Dietary omega‐3 polyunsaturated fatty acid deprivation lowers seizure threshold in rats
Bibliographic record
Abstract
Several candidate genes that play a role in seizure etiology have been identified. Yet, the impact of environmental influences such as dietary omega‐3 polyunsaturated fatty acids (n‐3 PUFA) is not known. We therefore tested the impact of chronic dietary n‐3 PUFA deprivation on seizure threshold in the cortex and amygdala. Rats were surgically implanted with electrodes in the cortex or amygdala, and subsequently randomized to the AIN‐93G diet containing n‐3 PUFA derived from soybean oil, or a modified n‐3 PUFA‐deficient version derived from coconut and safflower oil. The rats were maintained on the diets for 33 weeks. Seizure thresholds were measured monthly by electrically stimulating the cortex and amygdala. At the end of 33 weeks, seizure threshold was assessed following a bolus subcutaneous injection of oleic (OA) or docosahexaenoic acids (DHA). Dietary n‐3 PUFA deprivation resulted in a statistically significant decrease in cortical and amygdaloid thresholds by week 16, relative to baseline (P<0.05). The decrease in thresholds was not observed in rats on the control, soybean oil diet. Compared to a bolus injection of OA, acute injection of DHA raised seizure threshold in rats on the control diet but not the n‐3 PUFA deficient diet (P<0.05). These findings demonstrate for the first time that dietary n‐3 PUFA deficiency increases seizure susceptibility in rats. Grant Funding Source Canadian Institutes of Health research
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".