Dietary intake of unsaturated fatty acids modulates physiological properties of entorhinal cortex neurons in mice
Bibliographic record
Abstract
Dietary lipids modify brain fatty acid profile, but evidence of their direct effect on neuronal function is sparse. The enthorinal cortex (EC) neurons connecting to the hippocampus play a critical role in learning and memory. Here, we have exposed mice to diets based on canola:soybean oils (40 : 10, g/kg) or safflower : corn oils (25 : 25, g/kg) to investigate the relationship between the lipid profile of brain fatty acids and the intrinsic properties of EC neurons. Consumption of canola : soybean oil-enriched diet led to the increase of the monounsaturated fatty acid oleic acid and to a decrease of arachidonic acid in ethanolamine glycerophospholipids of the white matter. We also found an important rise in docosahexaenoic acid (DHA) within ethanolamine glycerophospholipids and phosphatidylserine of gray matter. The canola:soybean oil treatment led to a shorter duration of action potential (-21%), a reduction in the duration of postsynaptic response (-21%) and increased firing activity (+43%). Data from additional experiments with animals fed DHA alone or DHA with canola oil suggested that dietary monounsaturated fatty acid may have contributed to these effects on EC neuron physiology. Since neuronal function within the enthorhinal-hippocampal loop is critical to learning and memory processes, the present data may provide a functional basis for the beneficial cognitive effects of canola oil-based diets.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".