Dietary low linolenic acid compared with docosahexaenoic acid alter synaptic plasma membrane phospholipid fatty acid composition and sodium–potassium ATPase kinetics in developing rats
Bibliographic record
Abstract
The objective of this study was to investigate if maternal dietary 20:4n-6 arachidonic acid (AA) and 22:6n-3 compared with adequate or low levels of 18:3n-3 linolenic acid (LNA) increases synaptic plasma membrane (SPM) cholesterol and phospholipid content, phospholipid 20:4n-6 and 22:6n-3 content, and Na,K-ATPase kinetics in rat pups at two and five weeks of age. At parturition, Sprague-Dawley rats were fed semi-purified diets containing either AA + docosahexaenoic acid (DHA), adequate LNA (control; 18:2n-6 : 18:3n-3 ratio of 7.1 : 1) or low LNA (18:2n-6 : 18:3n-39 ratio of 835 : 1). During the first two weeks of life, the rat pups received only their dams' milk. After weaning, pups received the same diet as their respective dams to five weeks of age. No significant difference was observed among rat pups fed the diet treatments for SPM cholesterol or total and individual phospholipid content at two and five weeks of age. Fatty acid analysis revealed that maternal dietary AA + DHA, compared with feeding the dams the control diet or the low LNA diet, increased 20:4n-6 in phosphatidylserine and 22:6n-3 content of SPM phospholipids. Rats fed dietary AA + DHA or the control diet exhibited a significantly increased Vmax for SPM Na,K-ATPase. Diet treatment did not alter the Km (affinity) of SPM Na,K-ATPase in rat pups at two and five weeks of age. It is concluded that dietary AA + DHA does not alter SPM cholesterol and phospholipid content but increases the 22:6n-3 content of SPM phospholipids modulating activity of Na,K-ATPase.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".