The Ratio of Linoleic and Linolenic Acid in the Pre-hibernation Diet Influences NFκB Signaling in Garden Dormice During Torpor
Bibliographic record
Abstract
The fatty acid composition of a pre-hibernation diet can influence the depth and duration of metabolic suppression achieved by hibernators. More specifically, a diet high in n-6 polyunsaturated fatty acids (PUFAs) relative to n-3 PUFAs is essential to maximize torpor expression. However, few studies have investigated how diets with different n-6/n-3 PUFA ratios change stress-inducible cell signaling. Garden dormice (Eliomys quercinus) were fed one of three diets designed with different ratios of n-6 PUFA linoleic acid (LA) and n-3 PUFA linolenic acid (ALA). Then, NFκB signaling was assessed in the white adipose, brown adipose, and liver tissues of euthermic and hibernating dormice via multiplex and RT-qPCR analyses of relative protein and transcript levels, respectively. Dormice fed a high LA diet regulated NFκB signaling in a protective manner in all tissues. NFκB signaling was generally decreased in the high LA group, with significant decreases in the protein levels of NFκB mediators IKKα/β, IκBα, and downstream pro-apoptotic protein FADD. Liver and white adipose from torpid dormice fed a high LA diet increased sod2 expression relative to the other diets or relative to euthermic controls, indicating protection against ROS generated from potentially increased β-oxidation of n-6 PUFAs. The low LA diet increased biomarkers for apoptosis relative to other diets and relative to euthermia, suggesting low LA diets may be detrimental to hibernator health. Overall, this study suggests that changes in the ratio of n-6/n-3 PUFAs in the diet influences apoptotic and antioxidant responses in white adipose, brown adipose, and liver of hibernating garden dormice.
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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) | 0.000 | 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".