Sex-dependent differences in tissue and blood n-3 PUFA levels following ALA or ALA + DHA feeding of liver-specific Elovl2-KO and control mice
Bibliographic record
Abstract
Docosahexaenoic acid (DHA, 22:6n-3) must be consumed from the diet or synthesized from polyunsaturated fatty acid (PUFA) precursors, such as α-linolenic acid (ALA, 18:3n-3). Elongase 2 (encoded by Elovl2 gene) catalyzes two elongation reactions in the PUFA biosynthesis pathway and may be important in regulating the observed sex differences in n-3 PUFA levels. Our aim was to determine how targeted knockout of liver Elovl2 affects tissue and blood n-3 PUFA levels in male and female C57BL/6J mice. Twenty-eight-day old male and female liver Elovl2-KO and control mice were placed onto one of two dietary protocols for a total of 8 weeks (4-8 mice per genotype, per diet, per sex): 1) an 8-week 2 % ALA in total fat diet or 2) a 4-week 2 % ALA diet followed by a 4-week 2 % ALA + 2 % DHA diet. Following this 8-week feeding period, 12-week-old mice were sacrificed and serum, red blood cells (RBC), liver, heart and brain were collected and fatty acid levels measured. Significant interaction effects (p < 0.05, sex x genotype) for serum, RBC, liver and heart DHA levels were identified. In serum and liver, DHA levels were significantly different (p < 0.01) between all groups with male controls > female controls > female KO > male KO in serum and female controls > male controls > female KO > male KO in liver. In RBCs and the heart, female controls = male controls > female KO > male KO (p < 0.001). The addition of DHA to diet removed the interaction effects on DHA levels in the serum, liver and heart, yielding a significant sex effect in serum, liver (female > male, p < 0.01) and brain (male > female, p < 0.05) and genotype effect in serum and heart (control > KO, p < 0.05). Ablation of liver Elovl2 results in significantly lower blood and tissue DHA in a sex-dependent manner, suggesting a role for Elovl2 on sex differences in n-3 PUFA levels.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".