Dietary Omega‐3 Fatty Acids Prevented Adipocyte Hypertrophy by Downregulating <i>DGAT</i>‐<i>2</i> and <i>FABP</i>‐<i>4</i> in a Sex‐Dependent Fashion
Bibliographic record
Abstract
Obesity is characterized by an increase in fat mass primarily as a result of adipocyte hypertrophy. Diets enriched in omega (n)-3 polyunsaturated fatty acids (PUFA) are suggested to reduce obesity, however, the mechanisms are not well understood. We investigated the effect of n-3 PUFA on adipocyte hypertrophy and the key genes involved in adipocyte hypertrophy. Female C57BL/6 mice were fed semi-purified diets (20 % w/w fat) containing high n-3 PUFA before mating, during pregnancy, and until weaning. Male and female offspring were continued on high n-3 PUFA (10 % w/w), medium n-3 PUFA (4 % w/w), or low n-3 PUFA (2 % w/w) diet for 16 weeks postweaning. Adipocyte area was quantified using microscopy, and gonadal mRNA expression of acyl CoA:diacylglycerol acyltransferase-2 (DGAT-2), fatty acid binding protein-4 (FABP-4) and leptin were measured. The high n-3 PUFA group showed higher levels of total n-3 PUFA in gonadal TAG compared to the medium and low n-3 PUFA groups (P < 0.001). The high n-3 PUFA male group had a lower adipocyte area compared to the medium and low n-3 PUFA group (P < 0.001); however, no difference was observed in females. The high n-3 PUFA male group showed lower mRNA expression of FABP-4, DGAT-2 and leptin compared to the low n-3 PUFA group, with no difference in females. Plasma lipid levels were lower in the high n-3 PUFA group compared to the other groups. Our findings show for the first time that n-3 PUFA prevents adipocyte hypertrophy by downregulating FABP-4, DGAT-2 and leptin; the effects are however sex-specific.
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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) | 0.002 | 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".