Breast Milk from Non-Obese Women with a High Omega-6 to Omega-3 Fatty Acid Ratio, but Not from Women with Obesity, Increases Lipogenic Gene Expression in 3T3-L1 Preadipocytes, Suggesting Adipocyte Dysfunction
Bibliographic record
Abstract
Maternal body mass index is associated with breast milk (BM) fatty acid composition. This study investigated the effects of BM omega (n)-6:n-3 polyunsaturated fatty acids (PUFAs) from non-obese women and women with obesity on the process of adipogenesis in 3T3-L1 preadipocytes. BM samples were collected from non-obese women (BMNO) and women with obesity (BMO) at one month postpartum. The fatty acid composition was measured, and BMNO and BMO groups with the lowest (Q1) and highest (Q4) quartiles of n-6:n-3 PUFA ratios were identified. 3T3-L1 preadipocytes were differentiated in the presence or absence of BM. Lipid accumulation and the expression of genes involved in lipogenesis and lipolysis were measured. Treatment with BMNO containing high (vs. low) n-6:n-3 PUFA ratios significantly increased the mRNA expression of lipogenic genes (acetyl-CoA carboxylase, fatty acid synthase, and stearoyl-CoA desaturase); however, there was no effect when cells were treated with BMO (with either low or high n-6:n-3 PUFA ratios). Treatment with BMO (high n-6:n-3 PUFA ratio) caused larger lipid droplets. Our findings demonstrated that BMNO with a high n-6:n-3 PUFA ratio was associated with a higher expression of lipogenic genes, while BMO with a high n-6:n-3 PUFA ratio showed larger lipid droplets, suggesting adipocyte dysfunction. These findings may have implications in the BM-mediated programming of childhood obesity.
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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 | 0.000 |
| 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".