Diets rich in <i>n</i> -6 PUFA induce intestinal microbial dysbiosis in aged mice
Bibliographic record
Abstract
Controversies have emerged regarding the beneficial v. detrimental effects of dietary n-6 PUFA. The alteration of the intestinal microbiota, a phenomenon termed dysbiosis, occurs during several chronic inflammatory diseases, but has not been well studied in an aged population. With present ‘Western’ diets predominantly composed of n-6 PUFA, we hypothesised that PUFA-rich diets cause intestinal dysbiosis in an aged population. C57BL/6 mice (aged 2 years) were fed a high-fat (40% energy), isoenergetic and isonitrogenous diet composed of rapeseed oil, maize oil or maize oil supplemented with fish oil. We examined ileal microbiota using fluorescence in situ hybridisation and stained tissues by immunofluorescence for the presence of immune cells and oxidative stress. We observed that feeding high-fat diets rich in n-6 PUFA promoted bacterial overgrowth but depleted microbes from the Bacteroidetes and Firmicutes phyla. This corresponded with increased body mass and infiltration of macrophages and neutrophils. Fish oil supplementation (rich in long-chain n-3 PUFA like DHA and EPA) restored the microbiota and inflammatory cell infiltration and promoted regulatory T-cell recruitment. However, fish oil supplementation was associated with increased oxidative stress, evident by the increased presence of 4-hydroxynonenal, a product of lipid peroxidation. These results suggest that an n-6 PUFA-rich diet can cause dysbiosis and intestinal inflammation in aged mice. However, while fish oil supplementation on an n-6 PUFA diet reverses dysbiosis, the combination of n-6 and n-3 PUFA, like DHA/EPA, leads to increased oxidative stress, which could exacerbate gastrointestinal disorders in the elderly.
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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 | 0.001 |
| 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".