Bibliographic record
Abstract
In the gut, there is a complex relationship formed between the host and the bacteria which is further influenced by dietary antigens. The dynamics of this tripartite relationship is for the most part unknown. An imbalance between harmful and protective gut bacteria, termed dysbiosis, has been associated with high fat diets. Dysbiosis has been linked to several inflammatory conditions, such as inflammatory bowel disease and diabetes. Whether different types of fatty acids have similar effects is not fully known. This is important because in Canada, while saturated fatty (SFA) consumption has remained the same, total fat containing n-6 polyunsaturated fatty acid (PUFA) has increased by 54%. To understand the host-microbe dynamic in the gut in response to different lipid diets, we combined 16S rRNA metagenomic sequencing of the microbiome, computational metagenomic prediction of microbiota function and mass spectrometry-based relative quantification of the bacterial and host metaproteome of the colon. We exposed 3 week old C57BL/6 mice to isonitrogenous and isocaloric diets composed of 40% energy from either anhydrous milk fat, corn oil, olive oil or a low fat diet for 5 weeks and then collected their small and large intestinal tissues for analysis. Overall, the corn oil diet rich in n-6 PUFA resulted in a microbiome that showed enhanced virulence associated with increased host inflammation, oxidative stress and increased barrier dysfunction evident by a reduction in protective mucin2 proteins and increase in inflammatory mucin13 proteins. While the milk fat diet rich in SFA resulted in a host-microbe relationship that promoted inflammation, there was also a compensatory protective response evident by the increased tissue repair proteins. In contrast, the olive oil diet rich in monounsaturated fatty acids (MUFA) resulted in increased digestive proteins. We conclude that various lipids uniquely alter the host-microbe dynamic in the gut. Overall, n-6 PUFA increases the potential for pathobiont survival and invasion in an inflamed, oxidized and damaged gut while SFA promotes tissue repair and MUFA enhances metabolism. These results have the potential to guide evidence-based nutrition recommendations to inflammatory bowel disease patients who suffer from malnutrition yet are currently advised to eat low fat diets.
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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 | 0.001 | 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".