Industrial and Ruminant Trans-Fatty Acids-Enriched Diets Differentially Modulate the Microbiome and Fecal Metabolites in C57BL/6 Mice
Bibliographic record
Abstract
Industrially originated trans-fatty acids (I-tFAs), such as elaidic acid (EA), and ruminant trans-fatty acids (R-tFAs), such as trans-palmitoleic acid (TPA), may have opposite effects on metabolic health. The objective was to compare the effects of consuming 2–3% I-tFA or R-tFA on the gut microbiome and fecal metabolite profile in mice after 7 and 28 days. Forty C57BL/6 mice were assigned to one of the four prepared formulations: lecithin nanovesicles, lecithin nanovesicles with EA or TPA, or water. Fecal samples and animals’ weights were collected on days 0, 7, and 28. Fecal samples were used to determine gut microbiome profiles by 16S rRNA sequencing and metabolite concentrations by GC/MS. At 28 days, TPA intake decreased the abundance of Staphylococcus sp55 but increased Staphylococcus sp119. EA intake also increased the abundance of Staphylococcus sp119 but decreased Ruminococcaceae UCG-014, Lachnospiraceae, and Clostridium sensu stricto 1 at 28 days. Fecal short-chain fatty acids were increased after TPA while decreased after EA after 7 and 28 days. This study shows that TPA and EA modify the abundance of specific microbial taxa and fecal metabolite profiles in distinct ways.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".