The type of fatty acid dictates their impact on gut permeability and nutrient absorption
Bibliographic record
Abstract
We showed that short- and long-term (3 to 12 weeks) high-fat diet (HFD) feeding reduced protein expression of nutrient transporters in the proximal jejunum of mice. The most abundant fatty acids (FA) in HFD were oleic (OA), palmitic (PA) and stearic (EA) acid. Because PA and EA are generally regarded as pro-inflammatory, we hypothesize that dietary PA and EA alter gut permeability and absorption via inflammatory activation. To test this hypothesis, we orally administered HFD-matched doses of OA, PA, and EA to male C57BL/6 mice, fed on purified diet control (LFD), for 3 weeks. Food intake and body weight were monitored, and composition were also evaluated. We next qPCR-assessed the mRNA expression of cytokines ( TNF-α, IL-6, IL-1β, IFN-γ, IL-10) and inflammatory signaling transducers ( MD-2 and Myd88) as well as the protein content of nutrient transporters (Glut2, Pept1, Fat/cd36 and Npc1l1) and cell-cell adhesion proteins (Occludin) in the gut. Small intestinal permeability was assessed ex vivo and gut morphology was histologically determined. In addition, Caco-2 enterocytes were used to assess the impact of specific cytokines on nutrient transport and gut barrier integrity. All dietary FA reduced food intake without affecting lean or fat mass. In the jejunum, OA increased TNF-α gene expression whereas PA upregulated IFN-γ and MD-2 gene expression. Furthermore, OA reduced the nutrient transporters Glut2, Pept1, and Fat/cd36 without affecting Npc1l1, whereas PA and EA reduced Occludin protein content. PA, but not OA and EA, increased jejunum paracellular permeability ex vivo and increased villus length. In Caco-2 cells, while Tnf-α did not affect Glut2, Pept1 and Fat/cd36 or Npc1l1 content, Ifn-γ downregulated Occludin protein content. We conclude that OA and, more potently, PA exert inflammatory effects which contribute to damage gut barrier integrity and downregulate nutrient absorption. Our data point to IFN-γ as a main player coupling dietary stress from PA to altered gut homeostasis. Funding: FAPESP (grants number: 2014/12871-9, 2019/05086-7, 2020/12201-4, and 2022/14545). This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.
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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) | 0.001 | 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".