Indole Alleviates Diet‐Induced Hepatic Steatosis and Inflammation in a Manner Involving Myeloid Cell 6‐Phosphofructo‐2‐Kinase/Fructose‐2,6‐Biphosphatase 3
Bibliographic record
Abstract
BACKGROUND AND AIMS: Indole is a microbiota metabolite that exerts anti-inflammatory responses. However, the relevance of indole to human non-alcoholic fatty liver disease (NAFLD) is not clear. It also remains largely unknown whether and how indole acts to protect against NAFLD. The present study sought to examine the association between the circulating levels of indole and liver fat content in human subjects and explore the mechanisms underlying indole actions in mice with diet-induced NAFLD. APPROACH AND RESULTS: In a cohort of 137 subjects, the circulating levels of indole were reversely correlated with body mass index. In addition, the circulating levels of indole in obese subjects were significantly lower than those in lean subjects and were accompanied with increased liver fat content. At the whole-animal level, treatment of high-fat diet (HFD)-fed C57BL/6J mice with indole caused significant decreases in the severity of hepatic steatosis and inflammation. In cultured cells, indole treatment stimulated the expression of 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 3 (PFKFB3), a master regulatory gene of glycolysis, and suppressed macrophage proinflammatory activation in a PFKFB3-dependent manner. Moreover, myeloid cell-specific PFKFB3 disruption exacerbated the severity of HFD-induced hepatic steatosis and inflammation and blunted the effect of indole on alleviating diet-induced NAFLD phenotype. CONCLUSIONS: Taken together, our results demonstrate that indole is relevant to human NAFLD and capable of alleviating diet-induced NAFLD phenotypes in mice in a myeloid cell PFKFB3-dependent manner. Therefore, indole mimetic and/or macrophage-specific PFKFB3 activation may be the viable preventive and/or therapeutic approaches for inflammation-associated diseases including NAFLD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".