Manganese-Induced Oxidative Stress Contributes to Intestinal Lipid Deposition <i>via</i> the Deacetylation of PPARγ at K339 by SIRT1
Bibliographic record
Abstract
Aims: Excessive manganese (Mn) exposure is toxic, and induces lipid deposition, but the underlying mechanisms remain elusive. Herein, we explored how dietary Mn supplementation affects lipid deposition and metabolism in the intestine of vertebrates using the yellow catfish Pelteobagrus fulvidraco as the model. Results: High-Mn (H-Mn) diet increased intestinal Mn content, promoted lipid accumulation and lipogenesis, and inhibited lipolysis. In addition, it induced oxidative stress, upregulated metal-response element-binding transcription factor-1 (MTF-1), and peroxisome proliferator-activated receptor gamma (PPARγ) protein expression in the nucleus, induced PPARγ acetylation, and the interaction between PPARγ and retinoid X receptor alpha (RXRα), while it downregulated sirtuin 1 (SIRT1) expression and activity. Mechanistically, Mn activated the MTF-1/divalent metal transporter 1 (DMT1) pathway, increased Mn accumulation in the mitochondria, and induced oxidative stress. This in turn promoted lipid deposition via deacetylation of PPARγ at K339 by SIRT1. Subsequently, PPARγ mediated Mn-induced lipid accumulation through transcriptionally activating fatty acid translocase, stearoyl-CoA desaturase 1, and perilipin 2 promoters. Innovation: These studies uncover a previously unknown mechanism by which Mn induces lipid deposition in the intestine via the oxidative stress–SIRT1–PPARγ pathway. Conclusion: High dietary Mn intake activates MTF-1/DMT1 and oxidative stress pathways. Oxidative stress-mediated PPARγ deacetylation at K339 site contributes to increased lipid accumulation. Our results provided a direct link between Mn and lipid metabolism via the oxidative stress–SIRT1–PPARγ axis. Antioxid. Redox Signal . 37, 417–436.
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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 | 0.001 | 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 | 0.001 | 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".