4-Phenylbutyric acid improves free fatty acid-induced hepatic insulin resistance in vivo
Bibliographic record
Abstract
Plasma free fatty acids (FFAs) are elevated in obesity and can induce insulin resistance via endoplasmic reticulum (ER) stress. However, it is unknown whether hepatic insulin resistance caused by the elevation of plasma FFAs is alleviated by chemical chaperones. Rats received one of the following i.v. treatments for 48 h: saline, intralipid plus heparin (IH), IH plus the chemical chaperone 4-phenylbutyric acid (PBA), or PBA alone and a hyperinsulinemic-euglycemic clamp was performed during the last 2 h. PBA co-infusion normalized IH-induced peripheral insulin resistance, similar to our previous findings with an antioxidant and an IκBα kinase β (IKKβ) inhibitor. Different from our previous results with the antioxidant and IKKβ inhibitor, PBA also improved IH-induced hepatic insulin resistance in parallel with activation of Akt. Unexpectedly, IH did not induce markers of ER stress in the liver, but PBA prevented IH-induced elevation of phosphorylated eukaryotic initiation factor-2α protein in adipose tissue. PBA tended to decrease circulating fetuin-A and significantly increased circulating fibroblast growth factor 21 (FGF21) without affecting markers of activation of hepatic protein kinase C-δ or p38 mitogen-activated protein kinase that we have previously involved in hepatic insulin resistance in this model. In conclusion: (i) PBA prevented hepatic insulin resistance caused by prolonged plasma FFA elevation without affecting hepatic ER stress markers; (ii) the PBA effect is likely due to increased FGF21 and/or decreased fetuin-A, which directly signal to upregulate Akt activation.
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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 | 0.000 |
| 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".