Effect of a p38 MAPK inhibitor on FFA-induced hepatic insulin resistance in vivo
Bibliographic record
Abstract
The mechanisms whereby prolonged plasma free fatty acids elevation, as found in obesity, causes hepatic insulin resistance are not fully clarified. We herein investigated whether inhibition of p38 mitogen-activated protein kinase (MAPK) prevented hepatic insulin resistance following prolonged lipid infusion. Chronically cannulated rats were subdivided into one of four intravenous (i.v.) treatments that lasted 48 h: Saline (5.5 μl min(-1)), Intralipid plus heparin (IH, 20% Intralipid+20 U ml(-1) heparin; 5.5 μl min(-1)), IH+p38 MAPK inhibitor (SB239063) and SB239063 alone. During the last 2 h of treatment, a hyperinsulinemic (5 mU kg(-1) min(-1)) euglycemic clamp together with [3-(3)H] glucose methodology was carried out to distinguish hepatic from peripheral insulin sensitivity. We found that SB239063 prevented IH-induced hepatic insulin resistance, but not peripheral insulin resistance. SB239063 also prevented IH-induced phosphorylation of activating transcription factor 2 (ATF2), a marker of p38 MAPK activity, in the liver. Moreover, in another lipid infusion model in mice, SB239063 prevented hepatic but not peripheral insulin resistance caused by 48 h combined ethyloleate plus ethylpalmitate infusion. Our results suggest that inhibition of p38 MAPK may be a useful strategy in alleviating hepatic insulin resistance in obesity-associated disorders.
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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) | 0.002 | 0.001 |
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".