Duration of rise in free fatty acids determines salicylate's effect on hepatic insulin sensitivity
Bibliographic record
Abstract
We have shown in rats that sodium salicylate (SS), which inhibits IkBa kinase B (IKKB), prevents hepatic and peripheral insulin resistance caused by short-term (7 h) i.v. administration of Intralipid and heparin (IH). We wished to further determine whether this beneficial effect of SS persisted after prolonged (48 h) IH infusion, which better mimics the chronic free fatty acid (FFA) elevation of obesity. Hence, we performed hyperinsulinemic euglycemic clamps with tritiated glucose methodology to determine hepatic and peripheral insulin sensitivity in rats infused with saline, IH, IH and SS, or SS alone. SS prevented peripheral insulin resistance (P<0.05) caused by prolonged plasma FFA elevation; however, it did not prevent hepatic insulin resistance. In skeletal muscle, protein levels of phospho-IkBa were augmented by prolonged IH administration and this was prevented by SS, suggesting that IH activates while SS prevents the activation of IKKB. Markers of IKKB activation, namely protein levels of phospho-IkBa and IkBa, indicated that IKKB is not activated in the liver after prolonged FFA elevation. Phosphorylation of serine 307 at insulin receptor substrate (IRS)-1, which is a marker of proximal insulin resistance, was not altered by IH administration in the liver, suggesting that this is not a site of hepatic insulin resistance in the prolonged lipid infusion model. Our results suggest that the role of IKKB in fat-induced insulin resistance is time and tissue dependent and that hepatic insulin resistance induced by prolonged lipid elevation is not due to an IRS-1 serine 307 kinase.
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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) | 0.002 | 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".