C-reactive protein impairs hepatic insulin sensitivity and insulin signaling in rats: Role of mitogen-activated protein kinases
Bibliographic record
Abstract
UNLABELLED: Plasma C-reactive protein (CRP) concentration is increased in the metabolic syndrome, which consists of a cluster of cardiovascular disease risk factors, including insulin resistance. It is not known, however, whether CRP is merely a marker of accompanying inflammation or whether it contributes causally to insulin resistance. The objective of this study is to investigate the role that CRP may play in the development of insulin resistance. We examined the effect of single-dose intravenous administration of purified human (h)CRP on insulin sensitivity in Sprague-Dawley rats using the euglycemic, hyperinsulinemic clamp technique. hCRP was associated with impaired insulin suppression of endogenous glucose production with no reduction in peripheral tissue glucose uptake, suggesting that hCRP mediated insulin resistance in the liver but not extrahepatic tissues. We further assessed components of the insulin signaling pathway and mitogen-activated protein kinases (MAPKs) in the liver. Liver tissues derived from hCRP-treated rats showed reduced insulin-stimulated insulin receptor substrate (IRS) tyrosine phosphorylation, IRS/phosphatidylinositol 3-kinase (PI3K) association, and Akt phosphorylation, consistent with hCRP-induced impairment of hepatic insulin signaling. Furthermore, hCRP enhanced phosphorylation of extracellular signal-regulated kinase (ERK)1/2 and p38 MAPK as well as IRS-1 Ser(612) . Finally, we observed in primary cultured rat hepatocytes that U0126 (a selective inhibitor of MAPK/ERK kinase1/2) corrected hCRP-induced impairment of insulin signaling. CONCLUSIONS: hCRP plays an active role in inducing hepatic insulin resistance in the rat, at least in part by activating ERK1/2, with downstream impairment in the insulin signaling pathway.
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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) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".