<i>N</i>-acetylcysteine and taurine prevent hyperglycemia-induced insulin resistance in vivo: possible role of oxidative stress
Bibliographic record
Abstract
Exposure to high concentrations of glucose and insulin results in insulin resistance of metabolic target tissues, a characteristic feature of type 2 diabetes. High glucose has also been associated with oxidative stress, and increased levels of reactive oxygen species have been proposed to cause insulin resistance. To determine whether oxidative stress contributes to insulin resistance induced by hyperglycemia in vivo, nondiabetic rats were infused with glucose for 6 h to maintain a circulating glucose concentration of 15 mM with and without coinfusion of the antioxidant N-acetylcysteine (NAC), followed by a 2-h hyperinsulinemic-euglycemic clamp. High glucose (HG) induced a significant decrease in insulin-stimulated glucose uptake [tracer-determined disappearance rate (Rd), control 41.2 +/- 1.7 vs. HG 32.4 +/- 1.9 mg. kg-1. min-1, P < 0.05], which was prevented by NAC (HG + NAC 45.9 +/- 3.5 mg. kg-1. min-1). Similar results were obtained with the antioxidant taurine. Neither NAC nor taurine alone altered Rd. HG caused a significant (5-fold) increase in soleus muscle protein carbonyl content, a marker of oxidative stress that was blocked by NAC, as well as elevated levels of malondialdehyde and 4-hydroxynonenal, markers of lipid peroxidation, which were reduced by taurine. In contrast to findings after long-term hyperglycemia, there was no membrane translocation of novel isoforms of protein kinase C in skeletal muscle after 6 h. These data support the concept that oxidative stress contributes to the pathogenesis of hyperglycemia-induced insulin resistance.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".