Structural and functional changes in human insulin induced by methylglyoxal
Bibliographic record
Abstract
Elevated methylglyoxal (MG) levels have been reported in insulin-resistance syndrome. The present study investigated whether MG, a highly reactive metabolite of glucose, induced structural and functional changes of insulin. Incubation of human insulin with MG in vitro yielded MG-insulin adducts, as evidenced by additional peaks observed on mass spectrometric (MS) analysis of the incubates. Tandem MS analysis of insulin B-chain adducts confirmed attachment of MG at an arginine residue. [3H]-2-deoxyglucose uptake by 3T3-L1 adipocytes was significantly and concentration-dependently decreased after the treatment with MG-insulin adducts, in comparison with the effect of native insulin at the same concentrations. A significant decrease of glucose uptake induced by MG-insulin adducts was also observed in L8 skeletal muscle cells. MG alone had no effect on glucose uptake or the transcriptional expression of insulin receptor. Unlike native insulin, MG-insulin adducts did not inhibit insulin release from pancreatic beta-cells. The degradation of MG-insulin through liver cells was also decreased. In conclusion, MG modifies insulin by attaching to internal arginine residue in beta-chain of insulin. The formation of this MG-insulin adduct decreases insulin-mediated glucose uptake, impairs autocrine control of insulin secretion, and decreases insulin clearance. These structural and functional abnormalities of insulin molecule may contribute to the pathogenesis of 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) | 0.000 | 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 | 0.000 |
| 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".