Upregulation of aldolase B and overproduction of methylglyoxal in vascular tissues from rats with metabolic syndrome
Bibliographic record
Abstract
AIMS: Methylglyoxal (MG) overproduction has been reported in metabolic syndrome with hyperglycaemia (diabetes) or without hyperglycaemia (hypertension), and the underlying mechanism was investigated. METHODS AND RESULTS: Contributions of different pathways or enzymes to MG formation were evaluated in aorta or cultured vascular smooth muscle cells (VSMCs). In all four animal models of metabolic syndrome, i.e. chronically fructose-fed hypertensive Sprague-Dawley rats, spontaneously hypertensive rats, obese non-diabetic Zucker rats, and diabetic Zucker rats, serum and aortic MG and fructose levels were increased, and the expression of GLUT5 (transporting fructose) and aldolase B (converting fructose to MG) in aorta were up-regulated. Aortic expressions of aldolase A, semicarbazide-sensitive amine oxidase (SSAO), and cytochrome P450 2E1 (CYP 2E1), accounting for MG formation during glycolysis, protein, and lipid metabolism, respectively, was unchanged/reduced. Fructose (25 mM) treatment of VSMCs up-regulated the expression of GLUT5 and aldolase B and accelerated MG formation. Insulin (100 nM) increased GLUT5 expression and augmented fructose-increased cellular fructose accumulation and MG formation. Glucose (25 mM) treatment activated the polyol pathway and enhanced fructose formation, leading to aldolase B upregulation and MG overproduction. Inhibition of the polyol pathway reduced the glucose-increased aldolase B expression and MG generation. The excess formation of MG in under these conditions was eliminated by knock-down of aldolase B, but not by knock-down of aldolase A or inhibition of SSAO or CYP 2E1. CONCLUSION: Upregulation of aldolase B by accumulated fructose is a common mechanism for MG overproduction in VSMCs and aorta in different models of metabolic syndrome.
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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 | 0.001 | 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".