Methylglyoxal, a Reactive Glucose Metabolite, Increases Renin Angiotensin Aldosterone and Blood Pressure in Male Sprague-Dawley Rats
Bibliographic record
Abstract
BACKGROUND: The majority of people with diabetes develop hypertension along with increased activity of the renin-angiotensin system. Methylglyoxal, a reactive glucose metabolite, is elevated in diabetic patients. We investigated the effects of methylglyoxal on the renin-angiotensin system and blood pressure. METHODS: Male Sprague-Dawley rats were treated with a continuous infusion of methylglyoxal with a minipump for 4 weeks. Organs/tissues and cultured vascular smooth muscle cells (VSMCs) were used for molecular studies. High-performance liquid chromatography, Western blotting, and quantitative real-time polymerase chain reaction were used to measure methylglyoxal, proteins, and mRNA, respectively. Small interfering RNA for angiotensinogen and the receptor for advanced glycation endproducts (RAGE) were used to study mechanisms. RESULTS: Methylglyoxal-treated rats developed a significant increase in blood pressure and plasma levels of aldosterone, renin, angiotensin, and catecholamines. Methylglyoxal level and protein and mRNA for angiotensin, AT1 receptor, adrenergic α1D receptor, and renin were significantly increased in the aorta and/or kidney of methylglyoxal-treated rats, a novel finding. Alagebrium attenuated the above effects of methylgloyxal. Treatment of cultured VSMCs with methylglyoxal or high glucose (25 mM) significantly increased cellular methylglyoxal and protein and mRNA for nuclear factor kappa B (NF-κB), angiotensin, AT1 receptor, and α1D receptor, which were prevented by inhibition of NF-κB, and by alagebrium. Silencing of mRNA for RAGE prevented the increase in NF-kB induced by methylglyoxal. Silencing of mRNA for angiotensinogen prevented the increase in NF-κB, angiotensin, AT1 receptor, and α1D receptor. CONCLUSIONS: Methylglyoxal activates NF-κB through RAGE and thereby increases renin-angiotensin levels, a novel finding, and a probable mechanism of increase in blood pressure.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".