Knockdown of Glyoxalase 1 Mimics Diabetic Nephropathy in Nondiabetic Mice
Bibliographic record
Abstract
Differences in susceptibility to diabetic nephropathy (DN) between mouse strains with identical levels of hyperglycemia correlate with renal levels of oxidative stress, shown previously to play a central role in the pathogenesis of DN. Susceptibility to DN appears to be genetically determined, but the critical genes have not yet been identified. Overexpression of the enzyme glyoxalase 1 (Glo1), which prevents posttranslational modification of proteins by the glycolysis-derived α-oxoaldehyde, methylglyoxal (MG), prevents hyperglycemia-induced oxidative stress in cultured cells and model organisms. In this study, we show that in nondiabetic mice, knockdown of Glo1 increases to diabetic levels both MG modification of glomerular proteins and oxidative stress, causing alterations in kidney morphology indistinguishable from those caused by diabetes. We also show that in diabetic mice, Glo1 overexpression completely prevents diabetes-induced increases in MG modification of glomerular proteins, increased oxidative stress, and the development of diabetic kidney pathology, despite unchanged levels of diabetic hyperglycemia. Together, these data indicate that Glo1 activity regulates the sensitivity of the kidney to hyperglycemic-induced renal pathology and that alterations in the rate of MG detoxification are sufficient to determine the glycemic set point at which DN occurs.
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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) | 0.000 | 0.000 |
| 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 | 0.001 | 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".