Up‐regulation of aldolase<scp>A</scp>and methylglyoxal production in adipocytes
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: We previously reported that up-regulation of aldolase B, a key enzyme in fructose metabolism, was mainly responsible for vascular methylglyoxal (MG) overproduction under different pathological conditions. Here we investigated whether aldolase A, an enzyme of the glycolytic pathway, also caused MG overproduction in insulin-sensitive adipocytes. EXPERIMENTAL APPROACH: The relative contributions of different metabolic pathways or enzymes to MG generation were evaluated in cultured 3T3-L1 adipocytes. KEY RESULTS: Glucose (25 mM) had no effect on aldolase A gene expression, but insulin (100 nM) up-regulated aldolase A mRNA and protein levels in the absence or presence of 25 mM glucose in adipocytes. Treatment with insulin increased levels of basal or glucose (25 mM)-induced MG and glucose 6-phosphate. However, insulin, glucose (25 mM) or their combination had no effect on cellular levels of sorbitol and fructose, but down-regulated gene expression of aldolase B to a similar extent, when compared with the control group. Incubation of 3T3-L1 adipocytes with fructose, acetone, acetol, threonine or glycine (25 mM), with or without insulin did not alter cellular MG levels. The elevated MG levels induced by insulin, glucose (25 mM) or their combination in adipocytes was completely reduced by siRNA knock down of aldolase A or application of 2-deoxy-D-glucose (a non-specific inhibitor of glucose uptake and glycolysis), but not by knock down of aldolase B. CONCLUSION AND IMPLICATIONS: Insulin enhanced MG overproduction in insulin-sensitive adipocytes by up-regulating aldolase A, a mechanism that could be involved in the development of insulin resistance and obesity.
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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 | 0.001 |
| 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".