Modification of Akt1 by methylglyoxal promotes the proliferation of vascular smooth muscle cells
Bibliographic record
Abstract
Methylglyoxal (MG), a reactive dicarbonyl molecule, can modify protein to form advanced glycation endproducts. Increased MG level has been implicated in proliferative vascular diseases, but the underlying mechanisms are not clear yet. The serine/threonine kinase, Akt, regulates multiple signaling pathways that control cell proliferation. Using mass spectrometric analysis, we have detected the modification of Akt1 by MG at Cys(77). This structural modification increased Akt1 phosphorylation at Ser(473) and Thr(308). Akt1 phosphorylation and activity were also increased by MG treatment (<50 μM) in cultured vascular smooth muscle cells (VSMCs). MG treatment of VSMCs led to increased DNA synthesis (EC(50)=5.8 μM), cell proliferation, phosphorylation of p21 and glycogen synthase kinase-3α/β (GSK-3α/β), and increased cyclin-dependent kinase 2 (CDK2) activity. These effects of MG were significantly inhibited by silencing Akt1 or by an Akt inhibitor. Overexpression of Akt1 Cys(77)Ser mutant in HEK-293 cells increased cell proliferation and DNA synthesis, concurrent with an increase in Akt1 activity, which could not be further augmented by MG treatment. It is concluded that MG-induced VSMC proliferation is mediated by the activation of Akt1 via the modification of Akt1 at Cys(77).
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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".