ATIC-Associated De Novo Purine Synthesis Is Critically Involved in Proliferative Arterial Disease
Bibliographic record
Abstract
Background: Proliferation of vascular smooth muscle cells (VSMCs) is a hallmark of arterial diseases, especially in arterial restenosis after angioplasty or stent placement. VSMCs reprogram their metabolism to meet the increased requirements of lipids, proteins, and nucleotides for their proliferation. De novo purine synthesis is one of critical pathways for nucleotide synthesis. However, its role in proliferation of VSMCs in these arterial diseases has not been defined. Methods: De novo purine synthesis in proliferative VSMCs was evaluated by liquid chromatography-tandem mass spectrometry. The expression of ATIC (5-aminoimidazole-4-carboxamide ribonucleotide formyltransferase/inosine monophosphate cyclohydrolase), the critical bifunctional enzyme in the last 2 steps of the de novo purine synthesis pathway, was assessed in VSMCs of proliferative arterial neointima. Global and VSMC-specific knockout of Atic mice were generated and used for examining the role of ATIC-associated purine metabolism in the formation of arterial neointima and atherosclerotic lesions. Results: In this study, we found that de novo purine synthesis was increased in proliferative VSMCs. Upregulated purine synthesis genes, including ATIC, were observed in the neointima of the injured vessels and atherosclerotic lesions both in mice and humans. Global or specific knockout of Atic in VSMCs inhibited cell proliferation, attenuating the arterial neointima in models of mouse atherosclerosis and arterial restenosis. Conclusions: These results reveal that de novo purine synthesis plays an important role in VSMC proliferation in arterial disease. These findings suggest that targeting ATIC is a promising therapeutic approach to combat arterial diseases.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".