RGC-32 Increases p34CDC2 Kinase Activity and Entry of Aortic Smooth Muscle Cells into S-phase
Bibliographic record
Abstract
Proliferation of aortic smooth muscle cells contributes to atherogenesis and neointima formation. Sublytic activation of complement, particularly C5b-9, induces cell cycle progression in aortic smooth muscle cells. RGC-32 is a novel protein that may promote cell cycle progression in response to complement activation. We cloned human RGC-32 cDNA from a human fetal brain cDNA library. The human RGC-32 cDNA encodes a 117-amino acid protein with 92% similarity to the rat and mouse protein. Human RGC-32 maps to chromosome 13 and is expressed in most tissues. Sublytic complement activation enhanced RGC-32 mRNA expression in human aortic smooth muscle cells and induced nuclear translocation of the protein. RGC-32 was physically associated with cyclin-dependent kinase p34CDC2 and increased the kinase activity in vivo and in vitro. In addition, RGC-32 was phosphorylated by p34CDC2-cyclin B1 in vitro. Mutation of RGC-32 protein at Thr-91 prevented the p34CDC2-mediated phosphorylation and resulted in loss of p34CDC2 kinase enhancing activity. Overexpression of RGC-32 induced quiescent aortic smooth muscle cells to enter S-phase. These data indicate that cell cycle activation by C5b-9 may involve p34CDC2 activity through RGC-32. RGC-32 appears to be a cell cycle regulatory factor that mediates cell proliferation, both as an activator and substrate of p34CDC2.
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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".