Selective Expression of the Proprotein Convertases Furin, PC5, and PC7 in Proliferating Vascular Smooth Muscle Cells of the Rat Aorta In Vitro
Bibliographic record
Abstract
The aim of this study was to investigate whether transformation of quiescent vascular smooth muscle cells (VSMCs) into proliferating secretory cells is accompanied by an expression of processing enzymes that activate de novo-synthesized growth factors. Three enzymes belonging to the family of the kexin/subtilisin-like mammalian proprotein convertases (PCs), furin, PC5, and PC7, were found to be upregulated after balloon denudation in vivo. To determine their importance in these cell processes, we investigated their gene regulation using a short-term organ culture system. After incubation of rat aorta for 4 and 24 hr in serum-free medium, we demonstrated a significant induction of VSMC proliferation. The affected subset of VSMCs, positive for alpha-smooth muscle actin, also expressed proliferating cell nuclear antigen (PCNA). Our results revealed a parallel upregulation of furin, PC5, and PC7 in PCNA-immunolabeled cells. As a substrate model for comparison with PCs we used nerve growth factor (NGF). NGF is known to be activated by PCs. As shown by Northern blotting analysis, NGF mRNA concentration was significantly increased in cultured explants. NGF was released into the culture medium. In conclusion, both PCs and NGF are coordinately modulated on induction of VSMC proliferation.
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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".