Platelet-derived growth factor BB modulates PCNA protein synthesis partially through the transforming growth factor beta signalling pathway in vascular smooth muscle cells
Bibliographic record
Abstract
PDGF-BB (Platelet-derived growth factor BB) and TGF-beta1(transforming growth factor beta1) are important growth factors in the modulation of vascular smooth muscle cell (VSMC) proliferation and PCNA (proliferating cell nuclear antigen) expression in VSMCs. PCNA expresses at a high level in proliferating cells. The present study aims to assess the effects of PDGF-BB-induced overexpression of TGF-beta1 on PCNA in VSMCs. The downstream proteins of the TGF-beta signalling system in VSMCs, including TGF-beta type I receptor (ALK-5 in VSMCs), Smurf2, Smad2, pSmad2/3, Smad4, and Smad7, were also investigated. Our results revealed that PDGF-BB significantly increased the expressions of TGF-beta1 and PCNA, and the increase in PCNA can be partially inhibited by neutralizing anti-TGF-beta1 antibody. Furthermore, PDGF-BB increased the expression of ALK-5, Smurf2, pSmad2/3, and Smad4, but lowered the levels of Smad2 and Smad7; these alterations were partially restored by neutralizing anti-TGF-beta1 antibody. These findings suggest that PDGF-BB promotes PCNA expression in VSMCs partially through TGF-beta1 overexpression, and that the TGF-beta signalling system involves the molecular mechanism of PDGF-BB in VSMCs.
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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".