Plin5 inhibits proliferation and migration of vascular smooth muscle cell through interacting with PGC-1α following vascular injury
Bibliographic record
Abstract
Abnormal proliferation and migration of vascular smooth muscle cell (VSMC) is a hallmark of vascular neointima hyperplasia. Perilipin 5 (Plin5), a regulator of lipid metabolism, is also confirmed to be involved in vascular disorders, such as microvascular endothelial dysfunction and atherosclerosis. To investigate the regulation and function of plin5 in the phenotypic alteration of VSMC, -an animal model of vascular intima hyperplasia was established in C57BL/6 J and Plin5 knockdown (Plin5±) mice by wire injure. Immunohistochemical staining was used to analyze neointima hyperplasia in artery. Ki-67, dihydroethidium immunofluorescence staining and wound healing assay were used to measure proliferation, reactive oxygen species (ROS) generation and migration of VSMC, respectively. Plin5 was downregulated in artery subjected to vascular injury and in VSMC subjected to platelet-derived growth factor (PDGF)-BB. Plin5 knockdown led to accelerated neointima hyperplasia, excessive proliferation and migration of VSMC after injury. In vitro, we observed increased ROS content in VSMC isolated from Plin5± mice. Antioxidative N-acetylcysteine (NAC) inhibited VSMC proliferation and migration induced by PDGF-BB or plin5 knockdown. More importantly, plin5-peroxlsome proliferator-activated receptor-γ coactivator (PGC)-1α interaction was also attenuated in VSMC after knockdown of plin5. Overexpression of PGC-1α suppressed PDGF-BB-induced ROS generation, proliferation, and migration in VSMC isolated from Plin5± mice. These data suggest that plin5 serves as a potent regulator of VSMC proliferation, migration, and neointima hyperplasia by interacting with PGC-1α and affecting ROS generation.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".