Inhibition of Versican Synthesis by Antisense Alters Smooth Muscle Cell Phenotype and Induces Elastic Fiber Formation In Vitro and in Neointima After Vessel Injury
Bibliographic record
Abstract
The proteoglycan versican is implicated in several atherogenic events, including stimulation of vascular smooth muscle cell (VSMC) growth and migration, retention of lipoproteins, and promotion of thrombogenesis. A high content of intimal versican also correlates with a low content of elastin, suggesting an inhibitory role for versican in elastogenesis. To determine whether reduced production of versican can be used to enhance elastogenesis, we transduced Fischer rat VSMC (FRSMC) with a versican antisense sequence using the retroviral vector LXSN. Stable expression of versican antisense (LVaSN) significantly reduced versican production, induced a flattened morphology, reduced cell proliferation and migration, increased tropoelastin synthesis, increased elastin binding protein (S-Gal/EBP), and increased deposition of elastic fibers in long-term cultures. Add-back of chondroitin sulfate chains, or versican, decreased S-Gal/EBP and elastic fiber formation. LVaSN cells seeded into balloon catheter-injured rat carotid arteries formed neointimae containing low levels versican, increased amounts of S-Gal/EBP, and increased elastin deposits 7 days postinjury. At 4 weeks, neointimae formed from LVaSN cells were highly structured and contained multiple layers of elastic fibers and lamellae. These results indicate a central role for versican and its constituent chondroitin sulfate chains in controlling cell phenotype, elastogenesis, and intimal structure.
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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".