Heparan sulfate side chains have a critical role in the inhibitory effects of perlecan on vascular smooth muscle cell response to arterial injury
Bibliographic record
Abstract
Perlecan is a proteoglycan composed of a 470-kDa core protein linked to three heparan sulfate (HS) glycosaminoglycan chains. The intact proteoglycan inhibits the smooth muscle cell (SMC) response to vascular injury. Hspg2(Δ3/Δ3) (MΔ3/Δ3) mice produce a mutant perlecan lacking the HS side chains. The objective of this study was to determine differences between these two types of perlecan in modifying SMC activities to the arterial injury response, in order to define the specific role of the HS side chains. In vitro proliferative and migratory activities were compared in SMC isolated from MΔ3/Δ3 and wild-type mice. Proliferation of MΔ3/Δ3 SMC was 1.5× greater than in wild type (P < 0.001), increased by addition of growth factors, and showed a 42% greater migratory response than wild-type cells to PDGF-BB (P < 0.001). In MΔ3/Δ3 SMC adhesion to fibronectin, and collagen types I and IV was significantly greater than wild type. Addition of DRL-12582, an inducer of perlecan expression, decreased proliferation and migratory response to PDGF-BB stimulation in wild-type SMC compared with MΔ3/Δ3. In an in vivo carotid artery wire injury model, the medial thickness, medial area/lumen ratio, and macrophage infiltration were significantly increased in the MΔ3/Δ3 mice, indicating a prominent role of the HS side chain in limiting vascular injury response. Mutant perlecan that lacks HS side chains had a marked reduction in the inhibition of in vitro SMC function and the in vivo arterial response to injury, indicating the critical role of HS side chains in perlecan function in the vessel wall.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".