Oxidized low‐density lipoprotein acts synergistically with β‐glycerophosphate to induce osteoblast differentiation in primary cultures of vascular smooth muscle cells
Bibliographic record
Abstract
Previous studies have localized osteoblast specific markers to sites of calcified atherosclerotic lesions. We therefore decided to use an established in vitro model of vascular calcification in order to confirm earlier reports of oxidized low-density lipoprotein (oxLDL) promoting the osteogenic differentiation of vascular smooth muscle cells. Treatment of primary bovine aortic smooth muscle cells (BASMCs) with beta-glycerophosphate was found to induce a time-dependent increase in osteoblast differentiation. In contrast, no effect was seen when BASMCs were cultured in the presence of oxLDL alone. However, when the BASMCs were cultured in the presence of both beta-glycerophosphate and oxLDL, beta-glycerophosphate's ability to induce osteoblast differentiation was significantly enhanced. In an attempt to resolve the mechanism by which this effect was occurring, we examined the effect of beta-glycerophosphate and oxLDL on several pathways known to be critical to the differentiation of osteoblasts. Surprisingly, beta-glycerophosphate alone was found to enhance Osterix (Osx) expression by inducing both Smad 1/5/8 activation and Runx2 expression. In contrast, oxLDL did not affect either Smad 1/5/8 activation or Runx2 activation but rather, it enhanced both beta-glycerophosphate-induced Osx expression and osteoblast differentiation in an extracellular signal-regulated kinase 1 and 2 (Erk 1 and 2) -dependent manner. When taken together, these findings suggest a plausible mechanism by which oxLDL may promote osteogenic differentiation and vascular calcification in vivo. J. Cell. Biochem. 105: 185-193, 2008. (c) 2008 Wiley-Liss, Inc.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.001 | 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".