Vascular Calcification Induced by Chronic Kidney Disease Is Mediated by an Increase of 1α-Hydroxylase Expression in Vascular Smooth Muscle Cells
Bibliographic record
Abstract
ABSTRACT Vascular calcification (VC) is a complication of chronic kidney disease that predicts morbidity and mortality. Uremic serum promotes VC, but the mechanism involved is unknown. A role for 1,25(OH)2D3 in VC has been proposed, but the mechanism is unclear because both low and high levels have been shown to increase it. In this work we investigate the role of 1,25(OH)2D3 produced in vascular smooth muscle cells (VSMCs) in VC. Rats with subtotal nephrectomy and kidney recipient patients showed increased arterial expression of 1α-hydroxylase in vivo. VSMCs exposed in vitro to serum obtained from uremic rats also showed increased 1α-hydroxylase expression. Those increases were parallel to an increase in VC. After 6 days with high phosphate media, VSMCs overexpressing 1α-hydroxylase show significantly higher calcium content and RUNX2 expression than control cells. 1α-hydroxylase null mice (KO) with subtotal nephrectomy and treated with calcitriol (400 ng/kg) for 2 weeks showed significantly lower levels of vascular calcium content, Alizarin red staining, and RUNX2 expression than wild-type (WT) littermates. Serum calcium, phosphorus, blood urea nitrogen (BUN), PTH, and 1,25(OH)2D3 levels were similar in both calcitriol-treated groups. In vitro, WT VSMCs treated with uremic serum also showed a significant increase in 1α-hydroxylase expression and higher calcification that was not observed in KO cells. We conclude that local activation of 1α-hydroxylase in the artery mediates VC observed in uremia. © 2016 American Society for Bone and Mineral Research.
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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) | 0.001 | 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".