SP085DUALITY OF CALCITRIOL-BASED INHIBITION OR PROPAGATION OF VASCULAR CALCIFICATION IN VITRO IS DEPENDENT ON NORMAL OR HIGH CALCIUM LEVELS, RESPECTIVELY
Bibliographic record
Abstract
Introduction and Aims: Calcitriol (1, 25-dihydroxyvitamin D3) is used to mitigate secondary hyperparathyroidism (SHPT) in patients with chronic kidney disease (CKD). However, the use of calcitriol has been found in vitro and in vivo to paradoxically both inhibit and increase vascular calcification (VC), a risk factor for cardiovascular disease (CVD). Methods: The study’s objective was to examine the impact of calcitriol on aortic calcification in vitro when exposed to different medium concentrations of Ca2+ and PO43-. Aortic tissue was harvested from 16 week-old Sprague Dawley rats (n = 12), with whole rings incubated in Dulbecco’s Modified Eagles Medium (DMEM) for 4 days. Incubation treatments consisted of control (Group 1, 0.9mM PO43- & 1.6mM Ca2+), high Ca2+ and low PO43- (Group 2, 0.9mM PO43- & 3.2mM Ca2+), normal Ca2+ and high PO43- (Group 3, 3.8mM PO43- & 1.6mM Ca2+), and high Ca2+ and high PO43- (Group 4, 3.8mM PO43- & 1.6mM Ca2+). Calcitriol (0nM, 1nM, 10nM, or 100nM) was added to different DMEM treatments. Media was switched every 48hours.
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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) | 0.004 | 0.001 |
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".