Abstract 212: Reduced Magnesium in the Vascular Microenvironment May Be the Switch That Increases Susceptibility to Vascular Calcification in Experimental Chronic Kidney Disease
Bibliographic record
Abstract
Cardiovascular disease (CVD) is the leading cause of death in patients with chronic kidney disease (CKD). Pathogenic vascular calcification (VC) in CKD, likely resulting from altered phosphate and calcium metabolism, is a critical harbinger of CVD in these patients. A growing body of evidence suggests a protective role for magnesium in attenuating VC. In this study, the objective was to elucidate the stoichiometry of mineral accumulation in the vascular media, particularly with regard to the relative abundance of magnesium, phosphate and calcium, during the various stages of progression of VC in male Sprague Dawley rats (n=40) with adenine-induced CKD (0.25% in diet) for up to 7 weeks. The adenine protocol generated a range of CKD severity (creatinine, 234 to 650 μmol/L, mean 353 ± 91 μmol/L) and we further modified the susceptibility to VC by altering vitamin K status. Specifically, we increased vitamin K intake (K1 @ 100 mg/kg diet) or decreased availability (warfarin, ~0.1 mg/kg/day) to induce a decreased and increased VC, respectively. Calcium, phosphate, and magnesium contents were analyzed in the thoracic aorta, abdominal aorta and pudendal arteries. Accumulating tissue phosphate (~2.5 to 1100 nmol/mg) positively correlated with both tissue calcium and magnesium levels (r2=0.99, p<0.0001; r2=0.86, p<0.0001 respectively). However, stoichiometric analysis revealed the relative magnesium abundance decreased markedly with progressing VC (~20% to <2% Mg when PO4 greater than 30 mmol/mg tissue), indicating a trajectory away from the more soluble magnesium containing crystal, whitlockite. Our research suggests that perturbations in Mg homeostasis can mediate changes in the microenvironment that facilitate the progression of VC. Specifically, a relative decrease of magnesium within the vascular media could reduce the protective capacity and potentiate the calcification process.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".