SP411COMBINED MAGNESIUM AND CALCITRIOL SUPPLEMENTATION ATTENUATES VASCULAR CALCIFICATION SEVERITY IN EXPERIMENTAL CHRONIC KIDNEY DISEASE
Bibliographic record
Abstract
Introduction and Aims: The study aim was to determine whether magnesium alone or combined magnesium and calcitriol treatments differentially impact the susceptibility to vascular calcification (VC) in experimental CKD. Methods: Male SD rats were maintained on an adenine diet (0.25%) for 7 wks. Animals were stratified by creatinine into 4 groups at 3 weeks. For the next 4 wks, each group was maintained on: (1) CKD-CON ( n=16), (2) MAG (0.2% Mg food, n=16), (3) CAL (calcitriol, 80ng/kg/day, n=16), or (4) CAL+MAG (calcitriol (80ng/kg/day) + 0.2% Mg food, n=16). Results: The serum creatinine was similar between groups (232±91 uM). Compared to CKD-CON, serum calcium was significantly elevated in the CAL and CAL + MAG groups. Serum magnesium was significantly elevated in the MAG, CAL+MAG and CAL groups. With calcitriol treatment, PTH was significantly suppressed (6X decrease) and FGF-23 was significantly elevated (~10X increase) compared to the non-CAL groups (p<0.05). There was a significant increase in the prevalence of VC in the calcitriol treated groups (CAL and CAL+MAG) compared to the CKD-CON and the MAG treatment groups (p50 nmol/mg tissue), compared to the CKD-CON and MAG groups where only 50-75% had VC (depending on the arterial bed). To determine the impact of calcitriol and magnesium on VC severity, only animals with von Kossa stainable VC (>50nmol/mg tissue calcium) were included in the analysis. There was a significant reduction (50%) in the calcium content (VC severity) in the CAL+MAG group compared to the CAL in the abdominal aorta, and iliac, carotid, and superior mesenteric arteries (p<0.05). As expected, the Ca/Mg ratio was significantly suppressed (50%) in the CAL+MAG compared to CAL in the abdominal aorta, and iliac, carotid, and superior mesenteric arteries, indicating there is twice as much magnesium in the microenvironment, compared to calcium (p<0.05). To determine whether the TRPM7 channel played a role in magnesium accrual, mRNA and protein levels were measured in abdominal aorta. CAL significantly reduced TRPM7 protein content in the abdominal aorta compared to CKD-CON and MAG; however, the TRPM7 mRNA and protein content was significantly greater in the combined CAL+MAG than the CAL group (p<0.05).
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".