Magnesium supplementation attenuates aldosterone‐induced hypertension, kidney damage and oxidative stress in genetically hypomagnesemic mice
Bibliographic record
Abstract
Hyperaldosteronsim is associated with hypertension, fibrosis and hypomagnesemia. Here we investigated the effect of Mg2+ supplementation on aldosterone‐induced hypertension and kidney damage in mice genetically bred to have normal (MgH) or low (MgL) intracellular Mg2+ level. Male MgH and MgL mice were infused with aldosterone. Basal systolic blood pressure (SBP) was higher in MgL vs MgH (p<0.05). Aldosterone infusion increased SBP, albuminuria and renal collagen deposition (P<0.05) in both strains. TRPM6 channels are key regulators of Mg2+ reabsorption. MgL mice had reduced basal TRPM6 expression (P<0.05). Aldosteone infusion increased renal TRPM6 expression in MgH (P<0.01) but not MgL mice. Aldosterone induced oxidative stress, NF‐êB activity and expression of pro‐inflammatory markers in both MgH (1‐fold) and MgL mice (2‐fold). Aldosterone failed to increase SBP in mice fed with high Mg2+ diet. In these animals, aldosterone‐induced deleterious effects were prevented. Our data show that Mg2+ supplementation attenuates aldosterone‐induced hypertension and renal damage through changes in oxidative stress and inflammatory pathways. These findings suggest that aberrations in Mg2+ status may be associated with elevated SBP and renal damage in chronic diseases associated with hyperaldosteronism. Supplementation with Mg2+ may be protective in this context. Support: HSFC, CIHR.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".