Modeling calcium and magnesium balance: Regulation by calciotropic hormones and adaptations under varying dietary intake
Bibliographic record
Abstract
Magnesium (Mg 2+ ) is crucial for several cellular and physiological processes and is tightly regulated due to health risks associated with imbalances. Mg 2+ , calcium (Ca 2+ ), parathyroid hormone, and vitamin D 3 are tightly coupled, ensuring proper bone metabolism and intestinal and renal absorption of Mg 2+ and Ca 2+ . While several Ca 2+ homeostasis models exist, no computational model has been developed to study Mg 2+ homeostasis. We developed a computational model of Mg 2+ homeostasis in male rats, integrating it with an existing Ca 2+ homeostasis model, to understand the interconnected physiological processes regulating their homeostasis. We then analyzed adaptations in these interconnected processes under (1) dietary Mg 2+ deficiency, (2) low/high dietary Ca 2+ with Mg 2+ deficiency, and (3) vitamin D 3 deficiency. Model simulations predicted severe hypomagnesemia and mild hypocalcemia with significant dietary Mg 2+ deficiency. Low dietary Ca 2+ improved, while high dietary Ca 2+ worsened Mg 2+ deficiency. Finally, vitamin D 3 deficiency caused severe hypocalcemia, with minimal impact on Mg 2+ homeostasis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".