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Mathematical Modeling of Magnesium Homeostasis in Male Rats

2024· article· en· W4398166110 on OpenAlexaffabout
Pritha Dutta, Anita T. Layton

Bibliographic record

VenuePhysiology · 2024
Typearticle
Languageen
FieldNursing
TopicMagnesium in Health and Disease
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMagnesiumHomeostasisBiologyChemistryCell biology

Abstract

fetched live from OpenAlex

Magnesium (Mg2+) is an important cofactor for numerous biological processes, including protein synthesis, nucleic acid stability, and neuromuscular excitability. Extracellular magnesium is tightly regulated, with plasma [Mg2+] maintained relatively constant between 1.6 and 2.3 mg/dL under normal physiological conditions. Almost all of the body’s Mg2+ (approximately 99%) is either stored in bone or within cells (DOI: 10.1053/j.ackd.2018.01.003). A normal daily Mg2+ intake averages around 300 mg, about half of which is absorbed by the intestine. The kidneys reabsorb 95-98% of the filtered Mg2+ and excrete only 2-5% through urine. To understand the interplay between intestine, kidneys, and bones to maintain Mg2+ homeostasis, we developed a computational model of Mg2+ homeostasis for male rats and incorporated it with a male rat calcium (Ca2+) homeostasis model. Our model consists of five compartments: plasma, intestine, kidneys, bones, and parathyroid gland. The model also includes parathyroid hormone and vitamin D3 since they significantly regulate Mg2+ and Ca2+ homeostasis. We used this model to simulate three conditions: change in dietary Mg2+, change in dietary vitamin D3, and administration of proton-pump inhibitors. In the case of variation in dietary Mg2+, our model predicted that the body compensates mainly through decreasing (in case of low dietary Mg2+) and increasing (in case of high dietary Mg2+) urinary Mg2+ excretion and the Mg2+ content in the rapidly exchangeable bone pool. Change in dietary Mg2+ does not have any significant effect on Ca2+ homeostasis. On the other hand, change in dietary vitamin D3 has significant effect on both Mg2+ and Ca2+ homeostasis, with the effect being more pronounced for Ca2+ compared to Mg2+. Our model predicted significant changes in intestinal Mg2+ and Ca2+ absorption, PTH secretion, urinary Mg2+ and Ca2+ excretion, and Mg2+ and Ca2+ content in the rapidly exchangeable bone pool following change in dietary vitamin D3. Administration of proton pump inhibitors (PPIs) such as omeprazole, which are a class of medicine commonly used to reduce stomach acid production, affect Mg2+ and Ca2+ transport in the intestine. PPIs reduce intestinal Mg2+ and Ca2+ absorption by 3.5-fold and 40%, respectively. The body compensates for this huge drop in intestinal Mg2+ absorption by tapping into the Mg2+ stored in the rapidly exchangeable bone pool in addition to decreasing urinary Mg2+ excretion. By contrast, the body can compensate for the drop in intestinal Ca2+ absorption by only decreasing urinary Ca2+ excretion. Thus, this model can be used to understand the compensatory mechanisms adopted by the body to maintain Mg2+ and Ca2+ homeostasis under various pathophysiological conditions and drug administrations. This work was supported by the Canada 150 Research Chair program, National Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant, and Canada Institutes of Health Research (CIHR) Project Grant to Anita Layton. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.029
GPT teacher head0.315
Teacher spread0.286 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes2
Has abstractyes

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