Evidence map›Paper›PMID 26109090›Full record

ArticleAmerican journal of physiology. Renal physiology2015

Parameter estimation for mathematical models of a nongastric H+(Na+)-K(+)(NH4+)-ATPase.

Mónica Nadal-Quirós, Leon C Moore, Mariano Marcano

Abstract read
In one paragraph

Article in American journal of physiology. Renal physiology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. A new microscope for the kidney: mathematics.American journal of physiology. Renal physiology · 2017
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Mónica Nadal-QuirósDepartment of Biology, University of Puerto Rico, Río Piedras, Puerto Rico;
Leon C MooreDepartment of Physiology and Biophysics, State University of New York Health Science Center, Stony Brook, New York;
Mariano MarcanoDepartment of Computer Science, University of Puerto Rico, Río Piedras, Puerto Rico mariano.marcano@upr.edu.

Funding

Upgrade Laboratories Facilities at UPR-Rio PiedrasR25GM061151 · NIGMS · UNIVERSITY OF PUERTO RICO RIO PIEDRAS · PI CARBALLEIRA, NESTOR MANUEL · 2001 to 2023
$32.5M
Optimal Mathematical Models of Renal Transport ProcessesSC1GM084744 · NIGMS · UNIVERSITY OF PUERTO RICO RIO PIEDRAS · PI MARCANO, MARIANO · 2008 to 2011
$595k
NIGMS NIH HHS 2-R25-GM061151NIGMS NIH HHS R25 GM061151NIGMS NIH HHS SC1-GM-084744
6 · The paper itself

Abstract

The role of nongastric H(+)-K(+)-ATPase (HKA) in ion homeostasis of macula densa (MD) cells is an open question. To begin to explore this issue, we developed two mathematical models that describe ion fluxes through a nongastric HKA. One model assumes a 1H(+):1K(+)-per-ATP stoichiometry; the other assumes a 2H(+):2K(+)-per-ATP stoichiometry. Both models include Na+ and NH4+ competitive binding with H+ and K+, respectively, a characteristic observed in vitro and in situ. Model rate constants were obtained by minimizing the distance between model and experimental outcomes. Both 1H(+)(1Na(+)):1K(+)(1NH4 (+))-per-ATP and 2H(+)(2Na(+)):2K(+)(2NH4 (+))-per-ATP models fit the experimental data well. Using both models, we simulated ion net fluxes as a function of cytosolic or luminal ion concentrations typical for the cortical thick ascending limb and MD region. We observed that (1) K+ and NH4+ flowed in the lumen-to-cytosol direction, (2) there was competitive behavior between luminal K+ and NH4+ and between cytosolic Na+ and H+, 3) ion fluxes were highly sensitive to changes in cytosolic Na+ or H+ concentrations, and 4) the transporter does mostly Na+ / K+ exchange under physiological conditions. These results support the concept that nongastric HKA may contribute to Na+ and pH homeostasis in MD cells. Furthermore, in both models, H+ flux reversed at a luminal pH that was <5.6. Such reversal led to Na+ / H+ exchange for a luminal pH of <2 and 4 in the 1:1-per-ATP and 2:2-per-ATP models, respectively. This suggests a novel role of nongastric HKA in cell Na+ homeostasis in the more acidic regions of the renal tubules.

Indexed as

Models, BiologicalH(+)-K(+)-Exchanging ATPaseHomeostasisHumansKidney Tubules, DistalLoop of HenleH(+)-K(+)-Exchanging ATPaseH+-K+-ATPasemacula densa cellmathematical modelNa+ homeostasisnongastric ATPase

Identifiers

PMID26109090
PMCPMC4556890

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.