Evidence map›Paper›PMID 27076052›Full record

ArticleIEEE transactions on bio-medical engineering2016

Computational Modeling of Spatiotemporal Ca(2+) Signal Propagation Along Hepatocyte Cords.

Aalap Verma, Hirenkumar Makadia, Jan B Hoek, Babatunde A Ogunnaike, Rajanikanth Vadigepalli

Abstract read
In one paragraph

Article in IEEE transactions on bio-medical engineering, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Computational Modeling in Liver Surgery.Frontiers in physiology · 2017
    Review
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

5 authors.

Aalap Verma
Hirenkumar Makadia
Jan B Hoek
Babatunde A Ogunnaike
Rajanikanth Vadigepalli

Funding

Ethanol Effects on the Transcriptional Regulatory Network in Liver Regeneration -R01AA018873 · NIAAA · THOMAS JEFFERSON UNIVERSITY · PI SRIVASTAVA, ANKITA · 2009 to 2025
$8.7M
NIAAA NIH HHS R01 AA018873
6 · The paper itself

Abstract

objectiveThe purpose of this study is to model the dynamics of lobular Ca(2+) wave propagation induced by an extracellular stimulus, and to analyze the effect of spatially systematic variations in cell-intrinsic signaling parameters on sinusoidal Ca(2+) response.

methodsWe developed a computational model of lobular scale Ca(2+) signaling that accounts for receptor- mediated initiation of cell-intrinsic Ca(2+) signal in hepatocytes and its propagation to neighboring hepatocytes through gap junction-mediated molecular exchange.

resultsAnalysis of the simulations showed that a pericentral-to-periportal spatial gradient in hormone sensitivity and/or rates of IP3 synthesis underlies the Ca(2+) wave propagation. We simulated specific cases corresponding to localized disruptions in the graded pattern of these parameters along a hepatic sinusoid. Simulations incorporating locally altered parameters exhibited Ca(2+) waves that do not propagate throughout the hepatic plate. Increased gap junction coupling restored normal Ca(2+) wave propagation when hepatocytes with low Ca(2+) signaling ability were localized in the midlobular or the pericentral region.

conclusionMultiple spatial patterns in intracellular signaling parameters can lead to Ca(2+) wave propagation that is consistent with the experimentally observed spatial patterns of Ca(2+) dynamics. Based on simulations and analysis, we predict that increased gap junction-mediated intercellular coupling can induce robust Ca(2+) signals in otherwise poorly responsive hepatocytes, at least partly restoring the sinusoidally oriented Ca (2+) waves. SIGNIFICANCE: Our bottom-up model of agonist-evoked spatial Ca(2+) patterns can be integrated with detailed descriptions of liver histology to study Ca(2+) regulation at the tissue level.

Indexed as

Computer SimulationModels, BiologicalAnimalsBiomedical EngineeringCalcium SignalingHepatocytesHumansLiverReceptors, VasopressinReceptors, Vasopressin

Identifiers

PMID27076052
PMCPMC5035187

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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.