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Calcium is an essential signaling molecule required for various cellular functions. Calcium pumps and ion channels on cell and organellar membranes, such as those on the endoplasmic reticulum (ER), regulate calcium concentrations inside the cell. They remain closed, keeping the cytosolic calcium levels low at a resting state.
Various transmembrane receptors, such as G protein-coupled receptors (GPCRs), elicit a response to extracellular signals by increasing cytosolic calcium. Activated GPCRs...

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Simulation of Calcium Dynamics in Realistic Three-Dimensional Domains.

James Sneyd¹, John Rugis¹, Shan Su¹

¹Department of Mathematics, University of Auckland, Auckland 1142, New Zealand.

|October 27, 2022

Summary

This study presents an automated method for creating 3D cell models, crucial for understanding how calcium ions ([Ca2+]) control saliva secretion in salivary gland cells. The new method is efficient and maintains accurate quantitative predictions.

Keywords:

calcium dynamics finite-element methods saliva secretion three-dimensional simulations

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Automated Analysis of Dynamic Ca2+ Signals in Image Sequences

Automated Analysis of Dynamic Ca2+ Signals in Image Sequences

Published on: June 16, 2014

Area of Science:

Cell biology
Physiology
Biophysics

Background:

Cytosolic calcium ions ([Ca2+]) act as vital intracellular messengers.
In salivary gland acinar cells, [Ca2+] regulates primary saliva secretion, with increases localized to apical regions.
Accurate modeling of [Ca2+] dynamics requires detailed spatial information of cellular calcium handling components.

Purpose of the Study:

To develop an efficient, automated method for constructing approximately anatomically accurate 3D salivary gland acinar cell models.
To validate that this new method preserves the quantitative accuracy of previous models in explaining [Ca2+]-controlled saliva secretion.

Main Methods:

Development of a semi-automated procedure for generating 3D cell reconstructions.
Validation of the new models using existing quantitative data on saliva secretion.
Comparison of model predictive capabilities with those derived from manually reconstructed cells.

Main Results:

An automated method for creating 3D cell models was successfully developed.
The new models, while less detailed than previous ones, were sufficient for accurate quantitative predictions of saliva secretion.
The efficiency of cell model construction was significantly improved.

Conclusions:

An automated approach offers a more efficient alternative for building 3D cell models for studying calcium signaling.
This method allows for quantitative modeling of [Ca2+]-mediated processes like saliva secretion without exhaustive manual reconstruction.
The findings support the use of simplified, yet quantitatively accurate, cell models in physiological research.