ArticleForces in mechanics2021
A three-dimensional finite element model of cAMP signals.
Article in Forces in mechanics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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.
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Who cites it
1 citing paper in PubMed, 1 citations in OpenAlex.
- A two-dimensional finite element model of intercellular cAMP signaling through gap junction channels.Journal of biomechanics · 2023Article
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Authors and funding
4 authors at 1 institution in 1 country.
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Abstract
This paper presents a three-dimensional finite element model for cyclic adenosine monophosphate (cAMP) signaling. Governing equations for the synthesis, diffusion, and degradation of cAMP were numerically implemented using the finite element method. Simulated results were displayed as time course plots of cAMP concentrations at selected nodes within the discretized geometry. The validity of the finite element model was assessed by comparing simulated results against analytical or other numerical solutions of cAMP concentration distribution for a spherical cellular volume. An endothelial cell was also simulated using its discretized geometry obtained from microscopic cellular cross-sectional images. Simulated solutions using the spherical cellular volume produced near identical cAMP concentration plots to the analytical solutions and were in good agreements with numerical results obtained from VCell, an existing software package for modeling cell biological systems. The validated 3-D finite element model was then employed to simulate the cAMP signaling pathway within a pulmonary microvascular endothelial cell geometry.
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Registered trials
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.