Evidence map›Paper›PMID 39869659›Full record

ArticlePLoS computational biology2025

Biophysical modeling and experimental analysis of the dynamics of C. elegans body-wall muscle cells.

Xuexing Du, Jennifer Crodelle, Victor James Barranca, Songting Li, Yunzhu Shi, Shangbang Gao, Douglas Zhou

Abstract read
In one paragraph

Article in PLoS computational biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

1 citing paper in PubMed.

  1. Article
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

7 authors.

Xuexing DuSchool of Mathematical Sciences, Shanghai Jiao Tong University, Shanghai, China.ORCID 0009-0002-8687-3218
Jennifer CrodelleDepartment of Mathematics and Statistics, Middlebury College, Middlebury, Vermont, United States of America.
Victor James BarrancaDepartment of Mathematics and Statistics, Swarthmore College, Swarthmore, Pennsylvania, United States of America.
Songting LiSchool of Mathematical Sciences, Shanghai Jiao Tong University, Shanghai, China.
Yunzhu ShiKey Laboratory of Molecular Biophysics of the Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China.
Shangbang GaoKey Laboratory of Molecular Biophysics of the Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China.
Douglas ZhouSchool of Mathematical Sciences, Shanghai Jiao Tong University, Shanghai, China.ORCID 0000-0001-6631-2961

Funding

Lingang LaboratoryNational Key R&D Program of ChinaNational Natural Science Foundation of ChinaStudent Innovation Center at Shanghai Jiao Tong University
6 · The paper itself

Abstract

This study combines experimental techniques and mathematical modeling to investigate the dynamics of C. elegans body-wall muscle cells. Specifically, by conducting voltage clamp and mutant experiments, we identify key ion channels, particularly the L-type voltage-gated calcium channel (EGL-19) and potassium channels (SHK-1, SLO-2), which are crucial for generating action potentials. We develop Hodgkin-Huxley-based models for these channels and integrate them to capture the cells' electrical activity. To ensure the model accurately reflects cellular responses under depolarizing currents, we develop a parallel simulation-based inference method for determining the model's free parameters. This method performs rapid parallel sampling across high-dimensional parameter spaces, fitting the model to the responses of muscle cells to specific stimuli and yielding accurate parameter estimates. We validate our model by comparing its predictions against cellular responses to various current stimuli in experiments and show that our approach effectively determines suitable parameters for accurately modeling the dynamics in mutant cases. Additionally, we discover an optimal response frequency in body-wall muscle cells, which corresponds to a burst firing mode rather than regular firing mode. Our work provides the first experimentally constrained and biophysically detailed muscle cell model of C. elegans, and our analytical framework combined with robust and efficient parametric estimation method can be extended to model construction in other species.

Indexed as

Caenorhabditis elegansModels, BiologicalMuscle CellsAction PotentialsAnimalsCaenorhabditis elegans ProteinsComputer SimulationCaenorhabditis elegans Proteins

Identifiers

PMID39869659
PMCPMC11781704

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.