Evidence map›Paper›PMID 40693535›Full record

ArticleeLife2025

Balancing reaction-diffusion network for cell polarization pattern with stability and asymmetry.

Yixuan Chen, Guoye Guan, Lei-Han Tang, Chao Tang

Abstract read
In one paragraph

Article in eLife, 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

4 authors.

Yixuan Chen *South Bay Interdisciplinary Science Center, Songshan Lake Materials Laboratory, Dongguan, China.ORCID https://orcid.org/0009-0004-3695-8752
Guoye Guan *South Bay Interdisciplinary Science Center, Songshan Lake Materials Laboratory, Dongguan, China.ORCID https://orcid.org/0000-0003-4479-4722
Lei-Han TangSouth Bay Interdisciplinary Science Center, Songshan Lake Materials Laboratory, Dongguan, China.ORCID https://orcid.org/0000-0002-2925-4691
Chao TangSchool of Physics, Peking University, Beijing, China.ORCID https://orcid.org/0000-0003-1474-3705

Funding

National Natural Science Foundation of China 12090053National Natural Science Foundation of China 32088101Research Grants Council of the Hong Kong SAR 12303219
6 · The paper itself

Abstract

Cell polarization is a critical process that separates molecular species into two distinct regions in prokaryotic and eukaryotic cells, guiding biological processes such as cell division and cell differentiation. Although several underlying antagonistic reaction-diffusion networks capable of setting up cell polarization have been identified experimentally and theoretically, our understanding of how to manipulate pattern stability and asymmetry remains incomplete, especially when only a subset of network components is known. Here, we present numerical results to show that the polarized pattern of an antagonistic 2-node network collapses into a homogeneous state when subjected to single-sided self-regulation, single-sided additional regulation, or unequal system parameters. However, polarity restoration can be achieved by combining two modifications with opposing effects. Additionally, spatially inhomogeneous parameters favoring respective domains stabilize their interface at designated locations. To connect our findings to cell polarity studies of the nematode

Indexed as

Caenorhabditis elegansCell PolarityAnimalsModels, BiologicalZygoteasymmetryCaenorhabditis elegansC. eleganscell polarizationcomputational biologyembryogenesisphysics of living systemsreaction-diffusion networkstabilitysystems biology

Identifiers

PMID40693535
PMCPMC12283076

What Socratic 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 Socratic graph.