ArticleRoyal Society open science2025
Analysis of the spatio-temporal dynamics of a Rho-GEF-H1-myosin activator-inhibitor reaction-diffusion system.
Article in Royal Society open science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- Using Floquet theory to unravel far-from equilibrium dynamics in reaction-diffusion systems.PNAS nexus · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study presents a detailed mathematical analysis of the spatio-temporal dynamics of the RhoA-GEF-H1-myosin signalling network, modelled as a coupled system of reaction-diffusion equations. By employing conservation laws and the quasi-steady state approximation, the dynamics is reduced to a tractable nonlinear system. First, we analyse the temporal system of ordinary differential equations (ODE) in the absence of spatial variation, characterizing stability, bifurcations and oscillatory behaviour through phase-plane analysis and bifurcation theory. As parameter values change, the temporal system transitions between stable dynamics; unstable steady states characterized by oscillatory dynamics; and co-existence between locally stable steady states, or co-existence between a locally stable steady state and a locally stable limit cycle. Second, we extend the analysis to the reaction-diffusion system by incorporating diffusion to the temporal ODE model, leading to a comprehensive study of Turing instabilities and spatial pattern formation. In particular, by adding appropriate diffusion to the temporal model: (i) the uniform steady state can be destabilized leading to the well-known Turing diffusion-driven instability (DDI); (ii) one of the uniform stable steady states in the bistable region can be driven unstable, while the other one remains stable, leading to the formation of travelling wave fronts; and (iii) a stable limit cycle can undergo DDI leading to the formation of spatial patterns. More importantly, the interplay between bistability and diffusion shows how travelling wavefronts can emerge, consistent with experimental observations of cellular contractility pulses. Theoretical results are supported by numerical simulations, providing key insights into the parameter spaces that govern pattern transitions and diffusion-driven instabilities.
Indexed as
Identifiers
What OpenQuestion holds
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.