publications

2026

1. arXiv

   

   Divergence of detachment forces in the finite Voronoi model

   Wei Wang and Brian A. Camley

   arXiv:2604.15481 [cond-mat.soft] , Apr 2026

   Abs DOI Bib HTML Code

   

   Detachment and fracture are central to many tissue-level processes, but they are challenging to simulate with Voronoi-type models that typically assume a confluent tissue. Here we analyze the finite Voronoi model, a nonconfluent extension of conventional Voronoi models, in which cell boundaries are composed of straight Voronoi edges and circular arcs of fixed radius ℓ. When the line tension on cell-medium interfaces exceeds the tension on cell-cell contacts, we find that the model exhibits a strong time-step dependence in the fracture timescale of initially intact active clusters: decreasing Δt can unphysically suppress cluster rupture events. We trace this behavior to a divergence of detachment forces in the finite Voronoi model and introduce a simple regularization. Finally, we calibrate the near-detachment mechanics against a deformable polygon model and examine how key physical parameters control the tissue fracture timescale under two different calibration strategies. Our results show that, for studies focused on fracture or intercellular adhesion in nonconfluent monolayers, a physically motivated calibration of near-detachment mechanics in the finite Voronoi model is essential.

   @article{wang2026divergence,
     title = {Divergence of detachment forces in the finite Voronoi model},
     author = {Wang, Wei and Camley, Brian A.},
     journal = {arXiv:2604.15481},
     year = {2026},
     month = apr,
     doi = {10.48550/arXiv.2604.15481},
   }

2. Phys. Rev. E

   

   Perfect adaptation in eukaryotic gradient sensing using cooperative allosteric binding

   Vishnu Srinivasan^†, Wei Wang, and Brian A. Camley

   Phys. Rev. E [Editors’ Suggestion] , Apr 2026

   Abs DOI Bib HTML Code

   

   Eukaryotic cells generally sense chemical gradients using the binding of chemical ligands to membrane receptors. To perform chemotaxis effectively in different environments, cells need to adapt to different concentrations. We present a model of gradient sensing where the affinity of receptor-ligand binding is increased when a protein binds to the receptor’s cytosolic side. This interior protein (allosteric factor) alters the sensitivity of the cell, allowing the cell to adapt to different ligand concentrations. We propose a reaction scheme where the cell alters the allosteric factor’s availability to adapt the average fraction of bound receptors to 1/2. We calculate bounds on the chemotactic accuracy of the cell and find that the cell can reach near-optimal chemotaxis over a broad range of concentrations. We find that the accuracy of chemotaxis depends strongly on the diffusion of the allosteric compound relative to other reaction rates. From this, we also find a tradeoff between adaptation time and gradient sensing accuracy.

   @article{z9xd-xbw5,
     title = {Perfect adaptation in eukaryotic gradient sensing using cooperative allosteric binding},
     author = {Srinivasan, Vishnu and Wang, Wei and Camley, Brian A.},
     journal = {Phys. Rev. E},
     volume = {113},
     issue = {4},
     pages = {044414},
     numpages = {14},
     year = {2026},
     month = apr,
     publisher = {American Physical Society},
     doi = {10.1103/z9xd-xbw5},
     url = {https://link.aps.org/doi/10.1103/z9xd-xbw5},
   }

3. Phys. Rev. E

   

   Controlling tissue size by active fracture

   Wei Wang and Brian A. Camley

   Phys. Rev. E, Mar 2026

   Abs DOI Bib HTML Code

   

   Groups of cells, including clusters of cancerous cells, multicellular organisms, and developing organs, may both grow and break apart. What physical factors control these fractures? In these processes, what sets the eventual size of clusters? We first develop a one-dimensional framework for understanding cell clusters that can fragment due to cell motility using an active particle model. We compute analytically how the break rate of cell-cell junctions depends on cell speed, cell persistence, and cell-cell junction properties. Next, we find the cluster size distributions, which differ depending on whether all cells can divide or only the cells on the edge of the cluster divide. Cluster size distributions depend solely on the ratio of the break rate to the growth rate—allowing us to predict how cluster size and variability depend on cell motility and cell-cell mechanics. Our results suggest that organisms can achieve better size control when cell division is restricted to the cluster boundaries or when fracture can be localized to the cluster center. Additionally, we derive a universal survival probability for an intact cluster 𝑆⁡(𝑡)=𝑒−𝑘𝑑⁢𝑡 at steady state if all cells can divide, which is independent of the rupture kinetics and depends solely on the cell division rate 𝑘𝑑. Finally, we further corroborate the one-dimensional analytics with two-dimensional simulations, finding quantitative agreement with some—but not all—elements of the theory across a wide range of cell motility. Our results link the general physics problem of a collective active escape over a barrier to size control, providing a quantitative measure of how motility can regulate organ or organism size.

   @article{dk15-hwzg,
     title = {Controlling tissue size by active fracture},
     author = {Wang, Wei and Camley, Brian A.},
     journal = {Phys. Rev. E},
     volume = {113},
     issue = {3},
     pages = {034405},
     numpages = {20},
     year = {2026},
     month = mar,
     publisher = {American Physical Society},
     doi = {10.1103/dk15-hwzg},
     url = {https://link.aps.org/doi/10.1103/dk15-hwzg},
   }

2025

1. PRX Life

   

   Confinement, Jamming, and Adhesion in Cancer Cells Dissociating from a Collectively Invading Strand

   Wei Wang, Robert A. Law, Emiliano Perez Ipiña, Konstantinos Konstantopoulos, and Brian A. Camley

   PRX Life, Feb 2025

   Abs DOI Bib HTML Code

   

   When cells in a primary tumor work together to invade into nearby tissue, this can lead to cell dissociations—cancer cells breaking off from the invading front—leading to metastasis. What controls the dissociation of cells and whether they break off singly or in small groups? Can this be determined by cell-cell adhesion or chemotactic cues given to cells? We develop a physical model for this question, based on experiments that mimic aspects of cancer cell invasion using microfluidic devices with microchannels of different widths. Experimentally, most dissociation events (“ruptures”) involve single cells breaking off, but we observe some ruptures of large groups (∼20 cells) in wider channels. The rupture probability is nearly independent of channel width. We recapitulate the experimental results with a phase-field cell motility model by introducing three different cell states (follower, guided, and high-motility “leader” cells) based on their spatial position. These leader cells may explain why single-cell rupture is the universal most probable outcome. Our simulation results show that cell-channel adhesion is necessary for cells in narrow channels to invade, and strong cell-cell adhesion leads to fewer but larger ruptures. Chemotaxis also influences the rupture behavior: Strong chemotaxis strength leads to larger and faster ruptures. Finally, we study the relationship between biological jamming transitions and cell dissociations. Our results suggest unjamming is necessary but not sufficient to create ruptures.

   @article{PRXLife.3.013012,
     title = {Confinement, Jamming, and Adhesion in Cancer Cells Dissociating from a Collectively Invading Strand},
     author = {Wang, Wei and Law, Robert A. and Perez Ipi\~na, Emiliano and Konstantopoulos, Konstantinos and Camley, Brian A.},
     journal = {PRX Life},
     volume = {3},
     issue = {1},
     pages = {013012},
     numpages = {20},
     year = {2025},
     month = feb,
     publisher = {American Physical Society},
     doi = {10.1103/PRXLife.3.013012},
     url = {https://link.aps.org/doi/10.1103/PRXLife.3.013012},
   }

2024

1. Biophys. J.

   

   Trade-offs in concentration sensing in dynamic environments

   Aparajita Kashyap^†, Wei Wang, and Brian A. Camley

   Biophysical Journal, May 2024

   Abs DOI Bib HTML Code

   

   When cells measure concentrations of chemical signals, they may average multiple measurements over time in order to reduce noise in their measurements. However, when cells are in an environment that changes over time, past measurements may not reflect current conditions—creating a new source of error that trades off against noise in chemical sensing. What statistics in the cell’s environment control this trade-off? What properties of the environment make it variable enough that this trade-off is relevant? We model a single eukaryotic cell sensing a chemical secreted from bacteria (e.g., folic acid). In this case, the environment changes because the bacteria swim—leading to changes in the true concentration at the cell. We develop analytical calculations and stochastic simulations of sensing in this environment. We find that cells can have a huge variety of optimal sensing strategies ranging from not time averaging at all to averaging over an arbitrarily long time or having a finite optimal averaging time. The factors that primarily control the ideal averaging are the ratio of sensing noise to environmental variation and the ratio of timescales of sensing to the timescale of environmental variation. Sensing noise depends on the receptor-ligand kinetics, while environmental variation depends on the density of bacteria and the degradation and diffusion properties of the secreted chemoattractant. Our results suggest that fluctuating environmental concentrations may be a relevant source of noise even in a relatively static environment.

   @article{kashyap2024trade,
     title = {Trade-offs in concentration sensing in dynamic environments},
     author = {Kashyap, Aparajita and Wang, Wei and Camley, Brian A.},
     journal = {Biophysical Journal},
     volume = {123},
     number = {10},
     pages = {1184--1194},
     month = may,
     year = {2024},
     publisher = {Elsevier},
     doi = {10.1016/j.bpj.2024.03.025},
   }

2. Phys. Rev. E

   

   Limits on the accuracy of contact inhibition of locomotion

   Wei Wang and Brian A. Camley

   Phys. Rev. E, May 2024

   Abs DOI Bib HTML Code

   

   Cells that collide with each other repolarize away from contact, in a process called contact inhibition of locomotion (CIL), which is necessary for correct development of the embryo. CIL can occur even when cells make a micron-scale contact with a neighbor—much smaller than their size. How precisely can a cell sense cell-cell contact and repolarize in the correct direction? What factors control whether a cell recognizes it has contacted a neighbor? We propose a theoretical model for the limits of CIL where cells recognize the presence of another cell by binding the protein ephrin with the Eph receptor. This recognition is made difficult by the presence of interfering ligands that bind nonspecifically. Both theoretical predictions and simulation results show that it becomes more difficult to sense cell-cell contact when it is difficult to distinguish ephrin from the interfering ligands, or when there are more interfering ligands, or when the contact width decreases. However, the error of estimating contact position remains almost constant when the contact width changes. This happens because the cell gains spatial information largely from the boundaries of cell-cell contact. We study using statistical decision theory the likelihood of a false-positive CIL event in the absence of cell-cell contact, and the likelihood of a false negative where CIL does not occur when another cell is present. Our results suggest that the cell is more likely to make incorrect decisions when the contact width is very small or so large that it nears the cell’s perimeter. However, in general, we find that cells have the ability to make reasonably reliable CIL decisions even for very narrow (micron-scale) contacts, even if the concentration of interfering ligands is ten times that of the correct ligands.

   @article{PhysRevE.109.054408,
     title = {Limits on the accuracy of contact inhibition of locomotion},
     author = {Wang, Wei and Camley, Brian A.},
     journal = {Phys. Rev. E},
     volume = {109},
     issue = {5},
     pages = {054408},
     numpages = {15},
     year = {2024},
     month = may,
     publisher = {American Physical Society},
     doi = {10.1103/PhysRevE.109.054408},
     url = {https://link.aps.org/doi/10.1103/PhysRevE.109.054408},
   }

2019

1. Phys. Rev. B

   

   Collective induced antidiffusion effect and general magnon Boltzmann transport theory

   Tao Liu, Wei Wang, and Jianwei Zhang

   Phys. Rev. B, Jun 2019

   Abs DOI Bib HTML

   

   Magnon transport and its efficient manipulation in FIs (ferromagnetic insulators) are important issues in magnon spintronics research, while the relaxation and decay of magnons are still in debates. In this paper, starting from the Hamiltonian of a magnetically ordered system, we derive and solve the general magnon Boltzmann equation. It is found that there exists an “antidiffusion driving effect” in magnon transport, which is caused by the collective interaction of a high density (or strong magnetic field) magnon gas in the limited magnetic background. This effect acts as a “spin pressure” on magnons, resulting in a decrease in magnon propagation length and an extra accumulation near the magnon generation boundary. By applying the derived magnon Boltzmann equation to several cases and comparing with the experiments, it is shown that our theory cannot only describe the influence of the external magnetic field on magnon transport but also confirm the fast drop regime in magnon transport is attributed to the boundary effect. The magnon Boltzmann method also predicts a new pathway for manipulations of magnon transport in FIs.

   @article{PhysRevB.99.214407,
     title = {Collective induced antidiffusion effect and general magnon Boltzmann transport theory},
     author = {Liu, Tao and Wang, Wei and Zhang, Jianwei},
     journal = {Phys. Rev. B},
     volume = {99},
     issue = {21},
     pages = {214407},
     numpages = {13},
     year = {2019},
     month = jun,
     publisher = {American Physical Society},
     doi = {10.1103/PhysRevB.99.214407},
     url = {https://link.aps.org/doi/10.1103/PhysRevB.99.214407},
   }