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Emanuel F. Teixeira

Publications and source records attributed to Emanuel F. Teixeira.

5 recordsLinked to original sources

Benchmarking the flow of epithelial cell monolayer with self-aligning deformable active membranes

Collective cell migration emerges from the interplay between motility, deformability and mechanical interactions, yet incorporating these ingredients into computationally efficient tissue models remains challenging. Here, we benchmark self-aligning deformable active membranes in a confined-flow geometry that mimics epithelial monolayer migration around a circular obstacle. In this model, cells are represented as deformable, adhesive membranes whose self-propulsion direction relaxes towards their velocity. By systematically varying the self-alignment timescale, cell-cell adhesion and inlet forcing, we characterize the resulting flows through collective alignment, relative density, neighbor rearrangements and spatial velocity fields. The model captures a broad spectrum of tissue behaviors, ranging from disordered, liquid-like flows to highly aligned, solid-like states. Compared with a related multiparticle model, self-aligning active membranes achieve stronger collective alignment, exhibit a more systematic density response and access states closer to both limits of the solid-liquid spectrum. We further show that increasing the target shape index promotes cell elongation and accelerates tissue flow, directly linking cell-scale deformability to tissue-scale transport. Finally, we compare simulated velocity profiles with experimental measurements from in vitro migrating MDCK epithelial cell monolayers and find qualitative agreement across multiple horizontal and vertical transects around the obstacle. These results establish self-aligning deformable active membranes as a versatile framework for connecting cell mechanics, shape adaptation and self-alignment to collective tissue migration in confined geometries.

cond-mat.soft↗

Collective self-sorting on a chip

We harness two established ingredients for collective demixing: differential speed and curvature to create a self-sorting device. In binary mixtures, motility differences drive spontaneous spatial segregation, while confinement geometry determines how rapidly and strongly this demixing develops. Using particle based simulations, we systematically identify the geometrical conditions that promote efficient segregation and use these results to guide the design of a finite sorting architecture. We then translate these physical mechanisms into a sequence of curved microfluidic units that progressively amplify the separation of the two species and direct them toward distinct collection regions. Experiments with binary Quincke-roller mixtures confirm that an initially mixed suspension progressively demixes as it propagates through the device, leading to strong enrichment downstream. Our results demonstrate how collective active demixing can be converted into a functional continuous sorting strategy, providing a route toward autonomous microfluidic separation based on particle motility and confinement geometry.

cond-mat.soft↗

Collective ballistic motion explains fast aggregation in adhesive active matter

Inspired by motile cells in tissue formation, we find that active systems of self-aligning adhesive particles undergo ballistic aggregation through a flocking transition. This kinetic regime emerges when the cluster persistence length grows faster with cluster mass than the intercluster distance does. We also identify and explain distinct non-collective kinetic regimes, including biologically relevant long-lived transients. Our analytical and numerical results offer a unified framework explaining the broad range of experimentally observed aggregation exponents in cellular systems and reveal physical principles potentially critical for timely tissue organization.

cond-mat.soft↗

Segregation in binary mixture with differential contraction among active rings

Cell cortex contraction is essential for shaping cells, enabling movement, ensuring proper division, maintaining tissue integrity, guiding development, and responding to mechanical signals - all critical for the life and health of multicellular organisms. Differential contractions in cell membranes, particularly when cells of different types interact, play a crucial role in the emergence of segregation. In this study, we introduce a model where rings composed of active particles interact through differential membrane contraction within a specified cutoff distance. We demonstrate that segregation arises solely from differential contraction, with the activity of the rings functioning similarly to an effective temperature. Additionally, we observed that segregation involves cluster fusion-diffusion process. However, the decay exponent of the segregation parameter we found is close to $λ\sim -1/3$, which differs from the $λ\sim -1/4$ predicted by previous theoretical approaches and simulations.

physics.bio-ph↗

Single Active Ring Model

Cellular tissue behavior is a multiscale problem. At the cell level, out of equilibrium, biochemical reactions drive physical cell-cell interactions in a typical active matter process. Cell modeling computer simulations are a robust tool to explore the countless possibilities and test hypotheses. Here, we introduce a two dimensional, extended active matter model for biological cells. A ring of interconnected self-propelled particles represents the cell. Translational modes, rotational modes, and mixtures of these appear as collective states. Using analytic results derived from active Brownian particles, we identify effective characteristic time scales for ballistic and diffusive movements. Finite-size scale investigation shows that the ring diffusion increases linearly with its size when in collective movement. A study on the ring shape reveals that all collective states are present even when bending forces are weak. In that case, when in translational mode, the collective velocity aligns with the largest ring's direction in a spontaneous polarization emergence.

cond-mat.soft↗