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To maintain normal functionality, it is necessary for a multicellular organism to generate robust responses to external temporal signals. However, the underlying mechanisms to coordinate the collective dynamics of cells remain poorly understood. Here, we study the calcium activity of biological neuron networks excited by periodic ATP stimuli. We use micropatterning to control the cells' physical connectivity. We find that whereas isolated cells become more synchronized in their calcium activity at long driving periods, connected cells become less synchronized, despite expressing more gap junctions which enable calcium exchange. To understand this result, we use a mathematical model in which a bifurcation analysis has previously shown coupling-induced desynchronization in an oscillatory network. Using parameters close to this bifurcation but in the excitable regime, we find that this desynchronization persists and can explain the experimental observations. The model further predicts that co-culturing with gap-junction-deficient cells should restore synchronization, which experiments confirm. Combining quantitative experiments, the physical and biological manipulation of cells, and mathematical modeling, our results suggest that cell-to-cell connectivity significantly affects how populations encode an external temporal signal as it slows down: Sparse networks synchronize due to longer entrainment, whereas highly connected networks can desynchronize due to dynamic frustration. Published by the American Physical Society2025 

Abstract The morphology and morphodynamics of cells as important biomarkers of the cellular state are widely appreciated in both fundamental research and clinical applications. Quantification of cell morphology often requires a large number of geometric measures that form a high-dimensional feature vector. This mathematical representation creates barriers to communicating, interpreting, and visualizing data. Here, we develop a deep learning-based algorithm to project 13-dimensional (13D) morphological feature vectors into 2-dimensional (2D) morphological latent space (MLS). We show that the projection has less than 5% information loss and separates the different migration phenotypes of metastatic breast cancer cells. Using the projection, we demonstrate the phenotype-dependent motility of breast cancer cells in the 3D extracellular matrix, and the continuous cell state change upon drug treatment. We also find that dynamics in the 2D MLS quantitatively agrees with the morphodynamics of cells in the 13D feature space, preserving the diffusive power and the Lyapunov exponent of cell shape fluctuations even though the dimensional reduction projection is highly nonlinear. Our results suggest that MLS is a powerful tool to represent and understand the cell morphology and morphodynamics. 

We introduce and study spatiotemporal online allocation with deadline constraints (SOAD), a new online problem motivated by emerging challenges in sustainability and energy. In SOAD, an online player completes a workload by allocating and scheduling it on the points of a metric space (X,d) while subject to a deadlineT. At each time step, a service cost function is revealed that represents the cost of servicing the workload at each point, and the player must irrevocably decide the current allocation of work to points. Whenever the player moves this allocation, they incur a movement cost defined by the distance metricd(⋅, ⋅) that captures, e.g., an overhead cost. SOAD formalizes the open problem of combining general metrics and deadline constraints in the online algorithms literature, unifying problems such as metrical task systems and online search. We propose a competitive algorithm for SOAD along with a matching lower bound establishing its optimality. Our main algorithm, ST-CLIP, is a learning-augmented algorithm that takes advantage of predictions (e.g., forecasts of relevant costs) and achieves an optimal consistency-robustness trade-off. We evaluate our proposed algorithms in a simulated case study of carbon-aware spatiotemporal workload management, an application in sustainable computing that schedules a delay-tolerant batch compute job on a distributed network of data centers. In these experiments, we show that ST-CLIP substantially improves on heuristic baseline methods. 

The metastasis of solid tumors hinges on cancer cells navigating through complex three-dimensional tissue environments, characterized by mechanical heterogeneity and biological diversity. This process is closely linked to the dynamic migration behavior exhibited by cancer cells, which dictates the invasiveness of tumors. In our study, we investigate tumor spheroids composed of breast cancer cells embedded in three-dimensional (3D) collagen matrices. Through a combination of quantitative experiments, artificial-intelligence-driven image processing, and mathematical modeling, we uncover rapid transitions in cell phenotypes and phenotype-dependent motility among disseminating cells originating from tumor spheroids. Persistent invasion leads to continuous remodeling of the extracellular matrix surrounding the spheroids, altering the landscape of migration phenotypes. Consequently, filopodial cells emerge as the predominant phenotype across diverse extracellular matrix conditions. Our findings unveil the complex mesoscale dynamics of invading tumor spheroids, shedding light on the complex interplay between migration phenotype plasticity, microenvironment remodeling, and cell motility within 3D extracellular matrices. Published by the American Physical Society2024 

Abstract Point defects typically reduce the thermal conductivity (κ) of a crystal due to increased scattering of heat‐carrying phonons, a mechanism that is well understood and widely used to enhance or impede heat transfer in the material for different applications. Here an opposite effect is reported where the introduction of point defects in graphite with energetic particle irradiation increases its cross‐planeκby nearly a factor of two, from 10.8 to 18.9 W m K⁻¹at room temperature. Integrated differential phase contrast imaging with scanning transmission electron microscopy revealed the creation of spiro interstitials in graphite by the irradiation. The enhancement inκis attributed to a remarkable mechanism that works to the benefit of phonon propagation in both the harmonic and anharmonic terms: these spiro interstitial defects covalently bridge neighboring basal planes, simultaneously enhancing acoustic phonon group velocity and reducing phonon–phonon scattering in the graphite structure. The enhancement ofκreveals an unconventional role of lattice defects in heat conduction, i.e., easing the propagation of heat‐carrying phonons rather than impeding them in layered materials, inspiring their applications for thermal management in heavily radiative environments. 

Abstract A major subglacial lake, Lake Snow Eagle (LSE), was identified in East Antarctica by airborne geophysical surveys. LSE, contained within a subglacial canyon, likely hosts a valuable sediment record of the geological and glaciological changes of interior East Antarctica. Understanding past lake activity is crucial for interpreting this record. Here, we present the englacial radiostratigraphy in the LSE area mapped by airborne ice-penetrating radar, which reveals a localized high-amplitude variation in ice unit thickness that is estimated to be ∼12 ka old. Using an ice-flow model that simulates englacial stratigraphy, we investigate the origin of this feature and its relationship to changes in ice dynamical boundary conditions. Our results reveal that local snowfall redistribution initiated around the early Holocene is likely the primary cause, resulting from a short-wavelength (∼10 km) high-amplitude (∼20 m) ice surface slope variation caused by basal lubrication over a large subglacial lake. This finding indicates an increase in LSE water volume during the Holocene, illustrating the sensitivity in volume of a major topographically constrained subglacial lake across a single glacial cycle. This study demonstrates how englacial stratigraphy can provide valuable insight into subglacial hydrological changes before modern satellite observations, both for LSE and potentially at other locations.