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Cell tracking with accurate error prediction
Full text linkCell tracking is an indispensable tool for studying development by time-lapse imaging. However, existing cell trackers cannot assign confidence to predicted tracks, which prohibits fully automated analysis without manual curation. We present a fundamental advance: an algorithm that combines neural networks with statistical physics to determine cell tracks with error probabilities for each step in the track. From these, we can obtain error probabilities for any tracking feature, from cell cycles to lineage trees, that function like P values in data interpretation. Our method, OrganoidTracker 2.0, greatly speeds up tracking analysis by limiting manual curation to rare low-confidence tracking steps. Importantly, it also enables fully automated analysis by retaining only high-confidence track segments, which we demonstrate by analyzing cell cycles and differentiation events at scale for thousands of cells in multiple intestinal organoids. Our approach brings cell dynamics-based organoid screening within reach and enables transparent reporting of cell-tracking results and associated scientific claims
Multifunctional Fluidic Units for Emergent, Responsive Robotic Behaviors
Full text linkFluidic circuits have shown significant promise in enabling complex functionality in soft robots with a minimal number of input signals. However, implementing complex behaviors typically involves numerous specialized components, resulting in intricate and nonversatile circuits. To address this challenge, a multifunctional fluidic unit designed to operate flexibly as a valve, sensor, or actuator is introduced. This unit provides an extensive design space that allows precise tuning to achieve the desired functionality. In particular, one configuration integrates all three functions simultaneously, resulting in a self-sensing oscillating actuator. By assembling multiple units—each customized for specific roles—complex robotic behaviors can be realized. The versatility and effectiveness of this modular approach are demonstrated by creating several robotic systems, including a controlled shaker, a multimodal hopper, and a crawler capable of sensing environmental boundaries. Furthermore, when these units are mechanically coupled via a shared body, it exhibit emergent passive behaviors, such as self-synchronization—a behavior that is elucidated with a Kuramoto model of networks of oscillators. This study highlights the potential of multifunctionality as a powerful and efficient strategy for realizing embodied intelligence in fluidic robotic systems
General framework for signal processing in nonlinear mass-spring networks with application to keyword spotting
Full text linkMechanical systems played a foundational role in computing history, and have regained interest due to their unique properties, such as low damping and the ability to process mechanical signals without transduction. However, recent efforts have focused primarily on elementary computations, implemented in systems based on predefined reservoirs, or in periodic systems such as arrays of buckling beams. Here we numerically demonstrate a passive mechanical system—in the form of a nonlinear mass-spring model—that tackles a real-world benchmark for keyword spotting in speech signals. The model is organized in a hierarchical architecture combining feature extraction and continuous-time convolution, with each individual stage tailored to the physics of the mass-spring systems considered. For each step in the computation, a subsystem is designed by combining a small set of low-order polynomial potentials. These potentials act as fundamental components that interconnect a network of masses. In analogy to electronic circuit design, where complex functional circuits are constructed by combining basic components into hierarchical designs, we refer to this framework as “springtronics.” We introduce springtronic systems with hundreds of degrees of freedom, achieving speech classification accuracy comparable to that of existing submilliwatt electronic systems
A soft robotic total artificial hybrid heart
Full text linkEnd-stage heart failure is a deadly disease. Current total artificial hearts (TAHs) carry high mortality and morbidity and offer low quality of life. To overcome current biocompatibility issues, we propose the concept of a soft robotic, hybrid (pumping power comes from soft robotics, innerlining from the patient’s own cells) TAH. The device features a pneumatically driven actuator (septum) between two ventricles and is coated with supramolecular polymeric materials to promote anti-thrombotic and tissue engineering properties. In vitro, the Hybrid Heart pumps 5.7 L/min and mimics the native heart’s adaptive function. Proof-of-concept studies in rats and an acute goat model demonstrate the Hybrid Heart’s potential for clinical use and improved biocompatibility. This paper presents the first proof-of-concept of a soft, biocompatible TAH by providing a platform using soft robotics and tissue engineering to create new horizons in heart failure and transplantation medicine
Global regulators enable bacterial adaptation to a phenotypic trade-off
Full text linkCellular fitness depends on multiple phenotypes that must be balanced during evolutionary adaptation. For instance, coordinating growth and motility is critical for microbial colonization and cancer invasiveness. In bacteria, these phenotypes are controlled by local regulators that target single operons, as well as by global regulators that impact hundreds of genes. However, how the different levels of regulation interact during evolution is unclear. Here, we measured in Escherichia coli how CRISPR-mediated knockdowns of global and local transcription factors impact growth and motility in three environments. We found that local regulators mostly modulate motility, whereas global regulators jointly modulate growth and motility. Simulated evolutionary trajectories indicate that local regulators are typically altered first to improve motility before global regulators adjust growth and motility following their trade-off. These findings highlight the role of pleiotropic regulators in the adaptation of multiple phenotypes
Electroencephalography-driven brain-network models for personalized interpretation and prediction of neural oscillations
Full text linkObjective: Develop an encephalography (EEG)-driven method that integrates interpretability, predictiveness, and personalization to assess the dynamics of the brain network, with a focus on pathological conditions such as pharmacoresistant epilepsy. Methods: We propose a method to identify dominant coherent oscillations from EEG recordings. It relies on the Koopman operator theory to achieve individualized EEG prediction and electrophysiological interpretability. We extend it with concepts from adiabatic theory to address the nonstationary and noisy EEG signals. Results: By simultaneously capturing the local spectral and connectivity aspects of patient-specific oscillatory dynamics, we are able to clarify the underlying dynamical mechanism. We use it to construct the corresponding generative models of the brain network. We demonstrate the proposed approach on recordings of patients in status epilepticus. Conclusions: The proposed EEG-driven method opens new perspectives on integrating interpretability, predictiveness, and personalization within a unified framework. It provides a quantitative approach for assessing EEG recordings, crucial for understanding and modulating pathological brain activity. Significance: This work bridges theoretical neuroscience and clinical practice, offering a novel framework for understanding and predicting brain network dynamics. The resulting approach paves the way for data-driven insights into brain network mechanisms and the design of personalized neuromodulation therapies
A single-phonon directional coupler
Full text linkIntegrated photonics has revolutionized fields such as telecommunications, quantum optics, and metrology by enabling compact, scalable circuits through highly confined optical modes. Within the field of quantum acoustics, phonons have emerged as a compelling alternative, offering advantages such as lower energy, smaller mode volume, and low propagation speeds, which make them ideal for interfacing diverse quantum systems. Developing integrated phononic circuits is thus essential for unlocking the full potential of quantum acoustics and advancing technologies such as quantum computing and hybrid systems. In this work, we demonstrate the first 4-port directional coupler for quantum mechanical excitations—a key building block for phononic circuits. By tuning the coupling region length, we achieve phononic beam splitters with controllable splitting ratios. We validate quantum-level performance by sending a single-phonon Fock state through the device. This work represents a foundational advance toward scalable, integrated phononic platforms for both classical and quantum applications
Early onset of snapping of slender beams under transverse forcing
No full textThe hysteretic snapping under transverse forcing of a compressed, buckled beam is fundamental for many devices and mechanical metamaterials. For a single-tip transverse pusher, an important limitation is that snapping requires the pusher to cross the longitudinal axis of the beam. Here, we show that dual-tip pushers allow early-onset snapping, where the beam snaps before the pusher reaches the longitudinal axis. As a consequence, we show that when a buckled beam under increased compression comes in contact with a dual-tip pusher, it can snap to the opposite direction — this is impossible with a single-tip pusher. Additionally, we reveal a novel two-step snapping regime, in which the beam sequentially loses contact with the two tips of the dual-tip pusher. To characterize this class of snapping instabilities, we employ a systematic modal expansion of the beam shape. This expansion allows us to capture and analyze the transition from one-step to two-step snapping geometrically. Finally we demonstrate how to maximize the distance between the pusher and the beam’s longitudinal axis at the moment of snapping. Together, our work opens up a new avenue for quantitatively and qualitatively controlling and modifying the snapping of buckled beams, with potential applications in mechanical sensors, actuators, and metamaterials
Chemostructurally Stable Polyionomer Coatings Regulate Proton-Intermediate Landscape in Acidic CO2 Electrolysis
Full text linkCO2 electroreduction (CO2R) in acidic media offers a path to high carbon utilization via local carbonate regeneration. However, this proton-rich environment challenges achieving a combined selectivity and rate toward multicarbon (C2+) products due to proton and intermediate competition. Here, we demonstrate a strategy to modulate local protons and intermediates, at these settings, using a polyionomer coating over benchmark copper gas diffusion electrodes. The polyionomer integrates amine (−NHx) function from branched polyethylenimine (PEI) with sulfonate (−SO3–) and amphiphilic functions from PFSA. We show that their chemical structure enables H-bonding interaction, leading to a stereochemical assembly that retains a structure–property relationship through a wide pH range (2–14). PFSA domains modulate *CO intermediates and local [CO2]/[H2O] and K+ environment, while partially protonated amines provide further control over proton availability and intermediate stabilization, which in combination enhance C–C coupling. When implemented in a flow cell (0.5 M K2/H2SO4, pH = 2), the optimized polyionomer coating enables a C2+ Faradaic efficiency of 61% at a single-pass CO2 utilization of 84%, including a conversion efficiency of 64% toward C2+, at a current density of at 0.3 A cm–2─an improvement of almost 30% in C2+ selectivity and 35% in carbon utilization compared to monofunctional coatings. These findings expand the toolbox of strategies to modulate CO2R microenvironments toward improved performance
Co-translational ribosome pairing enables native assembly of misfolding-prone subunits
Full text linkProtein complexes are pivotal to most cellular processes. Emerging evidence indicating dimer assembly by pairs of ribosomes suggests yet unknown folding mechanisms involving two nascent chains. Here, we show that co-translational ribosome pairing allows their nascent chains to ‘chaperone each other’, thus enabling the formation of coiled-coil homodimers from subunits that misfold individually. We developed an integrated single-molecule fluorescence and force spectroscopy approach to probe the folding and assembly of two nascent chains extending from nearby ribosomes, using the intermediate filament lamin as a model system. Ribosome proximity during early translation stages is found to be critical: when interactions between nascent chains are inhibited or delayed, they become trapped in stable misfolded states that are no longer assembly-competent. Conversely, early interactions allow the two nascent chains to nucleate native-like quaternary structures that grow in size and stability as translation advances. We conjecture that protein folding mechanisms enabled by ribosome cooperation are more broadly relevant to intermediate filaments and other protein classes