Biology subjects

Cheon, J.

Publications and source records attributed to Cheon, J..

7 recordsLinked to original sources

bioRxiv2025

MechanoMR microparticle (M3) sensors reveal dynamic stress loading as a driver of epithelial-mesenchymal transition

The dynamic mechanical response of tissues underlies their physiological function, yet direct, quantitative measurement of tissue stress in vivo has remained a major challenge. Here, we introduce the mechanoMR microparticle (M3, "M-cube") sensor, a hybrid soft-matter/nanoparticle probe that integrates directly into tissue mechanical networks while transducing local stress into quantitative magnetic resonance (MR) readouts with single-particle resolution. We demonstrate the utility of this platform across diverse model systems, including tumor spheroids, Xenopus embryos, and mouse xenografts, where the M3 sensor enables noninvasive, spatiotemporally resolved mapping of tissue stress dynamics during cancer development. Using this approach, we reveal that epithelial-mesenchymal transition (EMT) is accompanied by distinctive stress-remodeling patterns observable in vivo. Strikingly, we find that abrupt stress increases, rather than cumulative or peak stress magnitude, are the key determinants of EMT induction in cancer cells within the tumor microenvironment. Transcriptomic profiling under controlled stress-loading dynamics shows that sustained yet gradual stress escalation activates cytoprotective antioxidation pathways (e.g., FOXO/AMPK) that reinforce epithelial stability, whereas acute stress surges overwhelm these defense mechanisms, predisposing cells toward mesenchymal reprogramming. These findings establish the M3 sensor as a broadly applicable technology for linking dynamic mechanical cues to cell-state transitions in development, homeostasis, and disease.

bioengineering↗

bioRxiv2025

Gradual sensory maturation promotes abstract representation learning

Human infants begin life with limited visual capacities, such as low acuity and poor color sensitivity, due to gradual sensory maturation. In contrast, machine learning models are trained on high-fidelity inputs from the outset, often leading to shortcut learning and overfitting to spurious correlations. Here, we show that early sensory immaturity plays a critical role in shaping bias-resistant, abstract visual representations that conventional models struggle to develop. Using neural network simulations and human psychophysics experiments, we demonstrate that gradual sensory development supports the emergence of robust and generalizable internal representations, reduces reliance on superficial cues, and promotes disentangled representations that enable compositional reconstruction and visual imagination. Comparative analyses of human and model behavior reveal shared patterns of bias resistance and adaptive generalization, including resilience to misleading information. Our findings suggest that gradual sensory maturation is not merely a developmental constraint, but rather a key mechanism that enables abstract representation learning. One sentence summaryEarly-stage sensory immaturity guides the development of abstract, bias-resistant representations that enable generalization and compositionality, providing a functional account of gradual sensory maturation. HighlightsO_LIThe essential yet overlooked role of gradual sensory maturation was explored C_LIO_LIEarly sensory immaturity promotes abstract representations resistant to shortcut learning C_LIO_LIEmergent representations support compositional reconstruction of novel visual attributes C_LIO_LIHuman and model behaviors show similar bias resistance and adaptive generalization C_LI

neuroscience↗

bioRxiv2024

Self-Assembled Origami Neural Probes for Scalable, Multifunctional, Three-Dimensional Neural Interface

Flexible intracortical neural probes have drawn attention for their enhanced longevity in high-resolution neural recordings due to reduced tissue reaction. However, the conventional monolithic fabrication approach has met significant challenges in: (i) scaling the number of recording sites for electrophysiology; (ii) integrating of other physiological sensing and modulation; and (iii) configuring into three-dimensional (3D) shapes for multi-sided electrode arrays. We report an innovative self-assembly technology that allows for implementing flexible origami neural probes as an effective alternative to overcome these challenges. By using magnetic-field-assisted hybrid self-assembly, multiple probes with various modalities can be stacked on top of each other with precise alignment. Using this approach, we demonstrated a multifunctional device with scalable high-density recording sites, dopamine sensors and a temperature sensor integrated on a single flexible probe. Simultaneous large-scale, high-spatial-resolution electrophysiology was demonstrated along with local temperature sensing and dopamine concentration monitoring. A high-density 3D origami probe was assembled by wrapping planar probes around a thin fiber in a diameter of 80[~]105 m using optimal foldable design and capillary force. Directional optogenetic modulation could be achieved with illumination from the neuron-sized micro-LEDs (LEDs) integrated on the surface of 3D origami probes. We could identify angular heterogeneous single-unit signals and neural connectivity 360{degrees} surrounding the probe. The probe longevity was validated by chronic recordings of 64-channel stacked probes in behaving mice for up to 140 days. With the modular, customizable assembly technologies presented, we demonstrated a novel and highly flexible solution to accommodate multifunctional integration, channel scaling, and 3D array configuration.

neuroscience↗

bioRxiv2023

Synthetic lipid rafts formed by cholesterol nano-patch induce T cell activation

Lipid rafts cluster at the immunological synapse during activation and serve as signaling hubs in T cells. While cholesterol plays a crucial role in lipid raft formation, the impact of their spatial configuration remains less understood. Here, we introduce programmable DNA origami, cholesterol nano-patch, for nanoscale spatial control of cholesterols on live T cell membranes, enabling us to elucidate their roles in lipid raft formation, receptor activation, and intracellular signaling. We demonstrate that CNPs with high-density cholesterol arrangements efficiently bind to the T cell plasma membrane and form a large and polarized coalescence, leading to the stabilization of ordered lipid membrane domains by increasing the local concentration of cholesterols. These synthetic lipid rafts colocalize with flotillin-1, a raft-associated protein, and promote the membrane reorganization and physical segregation of key signaling molecules, such as T cell receptors, Lck and LAT kinases, and CD45. Consequently, this leads to early T cell activation in the absence of antigenic stimulation. Our DNA origami approach demonstrates the direct role of cholesterol in lipid raft formation, leading to membrane phase separation and protein reorganization, which are sufficient to induce early T cell activation.

bioengineering↗

bioRxiv2022

Invariance of object detection in untrained deep neural networks

The ability to perceive visual objects with various types of transformations, such as rotation, translation, and scaling, is crucial for consistent object recognition. In machine learning, invariant object detection for a network is often implemented by augmentation with a massive number of training images, but the mechanism of invariant object detection in biological brains -- how invariance arises initially and whether it requires visual experience -- remains elusive. Here, using a model neural network of the hierarchical visual pathway of the brain, we show that invariance of object detection can emerge spontaneously in the complete absence of learning. First, we found that units selective to a particular object class arise in randomly initialized networks even before visual training. Intriguingly, these units show robust tuning to images of each object class under a wide range of image transformation types, such as viewpoint rotation. We confirmed that this "innate" invariance of object selectivity enables untrained networks to perform an object-detection task robustly, even with images that have been significantly modulated. Our computational model predicts that invariant object tuning originates from combinations of non-invariant units via random feedforward projections, and we confirmed that the predicted profile of feedforward projections is observed in untrained networks. Our results suggest that invariance of object detection is an innate characteristic that can emerge spontaneously in random feedforward networks. HighlightsO_LIObject-selective units spontaneously emerge in untrained deep neural networks C_LIO_LIObject selectivity maintains robustly in a wide range of image transformations C_LIO_LIFeedforward model can explain spontaneous emergence of the invariance C_LIO_LIInnate invariance enables invariant object detection without learning to variations C_LI

neuroscience↗

bioRxiv2022

Magneto-acoustic protein nanostructures for non-invasive imaging of tissue mechanics in vivo

Measuring cellular and tissue mechanics inside intact living organisms is essential for interrogating the roles of force in physiological and disease processes, and is a major goal in the field of mechanobiology. However, existing biosensors for 3D tissue mechanics, primarily based on fluorescent emissions and deformable materials, are limited for in vivo measurement due to the limited light penetration and poor material stability inside intact, living organisms. While magneto-motive ultrasound (MMUS), which uses superparamagnetic nanoparticles as imaging contrast agents, has emerged as a promising modality for real-time in vivo imaging of tissue mechanics, it has poor sensitivity and spatiotemporal resolution. To overcome these limitations, we introduce magneto-gas vesicles (MGVs), a unique class of protein nanostructures based on gas vesicles and magnetic nanoparticles that produces differential ultrasound signals in response to varying mechanical properties of surrounding tissues. These hybrid protein nanostructures significantly improve signal strength and detection sensitivity. Furthermore, MGVs enable non-invasive, long-term, and quantitative measurement of mechanical properties within 3D tissues and organs in vivo. We demonstrated the performance of MGV-based mechano-sensors in vitro, in fibrosis models of organoids, and in vivo in mouse liver fibrosis models.

biochemistry↗

bioRxiv2020

Size-dependent protein segregation creates a spatial switch for Notch and APP signaling

Aberrant cleavage of Notch by {gamma}-secretase is implicated in numerous diseases, but how cleavage is regulated in space and time is unclear. Here, we report that cadherin-based adherens junctions (cadAJs) are sites of high cell-surface {gamma}-secretase activity, as well as sites of constrained physical space that excludes {gamma}-secretase substrates having large extracellular domains (ECDs) like Notch. ECD shedding initiates drastic spatial relocalization of Notch to cadAJs, allowing enzyme-substrate interactions and downstream signaling. Spatial mutations by adjusting the ECD size or the physical constraint alter signaling. Dysregulation of this spatial switch promotes precocious differentiation of ventricular zone neural progenitor cells in vivo. We show the generality of this spatial switch for amyloid precursor protein proteolysis. Thus, cadAJs create spatially distinct biochemical compartments regulating cleavage events involving {gamma}-secretase and preventing aberrant activation of receptors. One Sentence SummaryNotch cleavage by {gamma}-secretase is regulated through dynamic spatial control of receptors, adhesion molecules, and activating proteases

cell biology↗