Biology subjects

Suh, B.

Publications and source records attributed to Suh, B..

4 recordsLinked to original sources

bioRxiv2026

Inherent Biomechanical Properties of the Lung: In vivo-Ex vivo Comparisons in Mice

Mammalian lungs operate within a thoracic "cage" composed of parietal pleura, rib cage, skeletal muscle, and diaphragm, yet clinical ventilator metrics largely reflect the combined mechanics of lung and surrounding structures and the thoracic cage. We hypothesized that thoracic boundary conditions selectively alter measured lung biomechanics. We performed paired pulmonary function testing (FlexiVent) in C57BL6 mice of both sexes spanning development through adulthood, measuring quasi-static pressure-volume behavior and dynamic forced-oscillation parameters in vivo (supine, mechanically ventilated) and again ex vivo in the same lungs. In a subset, we additionally compared in vivo and ex vivo {micro}CT-derived lung volumes, including a pressure-fixed ex vivo protocol using snap freezing at controlled inflation pressure. Quasi-static pressure-volume curves were similar between conditions, with near-identity at higher pressures and only modest divergence at low pressures, consistent with thoracic structures primarily modulating recruitment/de-recruitment rather than intrinsic elastic recoil. Maximal volume at 30 cmH2O showed strong in vivo-ex vivo correlation and minimal bias, and static compliance and PV-loop hysteresis exhibited small biases relative to reported disease-model effect sizes. In contrast, dynamic mechanics demonstrated a clear in vivo elevation of tissue damping (G) with only modest change in tissue elastance (H) and little change in Newtonian resistance (Rn), producing a meaningful increase in hysteresivity ( = G/H). This dissociation implicates frequency-dependent mechanical heterogeneity (e.g., time-constant mismatch/pendelluft) imposed or amplified by nonuniform thoracic loading. Ex vivo {micro}CT enabled reliable whole-lung segmentation and correlated with ex vivo PFT volumes at matched pressures, whereas in vivo volumetry showed weaker agreement. These results indicate that thoracic structures contribute modest restriction but disproportionately increase dynamic dissipation and heterogeneity, suggesting that ex vivo functional testing and oscillometry-like metrics may better detect biomechanical changes inherent to lung parenchyma.

physiology↗

bioRxiv2026

Repeated experience drives multiscale engram reorganization to shape memory strength and precision

How memories are shaped by repeated experiences remains unclear. Reorganization of memory engram could underlie memory transformation. Here, by combining c-Fos-based engram cell tagging with optogenetics, spine imaging, and reactivation analyses in the dentate gyrus (DG) and medial prefrontal cortex (mPFC), we discovered a distinct system-wide engram reorganization following repeated learning; that is, a reshuffling of engram cells in the DG, as well as the rapid maturation of mPFC engram cells, forming a dual engram distributed within the hippocampal-mPFC network. These mPFC engram cells were crucial for relearning-dependent enhancement of memory precision. In addition, we found that reactivation of DG engram cells during retraining is critical for engram reorganization-dependent memory strengthening. These findings establish a causal link between engram reorganization and memory transformation by relearning.

neuroscience↗

bioRxiv2025

The graphene-based affinity cryo-EM grid for the endogenous protein structure determination

Following recent advancements in cryo-electron microscopy (cryo-EM) instrumentation and software algorithms, the next bottleneck in achieving high-resolution cryo-EM structures arises from sample preparation. To overcome this, we developed a graphene-based affinity cryo-EM grid, the Graffendor (GFD) grid, to target low-abundance endogenous protein complexes. To maintain grid quality and consistency within a single batch of 36 grids, we established a one-step crosslinking batch-production method using genetically modified ALFA nanobody as affinity probe (GFD-A grid). Using low concentrations of {beta}-galactosidase-2xALFA, we demonstrated the GFD-A grids efficiency in capturing tagged proteins and resolving its cryo-EM structure at 2.71 [A]. To test its application for endogenous proteins, we engineered yeast cells with a C-terminal tandem affinity tag (3xALFA-Tev-3xFlag: ATF) at Pop6, a shared component of RNase MRP and RNase P. Cryo-EM structures of RNase MRP and RNase P were resolved at 3.3 [A] and 3.0 [A] from cell lysates, and 3.6 [A] and 3.9 [A] from anti-flag elution, respectively. Notably, additional densities were observed in the structures obtained from cell lysates, which were absent in those from the anti-FLAG eluate. These findings establish the GFD-A grid as a robust platform for investigating endogenous proteins, capable of capturing transient interactions and enhancing the resolution of challenging cryo-EM structures with greater efficiency.

biochemistry↗

bioRxiv2024

A top-down insular cortex circuit crucial for non-nociceptive fear learning

Understanding how threats drive fear memory formation is crucial to understanding how organisms adapt to environments and treat threat-related disorders like PTSD. While traditional Pavlovian conditioning studies have provided valuable insights, the exclusive reliance on electric shock as a threat stimulus has limited our understanding of diverse threats. To address this, we developed a conditioning paradigm using a looming visual stimulus as an unconditioned stimulus (US) in mice and identified a distinct neural circuit for visual threat conditioning. Parabrachial CGRP neurons were necessary for both conditioning and memory retrieval. Upstream neurons in the posterior insular cortex (pIC) responded to looming stimuli, and their projections to the parabrachial nucleus (PBN) induced aversive states and drove conditioning. However, this pIC-to-PBN pathway was not required for foot-shock conditioning. These findings reveal how non-nociceptive visual stimuli can drive aversive states and fear memory formation, expanding our understanding of aversive US processing beyond traditional models.

neuroscience↗