{"id":3132,"date":"2023-01-18T17:18:06","date_gmt":"2023-01-18T23:18:06","guid":{"rendered":"https:\/\/kermitmurray.com\/msblog\/?page_id=3132"},"modified":"2023-01-18T17:18:06","modified_gmt":"2023-01-18T23:18:06","slug":"biorxiv-biophysics","status":"publish","type":"page","link":"https:\/\/kermitmurray.com\/msblog\/links\/journal-feeds\/biochemistry-journal-feeds\/biorxiv\/biorxiv-biophysics\/","title":{"rendered":"BioRxiv Biophysics"},"content":{"rendered":"\n<div class=\"wp-block-caxton-grid relative\"><div class=\"absolute absolute--fill\"><div class=\"absolute absolute--fill cover bg-center\" style=\"background-color:;background-image:linear-gradient( );\"><\/div><div class=\"absolute absolute--fill\" style=\"background-color:;background-image:linear-gradient( );opacity:1;\"><\/div><\/div><div class=\"relative caxton-columns caxton-grid-block\" style=\"padding-top:0;padding-left:0;padding-bottom:0;padding-right:0;grid-template-columns:repeat(12, 1fr)\" data-tablet-css=\"padding-left:em;padding-right:em;\" data-mobile-css=\"padding-left:em;padding-right:em;\">\n<div class=\"wp-block-caxton-section relative\" style=\"grid-area:span 1\/span 8\"><div class=\"absolute absolute--fill\"><div class=\"absolute absolute--fill cover bg-center\" style=\"background-color:;background-image:linear-gradient( );\"><\/div><div class=\"absolute absolute--fill\" style=\"background-color:;background-image:linear-gradient( );opacity:1;\"><\/div><\/div><div class=\"relative caxton-section-block\" style=\"padding-top:5px;padding-left:5px;padding-bottom:5px;padding-right:5px\" data-mobile-css=\"padding-left:1em;padding-right:1em;\" data-tablet-css=\"padding-left:1em;padding-right:1em;\">\n<p><strong><a href=\"https:\/\/www.biorxiv.org\/alertsrss\" target=\"_blank\" rel=\"noreferrer noopener\">Journal Home<\/a><\/strong><\/p>\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-caxton-section relative\" style=\"grid-area:span 1\/span 4\"><div class=\"absolute absolute--fill\"><div class=\"absolute absolute--fill cover bg-center\" style=\"background-color:;background-image:linear-gradient( );\"><\/div><div class=\"absolute absolute--fill\" style=\"background-color:;background-image:linear-gradient( );opacity:1;\"><\/div><\/div><div class=\"relative caxton-section-block\" style=\"padding-top:5px;padding-left:5px;padding-bottom:5px;padding-right:5px\" data-mobile-css=\"padding-left:1em;padding-right:1em;\" data-tablet-css=\"padding-left:1em;padding-right:1em;\">\n<p><strong><a href=\"http:\/\/connect.biorxiv.org\/biorxiv_xml.php?subject=Biophysics\" target=\"_blank\" rel=\"noreferrer noopener\">RSS<\/a><\/strong><\/p>\n<\/div><\/div>\n<\/div><\/div>\n\n\n<ul class=\"has-dates has-authors has-excerpts wp-block-rss\"><li class='wp-block-rss__item'><div class='wp-block-rss__item-title'><a href='https:\/\/www.biorxiv.org\/content\/10.64898\/2026.06.18.733180v1?rss=1'>Cell division dynamics generate heterogeneous contact-mediated signaling outputs<\/a><\/div><time datetime=\"2026-06-22T00:00:00-05:00\" class=\"wp-block-rss__item-publish-date\">June 22, 2026<\/time> <span class=\"wp-block-rss__item-author\">by Dawson, J. E., Malmi-Kakkada, A. N.<\/span><div class=\"wp-block-rss__item-excerpt\">Contact mediated cell-cell communication where direct physical contact between adjacent ligand cells and receptor cells trigger signal output is important during growth, development and regeneration of organisms. While the molecular machinery underlying contact mediated cell signaling is well explored, how the local spatial context of cells affect cell-cell contact mediated gene expression is not clear. Here, we present a vertex-based computational model to study spatial and temporal behavior of contact mediated signal output (which we refer to as output) in [&hellip;]<\/div><\/li><li class='wp-block-rss__item'><div class='wp-block-rss__item-title'><a href='https:\/\/www.biorxiv.org\/content\/10.64898\/2026.06.18.733270v1?rss=1'>The Dilated Cardiomyopathy E525K \u03b2-Myosin Mutation Causes Hypocontractility in Cardiomyocytes Without Altering Crossbridge Cycling<\/a><\/div><time datetime=\"2026-06-22T00:00:00-05:00\" class=\"wp-block-rss__item-publish-date\">June 22, 2026<\/time> <span class=\"wp-block-rss__item-author\">by Robeson, K. Z., McMillen, T. S., Cooiker, K., Kao, K. Y., Frebis, K., Geeves, M. A., Wescott, A. P., Soriano, R., Goldstein, A. J., Childers, M. C., Goluguri, R. R., Pathak, D., Sniadecki, N. J., Powers, J. D., Davis, J., Moussavi-Harami, F., Spudich, J. A., Ruppel, K. M., Regnier, M.<\/span><div class=\"wp-block-rss__item-excerpt\">The {beta}-cardiac myosin (MYH7) mutation E525K was first identified in 2012 in a patient with dilated cardiomyopathy (DCM). Work using engineered myosin constructs has shown that this mutation causes hypocontractility by stabilizing the interacting heads motif (IHM) of myosin despite the mutant E525K motor head exhibiting increased ATPase activity. However, no measurements have been made in myofilaments or cardiomyocytes to determine how this mutation affects contractile function. Here, we present force and contractile kinetics measurements from induced pluripotent stem cell [&hellip;]<\/div><\/li><li class='wp-block-rss__item'><div class='wp-block-rss__item-title'><a href='https:\/\/www.biorxiv.org\/content\/10.64898\/2026.06.17.732986v1?rss=1'>Mechanical tension expands the microtubule lattice stepwise and modulates kinesin-1 binding in an isoform-dependent manner<\/a><\/div><time datetime=\"2026-06-22T00:00:00-05:00\" class=\"wp-block-rss__item-publish-date\">June 22, 2026<\/time> <span class=\"wp-block-rss__item-author\">by Lurz, Y., Fischer, B. S. J., Mishra, J., Muras, L., Schaeffer, E., Ostap, E. M., Mohd Rafiq, N., Kulic, I., Pyrpassopoulos, S.<\/span><div class=\"wp-block-rss__item-excerpt\">Recent work has shown that the microtubule lattice possesses remarkable structural plasticity, with its conformation modulated by microtubule-associated proteins and motor proteins. However, how this plasticity responds to mechanical forces remains poorly understood. Here, we developed optical tweezers and fluorescence microscopy assays to measure the effect of tensile forces on single microtubules. Quantum dot decoration enabled nanometre-precision measurement of lattice distortions of ~0.33% under a change of mean tensile force = 10.6 pN, within the range of Fmin = 1.29 [&hellip;]<\/div><\/li><li class='wp-block-rss__item'><div class='wp-block-rss__item-title'><a href='https:\/\/www.biorxiv.org\/content\/10.64898\/2026.06.17.732968v1?rss=1'>Buzzing Frequency Influences Pollen Release in Buzz-Pollinated Poricidal Anthers<\/a><\/div><time datetime=\"2026-06-22T00:00:00-05:00\" class=\"wp-block-rss__item-publish-date\">June 22, 2026<\/time> <span class=\"wp-block-rss__item-author\">by Alvord, M., Cote, B., Morris, S., Jankauski, M.<\/span><div class=\"wp-block-rss__item-excerpt\">Buzz pollination is an important behavior in which bees use vibrations to extract pollen from poricidal anthers. However, the extent to which vibration frequency influences pollen release remains unclear. Here, we quantified pollen expulsion from Solanum sisymbriifolium anthers subjected to harmonic excitation over a broad frequency range encompassing the anther&#039;s first natural frequency. We excited anthers to expel pollen and measured anther kinematics and pollen release using high-speed videography. Particle tracking enabled continuous estimation of pollen release throughout each buzzing [&hellip;]<\/div><\/li><li class='wp-block-rss__item'><div class='wp-block-rss__item-title'><a href='https:\/\/www.biorxiv.org\/content\/10.64898\/2026.06.17.732958v1?rss=1'>LTP-patterned electromagnetic stimulation induces NMDA receptor-dependent synaptic plasticity in cortical networks<\/a><\/div><time datetime=\"2026-06-22T00:00:00-05:00\" class=\"wp-block-rss__item-publish-date\">June 22, 2026<\/time> <span class=\"wp-block-rss__item-author\">by Kansala, C., St.Jean, J., Nkansah-Okoree, V., Rouleau, N., Murugan, N. J.<\/span><div class=\"wp-block-rss__item-excerpt\">Bioinspired electromagnetic stimulation, in which fields are patterned after endogenous neural activity, have emerged as a potential non-invasive approach for modulating brain dynamics, yet the waveform parameters that determine biological specificity remain poorly defined. Complex electromagnetic patterns modeled after long-term potentiation (LTP) have been reported to alter learning and cortical injury outcomes in vivo, yet whether these fields engage cell-scale synaptic plasticity mechanisms remains unclear. Here, we show that a microtesla-strength electromagnetic field (EMF) patterned after electrophysiological signatures of long-term [&hellip;]<\/div><\/li><li class='wp-block-rss__item'><div class='wp-block-rss__item-title'><a href='https:\/\/www.biorxiv.org\/content\/10.64898\/2026.06.21.733238v1?rss=1'>Single-molecule insights into DNA gyrase in live bacteria<\/a><\/div><time datetime=\"2026-06-22T00:00:00-05:00\" class=\"wp-block-rss__item-publish-date\">June 22, 2026<\/time> <span class=\"wp-block-rss__item-author\">by Syeda, A. H., Leek, V. A., Maxwell, A., Leake, M. C.<\/span><div class=\"wp-block-rss__item-excerpt\">Molecular motors travelling along DNA introduce positive supercoils that present as barriers to replication leading to genome instability. To counter these, bacterial cells express DNA gyrase, a topoisomerase that introduces negative supercoils. While much is known about DNA gyrase from genetic and in vitro biochemical studies, the spatiotemporal dynamics of this enzyme remain a mystery. Only recently have we been able to observe the in vivo spatiotemporal dynamics down to single molecule level using advanced super-resolution microscopy techniques. We used [&hellip;]<\/div><\/li><li class='wp-block-rss__item'><div class='wp-block-rss__item-title'><a href='https:\/\/www.biorxiv.org\/content\/10.64898\/2026.06.20.733545v1?rss=1'>Simulation of cell-size systems at long timescales with flexible protein structures<\/a><\/div><time datetime=\"2026-06-22T00:00:00-05:00\" class=\"wp-block-rss__item-publish-date\">June 22, 2026<\/time> <span class=\"wp-block-rss__item-author\">by Yunas, K., Singh, A., Copeland, M. M., Tytarenko, A. M., Kundrotas, P. J., Halfmann, R., Kasyanov, P. O., Feinberg, E. A., Vakser, I. A.<\/span><div class=\"wp-block-rss__item-excerpt\">Protein behavior inside cells is dominated by the crowded nature of the intracellular environment. Progress in structure determination of proteins and protein complexes, based on advances in Artificial Intelligence, provides an opportunity for structure-based modeling of cellular phenomena. Such modeling at the atomic resolution has been advanced by the traditional simulation techniques, e.g. molecular dynamics. A recently developed docking-based approach implements Markov Chain Monte Carlo sampling of intermolecular energy landscapes, offering several orders of magnitude faster simulation protocols. The approach [&hellip;]<\/div><\/li><li class='wp-block-rss__item'><div class='wp-block-rss__item-title'><a href='https:\/\/www.biorxiv.org\/content\/10.64898\/2026.06.17.732700v1?rss=1'>BioBrain: A Multi-Agent Framework for Natural Language Driven Quantitative Microscopy Data Analysis<\/a><\/div><time datetime=\"2026-06-21T00:00:00-05:00\" class=\"wp-block-rss__item-publish-date\">June 21, 2026<\/time> <span class=\"wp-block-rss__item-author\">by Tsolakidis, K., Breuer, A., Bender, S. W. B., Margaritaki, S., Dreisler, M. W., Oikonomou, A., Hatzakis, N. S.<\/span><div class=\"wp-block-rss__item-excerpt\">Advances in fluorescence microscopy have dramatically expanded the range of biological questions that can be addressed, enabling quantitative observations of molecular interactions and cellular dynamics with unprecedented spatial and temporal resolution. However, the growing complexity of imaging data has outpaced our ability to analyze them. Despite numerous computational methods exist, they often rely on specialized software environments, heterogeneous data formats, and technical expertise, limiting adoption and widening the gap between data acquisition and quantitative biological interpretation. Here we introduce BioBrain, [&hellip;]<\/div><\/li><li class='wp-block-rss__item'><div class='wp-block-rss__item-title'><a href='https:\/\/www.biorxiv.org\/content\/10.64898\/2026.06.17.732910v1?rss=1'>Revealing interactions between glutathione peroxidase 4 and phosphoinositides<\/a><\/div><time datetime=\"2026-06-21T00:00:00-05:00\" class=\"wp-block-rss__item-publish-date\">June 21, 2026<\/time> <span class=\"wp-block-rss__item-author\">by Walters, S. H., Park, B., Labrecque, C. L., Musayev, F. N., Van Lehn, R. C., Fuglestad, B.<\/span><div class=\"wp-block-rss__item-excerpt\">Glutathione peroxidase 4 (GPx4) is the primary enzyme reducing lipid hydroperoxides, preventing membrane oxidative damage and protecting against ferroptosis. GPx4 is known to engage with lipid headgroups through electrostatic interactions, positioning the substrate for reduction. This work reveals and characterizes binding of highly anionic phosphoinositides (PIP lipids) by GPx4. PIPs are vital lipids in human cells and are central to many signaling processes, particularly in cytosolic facing membranes. Lipid overlay assays confirm interactions between GPx4 and phosphorylated PIPs, comparable to [&hellip;]<\/div><\/li><li class='wp-block-rss__item'><div class='wp-block-rss__item-title'><a href='https:\/\/www.biorxiv.org\/content\/10.64898\/2026.06.17.733030v1?rss=1'>Artificial Intelligence Models for Classifying Wrist Ligament Injuries Using Synthetically-Generated Joint Proximity Maps from Finite Element Models<\/a><\/div><time datetime=\"2026-06-21T00:00:00-05:00\" class=\"wp-block-rss__item-publish-date\">June 21, 2026<\/time> <span class=\"wp-block-rss__item-author\">by Chen, H.-Y., Camp, J., Trentadue, T. P., Thoreson, A. R., Leng, S., Holmes, D. R., Kakar, S., An, K.-N., Zhao, K. D., Andreassen, T. E.<\/span><div class=\"wp-block-rss__item-excerpt\">Background\/Purpose: Diagnosing wrist ligament injuries is challenging; early detection and treatment are important to prevent osteoarthritis progression. Interosseous proximity maps, a proxy measure for joint space, can be generated from volumetric imaging data and may provide important information about wrist health. Artificial intelligence (AI) could enhance accuracy of noninvasive diagnosis based on imaging-derived metrics. This work demonstrates feasibility of AI training using synthetic proximity map data generated from finite element models (FEMs). Methods: Personalized wrist FEMs for two asymptomatic participants [&hellip;]<\/div><\/li><li class='wp-block-rss__item'><div class='wp-block-rss__item-title'><a href='https:\/\/www.biorxiv.org\/content\/10.64898\/2026.06.16.732593v1?rss=1'>Mechanical Checkpoint for Cell Division in Three-Dimensional Microenvironments<\/a><\/div><time datetime=\"2026-06-21T00:00:00-05:00\" class=\"wp-block-rss__item-publish-date\">June 21, 2026<\/time> <span class=\"wp-block-rss__item-author\">by Rabbi, M. F., Yim, D., Boyd, M., Nam, S., Chaudhuri, O., Kim, T.<\/span><div class=\"wp-block-rss__item-excerpt\">Cell division within mechanically confining extracellular matrices (ECMs) is a key regulator of tissue morphogenesis and cancer progression. Although the intracellular force generation mechanisms that drive volumetric growth and mitotic elongation are well characterized, how ECMs resist these forces remains poorly understood. Unlike linearly elastic materials, fibrillar ECMs exhibit nonlinear and viscoelastic behaviors that fundamentally alter how they oppose cell generated stresses. Using a fiber level computational model, we dissected the origins of ECM mediated mechanical confinement during mitosis. We [&hellip;]<\/div><\/li><li class='wp-block-rss__item'><div class='wp-block-rss__item-title'><a href='https:\/\/www.biorxiv.org\/content\/10.64898\/2026.06.21.733446v1?rss=1'>Live-cell imaging of enhancer-promoter dynamics reveals transient contact-driven gene activation<\/a><\/div><time datetime=\"2026-06-21T00:00:00-05:00\" class=\"wp-block-rss__item-publish-date\">June 21, 2026<\/time> <span class=\"wp-block-rss__item-author\">by Yang, J. H., Pinholt, H. D., Toppen, J., Huseyin, M. K., Jusuf, J. M., Katsifis, C. C., Kaestel-Hansen, J., Mirny, L. A., Zechner, C., Hansen, A. S.<\/span><div class=\"wp-block-rss__item-excerpt\">Enhancers are key regulators of mammalian gene expression, yet how they interact with promoters in space (contact vs. action-at-a-distance) and in time (transient vs. stable) remains poorly understood. Recent studies suggest that enhancers can activate promoters across distances exceeding 200 nanometers, challenging classical contact models, but limited spatiotemporal resolution has obscured the mechanistic details of enhancer-promoter (E-P) interactions and their link to transcription. Here, we engineered a synthetic biology platform optimized for the simultaneous visualization of E-P 3D distance and [&hellip;]<\/div><\/li><li class='wp-block-rss__item'><div class='wp-block-rss__item-title'><a href='https:\/\/www.biorxiv.org\/content\/10.64898\/2026.06.17.732854v1?rss=1'>Cell-sized droplet interfaces reorganize protein secondary structures through confinement-enhanced membrane interactions<\/a><\/div><time datetime=\"2026-06-21T00:00:00-05:00\" class=\"wp-block-rss__item-publish-date\">June 21, 2026<\/time> <span class=\"wp-block-rss__item-author\">by Pal, A., Masuda, K., Yanagisawa, M.<\/span><div class=\"wp-block-rss__item-excerpt\">Cell membranes are recognized as regulators of protein organization, yet it remains unclear whether membrane-associated structural transitions arise from membrane-induced destabilization or from the reorganization of proteins already destabilized before membrane contact. Here, we address this question using cell-sized lipid-coated droplets. Native serum albumin and lysozyme showed little structural reorganization, whereas their thermally denatured forms underwent membrane-dependent {beta}-sheet formation. Denatured albumin exhibited progressively enhanced {beta}-sheet-rich organization with increasing protein&#8211;membrane attraction, whereas denatured lysozyme selectively formed a localized {beta}-sheet-rich shell at [&hellip;]<\/div><\/li><li class='wp-block-rss__item'><div class='wp-block-rss__item-title'><a href='https:\/\/www.biorxiv.org\/content\/10.64898\/2026.06.17.732849v1?rss=1'>Extending the osmophobic effect to protein side chains with a unified transfer model across osmolyte classes<\/a><\/div><time datetime=\"2026-06-21T00:00:00-05:00\" class=\"wp-block-rss__item-publish-date\">June 21, 2026<\/time> <span class=\"wp-block-rss__item-author\">by Pereira, A. F., Araujo, J. O., Tarraga, W., Martinez, L.<\/span><div class=\"wp-block-rss__item-excerpt\">Understanding the role of the protein backbone and side chains on cosolvent-induced stabilization is essential for a molecular picture of osmolyte action. The dominant view has been that protecting osmolytes stabilize proteins primarily through unfavorable interactions with the peptide backbone &#8211; the osmophobic effect &#8211; with side chains playing a minor or opposing role. By revisiting the decomposition of amino acid transfer free energies with proper account of the mutual shielding between backbone and side-chain groups, we derive a transfer [&hellip;]<\/div><\/li><li class='wp-block-rss__item'><div class='wp-block-rss__item-title'><a href='https:\/\/www.biorxiv.org\/content\/10.64898\/2026.06.16.732656v1?rss=1'>Multiple routes to red-shifted chlorophyll d-based photosynthesis<\/a><\/div><time datetime=\"2026-06-20T00:00:00-05:00\" class=\"wp-block-rss__item-publish-date\">June 20, 2026<\/time> <span class=\"wp-block-rss__item-author\">by Mehra, H. S., Magdaong, N. C. M., Flesher, D. A., Shen, G., Ulrich, N. J., Brininger, C. M., Niedzwiedzki, D. M., Miller, S. R., Gisriel, C. J.<\/span><div class=\"wp-block-rss__item-excerpt\">Strains of the cyanobacterium Acaryochloris marina exhibit diverse far-red light-harvesting properties during chlorophyll d-based photosynthesis. Here, we show that differences in light absorption among A. marina strains arise exclusively from Photosystem I (PSI) and reflect variation in multiple low-energy chlorophyll states. Time-resolved fluorescence reveals different combinations of low-energy states among strains, generating a continuum of spectral phenotypes. Cryo-EM structures of PSI at ~1.8 angstrom resolution reveal similar low-energy states arising from distinct pigment environments, demonstrating that red-shifted absorption is not [&hellip;]<\/div><\/li><li class='wp-block-rss__item'><div class='wp-block-rss__item-title'><a href='https:\/\/www.biorxiv.org\/content\/10.64898\/2026.06.20.733508v1?rss=1'>Viral RNAs as Dual Graphs: Extending the Motif Universe of RNAs<\/a><\/div><time datetime=\"2026-06-20T00:00:00-05:00\" class=\"wp-block-rss__item-publish-date\">June 20, 2026<\/time> <span class=\"wp-block-rss__item-author\">by Zbib, J., Schlick, T.<\/span><div class=\"wp-block-rss__item-excerpt\">In the evolving landscape of RNA research, the classification and analysis of RNA motifs is necessary to uncover the intricate mechanisms governing cellular and viral processes. Here we apply the coarse-grained RAG (RNA-As-Graphs) framework to advance the classification and understanding of RNA motifs, with a focus on expanding the RNA Motif Atlas through the inclusion of novel viral RNA structures. By analyzing 273 experimentally resolved viral RNA structures from the Protein Data Bank (PDB) using RAG dual-graph representations, we identify [&hellip;]<\/div><\/li><li class='wp-block-rss__item'><div class='wp-block-rss__item-title'><a href='https:\/\/www.biorxiv.org\/content\/10.64898\/2026.06.18.733157v1?rss=1'>Defining reversible binding rates in 1D systems dependent on diffusion, density, and excluded volume<\/a><\/div><time datetime=\"2026-06-20T00:00:00-05:00\" class=\"wp-block-rss__item-publish-date\">June 20, 2026<\/time> <span class=\"wp-block-rss__item-author\">by Sang, M., Johnson, M. E.<\/span><div class=\"wp-block-rss__item-excerpt\">Binding reactions in effectively one-dimensional systems, such as proteins diffusing along DNA or other filaments, pose a fundamental coarse-graining challenge because stochastic trajectories are recurrent in one dimension and therefore do not admit a unique, separation-independent macroscopic association rate. As a result, continuum rate equations are not exact in 1D even for initially homogeneous systems. Here we develop a practical framework for mapping stochastic 1D reaction-diffusion dynamics onto effective kinetic models. Using mean-first-passage arguments and particle-based simulations, we define a [&hellip;]<\/div><\/li><li class='wp-block-rss__item'><div class='wp-block-rss__item-title'><a href='https:\/\/www.biorxiv.org\/content\/10.64898\/2026.06.18.733300v1?rss=1'>Dose-Dependent Softening of Bacterial Model Membranes by Structurally Distinct Antimicrobial Peptides: A Coarse-Grained Molecular Dynamics Study<\/a><\/div><time datetime=\"2026-06-20T00:00:00-05:00\" class=\"wp-block-rss__item-publish-date\">June 20, 2026<\/time> <span class=\"wp-block-rss__item-author\">by Saiba, R., Baratam, K., Chakraborty, D., Vemparala, S.<\/span><div class=\"wp-block-rss__item-excerpt\">Antimicrobial peptides (AMPs) act at the membrane interface, where they remodel lipid packing defects and redistribute lateral stresses, yet a quantitative, dose-dependent understanding of how they alter membrane mechanical properties remains incomplete. We use coarse-grained MARTINI 3 molecular dynamics simulations to systematically characterize the mechanical and microstructural response of a 70:30 POPE:POPG bilayer to three AMPs spanning distinct structural classes: aedesin (alpha-helical, 2MMM), arenicin-1 (beta-hairpin, 2JSB), and indolicidin (disordered, 1G89). For each peptide we vary the surface loading from one [&hellip;]<\/div><\/li><li class='wp-block-rss__item'><div class='wp-block-rss__item-title'><a href='https:\/\/www.biorxiv.org\/content\/10.64898\/2026.06.16.732530v1?rss=1'>Vesicle Internalization Proceeds via a Morphological Phase Transition<\/a><\/div><time datetime=\"2026-06-20T00:00:00-05:00\" class=\"wp-block-rss__item-publish-date\">June 20, 2026<\/time> <span class=\"wp-block-rss__item-author\">by Schachter, I., Jungwirth, P., Harries, D.<\/span><div class=\"wp-block-rss__item-excerpt\">Vesicle internalization proceeds through a series of multivesicular topologies essential for endocytic transport and cellular compartmentalization. The energetic landscapes of related transitions, including vesicle budding and pearling, are known to be governed by the coupling of spontaneous curvature, leaflet area asymmetry, and reduced volume. However, the physical principles driving the structural transformation of hemifused intermediates remain unresolved. Using a continuum elastic model, we identify a morphological phase transition in hemifused invaginating vesicles, from an initial lens-like geometry to an elongated [&hellip;]<\/div><\/li><li class='wp-block-rss__item'><div class='wp-block-rss__item-title'><a href='https:\/\/www.biorxiv.org\/content\/10.64898\/2026.06.16.731580v1?rss=1'>Non-contact direct sensing of material properties of biomolecular condensate using Scanning Ionic Conductance Microscopy<\/a><\/div><time datetime=\"2026-06-20T00:00:00-05:00\" class=\"wp-block-rss__item-publish-date\">June 20, 2026<\/time> <span class=\"wp-block-rss__item-author\">by Miljkovic, H., Pang, K., Ayar Dulabi, Z., Fatti, E., Naidu, A. S., Shi, J., Penedo, M., Weis, K., Yang, W., Radenovic, A.<\/span><div class=\"wp-block-rss__item-excerpt\">Biomolecular condensates are important regulators of cellular compartmentalization and biochemical processes. Understanding their material properties is critical to elucidate how they control molecular organization and dynamics within cells. However, quantitatively probing these properties remains challenging due to the wide range of length scales, concentrations, and timescales over which condensates operate, as well as the limited force ranges accessible to current nanoscale mechanical mapping methods. We explored the use of a non-contact 3D imaging tool Scanning Ion Conductance Microscopy (SICM) for [&hellip;]<\/div><\/li><\/ul>\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity is-style-wide\"\/>\n\n\n\n<h4 class=\"wp-block-heading\">Related Journals<\/h4>\n\n\n<ul class=\"su-siblings\"><li class=\"page_item page-item-3099\"><a href=\"https:\/\/kermitmurray.com\/msblog\/links\/journal-feeds\/biochemistry-journal-feeds\/biorxiv\/biorxiv-biochemistry\/\">BioRxiv Biochemistry<\/a><\/li>\n<li class=\"page_item page-item-3112\"><a href=\"https:\/\/kermitmurray.com\/msblog\/links\/journal-feeds\/biochemistry-journal-feeds\/biorxiv\/biorxiv-bioinformatics\/\">BioRxiv Bioinformatics<\/a><\/li>\n<li class=\"page_item page-item-3188\"><a href=\"https:\/\/kermitmurray.com\/msblog\/links\/journal-feeds\/biochemistry-journal-feeds\/biorxiv\/biorxiv-cancer-biology\/\">BioRxiv Cancer Biology<\/a><\/li>\n<li class=\"page_item page-item-3190\"><a href=\"https:\/\/kermitmurray.com\/msblog\/links\/journal-feeds\/biochemistry-journal-feeds\/biorxiv\/biorxiv-pharmacology-and-toxicology\/\">BioRxiv Pharmacology and Toxicology<\/a><\/li>\n<li class=\"page_item page-item-3114\"><a href=\"https:\/\/kermitmurray.com\/msblog\/links\/journal-feeds\/biochemistry-journal-feeds\/biorxiv\/biorxiv-systems-biology\/\">BioRxiv Systems Biology<\/a><\/li>\n<li class=\"page_item page-item-3193\"><a href=\"https:\/\/kermitmurray.com\/msblog\/links\/journal-feeds\/biochemistry-journal-feeds\/biorxiv\/biorxiv-zoology\/\">BioRxiv Zoology<\/a><\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Related Journals<\/p>\n","protected":false},"author":1,"featured_media":2652,"parent":3087,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":"","_links_to":"","_links_to_target":""},"class_list":["post-3132","page","type-page","status-publish","has-post-thumbnail","hentry","entry"],"_links":{"self":[{"href":"https:\/\/kermitmurray.com\/msblog\/wp-json\/wp\/v2\/pages\/3132","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/kermitmurray.com\/msblog\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/kermitmurray.com\/msblog\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/kermitmurray.com\/msblog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/kermitmurray.com\/msblog\/wp-json\/wp\/v2\/comments?post=3132"}],"version-history":[{"count":3,"href":"https:\/\/kermitmurray.com\/msblog\/wp-json\/wp\/v2\/pages\/3132\/revisions"}],"predecessor-version":[{"id":3135,"href":"https:\/\/kermitmurray.com\/msblog\/wp-json\/wp\/v2\/pages\/3132\/revisions\/3135"}],"up":[{"embeddable":true,"href":"https:\/\/kermitmurray.com\/msblog\/wp-json\/wp\/v2\/pages\/3087"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/kermitmurray.com\/msblog\/wp-json\/wp\/v2\/media\/2652"}],"wp:attachment":[{"href":"https:\/\/kermitmurray.com\/msblog\/wp-json\/wp\/v2\/media?parent=3132"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}