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Cell migration plays a critical role in biological processes such as embryonic development, wound healing, cancer metastasis, and immune response. While the molecular mechanisms regulating cell movement are well-studied, bridging the gap between these mechanisms and macroscopic cell behaviour remains a significant challenge due to the disparity in scale. At the subcellular level, an intermediate scale between molecular and cellular scales, cell membranes exhibit complex structural dynamics that are difficult to quantify and poorly understood. In this study, we utilized time-lapse scanning ion conductance microscopy to visualise subcellular nanoscale structural dynamics at the edges of breast cancer cells. Through quantitative analysis, we successfully identified three key features: (1) dynamic edges with abundant filopodia, (2) an inverse relationship between the local cell migration rate and lamellipodia thickness, and (3) changes in the length and distance between cytoskeleton-filament-related structures following a Poisson process. These findings provide new insights into cell migration dynamics and contribute to bridging the gap between macroscopic and microscopic cellular motion.
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http://dx.doi.org/10.1039/d4nr05161k | DOI Listing |
Inorg Chem
September 2025
Institutes of Physical Science and Information Technology, Key Laboratory of Structure and Functional Regulation of Hybrid Materials (Anhui University), Ministry of Education, Hefei 230601, P. R. China.
Precisely structured nanoclusters provide ideal platforms for elucidating structural evolution and structure-activity relationships. However, mechanistic understanding of dynamic core-shell rearrangements has long been impeded by the elusive nature of intermediates during transformation processes. Here, we show that ligand engineering-driven asymmetric thiolate exchange enables atomic-level visualization of structural evolution, thereby overcoming the long-standing challenge of intermediate capture.
View Article and Find Full Text PDFJ Chem Inf Model
September 2025
College of Agriculture and Biological Science, Dali University, Dali 671000, China.
The E76K mutation in protein tyrosine phosphatase (PTP) SHP2 is a recurrent driver of developmental disorders and cancers, yet the mechanism by which this single-site substitution promotes persistent activation remains elusive. Here, we combine path-based conformational sampling, unbiased molecular dynamics (MD) simulations, Markov state models (MSMs), and neural relational inference (NRI) to elucidate how E76K reshapes the activation landscape and regulatory architecture of SHP2. Using a minimum-action trajectory derived from experimentally determined closed and open structures, we generated representative transition intermediates to guide the unbiased MD simulations.
View Article and Find Full Text PDFPLoS One
September 2025
Department of Emergency Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China.
Background: Heat illness is a dangerous condition marked by a widespread inflammatory response. Although Pogostemon cablin (Blanco) Benth and its derivatives are clinically used, their mechanisms remain unclear.
Methods: 11 heat illness patients and 14 healthy volunteers from Southwest Medical University Affiliated Hospital were enrolled.
Elife
September 2025
Department of Chemistry, University of Massachusetts, Amherst, United States.
Voltage-dependence gating of ion channels underlies numerous physiological and pathophysiological processes, and disruption of normal voltage gating is the cause of many channelopathies. Here, long timescale atomistic simulations were performed to directly probe voltage-induced gating transitions of the big potassium (BK) channels, where the voltage sensor domain (VSD) movement has been suggested to be distinct from that of canonical Kv channels but remains poorly understood. Using a Core-MT construct without the gating ring, multiple voltage activation transitions were observed at 750 mV, allowing detailed analysis of the activated state of BK VSD and key mechanistic features.
View Article and Find Full Text PDFIEEE Trans Neural Netw Learn Syst
September 2025
This article proposes a novel model-based planning framework for freeway ramp metering (RM), denoted as Koopman-driven linearized model-based offline planning (KLMOP). This framework integrates the model predictive control (MPC) and offline reinforcement learning (RL) under assumptions of a linear Markov decision process (MDP) with the Koopman operator. KLMOP introduces a fully linearized control framework by learning and modeling the dynamics, reward function, and value function in a latent space through a Koopman-based latent dynamical model (KLDM) and a pessimistic value iteration (PEVI) algorithm.
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