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Chronic allodynia stemming from peripheral stump neuromas can persist for extended periods, significantly compromising patients' quality of life. Conventional managements for nerve stumps have demonstrated limited effectiveness in ensuring their orderly termination. In this study, we present a spatially confined conduit strategy, designed to enhance the self-organization of regenerating nerves after truncation. This innovative approach elegantly enables the autonomous slowing of axonal outgrowth in response to the gradually constricting space, concurrently suppressing neuroinflammation through YAP-mediated mechanotransduction activation. Meanwhile, the decelerating axons exhibit excellent alignment and remyelination, thereby helping to prevent failure modes in nerve self-organization, such as axonal twisting in congested regions and overgrowth beyond the conduit's capacity. Additionally, proteins associated with mechanical allodynia, including TRPA1 and CGRP, exhibit a gradual reduction in expression as spatial constraints tighten, a trend inversely validated by the administration of the YAP-targeted inhibitor Verteporfin. This spatially confined conduit strategy significantly alleviates allodynia, thus preventing autotomy behavior and reducing pain-induced gait alterations.
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http://dx.doi.org/10.1038/s41467-024-55118-9 | DOI Listing |
Front Neural Circuits
September 2025
School of Systems Science, Beijing Normal University, Beijing, China.
Bow-tie architecture (BTA) is widely observed in biological neural systems, yet the underlying mechanism driving its spontaneous emergence remains unclear. In this study, we identify a novel formation mechanism by training multi-layer neural networks under biologically inspired non-negative connectivity constraints across diverse classification tasks. We show that non-negative weights reshape network dynamics by amplifying back-propagated error signals and suppressing hidden-layer activity, leading to the self-organization of BTA without pre-defined architecture.
View Article and Find Full Text PDFSci Rep
August 2025
Institute of Technical Physics and Materials Science, HUN-REN Centre for Energy Research, P.O. Box 49, 1525, Budapest, Hungary.
The exploration of brain networks has reached an important milestone as relatively large and reliable information has been gathered for connectomes of different species. Analyses of connectome data sets reveal that the structural length follows the exponential rule, the distributions of in- and out-node strengths follow heavy-tailed lognormal statistics, while the functional network properties exhibit powerlaw tails, suggesting that the brain operates close to a critical point where computational capabilities and sensitivity to stimulus is optimal. Because these universal network features emerge from bottom-up (self-)organization, one can pose the question of whether they can be modeled via a common framework, particularly through the lens of criticality of statistical physical systems.
View Article and Find Full Text PDFACS Appl Mater Interfaces
July 2025
State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, and Engineering Research Center of Oral Translational Medicine, Ministry of Education and National Engineering Laboratory for Oral Regenerative Medicine, West China Hospital of Stomatology, Sichuan University
Insufficient blood circulation in injured regions is a critical challenge that hinders the application of engineered tissue in the regeneration of tissue defects or losses. Here, we developed a three-dimensional culture system that enables human microvascular units (MVUs) to expand and self-organize into vascularized microtissues containing well-formed microvascular structures and stem-cell-derived functional stroma. Moreover, the vascularized microtissue is customizable in both shape and size.
View Article and Find Full Text PDFFront Neural Circuits
July 2025
International Research Center for Neurointelligence (WPI-IRCN), The University of Tokyo Institutes for Advanced Study (UTIAS), The University of Tokyo, Tokyo, Japan.
Dissociated neuronal cultures provide a powerful, simplified model for investigating self-organized prediction and information processing in neural networks. This review synthesizes and critically examines research demonstrating their fundamental computational abilities, including predictive coding, adaptive learning, goal-directed behavior, and deviance detection. A unique contribution of this work is the integration of findings on network self-organization, such as the development of critical dynamics optimized for information processing, with emergent predictive capabilities, the mechanisms of learning and memory, and the relevance of the free energy principle within these systems.
View Article and Find Full Text PDFChaos
March 2025
Department of Physics and Astronomy, University of Potsdam, Karl-Liebknecht-Str. 24/25, D-14476 Potsdam-Golm, Germany.
Networks of nonlocally coupled leaky integrate-and-fire neurons exhibit a variety of complex collective behaviors, such as partial synchronization, frequency or amplitude chimeras, solitary states, and bump states. In particular, the bump states consist of one or many regions of asynchronous elements within a sea of subthreshold (quiescent) elements. The asynchronous domains travel in the network in a direction predetermined by the initial conditions.
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