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Focal white matter lesions drive grey matter inflammation and synapse loss
Abstract Focal white matter lesions occur in most neurodegenerative disorders 1–3 . Despite occurring early in disease, white matter lesions are considered to be independent of, or secondary to, grey matter neuroinflammation, synapse loss and altered neuronal activity 4–7 . Notably, their functional effect on neuronal circuits remains understudied. To address this, we generated a focal white matter lesion in the rat brain within a clinically relevant, anatomically well-defined circuit, in which these lesions occur in many neurodegenerative disorders 8–10 . Here we show that focal white matter lesions evoke transient neuronal activity changes and microgliosis, with subsequent synapse loss and increased microglial engulfment in the grey matter, which is reversed if myelin regeneration completes. Grey matter microgliosis is often considered to be detrimental; however, we show that it is an integral part of regeneration and is conserved across three distinct mouse circuits and lesioning methods. Preventing these transient changes in the grey matter blocks myelin regeneration in the white matter. Conversely, inducing myelin regeneration failure leads to chronic grey matter neuroinflammation. This recapitulates the low-grade inflammation considered to be a dominant mechanism underlying neurodegeneration 7,11,12 . Our findings reveal a form of regenerative plasticity coupling white matter integrity to grey matter function, which may underlie multiple neurodegenerative conditions, and highlight the potential of targeting myelin regeneration to prevent chronic neuroinflammation.
Genetic architecture of sugarcane traits in a polyploid genomics framework
Oceans in Asia smash heat records — what it means for extreme weather
Visualizing the impact of quenched disorder on 2D electron Wigner solids
Low-Energy Excitation Leading to Symmetry-Breaking Charge Separation in Near-Infrared-Absorbing Bisstyryltriphenylamine–BODIPY Dimers
Navigating a crowded developing brain leaves neurons with broken DNA
The brain region that could provide a cognitive ‘reservoir’ in old age
Confined migration induces non-lethal DNA damage in developing neurons
Reversible Regulation of Thermal Conductivity through Spin-Crossover Transitions
Cucurbituril-based anion-conducting membranes with supramolecular nanopores
Optical metasurfaces for general vision processing on the edge
Switching from Reforming to Selective Dehydrogenation for Ethane–CO <sub>2</sub> Coconversion on CeO <sub>2</sub> -Based Catalysts via Crystal-Facet Engineering
Fiery data hint that controlled forest fires benefit human health
How the brain builds sentences, neuron by neuron
Systematic partisan content skews in TikTok during the 2024 US elections
Abstract Social media platforms increasingly mediate political information exposure, yet the role of algorithmic curation in shaping political exposure remains contested 1,2 . This question is difficult to resolve on platforms in which users retain substantial control over their feeds 3,4 . The ‘For You’ feed of TikTok, which delivers content almost entirely through algorithmic recommendation, offers a setting in which user agency is sharply constrained. Here we show, through 323 audit experiments with controlled ‘sock puppet’ accounts seeded with Democratic or Republican content across three US states, that accounts seeded with partisan content exhibited systematic, asymmetric differences in partisan exposure. Across more than 280,000 recommendations collected over 27 weeks during the 2024 US presidential election campaign, Republican-seeded accounts received about 11.5% more co-partisan content than Democratic-seeded accounts, whereas Democratic-seeded accounts were exposed to about 7.5% more cross-partisan content—largely anti-Democratic material—even after adjusting for engagement metrics. These asymmetries are concentrated among high-reach Republican channels and in specific policy domains, including immigration, crime and foreign policy for Democrats, and abortion for Republicans. Our findings show partisan imbalances in political information exposure on a platform dominated by algorithmic recommendations, with implications for platform governance and democratic discourse.