ReviewFEBS letters2026
α-Synuclein aggregation landscape from phase separation to neurotoxic intermediates.
Review in FEBS letters, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
The aberrant aggregation of α-synuclein (αS) into insoluble amyloid fibrils is a hallmark of Parkinson's disease. Despite recent advances in characterising the properties of mature αS fibrils, the transient and heterogeneous intermediates that underlie cellular toxicity remain largely elusive. Here, we review the mechanistic principles of αS aggregation, focussing on liquid-liquid phase separation (LLPS) as a critical intermediate step. We discuss how the structural evolution of αS within the condensed phase governs the subsequent patterns of cellular dysfunction and pathological propagation. This framework supports an emerging state-centric paradigm in therapeutic discovery, where the physical properties of αS condensates are modulated to mitigate the deleterious effects of its misfolding, offering a new sophisticated alternative to classical inhibition strategies.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.