ReviewAdvanced healthcare materials2026
Small Extracellular Vesicles from Neural Cells: Physiological and Pathological Roles, and Potential in Neurodegenerative Therapy.
Review in Advanced healthcare materials, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
3 citing papers in PubMed.
- Extracellular vesicle-mediated bidirectional communication between the brain and peripheral organs in Alzheimer's disease: evidence, mechanisms, and translational perspectives.Journal of nanobiotechnology · 2026Review
- Integration of Transcriptional Signatures from Brain Tissue and Plasma Extracellular Vesicles of a Preclinical Tauopathy Mouse Model.International journal of molecular sciences · 2026Article
- Glioma-derived extracellular vesicles as drivers of immunotherapeutic resistance: mechanisms of immune reprogramming and metabolic intervention.Frontiers in immunology · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Small extracellular vesicles (sEVs) have emerged as central mediators of intercellular communication in the central nervous system (CNS) and are increasingly recognized for their dual roles in the pathogenesis and treatment of neurodegenerative diseases (NDDs). In disease contexts, sEVs facilitate the intercellular dissemination of pathogenic proteins and nucleic acids, thereby contributing to the propagation of Alzheimer's disease (AD) and Parkinson's disease (PD) pathology. Conversely, their intrinsic biocompatibility, capacity to traverse brain barriers, and inherent organotropic properties position sEVs as highly promising nanocarriers for CNS drug delivery. While mesenchymal stem cell-derived sEVs have been widely investigated in preclinical NDD models, accumulating evidence suggests that sEVs derived from neural cells, including neural stem cells, neurons, astrocytes, microglia, oligodendrocytes, and brain endothelial cells may offer superior brain targeting, disease relevance, and functional efficacy. This review provides a comprehensive and critical analysis of current knowledge on neural cell-derived sEVs, encompassing their physiological roles in brain homeostasis, their involvement in AD and PD pathogenesis, and their emerging therapeutic applications. We discuss cell-type-specific sEV cargo profiles, mechanisms underlying blood-brain and blood-cerebrospinal fluid barrier traversal, and recent advances in endogenous and exogenous engineering strategies that enhance cargo loading, targeting precision, and therapeutic performance. Importantly, we address key translational challenges that currently limit clinical implementation. By integrating mechanistic insights with therapeutic and engineering perspectives, this review highlights neural cell-derived sEVs as a biologically informed and versatile platform, underscoring their potential to advance next-generation neuro-nanomedicine for NDDs.
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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.