Introduction: Extracellular vesicles (EVs) mediate intercellular communication in the central nervous system (CNS) and are emerging as biomarkers of brain health and disease. However, the molecular composition of cell type-specific brain EVs, particularly astrocyte-derived EVs (ADEVs), remains poorly defined. Methods: We performed comparative proteomic analysis of neuronal (NDEVs), microglial (MDEVs), and astrocytic (ADEVs) from mouse brain using magnetic immunocapture and LC-MS/MS proteomic profiling. Results: Each EV subtype displayed distinct molecular fingerprints. NDEVs were enriched in synaptic proteins and neurogenesis-related proteins (e.g., APP and BDNF), whereas MDEVs contained immune and phagocytic markers (e.g., CX3CR1). Strikingly, the ADEV proteome closely mirrored the recently characterized GlialCAM interactome from leukodystrophy research, encompassing GlialCAM/MLC1 and associated partners involved in ion and water homeostasis (EAAT1/2, AQP4, GJA1), together with GPCRs such as GPRC5B. This overlap suggests that ADEVs encapsulate a molecular scaffold characteristic of astrocytic endfeet, potentially extending their signaling functions to the extracellular space. Conclusion: Our study provides a detailed comparative proteomic characterization of brain cell-type specific EVs, revealing that ADEVs contain the GlialCAM/MLC1 network and GPCRs. These findings position ADEVs as promising candidates for EV-based biomarkers and mechanistic studies in CNS disorders.
Generative AI Mental Health Chatbots as Therapeutic Tools: Systematic Review and Meta-Analysis of Their Role in Reducing Mental Health Issues
Background: To date, there is no comprehensive paper that systematically synthesizes the effect of generative AI chatbot’s impact on mental health. Can generative AI chatbots



