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Si us plau utilitzeu sempre aquest identificador per citar o enllaçar aquest document: https://hdl.handle.net/2445/231111
Emerging Insights into Brain Inflammation: Stem-Cell-Based Approaches for Regenerative Medicine
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Neuroinflammation is a complex immune response triggered by brain injury or pathological stimuli, and is highly exacerbated in neurodegenerative diseases. It plays a dual role in the central nervous system, promoting repair in acute stages while aggravating disease progression by contributing to neuronal loss, synaptic dysfunction, and glial dysregulation in chronic phases. Inflammatory responses are mainly orchestrated by microglia and infiltrated monocytes, which, when dysregulated, not only harm existing neurons, but also impair the survival and differentiation of neural stem and progenitor cells in the affected brain regions. Modulating neuroinflammation is crucial for harnessing its protective functions while minimizing its detrimental effects. Current therapeutic strategies focus on fine-tuning inflammatory responses through pharmacological agents, bioactive molecules, and stem cell-based therapies. These approaches aim to restore immune homeostasis, support neuroprotection, and promote regeneration in various neurological disorders. However, animal models sometimes fail to reproduce human-specific inflammatory responses in the brain. In this context, stem-cell-derived models provide a powerful tool to study neuroinflammatory mechanisms in a patient-specific and physiologically relevant context. These models facilitate high-throughput screening, personalized medicine, and the development of targeted therapies while addressing the limitations of traditional animal models, paving the way for more targeted and effective treatments.
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KARAM, Marie, ORTEGA GASCO, Alba and TORNERO, Daniel. Emerging Insights into Brain Inflammation: Stem-Cell-Based Approaches for Regenerative Medicine. International Journal of Molecular Sciences. 2025. Vol. 26, num. 7, pags. 3275. ISSN 1661-6596. [consulted: 3 of August of 2026]. Available at: https://hdl.handle.net/2445/231111