Zhen Zhang, Richard J Lobb, Rebecca E Lane, Xuan Vinh To, Xueming Niu, Fiach Antaw, Giovanni Pietrogrande, Craig Winter, Alain Wuethrich, Fatima Nasrallah, Matt Trau
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引用次数: 0
Abstract
Traumatic Brain Injury (TBI) triggers secondary molecular processes that contribute to mortality and morbidity. Neuroinflammation is a key factor affecting patient outcomes both acutely and chronically. Traditional diagnostic tools, such as computed tomography imaging and the Glasgow Coma Scale, are limited in detecting molecular changes, particularly related to neuroinflammation. Small extracellular vesicles (sEVs) are cell-specific vesicles that enable cell-to-cell communication and are involved in TBI pathology. In this study, brain-specific sEVs are isolated by targeting brain-associated markers, sodium/potassium-transporting ATPase subunit beta-2 (ATP1B2) and excitatory amino acid transporter 2 (EAAT2), and employed surface-enhanced Raman spectroscopy to profile inflammation-associated cytokine chemokine (C-C motif) ligand 2 (CCL2) bound to single sEV, allowing for blood-based monitoring of neuroinflammation. This approach enabled the direct assessment of neuroinflammation in both human TBI samples and a controlled cortical injury in a rat model. This study found elevated brain-specific sEVs with enhanced CCL2 in TBI samples compared to non-TBI cohorts. The results suggest that the TBI diagnostic platform can detect an increased level of brain-specific sEVs carrying neuroinflammatory signals in TBI clinical samples with high specificity and sensitivity, offering potential as a precise diagnostic tool for TBI diagnosis.
Small MethodsMaterials Science-General Materials Science
CiteScore
17.40
自引率
1.60%
发文量
347
期刊介绍:
Small Methods is a multidisciplinary journal that publishes groundbreaking research on methods relevant to nano- and microscale research. It welcomes contributions from the fields of materials science, biomedical science, chemistry, and physics, showcasing the latest advancements in experimental techniques.
With a notable 2022 Impact Factor of 12.4 (Journal Citation Reports, Clarivate Analytics, 2023), Small Methods is recognized for its significant impact on the scientific community.
The online ISSN for Small Methods is 2366-9608.