bioRxivBioengineering
How do neuroglial cells respond to ultrasound induced cavitation?
A. H. Wrede, J. Luo, R. Montazami, A. Kanthasamy, N. N. Hashemi
Abstract
Reactive astrocytes are known to play a vital role in the overall response of the brain during a traumatic brain injury (TBI). Modern studies have speculated the existence of cavitation in the skull during a TBI, which has alarming potential to cause detrimental damages. Previous studies have confirmed the upregulation of various harmful genes in neurodegenerative diseases. Studying the longitudinal presence of these harmful genes in response to cavitation allows for optimized understanding and treatment methods in cavitation exposure. We seek to characterize the longitudinal genetic expression levels that astrocytes exhibit after exposure to cavitation and further elucidate the startling presence of cranial cavitation. Astrocytic expression levels of various common genes that have been documented in TBI research are our target of interest, like, TNF, IL-1{beta}, and NOS1. Results summarize specific gene trends from 1-48 hours after cavitation. Our data concludes that maximum expression is not consistently exhibited immediately after cavitation exposure, and most genes have individualized genetic trends. IL-1{beta} shows a decreasing expression over 48 hours, and TNF shows upregulation until the 6 hour time point but then begins to decrease in expression. The upregulation of NOS1 has been documented in neurodegenerative diseases, like Alzheimers and Parkinsons disease. This study has shown a consistent upregulation in NOS1 expression from 0-48 hours. These results postulate a possible linkage between cavitation damage and neurodegenerative diseases. This analysis also provides novelty in optimizing treatments for astrocytic function post-TBI and legitimizing the concern of cranial cavitation existence. These results add motivation for future studies of cavitation elimination or minimization via advanced helmet and airbag engineering.
- organism: mouse
- assay: bulk RNA-seq
- research focus: differential expression
- approach: statistical model
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