US scientists find promising new stroke treatment; are working on recovery assessment tool

Trauma from an acute stroke can be quick and extensive – in less than 60 seconds, an ischaemic stroke kills 1.9 million brain cells. An analysis by a team at the University of Georgia’s Regenerative Bioscience Center (UGA-RBC) showed that brain cells near the site of the stroke injury starve and die from lack of oxygen, thus sending damage signals throughout the brain network and potentially compromising millions of healthy cells. They found, however, that brain areas treated with exosomes supported full recovery in swine, which exhibited neurodegeneration patterns as seen in humans with severe stroke.

Steven Stice, RBC Director, and his colleagues suggest a minimally invasive and non-operative exosome treatment to repair the damage caused by a midline shift – when the brain is being pushed to one side.Sometimes, lesions or tumours will induce pressure or inflammation in the brain, causing what typically appears as a straight line to shift. Exosomes are then used as powerful mediators of long-distance cell-to-cell communication that can change the behavior of a tumour and its neighboring cells.

“Basically, during a stroke, destructive free radicals are all over the place destroying things,” said Stice. “What the exosome technology does is communicate with jeopardised cells and work like an anti-inflammatory agent to interrupt and stop further damage.”

The RBC team anticipates that the patented neural exosome technology, called AB126, will be filed for clinical trials by 2021.

Meanwhile, as neuroimaging is essential for evaluating brain tissue and managing stroke recovery,Samantha Spellicy, a neuroscience graduate student at the Medical College of Georgia at Augusta University, is working on a new assessment scale to help with predicting patient outcomes in stroke.

Spellicy intends to use the same outcome assessments presented in the swine observational study with human patients, “I’m trying to come up with something that we can implement in clinics right now – the clinician could take more of a personalised approach based on the patient’s midline shift measurement, and predict recovery times specifically.”

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