Floating human plasma helps researchers detect diseases like opioid addiction

New research from UBC Okanagan, Harvard Medical School and Michigan State University suggests that levitating human plasma may lead to faster, more reliable and simpler disease detection.

“Human plasma proteins contain information on the occurrence and development of addiction and diseases,” says Sepideh Pakpour, an assistant professor with UBCO’s School of Engineering and one of the authors of the research.

Researchers use a stream of electricity that acts like a magnet to separate proteins from blood plasma. Plasma is the clear, liquid portion of blood that remains after red blood cells, white blood cells, platelets and other cellular components are removed.

"We know that this magnetic levitation has been around for years, an example of this is the usage of this system in levitated trains... but this system couldn't be used for biological components because the proteins in our samples are very, very small," explains Pakpour. 

Because of their size, it would take days to magnetize the proteins for research. 

"With the help of engineers and those in biomedical engineering, what we were able to do was making this system compatible for plasma samples and we saw some interesting results and we took it from there."

As plasma proteins are different densities, when separated the proteins levitate at different heights, and therefore become identifiable.

“We compared the differences between healthy proteins and diseased proteins to set benchmarks,” says Pakpour.

Pakpour is using the proteins to predict opioid dependencies and addictions, but the findings could one day lead to medical diagnoses using the technology.

“With this information and the plasma levitation, we were able to accurately detect rare proteins that are only found in individuals with opioid addictions.”

According to Pakpour, the researchers are particularly excited about the possibility of developing a portable and accurate new diagnostic tool for health care practitioners.

“More investigation is required, but our findings are certainly a step forward towards an optical imaging disease detection tool,” she adds.

The five-minute test uses machine learning and predictive models. It may one day lead to tools that can not only diagnose diseases but also help doctors prescribe medications that won’t lead to drug dependencies.