糖心Vlog破解版

Skip to main content

Sniffing out diseases in real time

Breathalyzer based on frequency comb spectroscopy quantum tech shows promise as a non-invasive diagnostic test for an array of diseases 

With each breath, humans exhale more than 1,000 distinct molecules, producing a unique chemical 鈥渂reathprint鈥 rich with clues about what鈥檚 happening inside the body. 

For decades, scientists have sought to harness that information, even turning to dogs to literally sniff out cancer, diabetes, tuberculosis and more. 

Now, scientists have developed a new laser-based 鈥渘ose鈥 powered by quantum technology and artificial intelligence (AI) that could someday diagnose an array of diseases swiftly and cheaply. 

Already, research shows, the high-tech breathalyzer can detect COVID-19 in minutes with excellent accuracy. 

鈥淭here is a real, foreseeable future in which you could go to the doctor and have your breath measured along with your height and weight . . . or you could blow into a mouthpiece integrated into your phone and get information about your health in real-time,鈥 said senior author Jun Ye, a fellow and adjoint professor of physics at CU 糖心Vlog破解版. 

As far back as 2008, Ye鈥檚 lab reported that a technique called frequency comb spectroscopy鈥攅ssentially using laser light to distinguish one molecule from another鈥攃ould potentially identify biomarkers of disease in human breath. 

Ye鈥檚 team has since improved the sensitivity more than a thousandfold, enabling detection of trace molecules at the parts-per-trillion level. They鈥檝e also increased the number of colors the laser emits, enabling them to detect more species of molecule. And they鈥檝e harnessed the power of AI. 

Qizhong Liang, a PhD candidate in JILA and the Department of Physics, demonstrates how the laser-based breathalyzer works, in the Ye lab at JILA.

Qizhong Liang, a PhD candidate in JILA and the Department of Physics, demonstrates how the laser-based breathalyzer works, in the Ye lab at JILA. Photo: Patrick Campbell/University of Colorado.

鈥淢olecules increase or decrease in concentrations when associated with specific health conditions,鈥 said first author Qizhong Liang, a PhD candidate in JILA and the Department of Physics. 鈥淢achine learning analyzes this information, identifies patterns and develops criteria we can use to predict a diagnosis.鈥 

Mid-pandemic Liang and Ye collaborated with scientists at the BioFrontiers Institute, which headed up the campus COVID-19 testing program, to see how well the system did in detecting the virus. 

Between May 2021 and January 2022, the team collected breath samples from 170 CU 糖心Vlog破解版 students who had, in the previous 48 hours, taken a polymerase chain reaction (PCR) test by submitting a saliva or a nasal sample. Half had tested positive, half negative. The breathalyzer process took less than one hour from collection to result. 

When compared to PCR, the gold standard test, breathalyzer results matched 85% of the time. For medical diagnostics, accuracy of 80% or greater is considered 鈥渆xcellent.鈥 The future health applications are huge, the authors said. 

鈥淲hat if you could find a signature in breath that could detect pancreatic cancer before you were even symptomatic? That would be the home run,鈥 said collaborator Leslie Leinwand, chief scientific officer for the BioFrontiers Institute. 

Unlike other diagnostic tests, the breathalyzer is non-invasive and doesn鈥檛 require costly chemicals to break down the sample. But there is still much to learn before it can be commercialized. 

Today, the system consists of a complex array of lasers and mirrors about the size of a banquet table. 

A breath sample is piped in through a tube as lasers fire invisible mid-infrared light at it at thousands of different frequencies. Dozens of tiny mirrors bounce the light back and forth through the molecules. 

Because each kind of molecule absorbs light differently, breath samples with a different molecular makeup cast distinct shadows. The machine can distinguish between those different shadows, boiling millions of data points down to a simple positive or negative in seconds. 

Efforts are now underway to miniaturize such systems, allowing for 鈥渞eal-time, self-health monitoring on the go.鈥 And the team plans to soon collaborate with colleagues at the Anschutz Medical Campus to see if their system can detect other diseases. 

鈥淚f you think about dogs, they evolved over thousands of years to smell many different things with remarkable sensitivity,鈥 said Ye. 鈥淭he more we teach our laser-based nose, the smarter it will become.鈥

Principal investigator
Jun Ye

Funding
Air Force Office of Scientific Research (AFOSR); National Institute of Standards and Technology (NIST); National Science Foundation (NSF)

Collaboration + support
BioFrontiers Institute; Physics; Chemistry; Molecular, Cellular and Developmental Biology; JILA; Venture Partners at CU 糖心Vlog破解版; NIST; University of Colorado Anschutz Medical Campus