Researchers report a method for screening for cystic fibrosis that involves swiping a microscope slide across a person's forehead in a process that takes around 2 minutes, compared with the current 3-hour test; the rapid test uses desorption electrospray ionization mass spectrometry to analyze compounds present in perspiration and uses machine learning to identify cystic fibrosis cases, with a documented 98% specificity and 96% sensitivity based on analysis of 277 perspiration samples, according to the authors.
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Article #19-09630: "Proof of concept for identifying cystic fibrosis from perspiration samples," by Zhenpeng Zhou, Daniel Alvarez, Carlos Milla, and Richard N. Zare.
MEDIA CONTACT: Richard N. Zare, Stanford University, CA; e-mail: zare@stanford.edu
Proceedings of the National Academy of Sciences