I was surfing around the Net one day and I found this article about scientists who are creating a machine that will detect acetone in someone’s breath. Acetone can be a sign that someone suffers from diabetes, so in theory this machine could use scent to diagnose this disease.
That story brought to mind other stories I’ve heard about people using dogs to sniff out cancer in people. According to this article:
“The results of the study showed that dogs can detect breast and lung cancer with sensitivity and specificity between 88% and 97%. The high accuracy persisted even after results were adjusted to take into account whether the lung cancer patients were currently smokers. Moreover, the study also confirmed that the trained dogs could even detect the early stages of lung cancer, as well as early breast cancer.”
People have even tried “smelling” schizophrenia. Read more »
*This blog post was originally published at Shrink Rap*
A new sensor developed at Stony Brook University may become a clinically useful tool for detecting disease biomarkers in breath. The nanoprobe-based technology is currently able to detect acetone, but should be modifiable to spot other compounds.
From the study abstract:
This paper describes a sensor nanotechnology suitable for non-invasive monitoring of a signaling gas, such as acetone, in exhaled breath. This is a nanomedicine tool comprised of a selective acetone nanoprobe working on the principle of ferroelectric poling sensing, and a microelectronics circuit for comparing the actual sensor signal to a predetermined threshold value, displaying the result using LED signals. This on/off type non-invasive diagnostics platform technology is based on nanotechnology, gives a fast response, it is simple to operate and inexpensive to manufacture, and may truly revolutionize personalized medicine.
Full story: New Sensor Nanotechnology Developed by Stony Brook University Researchers Simplifies Disease Detection…
Abstract in Sensor Letters: Nanosensor Device for Breath Acetone Detection
*This blog post was originally published at Medgadget*