Mouse version of 3q29 deletion: insights into schizophrenia/ASD pathways

Emory researchers see investigating 3q29 deletion as a way of unraveling schizophrenia’s biological and genetic Read more

B cells off the rails early in lupus

Emory scientists could discern that in people with SLE, signals driving expansion and activation are present at an earlier stage of B cell differentiation than previously Read more

Head to head narcolepsy/hypersomnia study

At the sleep research meeting in San Antonio this year, there were signs of an impending pharmaceutical arms race in the realm of narcolepsy. The big fish in a small pond, Jazz Pharmaceuticals, was preparing to market its recently FDA-approved medication: Sunosi/solriamfetol. Startup Harmony Biosciences was close behind with pitolisant, already approved in Europe. On the horizon are experimental drugs designed to more precisely target the neuropeptide deficiency in people with classic narcolepsy type 1 Read more

Digital Slide Archive

CAPTCHA some cancer cells

Humans are good at deciphering complex images, compared to computers. Until recently, internet users often needed to verify that they were human by completing a CAPTCHA security check. A familiar variety asked the user to check all the boxes that contain a car, or a street sign.

If we asked random people off the street to look at pathology slides and “quick, check all the boxes that contain tumor cells,” what would happen? The accuracy, compared to a trained pathologist, wouldn’t be very good.

Not as easy as labeling which boxes contain street signs!

This challenge of expertise – crowdsourcing and pathology are not immediately compatible – is what Lee Cooper and colleagues sought to overcome in a recent paper published in Bioinformatics. So they put together something they called “structured crowdsourcing.”

“We are interested in describing how the immune system behaves in breast cancers, and so we built an artificial intelligence system to look at pathology slides and identify the tissue components,” Cooper says.

His group was particularly interested in the aggressive form of breast cancer: triple negative. They used pathology slide images from the Cancer Genome Atlas, a National Cancer Institute resource. The goal was to mark up the slides and label which sections contained tumor, stroma, white blood cells, dead cells etc.

They used social media to recruit 25 volunteers — medical students and pathologists from around the world (Egypt, Bangladesh, Saudi Arabia, United Arab Emirates, Syria, USA). Participants underwent training and used Slack to communicate and learn about how to classify images. They collaborated using the Digital Slide Archive, a tool developed at Emory. Read more

Posted on by Quinn Eastman in Cancer Leave a comment