Study finds ‘important implications’ to understanding immunity against COVID-19

New research from Emory University indicates that nearly all people hospitalized with COVID-19 develop virus-neutralizing antibodies within six days of testing positive. The findings will be key in helping researchers understand protective immunity against SARS-CoV-2 and in informing vaccine development. The test that Emory researchers developed also could help determine whether convalescent plasma from COVID-19 survivors can provide immunity to others, and which donors' plasma should be used. The antibody test developed by Emory and validated Read more

Emory plays leading role in landmark HIV prevention study of injectable long-acting cabotegravir

Emory University played a key role in a landmark international study evaluating the safety and efficacy of the long-acting, injectable drug, cabotegravir (CAB LA), for HIV prevention. The randomized, controlled, double-blind study found that cabotegravir was 69% more effective (95% CI 41%-84%) in preventing HIV acquisition in men who have sex with men (MSM) and transgender women who have sex with men when compared to the current standard of care, daily oral emtricitabine/tenofovir disoproxil fumarate Read more

Yerkes researchers find Zika infection soon after birth leads to long-term brain problems

Researchers from the Yerkes National Primate Research Center have shown Zika virus infection soon after birth leads to long-term brain and behavior problems, including persistent socioemotional, cognitive and motor deficits, as well as abnormalities in brain structure and function. This study is one of the first to shed light on potential long-term effects of Zika infection after birth. “Researchers have shown the devastating damage Zika virus causes to a fetus, but we had questions about Read more

David Gutman

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