Brain organoid model shows molecular signs of Alzheimer’s before birth

In a model of human fetal brain development, Emory researchers can see perturbations of epigenetic markers in cells derived from people with familial early-onset Alzheimer’s disease, which takes decades to appear. This suggests that in people who inherit mutations linked to early-onset Alzheimer’s, it would be possible to detect molecular changes in their brains before birth. The results were published in the journal Cell Reports. “The beauty of using organoids is that they allow us to Read more

The earliest spot for Alzheimer's blues

How the most common genetic risk factor in AD interacts with the earliest site of neurodegeneration Read more

Make ‘em fight: redirecting neutrophils in CF

Why do people with cystic fibrosis (CF) have such trouble with lung infections? The conventional view is that people with CF are at greater risk for lung infections because thick, sticky mucus builds up in their lungs, allowing bacteria to thrive. CF is caused by a mutation that affects the composition of the mucus. Rabindra Tirouvanziam, an immunologist at Emory, says a better question is: what type of cell is supposed to be fighting the Read more


Simpler, more portable ECGs: Emory experts hosting computing challenge

An electrocardiogram or ECG is a basic non-invasive diagnostic tool for cardiologists, which conventionally uses 12 electrodes to gather information about electrical signals in the heart and its rhythms. Emory biomedical informatics specialists are hosting an international computing contest aimed at reducing that number as low as possible, so that future portable or wearable ECG devices can be smaller, more convenient and lower in cost.

“We are challenging the research community and industry to design algorithms that classify a large range of cardiac abnormalities using ECGs with varying numbers of channels,” says co-organizer Gari Clifford, PhD, chair of biomedical informatics at Emory University School of Medicine. “The aim is to determine how low we can go — that is, how many channels of data do we need to make an accurate diagnosis?”

The devices could aid in diagnosing common conditions such as atrial fibrillation or supraventricular tachycardia.

“Reduced-lead ECGs are more accessible than standard twelve-lead ECGs in many parts of the world, and the development of effective open-source algorithms for reading reduced-lead ECGs is key for tackling the growing problem of cardiac events internationally,” says co-organizer Matthew Reyna, PhD, assistant professor of biomedical informatics and pharmacology and chemical biology.

The 2021 PhysioNet/Computing in Cardiology Challenge is titled “Will Two Do? Varying Dimensions in Electrocardiography” and calls for designers to build an algorithm that can classify cardiac abnormalities based on 12, 6, 3 and 2-lead ECGs.

So that participants can try out their algorithms, contest organizers are sharing the world’s largest and most diverse set of publicly available ECG data: over 45,000 recordings from China, Europe, Russia and the USA. A similar amount of data has been hidden for the organizers to test the competitors’ algorithms, and a separate evaluation metric will reflects errors of misdiagnosis.

This year’s contest builds upon previous years; in 2017, the challenge was to classify atrial fibrillation based on a single lead, and last year’s was a challenge to diagnose a variety of cardiac problems using standard 12 leads. Contest participants are invited to submit an abstract describing their algorithm, open-source code for their algorithm and a paper on their work.

The contest culminates in the Computing in Cardiology conference, scheduled for September 12-15 in Brno, Czech Republic. More information about the contest is available at and requirements for entry and the schedule are detailed at the PhysioNet/Computing in Cardiology Challenge 2021 site. The initial deadline for applying to enter the contest is April 9, 2021.

The contest is part of PhysioNet, an archive of biomedical computing resources supported by the National Institute of Biomedical Imaging and Bioengineering (R01EB030362). It is being co-sponsored by the Gordon and Betty Moore Foundation, Google and MathWorks. Complementary MATLAB licenses and Google Cloud Platform credits are being made available for this year’s challenge. The sponsors are also making it possible to offer several prizes worth several thousand dollars.

Posted on by Quinn Eastman in Heart Leave a comment