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

Gari Clifford

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 PhysioNet.org 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

Memory screening using eye-tracking on mobile devices

Investigators at Emory Brain Health Center have developed a platform for evaluating visual memory, while someone views photos for a few minutes on an iPad.

Emory researchers, led by Goizuieta Alzheimer’s Disease Research Center director Allan Levey and biomedical informatics chair Gari Clifford, are working with the company Linus Health to develop the VisMET (Visuospatial Memory Eye-Tracking Test) technology further. Results from the most recent version were published in the journal IEEE Transaction on Biomedical Engineering, and the Emory/Linus team continues to refine the technology.

The goal is to screen people for memory issues, identifying those with mild cognitive impairment (MCI) or Alzheimer’s disease. The task — difficult to call it a test — was designed to be more efficient, easier to administer, and more enjoyable than tests currently used.

“We think this could be a sensitive and specific method for detecting visual memory impairment, and it’s convenient enough for use on a wider scale,” Levey says.

The VisMET technology is based on this observation. When someone with MCI or Alzheimer’s views a photo twice, and the photo has been changed the second time (example: an object in the scene has been removed), their eyes spend less time checking the new or missing element in the photo, compared with healthy people. This is because the regions of the brain that drive visual memory formation, such as the entorhinal cortex and hippocampus, are some of the earliest to deteriorate in MCI or Alzheimer’s.

Currently, when someone is evaluated for memory loss, they get a battery of “paper and pencil” tests to assess verbal memory. Researchers say the alternative of viewing photos on a tablet could be less intimidating for those taking the test, as well as easier to administer and score. The only instruction given to study participants was to enjoy the images.

“The current way memory tests are implemented can be stressful,” says software engineer Alvince Pongos, who is co-first author of the IEEE TBME paper, now at MIT’s McGovern Institute for Brain Research. “The difficulty of standard memory tests can lead to test-givers repeating task instructions many times, and to test-takers being confused and frustrated. If we design simpler tasks and make our tools available in the comfort of one’s home, then we remove barriers allowing more people to engage with their health information.”

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Posted on by Quinn Eastman in Neuro Leave a comment

Detecting heart failure via wearable devices

Cardiology researchers have been eagerly taking up consumer electronic devices that include pulse oximeters. Being able to conveniently measure the level of oxygen in someone’s blood is a useful tool, whether one is interested in sleep apnea or COVID-19.

The news that the new Apple Watch includes a pulse oximeter prompted Lab Land to check in with Amit Shah, an Emory cardiologist who has been experimenting with similar devices to discriminate patients with heart failure from those with other conditions.

Shah, together with Shamim Nemati, now at UCSD, and bioinformatics chair Gari Clifford recently published a pilot study on detecting heart failure using the Samsung Simband. The Simband was a prototype device that didn’t make it to the consumer market, but it carried sensors for optical detection of blood volume changes (photoplethysmography), like on the Apple Watch. 

Heart failure causes symptoms such as shortness of breath and leg swelling, but other conditions such as anemia or lung diseases can appear similarly. The idea was to help discriminate people who might need an examination by echocardiogram (cardiac ultrasound).

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