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Disease

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The Wall Street Journal

Wall Street Journal reporter Sara Castellanos spotlights Prof. Markus Buehler’s work combining virtual reality with sound waves to help detect subtle changes in molecular motions. Castellanos notes that Buehler and his team recently found, “coronaviruses can be more lethal or infectious depending on the vibrations within the spike proteins that are found on the surface of the virus.”

PBS NewsHour

Reporting for the PBS NewsHour, Miles O’Brien visits alumnus Dexter Ang ‘05 to learn more about how his startup, Pison, is developing a wrist-worn sensor that detects the faint electrical signals controlling simple hand gestures, allowing users to control digital interfaces using brain signals. “The device is connected to a smartphone, allowing control of it or other devices, conveyor belts in factories, drones, even pinball machines, to name a few,” notes O’Brien. He adds that Ang was inspired by his late mother, who contracted ALS, as “he wanted to make her life easier.”

WHDH 7

WHDH spotlights how MIT and Harvard researchers are creating wearable biosensors that could be used to detect Covid-19 in a person’s breath. “At the end of the day, what we wanted to do was basically to blend both to potentially produce a product that was more easily incentivized patients to both wear a mask and to get tested,” explains Luis Soenksen of the Abdul Latif Jameel Clinic for Machine Learning in Health.

CBS Boston

A new sensor developed by MIT and Harvard researchers can be embedded in a face mask and used to alert the wearer if they have Covid-19, reports CBS Boston. “Small disposable sensors can diagnose the wearer of the mask within 90 minutes," reports CBS Boston. "The technology has been used before to detect Ebola and Zika, but now researchers are embedding it into face masks and lab coats as a new method to safeguard health care workers.”

Boston Globe

Researchers from MIT and Harvard have developed a new sensor technology that can be embedded in a face mask to detect whether the wearer has Covid-19, reports Pranshu Verma for The Boston Globe. “We worked hard, sometimes bringing nonbiological equipment home and assembling devices manually,” says Luis Soenksen of the Abdul Latif Jameel Clinic for Machine Learning in Health. “It was definitely different from the usual lab infrastructure we’re used to working under, but everything we did has helped us ensure that the sensors would work in real-world pandemic conditions.”

Fast Company

Researchers from MIT and Harvard have developed a face mask outfitted with sensors that can detect if the wearer has Covid-19, reports Adele Peters for Fast Company. “If testing and sensing at a biological molecular level could be done in a format that can follow people around instead of people having to go to the clinic, maybe you can encourage people to get more testing done,” says Luis Soenksen, a Venture Builder at MIT’s Abdul Latif Jameel Clinic for Machine Learning in Health.

The Washington Post

Professor Martin Bazant and Professor John Bush have developed a new safety guideline to limit the risk of airborne Covid-19 transmission in different indoor settings. “For airborne transmission, social distancing in indoor spaces is not enough, and may provide a false sense of security,” says Bazant. “Efficient mask use is the most effective safety measure, followed by room ventilation, then filtration,” adds Bush.

Quartz

MIT researchers are applying machine learning algorithms typically used for natural language processing to identify coronavirus variants, reports Brian Browdie for Quartz. “Besides being able to quantify the potential for mutations to escape, the research may pave the way for vaccines that broaden the body’s defenses against variants or that protect recipients against more than one virus, such as flu and the novel coronavirus, in a single shot,” writes Browdie. 

Gizmodo

Gizmodo reporter Andrew Liszewski spotlights MIT startup OPT Industries, which has created a new type of Covid-19 nasal swab “that’s faster at absorbing samples, and better at releasing it for analysis.”

Vox

Research scientist Andreas Mershin speaks with Noam Hassenfeld of Vox about his work developing a new AI system that could be used to detect disease using smell.

Scientific American

A new AI-powered system developed by researchers from MIT and other institutions can detect prostate cancer in urine samples as accurately as dogs can, reports Tanya Lewis and Prachi Patel for Scientific American. “We found we could repeat the training you use for dogs on the machines until we can’t tell the difference between the two,” says research scientist Andreas Mershin.

ITV

 ITV reporter Liz Summers spotlights how researchers from MIT and other institutions have developed a new system that could eventually be used to help detect diseases via smell. The researchers hope the results could “eventually result in the production of a ‘robotic nose’ perhaps in the form of a smartphone app.”

United Press International (UPI)

UPI reporter Brian P. Dunleavy writes that MIT researchers have developed a new system, modeled on a dog’s keen sense of smell, that could be used to help detect disease using smell. “We see the dogs and their training research as teaching our machine learning [sense of smell] and artificial intelligence algorithms how to operate,” says research scientist Andreas Mershin.

BBC News

A team of researchers from MIT and other institutions have created a new sensor that could be used to sniff out disease, reports Charlie Jones for the BBC. Research scientist Andreas Mershin says "Imagine a day when smartphones can send an alert for potentially being at risk for highly aggressive prostate cancer, years before a doctor notices a rise in PSA levels.”

Fast Company

Fast Company reporter Ruth Reader writes that researchers from MIT and other institutions have developed a new miniaturized detector that could be used to detect diseases by smell. “This paper was about integrating all the techniques that we know can work independently and finding out what of all this can go and become [part of] an integrated smartphone-based diagnostic,” says research scientist Andreas Mershin.