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The Boston Globe

Elemind Technologies, a neuro-tech startup founded by scientists from MIT and elsewhere, is developing, “an approach that redirects brain wave through non-invasive stimulation – using sound, light, touch and electric pulses –  to potentially address a range of neurological conditions in a more targeted ways than drugs,” reports Robert Weisman for The Boston Globe

The Boston Globe

Researchers from MIT and elsewhere have developed an AI model that is capable of identifying 3 ½ times more people who are at high-risk for developing pancreatic cancer than current standards, reports Felice J. Freyer for The Boston Globe. “This work has the potential to enlarge the group of pancreatic cancer patients who can benefit from screening from 10 percent to 35 percent,” explains Freyer. “The group hopes its model will eventually help detect risk of other hard-to-find cancers, like ovarian.”

Wired

Prof. Ron Weiss co-founded Strand Therapeutics, a biotech company developing mRNA therapies, reports Emily Mullin for Wired. “The notion is that genetic circuits can really have significant impact on safety and efficacy,” says Weiss. “This begins to really open up the door for creating therapies whose sophistication can match the underlying complexity of biology.”

STAT

Prof. Jonathan Weissman and his colleagues have developed a new tool for monitoring changes in human blood cells, which could one day help researchers predict disease risk, reports Megan Molteni for STAT. “The technology paves the way for a day in the not too distant future where it is conceivable that from a simple blood draw, a doctor could get a sense of what’s going on in that patient’s bone marrow,” writes Molteni, “picking up perturbations there that could help predict a diverse range of diseases.”

Science

Carmen Martin-Alonso PhD '23 speaks with Zakiya Whatley on the Science podcast to discuss her recent research focused on developing new methods to improve liquid biopsies for cancer. “I think this is super, super promising for the field of oncology where having more sensitive ctDNA-based liquid biopsies could really transform patient management,” says Alonso. “And in the same way as radio label converse agents have transformed imaging, we think that priming agents could transform the utility of liquid biopsies.”

The Washington Post

Alicia Chong Rodriguez SM ’17, SM ’18 founded Bloomer Tech, a health tech startup that aims to improve health care diagnostics for women using medical-grade data to develop new therapies and care models, reports Carol Eisenberg for The Washington Post. Rodriguez and her colleagues "developed, patented and tested flexible washable circuits to turn articles of clothing into devices that can relay reams of information to the wearer’s smartphone,” writes Eisenberg.

Popular Mechanics

Popular Mechanics reporter Jill Waldbieser spotlights Prof. Hugh Herr and his work developing prosthetic limbs that integrate with their human hosts using a surgical technique that preserves the sensation in artificial limbs. “In the future, on the order of five years or so, we’ll be so good at this, we’ll completely restore the signals from the prosthetic to the brain and from the brain to the prosthetic, like the limb was never amputated,” says Herr.

Politico

Researchers at MIT and elsewhere developed an artificial intelligence predictive model that can be used to detect which strains of Covid-19 could become dominant and lead to a new wave of illness, reports Ruth Reader, Carmen Paun, Daniel Payne and Eric Schumaker for Politico. The model, “found three strong predictors of a dominant variant: the number of infections a strain causes in its first week relative to the number of times it appears in sequencing, the number of mutations in the spike protein, and the number of weeks since the current dominant variant began circulating,” they note.

Forbes

Postdoctoral associate Wen Shuhao and postdoctoral fellows Ma Jian and Lai Lipeng co-founded Xtalpi, a biotech startup that uses “artificial intelligence to find chemical compounds that could be developed into new drugs,” reports Zinnia Lee for Forbes. “By combining AI, quantum physics, cloud computing and robotic automation, Xtalpi said it helps increase the efficiency and success rate of identifying novel drug compounds,” writes Lee. “The company has recently expanded into discovering new chemical compounds for agricultural technology, cosmetics and other applications.”

Undark

Ashley Smart, associate director of the Knight Science Journalism Program, writes for Undark about the impact of commercialized genetic tests on research involving new genetic links. “Even among some researchers who are optimistic about using polygenic scores to screen for physical health conditions, there is one emerging application of polygenic scores that makes them uneasy: the prediction of risks for depression and other psychiatric conditions,” writes Smart.

TechCrunch

TechCrunch reporter Kylie Wiggers spotlights the SmartEM project by researchers from MIT and Harvard, which is aimed at enhancing lab work using, “a computer vision system and ML control system inside a scanning electron microscope” to examine a specimen intelligently. “It can avoid areas of low importance, focus on interesting or clear ones, and do smart labeling of the resulting image as well,” writes Wiggers.

The World

Research scientist Nataliya Kosmyna speaks with The World host Chris Harland-Dunaway about the science behind using non-invasive brain scans and artificial intelligence to understand people’s different thoughts and mental images.  

Fortune

Graduate student Sarah Gurev and her colleagues have developed a new AI system named EVEscape that can, “predict alterations likely to occur to viruses as they evolve,” reports Erin Prater for Fortune. Gurev says that with the amount of data the system has amassed, it “can make surprisingly accurate predications.”

The Wall Street Journal

A study by researchers from MIT and Harvard examined the potential impact of the use of AI technologies on the field of radiology, reports Laura Landro for The Wall Street Journal. “Both AI models and radiologists have their own unique strengths and areas for improvement,” says Prof. Nikhil Agarwal.