Prof. Deblina Sarkar speaks with Bloomberg Businessweek Daily reporters Carol Massar and David Gura about her work using microscopic technology to treat and identify health issues. We are building “tiny nanoelectronics chips which can seamlessly integrate with our body and brain,” says Sarkar. “This can diagnose disease or treat diseases which even drugs cannot fix.”
Using molecular evidence buried in rocks, researchers at MIT suggest that some of the Earth’s first living creatures are ancestors of the modern sea sponge, reports Ashley Fike for Vice. “The discovery suggests the earliest animals were simple, filter-feeding organisms that slowly cleaned the seas while the rest of the evolution was still figuring itself out,” says Fike. “These early sponges likely had no skeletons, nerves, or eyes – just porous bodies that absorbed water and nutrients. Yet they paved the way for everything that came next, from insects to mammals to us.”
A new study by MIT researchers suggests sea sponges may have been the “first animals to inhabit the Earth,” reports Maria Azzura Volpe for Newsweek. “In their work, the researchers linked so-called ‘chemical fossils’ found in ancient rocks to the ancestors of a class of modern-day sea sponges known as demosponges,” explains Volpe. “These chemical fossils—the molecular remnants of once-living organisms that have been buried, transformed, and preserved in sediment over time—were discovered in rocks that date back to more than 541 million years ago, during the Ediacaran Period.”
MIT researchers have uncovered new evidence that suggests some of Earth’s first living creatures are ancestors of the modern sea sponge, reports Andrew Paul for Popular Science. The researchers identified 541 million-year-old chemical fossils embedded in sediment that they believe may indicate that some of Earth’s earliest creatures were the ancient relatives of today’s sea sponges.
Strand Therapeutics, co-founded Jake Becraft PhD '19, has developed a programmable drug that could one day shrink tumors in cancer patients, reports Amy Feldman for Forbes. “It shocked even us,” says Becraft. “You hope something happens, but you don’t expect to see a huge response because these patients have already proven to have cancers so resistant to treatment.”
A study by researchers at MIT and elsewhere has proposed an alternative scenario to how life survived “Snowball Earth,” a “super ice age that froze the entire planet from poles to the equator” during the Cryogenian period, reports David Bressan for Forbes. “The scientists found that lifeforms could have survived the global freeze by thriving in watery oases on the surface,” explains Bressan.
MIT researchers have developed a method to grow artificial muscle tissue that twitches and flexes in multiple, coordinated directions, and could be useful for building “biohybrid” robots, reports Andrew Corselli for Tech Briefs. Prof. Ritu Raman explains that her lab is focused on creating “artificial muscle tissues that can be used to understand and treat muscle diseases that impact healthy human mobility,” and making “safe muscle-powered robots that can perform complex tasks in dangerous environments that are not suitable for humans.”
MIT researchers have developed a new method to grow artificial muscles for soft robots that can move in multiple directions, mimicking the iris of an eye, reports Mrigakshi Dixit for Interesting Engineering. The researchers developed a new technique called “stamping” to create “an artificial iris-like structure,” Dixit explains. “For this, they 3D-printed a tiny stamp, patterned with microscopic grooves. This stamp is then pressed into a soft hydrogel to create a blueprint for muscle growth.”
Prof. Ed Boyden and Prof. Li-Huei Tsai have “found that if gamma waves through non-invasive stimulation, were put back into baseline frequency, it could slow down the process in certain brain diseases such as Alzheimer’s,” reports Hansa Bhargava for Forbes.
Graduate student Lauren “Ren” Ramlan programmed Doom, an iD software video game, to run on a display made from E.coli cells, reports Andrew Paul for Popular Science. For the project to work, “Ramlan first grew cells within a 32×48 1-bit well plate, then connected the makeshift screen to a controller capable of processing and translating binary code into the ‘addition or omission of a repressor controlling the fluorescence of the cells,’” writes Paul. “Basically, Ramlan swapped a traditional screen’s tiny light diodes for glowing bacterial cells."
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.”
Researchers from MIT have developed, “nanoelectronics they hope can one day enter the brain and treat conditions like Alzheimer’s by monitoring some of these brain patterns,” reports Elizabeth Hlavinka for Salon. “Their device, which they call Cell Rover, serves as a sort of antenna that can help external devices monitor cells.”
MIT researchers have developed a new cell imaging technique that offers “the ability to observe up to seven different molecules simultaneously,” writes Amal Jos Chacko for Interesting Engineering. “This could open the door to a deeper understanding of cellular functions, aging, and diseases.”
Researchers from MIT and Harvard have explored astrocytes, a group of brain cells, from a computational perspective and developed a mathematical model that shows how they can be used to build a biological transformer, reports Kyle Wiggers for TechCrunch. “The brain is far superior to even the best artificial neural networks that we have developed, but we don’t really know exactly how the brain works,” says research staff member Dmitry Krotov. “There is scientific value in thinking about connections between biological hardware and large-scale artificial intelligence networks. This is neuroscience for AI and AI for neuroscience.