Injectable antenna could safely power deep-tissue medical implants

injectable-antenna-could-safely-power-deep-tissue-medical-implants

Researchers from the MIT Media Lab have developed an antenna — about the size of a fine grain of sand — that can be injected into the body to wirelessly power deep-tissue medical implants, such as pacemakers in cardiac patients and neuromodulators in people suffering from epilepsy or Parkinson’s disease.

“This is the next major step in miniaturizing deep-tissue implants,” says Baju Joy, a PhD student in the Media Lab’s Nano-Cybernetic Biotrek research group. “It enables battery-free implants that can be placed with a needle, instead of major surgery.”

paper detailing this work was published in the October issue of IEEE Transactions on Antennas and Propagation. Joy is joined on the paper by lead author Yubin Cai, PhD student at the Media Lab; Benoît X. E. Desbiolles and Viktor Schell, former MIT postdocs; Shubham Yadav, an MIT PhD student in media arts and sciences;

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AI maps how a new antibiotic targets gut bacteria

ai-maps-how-a-new-antibiotic-targets-gut-bacteria

For patients with inflammatory bowel disease, antibiotics can be a double-edged sword. The broad-spectrum drugs often prescribed for gut flare-ups can kill helpful microbes alongside harmful ones, sometimes worsening symptoms over time. When fighting gut inflammation, you don’t always want to bring a sledgehammer to a knife fight.

Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and McMaster University have identified a new compound that takes a more targeted approach. The molecule, called enterololin, suppresses a group of bacteria linked to Crohn’s disease flare-ups while leaving the rest of the microbiome largely intact. Using a generative AI model, the team mapped how the compound works, a process that usually takes years but was accelerated here to just months.

“This discovery speaks to a central challenge in antibiotic development,” says Jon Stokes, senior author of a new paper on the work,

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Machine-learning tool gives doctors a more detailed 3D picture of fetal health

machine-learning-tool-gives-doctors-a-more-detailed-3d-picture-of-fetal-health

For pregnant women, ultrasounds are an informative (and sometimes necessary) procedure. They typically produce two-dimensional black-and-white scans of fetuses that can reveal key insights, including biological sex, approximate size, and abnormalities like heart issues or cleft lip. If your doctor wants a closer look, they may use magnetic resonance imaging (MRI), which uses magnetic fields to capture images that can be combined to create a 3D view of the fetus.

MRIs aren’t a catch-all, though; the 3D scans are difficult for doctors to interpret well enough to diagnose problems because our visual system is not accustomed to processing 3D volumetric scans (in other words, a wrap-around look that also shows us the inner structures of a subject). Enter machine learning, which could help model a fetus’s development more clearly and accurately from data — although no such algorithm has been able to model their somewhat random movements and various body shapes.

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New RNA tool to advance cancer and infectious disease research and treatment

new-rna-tool-to-advance-cancer-and-infectious-disease-research-and-treatment

Researchers at the Antimicrobial Resistance (AMR) interdisciplinary research group of the Singapore-MIT Alliance for Research and Technology (SMART), MIT’s research enterprise in Singapore, have developed a powerful tool capable of scanning thousands of biological samples to detect transfer ribonucleic acid (tRNA) modifications — tiny chemical changes to RNA molecules that help control how cells grow, adapt to stress, and respond to diseases such as cancer and antibiotic‑resistant infections. This tool opens up new possibilities for science, health care, and industry — from accelerating disease research and enabling more precise diagnostics to guiding the development of more effective medical treatments for diseases such as cancer and antibiotic-resistant infections.

For this study, the SMART AMR team worked in collaboration with researchers at MIT, Nanyang Technological University in Singapore, the University of Florida, the University at Albany in New York, and Lodz University of Technology in Poland.

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MIT researchers develop AI tool to improve flu vaccine strain selection

mit-researchers-develop-ai-tool-to-improve-flu-vaccine-strain-selection

Every year, global health experts are faced with a high-stakes decision: Which influenza strains should go into the next seasonal vaccine? The choice must be made months in advance, long before flu season even begins, and it can often feel like a race against the clock. If the selected strains match those that circulate, the vaccine will likely be highly effective. But if the prediction is off, protection can drop significantly, leading to (potentially preventable) illness and strain on health care systems.

This challenge became even more familiar to scientists in the years during the Covid-19 pandemic. Think back to the time (and time and time again), when new variants emerged just as vaccines were being rolled out. Influenza behaves like a similar, rowdy cousin, mutating constantly and unpredictably. That makes it hard to stay ahead, and therefore harder to design vaccines that remain protective.

To reduce this uncertainty,

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New postdoctoral fellowship program to accelerate innovation in health care

new-postdoctoral-fellowship-program-to-accelerate-innovation-in-health-care

The MIT Health and Life Sciences Collaborative (MIT HEALS) is launching the Biswas Postdoctoral Fellowship Program to advance the work of outstanding early-career researchers in health and life sciences. Supported by a gift from the Biswas Family Foundation, the program aims to help apply cutting-edge research to improve health care and the lives of millions.

The program will support exceptional postdocs dedicated to innovation in human health care through a full range of pathways, such as leveraging AI in health-related research, developing low-cost diagnostics, and the convergence of life sciences with such areas as economics, business, policy, or the humanities. With initial funding of $12 million, five four-year fellowships will be awarded for each of the next four years, starting in early 2026.

“An essential goal of MIT HEALS is to find new ways and opportunities to deliver health care solutions at scale, and the Biswas Family Foundation shares our commitment to scalable innovation and broad impact.

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MIT and Mass General Hospital researchers find disparities in organ allocation

mit-and-mass-general-hospital-researchers-find-disparities-in-organ-allocation

In 1954, the world’s first successful organ transplant took place at Brigham and Women’s Hospital, in the form of a kidney donated from one twin to the other. At the time, a group of doctors and scientists had correctly theorized that the recipient’s antibodies were unlikely to reject an organ from an identical twin. One Nobel Prize and a few decades later, advancements in immune-suppressing drugs increased the viability of and demand for organ transplants. Today, over 1 million organ transplants have been performed in the United States, more than any other country in the world.

The impressive scale of this achievement was made possible due to advances in organ matching systems: The first computer-based organ matching system was released in 1977. Despite continued innovation in computing, medicine, and matching technology over the years, over 100,000 people in the U.S. are currently on the national transplant waiting list and 13 people die each day waiting for an organ transplant. 

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MIT and Mass General Brigham launch joint seed program to accelerate innovations in health

mit-and-mass-general-brigham-launch-joint-seed-program-to-accelerate-innovations-in-health

Leveraging the strengths of two world-class research institutions, MIT and Mass General Brigham (MGB) recently celebrated the launch of the MIT-MGB Seed Program. The new initiative, which is supported by Analog Devices Inc. (ADI), will fund joint research projects led by researchers at MIT and Mass General Brigham. These collaborative projects will advance research in human health, with the goal of developing next-generation therapies, diagnostics, and digital tools that can improve lives at scale. 

The program represents a unique opportunity to dramatically accelerate innovations that address some of the most urgent challenges in human health. By supporting interdisciplinary teams from MIT and Mass General Brigham, including both researchers and clinicians, the seed program will foster groundbreaking work that brings together expertise in artificial intelligence, machine learning, and measurement and sensing technologies with pioneering clinical research and patient care.

“The power of this program is that it combines MIT’s strength in science,

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LLMs factor in unrelated information when recommending medical treatments

llms-factor-in-unrelated-information-when-recommending-medical-treatments

A large language model (LLM) deployed to make treatment recommendations can be tripped up by nonclinical information in patient messages, like typos, extra white space, missing gender markers, or the use of uncertain, dramatic, and informal language, according to a study by MIT researchers.

They found that making stylistic or grammatical changes to messages increases the likelihood an LLM will recommend that a patient self-manage their reported health condition rather than come in for an appointment, even when that patient should seek medical care.

Their analysis also revealed that these nonclinical variations in text, which mimic how people really communicate, are more likely to change a model’s treatment recommendations for female patients, resulting in a higher percentage of women who were erroneously advised not to seek medical care, according to human doctors.

This work “is strong evidence that models must be audited before use in health care — which is a setting where they are already in use,” says Marzyeh Ghassemi,

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First-of-its-kind device profiles newborns’ immune function

first-of-its-kind-device-profiles-newborns’-immune-function

Researchers from the Singapore-MIT Alliance for Research and Technology (SMART), MIT’s research enterprise in Singapore, along with colleagues from KK Women’s and Children’s Hospital (KKH), have developed a first-of-its-kind device to profile the immune function of newborns.   Using a single drop of blood, the BiophysicaL Immune Profiling for Infants (BLIPI) system provides real-time insights into newborns’ immune responses, enabling the early detection of severe inflammatory conditions and allowing for timely interventions. This critical innovation addresses the urgent and unmet need for rapid and minimally invasive diagnostic tools to protect vulnerable newborns, especially those born prematurely. Critical unmet need in newborn care Premature infants are particularly vulnerable to life-threatening conditions such as sepsis and necrotizing enterocolitis (NEC). Newborn sepsis — a bloodstream infection occurring in the first weeks of life — is a major global health challenge, causing up to 1 million infant deaths worldwide annually. NEC, a serious intestinal disease that causes severe inflammation,  » Read More