Lifeboat Foundation

Training a machine-learning model to effectively perform a task, such as image classification, involves showing the model thousands, millions, or even billions of example images. Gathering such enormous datasets can be especially challenging when privacy is a concern, such as with medical images. Researchers from MIT and the MIT-born startup DynamoFL have now taken one popular solution to this problem, known as federated learning, and made it faster and more accurate.

Federated learning is a collaborative method for training a machine-learning model that keeps sensitive user data private. Hundreds or thousands of users each train their own model using their own data on their own device. Then users transfer their models to a central server, which combines them to come up with a better model that it sends back to all users.

A collection of hospitals located around the world, for example, could use this method to train a machine-learning model that identifies brain tumors in medical images, while keeping patient data secure on their local servers.

According to research from the Center for Genomic Regulation (CRG) published in the journal Nature, immature human egg cells bypass a critical metabolic process believed to be necessary for producing energy.

The cells modify their metabolism to stop producing reactive oxygen species, dangerous molecules that can accumulate, damage DNA

DNA, or deoxyribonucleic acid, is a molecule composed of two long strands of nucleotides that coil around each other to form a double helix. It is the hereditary material in humans and almost all other organisms that carries genetic instructions for development, functioning, growth, and reproduction. Nearly every cell in a person’s body has the same DNA. Most DNA is located in the cell nucleus (where it is called nuclear DNA), but a small amount of DNA can also be found in the mitochondria (where it is called mitochondrial DNA or mtDNA).

Together with a Duke University team led by Dr. Barton Haynes, Alt and Luo then assessed the efficacy of these antibodies. Antibodies from three of the nine lineages were effective in neutralizing the original Wuhan-Hu-1 virus. The SP1-77 antibody and other members of its lineage, in particular, demonstrated extremely wide activity, neutralizing Alpha, Beta, Gamma, Delta, and all prior and current Omicron strains.

A new approach to virus neutralization

What caused the SP1-77 antibody to be so broadly neutralizing? Structural studies by a collaborating team led by Bing Chen, Ph.D. and Jun Zhang, Ph.D. at Boston Children’s Hospital and the Haynes group at Duke, showed that SP1-77 works differently from current antibodies (either therapeutic antibodies or those we make in response to current vaccines).

Were you unable to attend Transform 2022? Check out all of the summit sessions in our on-demand library now! Watch here.

The last two years saw cloud technology heavily encouraged across almost every sector. For businesses wishing to thrive in the chaos of the pandemic, the move to cloud environments became a necessity amidst the shift to remote work and the frequent inability to access data centers.

As a result, more businesses than ever — including many in established industries such as manufacturing, retail and healthcare — have accelerated their adoption of cloud-first models and strategies. This approach is empowering these industries with more agility and efficiency in what has been a very uncertain time for the world and thus, for business.

These unnecessary experiments can cause another pandemic.

CRISPR has been used to rearrange the chromosomes of lab mice, a world’s first in mammals and a breakthrough in bioengineering.

A groundbreaking mathematical equation that could transform medical procedures, natural gas extraction, and plastic packaging production in the future has been discovered.

The new equation, developed by scientists at the University of Bristol, indicates that diffusive movement through permeable material can be modeled exactly for the very first time. It comes a century after world-leading physicists Albert Einstein and Marian von Smoluchowski derived the first diffusion equation, and marks important progress in representing motion for a wide range of entities from microscopic particles and natural organisms to man-made devices.

Until now, scientists looking at particle motion through porous materials, such as biological tissues, polymers, various rocks and sponges have had to rely on approximations or incomplete perspectives.

Were you unable to attend Transform 2022? Check out all of the summit sessions in our on-demand library now! Watch here.

While business transformation has always been critical to staying relevant and competitive, global disruptions brought on by the COVID-19 pandemic created an urgency to accelerate innovation to keep pace with market conditions and changes in customer demand. In fact, many digitally transformed companies have not only survived — they’ve thrived.

According to a 2021 McKinsey Survey, top-performing companies now obtain a larger share of their sales from products or services that didn’t exist just one year ago. These companies are making more aggressive plans to differentiate themselves with technology, and some are preparing to reinvent their value proposition altogether.

Tissue engineering and stem cells.

A series of talks on stem cells and tissue engineering.

In recent years, roboticists and material scientists worldwide have been trying to create artificial systems that resemble human body parts and reproduce their functions. These include artificial skins, protective layers that could also enhance the sensing capabilities of robots.

Researchers at Donghua University in China and the Jülich Centre for Neutron Science (JCNS) in Germany have recently developed a new and highly promising artificial ionic skin based on a self-healable elastic nanomesh, an interwoven structure that resembles human skin. This artificial skin, introduced in a paper published in Nature Communications, is soft, fatigue-free and self-healing.

“As we know, the skin is the largest organ in the human body, which acts as both a protective layer and sensory interface to keep our body healthy and perceptive,” Shengtong Sun, one of the researchers who carried out the study, told TechXplore. “With the rapid development of artificial intelligence and soft robotics, researchers are currently trying to coat humanoid robots with an ‘artificial skin’ that replicates all the mechanical and sensory properties of human skin, so that they can also perceive the everchanging external environment like us.”