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New method offers broader and faster detection of protein-ligand interactions

Long-known as the ‘workhorses of the cell,’ proteins are responsible for powering nearly every function in the body. Often critical to this is their interactions with other small molecules known as ligands. In a new study published in Nature Structural and Molecular Biology, the researchers introduce HT-PELSA, a high-throughput adaptation of an earlier tool that detects these interactions. This new tool can process samples at an unprecedented scale, a breakthrough that promises to accelerate drug discovery and our understanding of fundamental biological processes.

Still a fairly new tool itself, the original PELSA (peptide-centric local stability assay) method, launched last year by researchers identifies protein-ligand interactions by tracking how ligand binding affects protein stability. When a ligand binds to a protein, that part of the protein becomes more stable and less prone to the effects of enzymes like trypsin, which cuts proteins into smaller peptide fragments.

What made PELSA especially noteworthy was its ability to detect peptide-level changes in stability across the entire proteome – that is, across all of the proteins in an organism. Although effective, nearly every step in the PELSA workflow is done by hand, meaning scientists can only process a few samples at a time. This not only requires a lot of time and effort but also increases the risk of contamination and accidental error.

HT-PELSA streamlines this process significantly by shifting from full-size tubes to micro-wells. Such a change enables automation of PELSA’s steps and allows researchers to analyse hundreds of samples in parallel while maintaining the same sensitivity and reproducibility.

“Before, I could only do at most, maybe 30 samples per day,” said the first author of the study. “Now, with HT-PELSA, we can scan 400 samples per day – it has highly simplified the workflow”

While in PELSA, trypsin-cleaved peptides are separated from whole proteins based on their mass, HT-PELSA leverages the water-repellant nature of proteins. It utilises a surface that proteins stick to more readily than peptides, thus allowing the scientists to separate the two. This not only further automates the process, but also enables the detection of membrane proteins that, up until now, were hard or even impossible to study.

Scientists develop a glasses-free 3D system with a little help from AI

Watching 3D movies and TV shows is a fun and exciting experience, where images leap out of the screen. To get this effect, you usually have to wear a special pair of glasses. But that could soon be a thing of the past as scientists have developed a new display system that delivers a realistic 3D experience without the need for any eyewear.

The main reason why we’ve waited so long for a screen like this is a tough physics rule called the Space-Bandwidth Product (SBP). To get a perfect 3D image, you need a big screen (the “space”) and a wide viewing area (the “bandwidth”) so the picture looks good even when you turn your head. Unfortunately, according to the rule, you can’t have both at the same time. If you make the screen big, the viewing angle shrinks. If you increase the viewing area, the TV must get smaller. All previous attempts to break this trade-off have failed. But not this time.

Classical Indian dance inspires new ways to teach robots how to use their hands

Researchers at the University of Maryland, Baltimore County (UMBC) have extracted the building blocks of precise hand gestures used in the classical Indian dance form Bharatanatyam—and found a richer “alphabet” of movement compared to natural grasps. The work could improve how we teach hand movements to robots and offer humans better tools for physical therapy.

A paper describing this work is published in the journal Scientific Reports.

Ramana Vinjamuri, a professor at UMBC and lead researcher on the work, has focused his lab on understanding how the brain controls complex hand movements. More than a decade ago, he and his research partners began searching for and cataloging the building blocks of hand motions, drawing on a concept called kinematic synergies, in which the brain simultaneously coordinates multiple joint movements to simplify complex motions.

A direct leap into terahertz: Dirac materials enable efficient signal conversion at room temperature

Highspeed Internet, autonomous driving, the Internet of Things: data streams are proliferating at enormous speed. But classic radio technology is reaching its limits: the higher the data rate, the faster the signals need to be transmitted.

Researchers at the Helmholtz-Zentrum Dresden-Rossendorf (HZDR) have now demonstrated that weak radio signals can be efficiently converted into significantly higher frequencies using this material that is just several tens of nanometers thick. And at room temperature, at that. The results open up prospects for future generations of mobile communications and high-resolution sensor technology. The paper is published in the journal Communications Physics.

The more data to be transmitted simultaneously, the higher the carrier frequency must be. As a result, research is now delving into the terahertz range. This frequency spectrum lies outside the microwave range currently used and, so far, has been difficult to access technologically.

China’s AI Chip Output Is Expected to Far Exceed Domestic Demand, as NVIDIA’s CEO Warns the World About the AI ‘Belt & Road’ Initiative

China’s AI industry is evolving at a rapid pace, to the point where domestic chip manufacturers are expected to outproduce regional demand, and NVIDIA CEO has warned about the ‘Chinese AI diffusion’ in place.

Ever since China has moved towards focusing on the adoption of domestic AI solutions, the region has seen a massive rise in chip production, since companies like Huawei, Cambricon, Biren, and many others are coming up with AI chips, with the ‘promise’ of replacing NVIDIA’s tech stack entirely. Based on an analysis by Bernstein (via Jukan), it is estimated that China’s AI chip supply is expected to rise significantly over the years, potentially surpassing domestic demand by 2028. This indicates that the nation has plans to move its tech stack towards the global market. NVIDIA’s CEO Jensen Huang has labeled this move as the AI ‘Belt & Road’ Initiative.

Out of all the Chinese AI firms competing, it is expected that Huawei will capture a whopping 50% share by 2026, significantly shrinking NVIDIA’s lead in the region. One of the main bottlenecks faced by firms like Huawei is the lack of semiconductor production capabilities. However, it appears that the firm plans to address this issue soon, through its own fab buildout, which will be facilitated by collaboration with local governments, as well as companies like SMIC. Similarly, Huawei also faces an HBM capacity problem, but based on Bernstein’s estimates, it is expected that all supply constraints will be addressed.

“Nobody Wanted NVIDIA’s First AI Supercomputer Except Elon Musk,” Reveals Jensen Huang; Fast-Forward, and Everyone’s Desperate to Buy One

NVIDIA’s CEO was surprisingly spotted on the Joe Rogan podcast, and one of the interesting stories he mentioned was how the interest in NVIDIA’s first AI machine was almost nonexistent.

Jensen, appearing on the ‘Joe Rogan Experience’ platform, was something that I wasn’t expecting at all, but it appears that NVIDIA’s CEO has become a mainstream personality, not just at the AI front, but also for the entire tech world. Jensen Huang talked about various aspects of his life and the journey of NVIDIA over the years, but one of the more interesting statements was around how Team Green spent ‘billions’ creating the very first DGX-1 AI system, but when Jensen went out to the market, the interest around the machine was ‘zero’, until Elon stepped up.

And when I announced DGX-1, nobody in the world wanted it. I had no purchase orders, not one. Nobody wanted to buy it. Nobody wanted to be part of it. Except for Elon.

Is AI the Next Evolution of Our Minds?

What if the future of intelligence isn’t human? In this video, we explore Hans Moravec’s prophetic vision about Artificial Intelligence from his breakthrough book, Mind Children—a world where conscious, superintelligent AIs don’t just outthink us, but carry our legacy forward. Instead of fearing them, should we embrace them as the next phase of mind? If consciousness is our greatest gift, maybe our most important mission is to make sure it survives—even if that means passing the torch to our digital descendants.

0:00 Intro.
1:46 The Inevitability of Smarter, Conscious Machines.
4:45 Beyond Biology: The Short-Sightedness of Flesh-Centric Thinking.
6:09 AI Consciousness: A Lifeboat for the Mind.
8:07 Toward a Conscious Future.
9:02 Outro

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