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Satiation variability prediction using AI for obesity treatment

Meal size and termination is regulated by a process called satiation, which varies widely among adults with obesity.

The researchers assessed calories to satiation (CTS) and integrated a machine learning genetic risk score (CTSGRS) to predict obesity treatment outcomes.

High CTS or CTSGRS identified individuals who responded better to phentermine-topiramate, whereas low CTS or CTSGRS predicted greater weight loss with liraglutide, highlighting personalized obesity therapy.

Squishy ‘smart cartilage’ could target arthritis pain as soon as flareups begin

Researchers have developed a material that can sense tiny changes within the body, such as during an arthritis flareup, and release drugs exactly where and when they are needed.

The squishy material can be loaded with that are released in response to small changes in pH in the body. During an flareup, a joint becomes inflamed and slightly more acidic than the surrounding tissue.

The material, developed by researchers at the University of Cambridge, has been designed to respond to this natural change in pH. As acidity increases, the material becomes softer and more jelly-like, triggering the release of drug molecules that can be encapsulated within its structure. Since the material is designed to respond only within a narrow pH range, the team says that drugs could be released precisely where and when they are needed, potentially reducing side effects.

The Hofstadter butterfly: Twisted bilayer graphene reveals two distinct strongly interacting topological phases

Magic-angle twisted bilayer graphene (MATBG) is a material created by stacking two sheets of graphene onto each other, with a small twist angle of about 1.1°. At this “magic angle,” electrons move very slowly, which can lead to the emergence of highly correlated electron states.

Due to its unique properties and characteristics, MATBG has become the focus of numerous studies rooted in physics and materials science. Some physicists discovered that when an is applied to MATBG, the flat energy bands in the material transform into a fractal-like energy pattern known as a Hofstadter spectrum.

Researchers at University of Washington, Florida State University and other institutes recently carried out a study aimed at further investigating the emergence of these energy patterns in ultraclean MATBG.

How evolution explains autism rates in humans

A paper in Molecular Biology and Evolution finds that the relatively high rate of autism-spectrum disorders in humans is likely due to how humans evolved in the past. The paper is titled “A general principle of neuronal evolution reveals a human accelerated neuron type potentially underlying the high prevalence of autism in humans.”

A new way to control terahertz light for faster electronics

In a breakthrough for next-generation technologies, scientists have learned how to precisely control the behavior of tiny waves of light and electrons, paving the way for faster communications and quantum devices.

Controlling light at the smallest scales is crucial for creating incredibly small, fast and efficient devices. Instead of bulky wires and circuits, we can use light to transmit information. One challenge of this approach is that light, with its relatively large wavelength, is not easily confined to small spaces.

However, in a study published in the journal Light: Science & Applications, researchers have developed a method to control tiny waves of light and electrons called Dirac plasmon polaritons (DPPs).

INTEGRAL observes exceptionally bright X-ray flares from Cygnus X-1

Using ESA’s INTEGRAL spacecraft, astronomers have detected exceptionally bright X-ray flares from the Cygnus X-1 X-ray binary system. This is the first time that such strong flaring activity has been observed in this system although it has been monitored for decades. The new findings were detailed in a paper published August 28 on the pre-print server arXiv.

Can Microsoft’s analog optical computer be the answer to more energy-efficient AI and optimization tasks?

The constant scaling of AI applications and other digital technologies across industries is beginning to tax the energy grid due to its intensive energy consumption. Digital computing’s energy and latency demands will likely continue to rise, challenging their sustainability.

Unsurprisingly, the reliance on these technologies in our modern world has researchers scrambling to produce more energy-efficient ways to move forward—and Microsoft might be ahead of the game. Microsoft’s researchers, along with a team from Cambridge University, have developed a new analog optical computer (AOC) that has the potential to give AI, as well as combinatorial optimization, a much needed boost in efficiency.

The AOC prototype is described in a recent study by the group that was published in Nature. The group combined analog electronics and microLED arrays, spatial light modulators, and photodetector arrays to accelerate both AI inference and combinatorial optimization on a single platform.

Scientists harness the power of collapsing bubbles to propel tiny robots

A team of scientists from China and the U.S. is pioneering the development of bubble-powered robots, which could one day replace needles for painless drug delivery into the body. Inspired by nature, the researchers developed a new technique that harnesses the energy released by a collapsing bubble in a liquid, a process known as cavitation.

The natural world has evolved ingenious ways to exploit cavitation for movement. For example, ferns use it within specialized cells in their sporangia to catapult spores, and mantis shrimps snap their appendages with such force that the resulting bubbles collapse with enough energy to stun their prey.

In their study, published in the journal Science, the team details how they used cavitation as a propulsion system for . They built millimeter-sized robots, called “jumpers,” out of , polypyrrole and titanium carbide that heated up quickly when hit by a laser.

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