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Dark matter detector succeeds in performing measurements with nearly no radioactive interference

In their search for dark matter, scientists from the XENON Collaboration are using one of the world’s most sensitive dark matter detectors, XENONnT at the Gran Sasso Laboratory of the National Institute of Nuclear Physics INFN in Italy, to detect extremely rare particle interactions. These could provide clues about the nature of dark matter. The problem, however, is that tiny amounts of natural radioactivity generate background events that can mask these weak signals.

The XENONnT experiment has made a breakthrough by significantly reducing one of the most problematic contaminants— , a radioactive gas. For the first time, the research team has succeeded in reducing the detector’s radon-induced radioactivity to a level a billion times lower than the very low natural radioactivity of the human body.

The underlying technology, which the XENONnT consortium reports in the current issue of the Physical Review X, was developed by a team led by particle physicist Prof Christian Weinheimer from the University of Münster.

Most effective digital interventions to stop smoking identified

Smoking remains one of the most deleterious habits for human health, as it is known to increase the risk of several life-threatening diseases, including lung and throat cancers, heart disease and strokes. While most smokers are well aware of its associated health risks, ceasing this habit can be a very difficult process.

Moreover, conventional programs for cessation, such as those based on psychotherapy or , are not financially or physically accessible for all individuals who wish to stop smoking. In recent years, behavioral scientists and psychologists have been working with engineers to create digital interventions that support people in their efforts to quit this unhealthy habit.

Researchers at Sichuan University in China have carried out a and meta-analysis of past research studies investigating the effectiveness of various digital interventions for smoking cessation. The results of their analyses, presented in a paper published in Nature Human Behavior, suggest that personalized and group-customized technology-based programs could be particularly beneficial for smokers who wish to quit, with middle-aged individuals responding better than younger populations.

Democratizing AI scientists using ToolUniverse

AI scientists are emerging computational systems that serve as collaborative partners in discovery. These systems remain difficult to build because they are bespoke, tied to rigid workflows, and lack shared environments that unify tools, data, and analyses into a common ecosystem. In omics, unified ecosystems have transformed research by enabling interoperability, reuse, and community-driven development; AI scientists require comparable infrastructure. We present ToolUniverse, an ecosystem for building AI scientists from any language or reasoning model, whether open or closed. TOOLUNIVERSE standardizes how AI scientists identify and call tools, integrating more than 600 machine learning models, datasets, APIs, and scientific packages for data analysis, knowledge retrieval, and experimental design. It automatically refines tool interfaces for correct use by AI scientists, creates new tools from natural language descriptions, iteratively optimizes tool specifications, and composes tools into agentic workflows. In a case study of hypercholesterolemia, ToolUniverse was used to create an AI scientist to identify a potent analog of a drug with favorable predicted properties. The open-source ToolUniverse is available at https://aiscientist.tools.

Engineers create first artificial neurons that could directly communicate with living cells

A team of engineers at the University of Massachusetts Amherst has announced the creation of an artificial neuron with electrical functions that closely mirror those of biological ones. Building on their previous work using protein nanowires synthesized from electricity-generating bacteria, the team’s discovery means that we could see immensely efficient computers built on biological principles which could interface directly with living cells.

“Our brain processes an enormous amount of data,” says Shuai Fu, a graduate student in electrical and engineering at UMass Amherst and lead author of the study published in Nature Communications. “But its power usage is very, very low, especially compared to the amount of electricity it takes to run a Large Language Model, like ChatGPT.”

The human body is over 100 times more electrically efficient than a computer’s electrical circuit. The is composed of billions of neurons, specialized cells that send and receive all over the body. While it takes only about 20 watts for your brain to, say, write a story, an LLM might consume well over a megawatt of electricity to do the same task.

Your pancreas may be making its own version of Ozempic

Alpha cells in the pancreas can produce GLP1, not just glucagon, offering a surprising backup system for blood sugar control.

Duke University scientists have discovered that pancreatic alpha cells, long believed to only produce glucagon, actually generate powerful amounts of GLP-1 — the same hormone mimicked by popular diabetes drugs like semaglutide (Ozempic and Wegovy). Even more surprisingly, when glucagon production is blocked, alpha cells “switch gears” and boost GLP-1 output, enhancing insulin release and blood sugar control.

A new study from Duke University School of Medicine is challenging long-standing views on blood sugar regulation — and pointing to a surprising new ally in the fight against type 2 diabetes.

HIV mystery uncovered: How the virus reprograms host cells to create perfect hiding places

For over three decades, HIV has played an elaborate game of hide-and-seek with researchers, making treating—and possibly even curing—the disease a seemingly insurmountable obstacle to achieve.

But scientists at Case Western Reserve University have made a breakthrough discovery that could fundamentally change strategies for treating HIV.

The team identified for the first time how HIV enters a in infected cells that allows the virus to “hide” from the immune system and current treatments.

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