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In research inspired by the principles of quantum mechanics, researchers from Pompeu Fabra University (UPF) and the University of Oxford reveal new findings to understand why the human brain is able to make decisions quicker than the world’s most powerful computer in the face of a critical risk situation. The human brain has this capacity despite the fact that neurons are much slower at transmitting information than microchips, which raises numerous unknown factors in the field of neuroscience.

The research is published in the journal Physical Review E.

It should be borne in mind that in many other circumstances, the human brain is not quicker than technological devices. For example, a computer or calculator can resolve mathematical operations far faster than a person. So, why is it that in critical situations—for example, when having to make an urgent decision at the wheel of a car—the human brain can surpass machines?

Adding immunotherapy to a new type of inhibitor that targets multiple forms of the cancer-causing gene mutation KRAS kept pancreatic cancer at bay in preclinical models for significantly longer than the same targeted therapy by itself, according to researchers from the Perelman School of Medicine at the University of Pennsylvania and Penn Medicine’s Abramson Cancer Center. The results, published in Cancer Discovery, prime the combination strategy for future clinical trials.

Patients with pancreatic cancer have an overall poor prognosis: in most patients, the disease has already spread at the time of diagnosis, resulting in limited treatment options. Nearly 90 percent of pancreatic cancers are driven by KRAS mutations, the most common cancer-causing gene mutation across cancer types, which researchers long considered “undruggable.”

In 2021, the first KRAS inhibitor was approved to treat with KRAS G12C mutations, but with longer follow-up, it has become clear that KRAS-mutant cancers can quickly evolve to resist therapies targeted at one specific form of the gene mutation.

Searching for life on other celestial bodies, or at the very least the necessary components to support it, has been fascinating scientists and enthusiasts for centuries. While planets are the obvious choice, their moons can also harbor the chemical ingredients for life.

Saturn is orbited by 146 moons, with Enceladus being the sixth largest at approximately 500km in diameter. This small, icy moon is characterized by its highly reflective white surface and geyser-like jets releasing ice and water vapor hundreds of kilometers into space from its south pole.

NASA’s Cassini spacecraft identified these jets in 2005, before going on to sample them in 2008, 2009 and 2015. Consequently, scientists found that the hot mineral-rich waters possess the necessary components for life, despite the moon’s surface reaching extreme temperatures of −201°C.

Researchers at the TechMed Center of the University of Twente and Radboud University Medical Center have removed blood clots with wireless magnetic robots. This innovation promises to transform treatment for life-threatening vascular conditions like thrombosis.

Cardiovascular diseases such as thrombosis are a major global health challenge. Each year worldwide, 1 in 4 people die from conditions caused by blood clots. A blood clot blocks a blood vessel, preventing the blood from delivering oxygen to certain areas of the body.

Minimally invasive Traditional treatments struggle with clots in hard-to-reach areas. But magnetic microrobots bring hope to patients with otherwise inoperable clots. The screw-shaped robots can navigate through intricate vascular networks since they are operated wirelessly.

In the spring of 2022, Tim Story’s doctor told him that he likely had just months to live. Story, a high school football coach in Hattiesburg, Mississippi, had been diagnosed with Stage 3 small bowel cancer two years earlier, at the age of 49, after mysterious pains in his side turned out to be a tumor in his small intestine. Surgery and several grueling rounds of chemotherapy and immunotherapy had failed to stop the cancer, which had spread to other organs.

The Nano Materials Research Division at the Korea Institute of Materials Science (KIMS), led by Dr. Tae-Hoon Kim and Dr. Jung-Goo Lee has successfully developed a grain boundary diffusion process that enables the fabrication of high-performance permanent magnets without the use of expensive heavy rare earth elements. This pioneering technology marks the world’s first achievement in this field.

The findings are published in Acta Materialia.

Permanent magnets are key components in various high-value-added products, including electric vehicle (EV) motors and robots. However, conventional permanent magnet manufacturing processes have been heavily dependent on heavy rare earth elements, which are exclusively produced by China, leading to high resource dependency and .

“‘Incipient ferroelectricity’ means there’s no stable ferroelectric order at room temperature,” lead author Dipanjan Sen explains of the property that the team investigated. “Instead, there are small, scattered clusters of polar domains. It’s a more flexible structure compared to traditional ferroelectric materials.”

Typically, the “relaxor” behavior of incipient ferroelectric materials at room temperature is a drawback, making their operation less predictable and more fluid — but the team’s breakthrough was to approach it as an advantage instead, showing how it could be of use in devices like neuromorphic processors that increase machine learning and artificial intelligence performance by processing information like the neurons in the human brain.

“To test this,” co-author Mayukh Das says, “we performed a classification task using a grid of three-by-three pixel images fed into three artificial neurons. The devices were able to classify each image into different categories. This learning method could eventually be used for image identification and classification or pattern recognition. Importantly, it works at room temperature, reducing energy costs. These devices function similarly to the nervous system, acting like neurons and creating a low-cost, efficient computing system that uses a lot less energy.”

In September 2024, OpenAI released its o1 model, trained on large-scale reinforcement learning, giving it “advanced reasoning” capabilities. Unfortunately, the details of how they pulled this off were never shared publicly. Today, however, DeepSeek (an AI research lab) has replicated this reasoning behavior and published the full technical details of their approach. In this article, I will discuss the key ideas behind this innovation and describe how they work under the hood.