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AI-designed universal vaccine clears first human trial, targets future coronavirus threats with needle-free delivery

The first human clinical trial of a universal Sarbeco coronavirus vaccine, developed by the University of Cambridge and spin-out DIOSynVax (DVX) Ltd, has shown that the vaccine is safe and has no significant side effects.

The trial, involving 39 healthy volunteers, tested a vaccine designed to provide protection against multiple Sarbeco coronaviruses—the large group of viruses that occur in nature including SARS-CoV-2, which caused the COVID pandemic.

The vaccine triggered immune responses in the volunteers not only to SARS-CoV-2 and SARS, but to related bat viruses that could potentially jump from animals to humans and cause future pandemics.

Memory, agency, and learning in biological and AI systems with Michael Levin and Katrina Schleisman

What if memory isn’t storage at all — but a message from your past self that has to be interpreted?

In this episode, biologist Michael Levin and cognitive neuroscientist Katrina Schleisman join me to take apart one of the most quietly broken ideas in science and AI: that memory works like a hard drive. It doesn’t. And once you see why, a lot of assumptions about minds, machines, and what it means to \.

Massimo (@Rainmaker1973) on X

Scientists have identified a reversal of the long-standing Flynn effect—the roughly 200-year trend of rising average intelligence (measured via IQ and cognitive tests) across generations. For the first time in modern recorded history, Generation Z (born roughly 1997–2012) shows lower performance than previous generations in key cognitive domains, including attention, memory, literacy, numeracy, executive function, problem-solving, and general IQ—despite spending more years in formal education than ever before. Neuroscientist and educator Dr. Jared Cooney Horvath, PhD, MEd, testified before the U.S. Senate Committee on Commerce, Science, and Transportation on January 15, 2026, highlighting this shift. In his written testimony, he stated that cognitive development in children across much of the developed world has stalled or reversed over the past two decades, with declines evident in international assessments (e.g., PISA, TIMSS) and other large-scale data starting around the mid-2000s and accelerating post-2010. Horvath attributes the primary driver not to reduced schooling, but to the widespread integration of digital screens and educational technology (EdTech) in classrooms. He argues that human brains evolved for deep, focused learning through face-to-face interaction and sustained attention, not fragmented skimming or constant task-switching encouraged by devices. Key points from his testimony include: — Teens now spend over half their waking hours on screens, with significant portions in school involving computers or tablets—often leading to off-task behavior and shallower processing. — Evidence from meta-analyses and national/international studies shows a consistent pattern: higher classroom screen exposure correlates with weaker outcomes in reading, math, science, and higher-order reasoning. — Digital tools may aid narrow, repetitive skill practice in controlled settings, but in core academic contexts, they tend to reduce depth of understanding, retention, and critical thinking. Horvath describes this as a “structural mismatch” between human cognition and how digital platforms are designed (to capture and fragment attention), warning that unchecked EdTech adoption risks long-term harm to workforce skills, innovation, and societal reasoning. [Horvath, J. C. (2026). Written testimony before the U.S. Senate Committee on Commerce, Science, and Transportation. U.S. Senate]

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Quantum mechanics theory may work without imaginary numbers, new analysis suggests

Physicists from Heinrich Heine University Düsseldorf (HHU) have examined a fundamental property of quantum mechanics in collaboration with the German Aerospace Center (DLR). In an article published in the journal Physical Review Letters, they show that this theory does not necessarily need to be formulated with imaginary numbers—real numbers can, in fact, also be used.

The physical theory of quantum mechanics describes the world of atomic and subatomic particles. Its development began in the 1900s with physicists such as Max Planck, Niels Bohr, Werner Heisenberg and Erwin Schrödinger.

Quantum mechanics can effectively describe phenomena at microscopic scales, including, for example, the diffraction of particles at a double slit —which shows that particles also exhibit wave-like behavior—and the quantum tunneling effect, in which a certain probability exists that particles can penetrate a barrier even if they have insufficient energy to do so. Particularly important phenomena today include entanglement and coherence, which are key for applications such as quantum computers and communication.

Faster aptamer screening finds synthetic alternatives to antibodies in days instead of months

Aptamers are short DNA or RNA strands that can recognize and bind to a specific target molecule with high precision. Similar to antibodies, they can be used to detect these molecules or modulate their activity. Unlike antibodies, they are much more stable, can be produced synthetically and can be chemically modified to achieve the desired properties. As a result, they can offer capabilities that cannot be achieved with antibodies.

As demand grows for accurate and rapid diagnostic tools, aptamers are often better suited to these applications than antibodies. However, developing aptamers is both experimentally demanding and time-consuming. A team of scientists from IOCB Prague, led by Dr. Marek Ondruš and Prof. Michal Hocek, has now developed a technology that significantly shortens the development process. Their research is published in the journal Nature Communications.

Driverless cars are on the rise and now we may know why they crash

For the first time, new algorithms may be able to automatically explain why some self-driving cars crash—a question crucial to answer as more autonomous vehicles take to the roads. This new approach, developed by researchers at King’s College London, reviews past events to explain why specific instances of failure happened, in the hope that this can be used to make improvements in the future.

The research was presented at the 2026 IEEE International Conference of Robotics and Automation.

Self-driving vehicles are increasingly being rolled out across the globe, in cities like London and San Francisco, but collisions and serious breaches of road safety have put pressure on manufacturers to explain why they make the mistakes they do. This is often hard to do, and current methods only provide limited explanations for these.

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