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Blood test detects aggressive brain tumors early and could reduce need for risky surgery

Researchers at the University of Sussex, in collaboration with scientists from different institutes worldwide, have identified a blood test capable of early diagnosis of the most aggressive form of brain tumor. The technology has the potential to save lives. Lead author Professor Georgios Giamas and his team have identified distinctive biomarkers (molecules that act as signs of normal processes, diseases, or responses to treatment) within patient blood samples, which could signal the presence of glioblastoma, one of the most aggressive forms of brain tumor.

The study published in Cell Reports Medicine investigated whether a simple blood test—analyzing the cargo of tiny particles called small extracellular vesicles (sEVs) that are released by cells into the bloodstream—could accurately detect and classify these tumors.

More than 11,000 people are diagnosed with a primary brain tumor in the U.K. each year. Glioblastoma is the most common high grade primary brain tumor in adults, which means it can grow and spread exceptionally quickly. Currently, diagnosing glioma often requires risky brain surgery.

Primary sclerosing cholangitis

Primary sclerosing cholangitis is a rare, chronic cholestatic liver disease characterised by biliary inflammation and fibrosis. Inflammatory bowel disease co-occurs in 50–80% of individuals with primary sclerosing cholangitis and there is an increased risk for hepatobiliary and colorectal cancers. Primary sclerosing cholangitis presentation is highly variable but there is usually a slowly progressive fibrosis of the bile ducts with strictures, development of liver fibrosis and cirrhosis, and eventually a need for liver transplantation, after which primary sclerosing cholangitis can reoccur.

Sinus MCs are enriched in burn pit–exposed military veterans with CRS and in mice exposed to environmental combustion-related compounds

Address correspondence to: Taylor A. Doherty, UCSD, 9,500 Gilman Drive, La Jolla, California 92093–0635, USA. Phone: 858.822.7563; Email: [email protected].

Find articles by Wang, X. in: | Google Scholar

¹VA San Diego Healthcare System, La Jolla, California, USA.

How Automation and AI Are Transforming Organoid Research

The life sciences are in the midst of a crucial shift, driven by the emergence of organoid-based models and the power of automation. Organoids—three-dimensional cell cultures that mimic human tissue architecture and function—are enabling researchers to ask and answer questions that were once beyond reach. Paired with advances in automation, robotics, and artificial intelligence (AI), these models are transforming drug discovery and preclinical testing, offering a more human-relevant alternative to outdated 2D cell cultures and animal models. This revolution is reshaping the pharmaceutical industry, while also holding the potential to accelerate progress in personalized medicine.

Beyond 2D: The Rise of Organoids

For decades, preclinical research has relied on 2D cell cultures, single-cell-type 3D spheroid models, and animal models, despite their limitations in replicating human biology. Organoids, which are derived from stem cells, offer a more accurate representation of human tissues, recapitulating complex biological processes such as organ-specific functionality and cellular interactions. These miniature self-organizing biological systems are being used to model diseases, test drug efficacy and toxicity, and even explore regenerative medicine.

What a Neutron Star Is Really Made Of

What happens to matter when it’s crushed beyond the point where atoms can exist? Inside a neutron star, the densest visible object in the universe, matter is compressed into states so extreme that physicists still don’t fully understand what’s there.

In this calm long-form space documentary, we take a journey layer by layer through the interior of a neutron star — from the crystalline crust where exotic nuclei form structures unlike anything on Earth, through the bizarre \.

Universal Quantum Computing as a Markov Chain

Let’s say you have a probabilistic computer with a single bit of memory. Some algorithms on the computer will stochastically flip the single bit of memory such that its new value will be uniformly distributed with a 50% chance of being 0 and a 50% chance of being 1. Other programs will place it into a degenerate distribution, meaning it either has 100% chance of being 0 every time you run the program, or other programs will produce 1 100% of the time.

A magician tells you to run one of the programs in one of the two categories of your choosing and then copy the computer’s memory state onto a thumb drive and hand it to him. You pick one, run the program, copy the bit of the memory to your thumb drive, then hand it to the magician. The magician then does something with the thumb drive you cannot see, then looks up at you and tell you exactly what category the program you ran to produce that bit came from.

Curious, you repeat this many times over: you run a program from one of the two categories (degenerate or uniform), copy the bit value produced from the algorithm, and then hand the thumb drive to the magician. Each and every time he always correctly guesses which category of program was ran to produce it.

How Elasticity Shapes Nematic Criticality

A 19th-century theory of elasticity inspires a new way to analyze a quantum phase transition that has become central to modern quantum materials research.

When a crystalline metal enters a so-called nematic state, the onset of strong fluctuations among interacting electrons spontaneously breaks the crystal’s rotational symmetry and distorts both the physical lattice and the notional Fermi surface. This transition, known as nematic criticality, has been observed near the onset of superconductivity in cuprates, pnictides, and twisted bilayer graphene and could hold the key to explaining these poorly understood forms of superconductivity. Now Joe Meese and Rafael Fernandes of the University of Illinois-Champaign have proposed that nematic criticality is more selective in how it breaks rotational symmetry than previously assumed [1, 2]. The selectivity arises not from a novel microscopic mechanism but from a geometric constraint.

Nematic order typically develops spontaneously upon cooling; hydrostatic pressure can shift the transition, while uniaxial stress can tune the transition or induce nematicity by linearly coupling to lattice strain. Because of this connection, nematic order obeys the same mechanical laws as other continuous lattice deformations do. Consequently, as Meese and Fernandes showed, nematic order splits into two classes. One class is compatible with the lattice and can turn critical; the other is incompatible with the lattice and is therefore suppressed (Fig. 1). In the conventional picture, the energy cost of completing a nematic transition is “softened”—that is, reduced by the emergence of fluctuations as the transition is approached. That condition remains true in Meese and Fernandes’ picture, but the softening is not spread over all the possible distortions allowed by symmetry. Rather, elasticity itself selects the modes that participate in nematic criticality.

Bringing quantum time into the lab—a single clock can run young and old at once

Few concepts in physics are as familiar, yet as enigmatic, as time. In Einstein’s theory of relativity, time is not absolute: its passage depends on motion and gravity. But when combined with quantum physics, this relativistic form of time becomes even more counterintuitive.

According to quantum theory, the flow of time itself may exist in a genuine quantum superposition, ticking faster and slower at the same time. Now, a new paper titled “Quantum signatures of proper time in optical ion clocks”, published in Physical Review Letters, shows that this striking possibility may soon be tested in the laboratory.

In this work, a team led by Assistant Professor of theoretical physics Igor Pikovski at Stevens Institute of Technology, in collaboration with experimental groups of Christian Sanner at Colorado State University and Dietrich Leibfried at the National Institute of Standards and Technology (NIST), explores quantum aspects of the flow of time and how they can be accessed with atomic clocks.

A long-sought quantum computing milestone arrives as fermionic atom gates top 99% accuracy

Two independent research teams have each demonstrated collisional quantum gates using fermionic atoms: a long-sought milestone in quantum computing where logic operations are performed through the direct physical overlap of atoms, rather than forcing them into fragile, highly excited states.

The studies have been published simultaneously in Nature: the first led by Petar Bojović at the Max Planck Institute for Quantum Optics in Garching, Germany, and the second by Yann Kiefer and colleagues at ETH Zurich, Switzerland.

Quantum gas resists heating under periodic kicks, revealing many-body localization mechanism

A joint theoretical study by the University of Innsbruck and Zhejiang University has uncovered the microscopic origin of a striking quantum phenomenon: a periodically driven gas of ultracold atoms that simply refuses to heat up, defying classical expectations.

Push a swing repeatedly in rhythm, and it swings higher and higher, absorbing more and more energy. A quantum gas, however, can behave very differently. Under periodic kicks, quantum interference can freeze energy absorption entirely, a phenomenon known as dynamical localization. Whether this survives when particles interact with each other has been a long-standing open question. A 2025 experiment by the research group of Hanns-Christoph Nägerl at the Department of Experimental Physics confirmed that it can. But the microscopic reasons remained until now unclear.

A new theoretical study by Prof. Lei Ying’s team at Zhejiang University, in collaboration with Prof. Hanns-Christoph Nägerl’s group at the University of Innsbruck, published in Physical Review Letters, provides the missing explanation. The team developed a mathematical framework that transforms the complex-driven many-body problem into a tractable lattice model. This reveals that interactions introduce a universal power-law structure that reshapes localization—and ultimately drives its breakdown at intermediate interaction strengths.

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