This study explores the relationships among the vascular NOTCH3 ECD deposition load, the NOTCH3 variant genotype, and CADASIL disease severity.
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Experimental proof shows quantum world is even stranger than previously thought
The quantum world is famously weird—a single particle can be in two places at once, its properties are undefined until they are measured, and the very act of measuring a quantum system changes everything. But according to new research published in Physical Review Letters, the quantum world is even stranger than previously thought.
What happens at the quantum level is in stark contrast to the classical world (what we see every day), where objects have definite properties whether or not we look at them, and observing them doesn’t change their nature. To see whether any system is behaving classically, scientists use a mathematical test called the Leggett-Garg inequality (LGI). Classical systems always obey the LGI limit while quantum systems violate it, proving they are non-classical.
New deep-learning tool can tell if salmon is wild or farmed
A paper published in Biology Methods and Protocols, finds that it is now possible to distinguish wild from farmed salmon using deep learning, potentially greatly improving strategies for environmental protection. The paper is titled “Identifying escaped farmed salmon from fish scales using deep learning.”
Norway is home to the largest remaining wild populations of wild salmon and is also one of the largest producers of farmed salmon. Atlantic salmon abundance in Norway has declined by over 50% since the 1980s and is now at historically low levels. Escaped farmed salmon are an important reason for this decline.
Norway produces over 1.5 million metric tons of farmed Atlantic salmon annually. Each year, however, approximately 300,000 farmed salmon escape into the wild.
Puzzling ultraviolet radiation in the birthplaces of stars
Researchers used the MIRI instrument onboard the James Webb Space Telescope (JWST) to identify the presence of ultraviolet radiation in five young stars in the Ophiuchus region, and to understand its role in the formation of stars. The discovery of UV radiation around these protostars and its significant impact on the surrounding material is a challenge to models describing the formation of stars.
The paper is published in Astronomy & Astrophysics, and the research team included Iason Skretas, a doctoral student at MPIfR, and Dr. Agata Karska (Center for Modern Inter-disciplinary Technologies at Nicolaus Copernicus University in Torun, Poland, and Max Planck Institute of Radio Astronomy (MPIfR), Bonn, Germany).
After nearly 100 years, scientists may have detected dark matter
In the early 1930s, Swiss astronomer Fritz Zwicky observed galaxies in space moving faster than their mass should allow, prompting him to infer the presence of some invisible scaffolding—dark matter—holding the galaxies together. Nearly 100 years later, NASA’s Fermi Gamma-ray Space Telescope may have provided direct evidence of dark matter, allowing the invisible matter to be “seen” for the very first time.
Dark matter has remained largely a mystery since it was proposed so many years ago. Up to this point, scientists have only been able to indirectly observe dark matter through its effects on observable matter, such as its ability to generate enough gravitational force to hold galaxies together.
The reason dark matter can’t be observed directly is that the particles that make up dark matter don’t interact with electromagnetic force—meaning dark matter doesn’t absorb, reflect or emit light.
Adaptive method helps light-based quantum processors act more like neural networks
Machine learning models called convolutional neural networks (CNNs) power technologies like image recognition and language translation. A quantum counterpart—known as a quantum convolutional neural network (QCNN)—could process information more efficiently by using quantum states instead of classical bits.
Photons are fast, stable, and easy to manipulate on chips, making photonic systems a promising platform for QCNNs. However, photonic circuits typically behave linearly, limiting the flexible operations that neural networks need.
Reducing social media use for just a week can improve mental health
In a new study, published in JAMA Network Open, 295 participants report promising mental health benefits after reducing their social media usage for a week. The cohort consisted of young adults from the ages of 18 to 24—the age group commonly associated with the highest social media usage, as well as a heightened risk of mental health issues.
Although many self-reports have surfaced online indicating that reducing social media use has been beneficial in various ways, the scientific link between social media use and youth mental health is still debated, with past studies showing mixed results.