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This study investigated neurodegeneration in MOGAD, independent of relapses, by comparing clinical, cognitive, and advanced MRI markers in MOGAD, relapsing-remitting MS, and healthy control.

Progression independent of relapse activity (PIRA) is a novel clinical concept in multiple sclerosis (MS) that describes an insidious, persistent disability accrual not related to attacks,1 occurring not only in progressive MS phenotypes but also in the early disease and relapsing-remitting phases (RRMS).1,2 PIRA seems to reflect the presence of chronic smoldering inflammation and subsequent neurodegenerative pathobiological processes in MS.2,3 Cognitive decline independent of relapse activity (cognitive PIRA) can be a sensitive measure of neurodegeneration in MS, even independent of clinical worsening,4,5 and in other neurodegenerative conditions.6,7 Longitudinal structural MRI (sMRI) brain volume loss, measured using MRI scans at different intervals, is a marker of progressive neuroaxonal loss and atrophy and has been used to assess treatment efficacy in MS.8–11 White matter atrophy involves myelin and axonal loss, often caused by Wallerian degeneration. Gray matter atrophy is widespread, affecting areas such as the neocortex, thalamus, hippocampus, and cerebellum, and is mainly due to neuroaxonal loss and neuronal shrinkage rather than demyelination.12–14

Diffusion-weighted imaging (dMRI) is an advanced MRI approach allowing the evaluation of the microstructural brain tissue damage. Neurite orientation dispersion and density imaging (NODDI) is a water-diffusion model, which can interpret changes within one of the three compartments: intra-axonal (neurite density index—NDI), extraneurite (ODI), and free water (isotropic volume fraction—ISOVF).15 The histopathologic validation studies on the NODDI model have shown significant correlations between the ODI and circular variance, a marker of neurite orientation variability, as well as between ODI and myelin staining fraction in MS samples.16 Negative correlations were observed between the NDI and circular variance in healthy controls (HCs) and positive correlations between NDI and markers of myelin, axon, and microglia content.

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IN A NUTSHELL 🔬 Japanese scientists have developed a groundbreaking technique using quantum mechanics to analyze plasma turbulence. 📊 The new method, called multi-field singular value decomposition, provides clearer insights into the interactions within fusion plasmas. 🌊 The research has implications beyond plasma physics, potentially impacting fields like weather dynamics and social systems. 🔍 By

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The harsh interstellar environment ought to destroy these carbon-rich molecules; experiments reveal their secret weapon.

Organic molecules called polycyclic aromatic hydrocarbons (PAHs) populate interstellar space and represent a major reservoir of carbon, an essential element for life. The smallest of these molecules mysteriously survive the harsh environment of space, and a research team has now explained how they do it [1]. In experiments in space-like conditions, the team showed that the molecules can use a process called recurrent fluorescence to shed some of the potentially destructive vibrational energy they receive from ultraviolet photons and molecular collisions. The results will help theorists model the dissemination of the building blocks of life throughout the cosmos.

PAHs form in dying stars and get ejected via supernovae into the interstellar medium. In 2021 they were detected in cold interstellar clouds (molecular clouds), and the JWST observatory has since confirmed widespread evidence for small PAHs at higher abundance than models predict. Small PAHs somehow survive ultraviolet radiation, molecular collisions, and other processes that trigger internal vibrations that can tear them apart.

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Scientists have been analyzing certain animals living within the CEZ for years, including bacteria, rodents, and even birds. One study back in 2016 found that Eastern tree frogs (Hyla orientalis), which are usually a green color, were more commonly black within the CEZ. The biologists theorize that the frogs experienced a beneficial mutation in melanin—pigments responsible for skin color—that helped dissipate and neutralize some of the surrounding radiation.

This made scientists ponder: could something similar be happening to Chernobyl’s wild dogs?

The study uncovered that the feral dogs living near the Chernobyl Power Plant showed distinct genetic differences from dogs living only some 10 miles away in nearby Chernobyl City. While this may seem to heavily imply that these dogs have undergone some type of rapid mutation or evolution due to radiation exposure, this study is only a first step in proving that hypothesis.

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In a monumental breakthrough, scientists have measured the speed of quantum entanglement for the first time—an achievement that is set to radically transform the way we understand the quantum world. For years, quantum entanglement was thought to be an instantaneous process, but this new research, published in Physical Review Letters, has pushed the boundaries of our knowledge, providing new insights into the quantum realm and setting the stage for revolutionary advances in data security and computational technologies.

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Physicists at the University of Oxford have set a new global benchmark for the accuracy of controlling a single quantum bit, achieving the lowest-ever error rate for a quantum logic operation—just 0.000015%, or one error in 6.7 million operations. This record-breaking result represents nearly an order of magnitude improvement over the previous benchmark, set by the same research group a decade ago.

To put the result in perspective: a person is more likely to be struck by lightning in a given year (1 in 1.2 million) than for one of Oxford’s quantum logic gates to make a mistake.

The findings, to be published in Physical Review Letters, are a major advance towards having robust and useful quantum computers.

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One of the current hot research topics is the combination of two of the most recent technological breakthroughs: machine learning and quantum computing.

An experimental study shows that already small-scale quantum computers can boost the performance of algorithms.

This was demonstrated on a photonic quantum processor by an international team of researchers at the University of Vienna. The work, published in Nature Photonics, shows promising for optical quantum computers.

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