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Indiana University School of Medicine scientists have developed a powerful new imaging technique to study bone marrow in mouse models. By overcoming key challenges unique to imaging this complex tissue, this advancement could support future drug development and therapies for conditions involving bone marrow, including cancers, autoimmune diseases and musculoskeletal disorders.

The new method was made possible by the multiplex imaging tool Phenocycler 2.0, which enabled researchers to visualize a record number of cellular markers within intact tissue from mice. The findings are published in Leukemia.

“Bone marrow is difficult to study because it is gelatinous and encased in hard bone,” said Sonali Karnik, Ph.D., assistant research professor of orthopedic surgery at the IU School of Medicine and co-lead author of the study. “Since bone marrow plays an important role in blood and immune cell formation and houses valuable stem cells, our unique imaging approach offers a useful tool for a variety of research applications.”

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A study led by Pompeu Fabra University reveals which brain mechanisms allow psychosis to remit. The results of this pioneering research could have important clinical implications for exploring new intervention strategies in patients with psychosis. The study was carried out in collaboration with one of the main psychiatry groups at Lausanne University Hospital (Switzerland).

The study examines differences in the neural connectivity patterns of patients who have recovered from psychosis and subjects who have not. Identifying these differences using computational models has enabled determining which patterns of neural connectivity facilitate the remission of the disease.

The results of the research have recently been published in an article in the journal Nature Mental Health. Its principal author is Ludovica Mana, a doctor and neuroscientist of the Computational Neuroscience group at the UPF Center for Brain and Cognition (CBC). The main co-investigators are Gustavo Deco and Manel-Vila Vidal, director and researcher with the same research group, respectively.

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Using the Australian Square Kilometer Array Pathfinder (ASKAP), astronomers have discovered 15 new giant radio galaxies with physical sizes exceeding 3 million light years. The finding was reported in a research paper published April 9 on the arXiv preprint server.

The so-called giant radio galaxies (GRGs) have an overall projected linear length exceeding at least 2.3 million light years. They are rare objects grown usually in low-density environments and display jets and lobes of synchrotron-emitting plasma. GRGs are important for studying the formation and the evolution of radio sources.

ASKAP is a 36-dish radio-interferometer operating at 700 to 1,800 MHz. It uses to achieve extremely high survey speed, making it one of the best instruments in the world for mapping the sky at radio wavelengths. Due to its large field of view, high resolution, and good sensitivity to low-surface brightness structures, ASKAP has been essential in the search for new GRGs.

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The detection of dark matter, an elusive form of matter believed to account for most of the universe’s mass, remains a long-standing goal within the physics research community. As this type of matter can only emit, reflect or absorb light very weakly, it cannot be observed using conventional telescopes and experimental methods.

Physicists have thus been trying to predict what it may consist of and proposing alternative approaches that could enable its detection. Dark compact objects are a class of dense and invisible structures that could be made up of dark matter, but that have never been directly observed so far.

Researchers at Queen’s University and the Arthur B. McDonald Canadian Astroparticle Physics Research Institute recently introduced a new possible method for detecting dark compact objects by probing their interactions with photons (i.e., light particles). Their newly proposed approach, outlined in a paper published in Physical Review Letters, is based on the idea that as dark compact objects pass between the Earth and a , they will dim the light emitted by this star.

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Coordinating complicated interactive systems, whether it’s the different modes of transportation in a city or the various components that must work together to make an effective and efficient robot, is an increasingly important subject for software designers to tackle. Now, researchers at MIT have developed an entirely new way of approaching these complex problems, using simple diagrams as a tool to reveal better approaches to software optimization in deep-learning models.

They say the new method makes addressing these complex tasks so simple that it can be reduced to a drawing that would fit on the back of a napkin.

The new approach is described in the journal Transactions of Machine Learning Research, in a paper by incoming doctoral student Vincent Abbott and Professor Gioele Zardini of MIT’s Laboratory for Information and Decision Systems (LIDS).

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A U of A engineering researcher is using sunlight and semiconductor catalysts to produce hydrogen by splitting apart water molecules into their constituent elements.

“The process to form the semiconductor, called thermal condensation polymerization, uses cheap and Earth-abundant materials, and could eventually lead to a more efficient, economical path to clean energy than existing ,” says project lead Karthik Shankar of the Department of Electrical and Computer Engineering, an expert in the field of photocatalysis.

In a collaboration between the U of A and the Technical University of Munich, results of the research were published in the Journal of the American Chemical Society.

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Advances in high-throughput phenotyping (HTP) platforms together with genotyping technologies have revolutionized breeding of varieties with desired traits relying on genomic prediction. Yet, we lack an understanding of the expression of multiple traits at different time points across the entire growth period of the plant.

A research team, including IPK Leibniz Institute and the Max Planck Institute of Molecular Plant Physiology, has developed a computational approach to solve this problem. The results were published in the journal Nature Plants.

The phenome of a plant comprises the entirety of traits expressed at any given time, and is the integrated outcome of the effects of genetic factors, and their . Understanding how the crop phenome changes over time can help predict individual traits at specific time points in crop development. However, this problem is challenging not only because of the intricate dependence between individual traits, but also due to differences in how the phenomes of specific genotypes change over the plant life cycle.

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Scientists are using cutting-edge techniques to track water ice on the Moon—an essential resource for future space missions.

A University of Hawai‘i team utilized ShadowCam to peer into the Moon’s perpetually dark craters, refining estimates of surface ice. Another team introduced a cosmic ray-based method to detect deeply buried ice, a breakthrough in lunar exploration. Both approaches could revolutionize how we locate usable water beyond Earth, with Hawai‘i emerging as a key player in the growing space frontier.

Unlocking lunar water: why ice on the moon matters.

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RIKEN scientists have discovered how to manipulate molybdenum disulfide into acting as a superconductor, metal, semiconductor, or insulator using a specialized transistor technique.

By inserting potassium ions and adjusting conditions, they could trigger dramatic changes in the material’s electronic state—unexpectedly even turning it into a superconductor or insulator. This new level of control over a single 2D material could unlock exciting breakthroughs in next-gen electronics and superconductivity research.

Unlocking versatility in a single material.

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In a dramatic leap for astrophysics, Chinese researchers have recreated a key cosmic process in the lab: the acceleration of ions by powerful collisionless shocks.

By using intense lasers to simulate space-like conditions, they captured high-speed ion beams and confirmed the decades-old theory that shock drift acceleration, not shock surfing, is the main driver behind these energy gains. This discovery connects lab physics with deep-space phenomena like cosmic rays and supernova remnants, paving the way for breakthroughs in both fusion energy and space science.

Breakthrough in particle acceleration observed in lab.

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