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Category: computing – Page 6

This week, researchers uncovered the negative pressure mechanisms plants use to communicate stress. Linguists found that the melody of spoken language in English functions as its own, distinct language. And there was also depressing news! Like the Trump administration slashing NASA’s budget, which could scrap the James Webb Space Telescope right at the beginning of its operational life (they’re also pushing to scrap the completed Nancy Grace Roman Space Telescope before its launch).

Additionally, researchers found that the video game Dark Souls has positive psychological effects on players; a physicist made a new contribution to the theory that the universe is a computational process; and scientists in Spain mapped the brain connectivity patterns of psychosis patients:

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Our brain’s remarkable ability to form and store memories has long fascinated scientists, yet most of the microscopic mechanisms behind memory and learning processes remain a mystery. Recent research points to the importance of biochemical reactions occurring at postsynaptic densities—specialized areas where neurons connect and communicate. These tiny junctions between brain cells are now thought to be crucial sites where proteins need to organize in specific ways to facilitate learning and memory formation.

More specifically, a 2021 study revealed that memory-related proteins can bind together to form droplet-like structures at postsynaptic densities. What makes these structures particularly intriguing is their unique “droplet-inside-droplet” organization, which scientists believe may be fundamental to how our brains create lasting memories. However, understanding exactly how and why such complex protein arrangements form has remained a significant challenge in neuroscience.

Against this backdrop, a research team has developed an innovative computational model that reproduces these intricate protein structures. Their paper, published online in Cell Reports, explores the mechanisms behind the formation of multilayered protein condensates.

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An avalanche is caused by a chain reaction of events. A vibration or a change in terrain can have a cascading and devastating impact.

A similar process may happen when living tissues are subject to being pushed or pulled, according to new research published in Nature Communications, by Northeastern University doctoral student Anh Nguyen and supervised by Northeastern physics professor Max Bi.

As , Bi and Nguyen use and mathematics to understand the mechanical processes that organisms undergo on a cellular level. With this more recent work, they have observed that when subjected to sufficient stress, tissues can “suddenly and dramatically rearrange themselves,” similar to how avalanches are formed in the wild.

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In 2023, EPFL researchers succeeded in sending and storing data using charge-free magnetic waves called spin waves, rather than traditional electron flows. The team from the Lab of Nanoscale Magnetic Materials and Magnonics, led by Dirk Grundler, in the School of Engineering, used radiofrequency signals to excite spin waves enough to reverse the magnetization state of tiny nanomagnets.

When switched from 0 to 1, for example, this allows the nanomagnets to store digital information, a process used in computer memory, and more broadly, in information and communication technologies.

This work was a big step toward sustainable computing, because encoding data via (whose quasiparticles are called magnons) could eliminate the energy loss, or Joule heating, associated with electron-based devices. But at the time, the spin wave signals could not be used to reset the to overwrite existing data.

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Cancer creates an immunosuppressive environment that hampers immune responses, allowing tumors to grow and resist therapy. One way the immune system fights back is by inducing ferroptosis, a type of cell death, in tumor cells through CD8 + T cells. This involves lipid peroxidation and enzymes like lysophosphatidylcholine acyltransferase 3 (Lpcat3), which makes cells more prone to ferroptosis. However, the mechanisms by which cancer cells avoid immunotherapy-mediated ferroptosis are unclear. Our study reveals how cancer cells evade ferroptosis and anti-tumor immunity through the upregulation of fatty acid-binding protein 7 (Fabp7).

To explore how cancer cells resist immune cell-mediated ferroptosis, we used a comprehensive range of techniques. We worked with cell lines including PD1-sensitive, PD1-resistant, B16F10, and QPP7 glioblastoma cells, and conducted in vivo studies in syngeneic 129 Sv/Ev, C57BL/6, and conditional knockout mice with Rora deletion specifically in CD8+ T cells, Cd8 cre; Rorafl mice. Methods included mass spectrometry-based lipidomics, targeted lipidomics, Oil Red O staining, Seahorse analysis, quantitative PCR, immunohistochemistry, PPARγ transcription factor assays, ChIP-seq, untargeted lipidomic analysis, ROS assay, ex vivo co-culture of CD8+ T cells with cancer cells, ATAC-seq, RNA-seq, Western blotting, co-immunoprecipitation assay, flow cytometry and Imaging Mass Cytometry.

PD1-resistant tumors upregulate Fabp7, driving protective metabolic changes that shield cells from ferroptosis and evade anti-tumor immunity. Fabp7 decreases the transcription of ferroptosis-inducing genes like Lpcat3 and increases the transcription of ferroptosis-protective genes such as Bmal1 through epigenetic reprogramming. Lipidomic profiling revealed that Fabp7 increases triglycerides and monounsaturated fatty acids (MUFAs), which impede lipid peroxidation and ROS generation. Fabp7 also improves mitochondrial function and fatty acid oxidation (FAO), enhancing cancer cell survival. Furthermore, cancer cells increase Fabp7 expression in CD8+ T cells, disrupting circadian clock gene expression and triggering apoptosis through p53 stabilization. Clinical trial data revealed that higher FABP7 expression correlates with poorer overall survival and progression-free survival in patients undergoing immunotherapy.

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PRESS RELEASE — Quantum computers promise to speed calculations dramatically in some key areas such as computational chemistry and high-speed networking. But they’re so different from today’s computers that scientists need to figure out the best ways to feed them information to take full advantage. The data must be packed in new ways, customized for quantum treatment.

Researchers at the Department of Energy’s Pacific Northwest National Laboratory have done just that, developing an algorithm specially designed to prepare data for a quantum system. The code, published recently on GitHub after being presented at the IEEE International Symposium on Parallel and Distributed Processing, cuts a key aspect of quantum prep work by 85 percent.

While the team demonstrated the technique previously, the latest research addresses a critical bottleneck related to scaling and shows that the approach is effective even on problems 50 times larger than possible with existing tools.

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Imagine if our computers could think more like us—learning from experience, adapting on the go, and doing all this while using just a fraction of the energy. That’s not science fiction anymore. Welcome to the world of Neuromorphic Computing 🧠—a field that’s redefining how machines process information by taking inspiration from the most powerful processor we know: the human brain.

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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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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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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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