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A “chaperone” molecule that slows the formation of certain proteins reversed disease signs, including memory impairment, in a mouse model of Alzheimer’s disease, according to a study from researchers at the Perelman School of Medicine at the University of Pennsylvania.

In the study, published in Aging Biology, researchers examined the effects of a compound called 4-phenylbutyrate (PBA), a fatty-acid molecule known to work as a “chemical chaperone” that inhibits . In mice that model Alzheimer’s disease, injections of PBA helped to restore signs of normal proteostasis (the protein regulation process) in the animals’ brains while also dramatically improving their performance on a standard memory test, even when administered late in the disease course.

“By generally improving neuronal and cellular health, we can mitigate or delay ,” said study senior author Nirinjini Naidoo, Ph.D., a research associate professor of Sleep Medicine. “In addition, reducing proteotoxicity— to the cell that is caused by an accumulation of impaired and misfolded proteins—can help improve some previously lost brain functions.”

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Taking inspiration from the human brain, researchers have developed a new synaptic transistor capable of higher-level thinking.

Designed by researchers at Northwestern University, Boston College and the Massachusetts Institute of Technology (MIT), the device simultaneously processes and stores information just like the . In new experiments, the researchers demonstrated that the transistor goes beyond simple machine-learning tasks to categorize data and is capable of performing associative learning.

Although previous studies have leveraged similar strategies to develop brain-like computing devices, those transistors cannot function outside cryogenic temperatures. The new device, by contrast, is stable at room temperatures. It also operates at fast speeds, consumes very little energy and retains stored information even when power is removed, making it ideal for real-world applications.

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In a novel study, researchers utilized ancient Mesopotamian bricks to gain insights into Earth’s magnetic field changes 3,000 years ago. This archaeomagnetic approach provides a more precise method for dating ancient artifacts and understanding historical magnetic field fluctuations.

Ancient bricks inscribed with the names of Mesopotamian kings have yielded important insights into a mysterious anomaly in Earth’s magnetic field 3,000 years ago, according to a new study involving UCL researchers.

The research, published on December 18 in the Proceedings of the National Academy of Sciences (PNAS), describes how changes in the Earth’s magnetic field imprinted on iron oxide grains within ancient clay bricks, and how scientists were able to reconstruct these changes from the names of the kings inscribed on the bricks.

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Researchers have discovered that AI memory consolidation processes resemble those in the human brain, specifically in the hippocampus, offering potential for advancements in AI and a deeper understanding of human memory mechanisms.

An interdisciplinary team consisting of researchers from the Center for Cognition and Sociality and the Data Science Group within the Institute for Basic Science (IBS) revealed a striking similarity between the memory processing of artificial intelligence (AI) models and the hippocampus of the human brain. This new finding provides a novel perspective on memory consolidation, which is a process that transforms short-term memories into long-term ones, in AI systems.

Advancing AI through understanding human intelligence.

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A groundbreaking detection of an extremely energetic cosmic ray by the Telescope Array experiment raises questions about its source, as it points to a cosmic void, challenging current theories in cosmic ray origins and high-energy physics.

Discovery of an Exceptional Extraterrestrial Particle

Researchers involved in the Telescope Array experiment have announced the detection of an extraordinarily energetic cosmic ray. This particle, which originated beyond our galaxy, possesses an astounding energy level of over 240 exa-electron volts (EeV). Despite this remarkable find, its exact source remains elusive, as its arrival direction does not point to any known astronomical entities.

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Absolutely empty – that is how most of us envision the vacuum. Yet, in reality, it is filled with an energetic flickering: the quantum fluctuations. Scientists are currently scientists are gearing up for a laser experiment intended to verify these vacuum fluctuations in a novel way, which could potentially provide clues to new laws in physics.

A research team from the Helmholtz-Zentrum Dresden-Rossendorf (HZDR) has developed a series of proposals designed to help conduct the experiment more effectively – thus increasing the chances of success. The team presents its findings in the scientific journal Physical Review D.

The physics world has long been aware that the vacuum is not entirely void but is filled with vacuum fluctuations – an ominous quantum flickering in time and space. Although it cannot be captured directly, its influence can be indirectly observed, for example, through changes in the electromagnetic fields of tiny particles.

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Neurons communicate through chemical signals known as neurotransmitters. Researchers at St. Jude Children’s Research Hospital, leveraging their expertise in structural biology, have successfully elucidated the structures of the vesicular monoamine transporter 2 (VMAT2), a key component of neuronal communication.

By visualizing VMAT2 in different states, scientists now better understand how it functions and how the different shapes the protein takes influence drug binding — critical information for drug development to treat hyperkinetic (excess movement) disorders such as Tourette syndrome. The work was recently published in the journal Nature.

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Researchers at MIT, the Broad Institute of MIT and Harvard, Integrated Biosciences, the Wyss Institute for Biologically Inspired Engineering, and the Leibniz Institute of Polymer Research have identified a new structural class of antibiotics.

Scientists have discovered one of the first new classes of antibiotics identified in the past 60 years, and the first discovered leveraging an AI-powered platform built around explainable deep learning.

Published in Nature today, December 20, the peer-reviewed paper, entitled “Discovery of a structural class of antibiotics with explainable deep learning,” was co-authored by a team of 21 researchers, led by Felix Wong, Ph.D., co-founder of Integrated Biosciences, and James J. Collins, Ph.D., Termeer Professor of Medical Engineering and Science at MIT and founding chair of the Integrated Biosciences Scientific Advisory Board.

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UCLA breaks new ground in alloy research, presenting the first 3D mapping of medium and high-entropy alloys, potentially revolutionizing the field with enhanced toughness and flexibility in these materials.

Alloys, which are materials such as steel that are made by combining two or more metallic elements, are among the underpinnings of contemporary life. They are essential for buildings, transportation, appliances and tools — including, very likely, the device you are using to read this story. In applying alloys, engineers have faced an age-old trade-off common in most materials: Alloys that are hard tend to be brittle and break under strain, while those that are flexible under strain tend to dent easily.

Advancements in Alloy Research.

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