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Cellular senescence in pediatric anthracycline-induced cardiomyopathy
Address correspondence to: James Martin, Baylor College of Medicine, One Baylor Plaza, Houston, Texas, 77,030, USA. Phone: 713.798.5931; Email: [email protected].
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1Department of Pediatrics, Baylor College of Medicine, Houston, Texas, USA.
Attackers Hijacked Over 300 Tor Exit Relays to Intercept SSH Connections
Attackers hijacked over 300 Tor exit relays to intercept SSH connections and steal passwords from users who accepted changed host keys.
As Japan pursues a chip-industry reboot, it’s being pressed to build America’s
Japan is in the midst of a major push to revive its chip sector, but its latest investments show how Tokyo is being pulled into helping the US build up its own semiconductor industry.
Advanced AI tool estimates biological age and predicts cancer survival from face photos
Researchers are using AI tools to analyze simple facial photographs to determine key indicators of a person’s health. Mass General Brigham researchers built FAHR-Face (Foundation Artificial Intelligence for Health Recognition), a large AI foundation model trained on over 40 million face images.
Rutgers And IBM Demonstrate Real-Time Control Across 100 Qubits
PRESS RELEASE — Researchers from Rutgers, IBM and collaborating institutions have shown that a quantum computer can check what is happening inside it and respond while it is running, repeatedly resetting parts of the system to bring chaotic behavior under control.
The advance is a critical step toward building larger, more reliable quantum computers.
Today’s quantum computers operate according to the unusual rules governing atoms and other extremely small particles. They could one day solve problems beyond the reach of conventional computers — designing better batteries and cleaner industrial catalysts, simulating molecules and materials too complex for today’s computers, and running certain artificial intelligence programs.
A powerful framework for analysing solid materials
To analyse that compound theoretically, Kusunose applied the concept of multipoles, which are useful for describing arrangements of electric charge or magnetic poles in space. The simplest multipole is a monopole; a single electric charge, such as a proton or an electron, is an example of a monopole. A dipole describes two equal but opposite charges; the north and south poles of a magnet are an example of a dipole, where the electric charge is replaced with a magnetic charge. Going up the multipole hierarchy adds increasing complexity. Any arrangement of electric charges or magnetic poles can be approximated by using a certain combination of multipoles — known as a multipole expansion.
Kusunose then embarked on an ambitious project to develop a truly comprehensive analysis framework of solids based on multipoles. That required quantum-mechanical expressions of four types of multipoles: electric multipoles, magnetic multipoles, and their vortex-like pattern, or toroidal, equivalents.
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A Stubborn Question Answered: New Research Reveals How the Milky Way’s Disk Formed
Figuring out how the Milky Way’s thin and thick disks formed is a tough question in astronomy. It relies on determining individual stellar ages accurately. Gaia was pretty good at that, and new research based on its data may have found the answer.
Using thousands of AI agents to uncover new leads in biological data
AI agents just uncovered promising new leads for neurodegenerative disease research—in just 32 minutes.
Here’s what thousands of GPT-Rosalind agents accomplished by working in parallel:
- Analyzed millions of mouse brain cells — Connected gene disruptions to findings in scientific literature — Identified unexpected biological mechanisms — Uncovered a potential link between cholesterol metabolism and neurodegeneration.
Research that could take human scientists months—or even a year—to carry out was completed in roughly half an hour.
The bigger story isn’t just speed. It’s how AI agents could help researchers uncover biological connections that might otherwise take far longer to find.
These are promising research leads, not yet confirmed discoveries—but they point to an exciting new role for AI in scientific discovery.