Scientists trained artificial intelligence on libraries of DNA and then asked the model to create recipes for viral genomes. Sixteen of them were viable, yielding new viruses.
A combination treatment exposed hidden pancreatic cancer cells to the immune system, reduced their spread, and helped mice live longer.
Researchers at the University of Minnesota Medical School have uncovered one reason pancreatic cancer is so difficult for the immune system to recognize and attack. The discovery points to a potential way to make immunotherapy more effective against a disease that has historically resisted many immune-based treatments.
The findings, published in Science Immunology, show that some pancreatic cancer cells can avoid destruction by shutting down the molecular system that normally reveals them to immune cells. Once these cells become harder to detect, they are more likely to survive, spread, and establish tumors elsewhere in the body.
The fast-ignition paradigm for inertial confinement fusion allows for extremely high gains but requires fuel to be heated very quickly to outpace hotspot disassembly and energy losses. This demands lasers with high power and intensity, posing engineering challenges that have called into question the fundamental practicality of fast ignition. Magnetized liner inertial fusion (MagLIF) circumvents these problems through its large-aspect-ratio cylindrical geometry and strong axial magnetic fields that allow for ignition at lower areal densities. Furthermore, MagLIF’s large aspect ratio and higher yields relax other constraints on energy deposition and repetition rate, while its axial magnetic fields can be used to collimate ignitor electrons and thereby increase allowed standoff distance and save on ignitor energy. This tremendous overall relaxation of the engineering constraints that have historically limited the practicality of fast ignition suggests that the paradigm may be considerably more viable in a MagLIF context.
A new study led by a Duke University scientist overturns a long-held idea about how primates, including humans, came to have such large and sophisticated brains. The research finds that the dramatic expansion of the primate neocortex was driven largely by vision, not by the disproportionate growth of the frontal lobe often associated with higher reasoning.
The research, published this week in the journal Science, was led by Richard F. Kay, a professor emeritus of Evolutionary Anthropology at Duke University Trinity College of Arts & Sciences and the Nicholas School of the Environment.
The neocortex—the outer, folded layer of the brain responsible for sensory perception, cognition and other complex functions—is greatly enlarged in primates compared with other mammals. Exactly how and why it grew so large over the past 56 million years has been difficult to pin down because brains do not fossilize.
Cancer care.
Immunotherapy.
OncoDaily.
Oncology.
Precision Oncology
In the deep, dim ocean, a world of eat-or-be-eaten, lighting up may seem like a counterintuitive survival strategy.
Nevertheless, it helps many animals hide from predators that might strike from below – a shine that conceals the shadow they cast against the faint light filtering down from above.
Now, however, scientists have found evidence that one of the most stunning bioluminescent animals in the ocean may have been using its light in another way all along.
PortSwigger says HTTP Terminator, an artificial intelligence (AI)-assisted research system built by James Kettle, generated and proved new HTTP desynchronization techniques after exploring 30,000 candidate desync vectors.
PortSwigger said a separate human-guided discovery cascade also exposed a zero-day in Apache Traffic Server. Kettle said HTTP Terminator tested 30,000 websites where scanning was authorized through bug bounty or vulnerability disclosure programs and found roughly 700 vulnerable targets before deeper validation and RQP research.
Kettle said those findings involved banks, government infrastructure, security products, and an airport.
The Longest Equation in Physics The model Lagrangian is a mathematical expression that summarizes the Standard Model of particle physics, which is the most successful theory of the fundamental interactions between elementary particles. It is composed of four different parts, each describing a different aspect of the Standard Model. The model Lagrangian is written in a compact notation that uses symbols and operators from quantum field theory, such as covariant derivatives, field strength tensors, Dirac matrices, and gauge group generators. It also uses various constants and parameters that are determined by experiments, such as coupling constants, masses, and mixing angles. It is one of the longest equations in physics because it contains many terms and factors that account for all the possible interactions and symmetries of the Standard Model. It was transcribed by Thomas Gutierrez who derived it from Martinus Veltman’s Diagrammatica: The Path to Feynman Diagrams.