Microscopic sensors that are as thin as a strand of hair but capable of taking multiple measurements simultaneously could revolutionize the diagnosis and monitoring of diseases like cancer. Researchers from Adelaide University’s Institute for Photonics and Advanced Sensing and the University of Stuttgart in Germany worked together to develop the tiny sensors using state-of-the-art, ultrafast 3D microprinting technology.

The unique sensors target specific biomarkers and are printed directly onto the tip of optical fibers...

New UNLV-led research is helping to unravel clues to a cosmic mystery that has eluded scientists for decades. Cataclysmic variables (CVs) are binary star systems in which primary stars—incredibly dense and compact white dwarfs—accumulate material from nearby companion stars. The material spirals in towards the white dwarf through what is known as an accretion disk. These deep space systems are responsible for a number of cosmic phenomena, including sudden bursts of light known as classical novae that temporarily appear to resemble new stars before fading away over time.

A long-standing mystery in cataclysmic variables
Modern astronomical instruments have enabled scientists to understand many of the mechanisms that drive CVs...

The trillions of microbes living in the human gut are increasingly recognized as important partners in human health. Scientists have linked the gut microbiome to several aspects of health, from metabolism and immunity to mental health.

A recent study suggests that these microbes may also influence an important aspect of fitness—muscle strength.

Muscle strength is a crucial feature of health for many reasons. It supports our joints and keeps our bones healthy, boosts athletic performance and even plays a role in metabolic health.

Muscle strength also helps us maintain independence later in life. As muscles gradually weaken as we get older, everyday tasks become harder and the risk of falls increases...

Researchers have developed a new kind of nanoelectronic device that could dramatically cut the energy consumed by artificial intelligence hardware by mimicking the human brain. The researchers, led by the University of Cambridge, developed a form of hafnium oxide that acts as a highly stable, low-energy “memristor”—a component designed to mimic the efficient way neurons are connected in the brain. The results are reported in the journal Science Advances.

Current AI systems rely on conventional computer chips that shuttle data back and forth between memory and processing units. This constant movement consumes large amounts of electricity, and global demand is exploding as AI adoption expands across industries.

Brain...