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A team of researchers led by the University of California San Diego has developed soft yet durable materials that glow in response to mechanical stress, such as compression, stretching or twisting. The materials derive their luminescence from single-celled algae known as dinoflagellates.

The work, inspired by the bioluminescent waves observed during red tide events at San Diego’s beaches, was published Oct. 20 in Science Advances.

“An exciting feature of these materials is their inherent simplicity—they need no electronics, no external power source,” said study senior author Shengqiang Cai, a professor of mechanical and aerospace engineering at the UC San Diego Jacobs School of Engineering. “We demonstrate how we can harness the power of nature to directly convert mechanical stimuli into light emission.”

The human brain is made up of two kinds of matter: the nerve cell bodies (gray matter), which process sensation, control voluntary movement, and enable speech, learning and cognition, and the axons (white matter), which connect cells to each other and project to the rest of the body.

Historically, scientists have concentrated on the gray matter of the cortex, figuring that’s where the action is, while ignoring white matter, even though it makes up half the brain. Researchers at Vanderbilt University are out to change that.

For several years, John Gore, Ph.D., director of the Vanderbilt University Institute of Imaging Science, and his colleagues have used functional magnetic resonance imaging (fMRI) to detect blood oxygenation-level dependent (BOLD) signals, a key marker of brain activity, in white matter.

The limitless world of chemistry and how researchers investigate it.

This model of computing would use 1/1000th of the energy today’s computers do. So why aren’t we using it?

Influenza viruses are believed to have sparked at least 14 human pandemics in the past 500 years; the most devastating of which began in 1918. Yet, despite intense study and considerable advances in public health, virus surveillance and virology, there is no simple answer to this pressing question: when and how will the next flu pandemic arise?

NIAID scientists including Jeffery K. Taubenberger, M.D., Ph.D., consider the many potential pathways to future influenza pandemics in a new viewpoints essay in Science Translational Medicine. There are no hard and fast ‘rules’ specifying, for example, what characteristics a given avian influenza virus must possess to allow it to efficiently infect… More.

Influenza pandemics have emerged for centuries but still cannot be accurately predicted.

A NIAID-funded study suggests a strategy to mitigate harmful side effects of nanoparticles in medicine. The researchers showed in animal models that a lab-made molecule safely prevented nanomedicines from activating a set of immune-system proteins called the complement system and causing negative side effects. This is significant because when nanoparticles activate complement, the resulting immune response can not only cause an adverse reaction, but also reduce the efficacy of nanomedicines.

More than 60,000 women in the U.S. get this type of cancer each year. Find out more about the symptoms and how it’s diagnosed and treated.

Breast changes are very common, and most breast changes are not cancer. Our health guide for women explains:

A breast lump may be benign or a symptom of breast cancer. Learn about follow-up after an abnormal mammogram. See pictures of breast cancer, cysts, and calcifications. Find out symptoms for benign breast conditions, precancers, and DCIS.

A large team of computer scientists and engineers at IBM Research has developed a dedicated computer chip that is able to run AI-based image recognition apps 22 times as fast as chips that are currently on the market.

In their paper published in the journal Science, the group describes the ideas that went into developing the chip, how it works and how well it performed when tested. Subramanian Iyer and Vwani Roychowdhury, both at the University of California, Los Angeles, have published a Perspective piece in the same journal issue, giving an in-depth analysis of the work by the team in California.

As AI-powered applications become mainstream tools used by professionals and amateurs alike, scientists continue work to make them better. One way to do that, Iyer and Roychowdhury note, is to move toward an “edge” computer system in which the data is physically closer to the AI applications that are using them.