SAN DIEGO, CA, Dec. 10, 2015 -- Ghosts are not your typical cell biology research subjects. But scientists at the Carnegie Institution for Science and the National Institute of Child Health and Human Development (NICHD) who developed a technique to observe muscle stem/progenitor cells migrating within injury sites in live mice, report that 'ghost fibers,' remnants of the old extracellular matrix left by dying muscle fibers, guide the cells into position for healing to begin.

Pretty much everything happening in the brain would fail without astrocytes. These star-shaped glial cells are known to have a critical role in synapse creation, nervous tissue repair, and the formation of the blood-brain barrier. But while we have decades of data in mice about these nervous system support cells, how relevant those experiments are to human biology (and the success of potential therapies) has been an open question.

Many of the body's processes follow a natural daily rhythm or so-called circadian clock, so there are certain times of the day when a person is most alert, when the heart is most efficient, and when the body prefers sleep. Even bacteria have a circadian clock, and in a December 10 Cell Reports study, researchers designed synthetic microbes to learn what drives this clock and how it might be manipulated.

"The answer seems to be especially simple: the clock proteins sense the metabolic activity in the cell," says senior author Michael Rust, of the University of Chicago's Institute for Genomics and Systems Biology.

ANN ARBOR--One out of every four dollars employers pay for health care is tied to unhealthy lifestyle choices or conditions like smoking, stress and obesity, despite the fact that most large employers have workplace wellness programs.

In the largest study of its kind, researchers from the University of Michigan looked at 10 modifiable health risks in roughly 223,500 people across seven industries, said Michael O'Donnell, first author on the study and director of the
U-M Health Management Research Center at the School of Kinesiology.

Researchers have created a computer model that captures humans' unique ability to learn new concepts from a single example. Though the model is only capable of learning handwritten characters from alphabets, the approach underlying it could be broadened to have applications for other symbol-based systems, like gestures, dance moves, and the words of spoken and signed languages. Recent years have seen steady advances in machine learning, yet people are still far better than machines at learning new concepts, often needing just an example or two compared to the tens or hundreds machines typically require. What's more, after learning a concept for the first time, people can typically use it in rich and diverse ways.

In one of the most comprehensive studies to date to analyze job outcomes for U.S. university graduates with funded doctoral degrees, researchers found that nearly 40% of the doctoral recipients evaluated went into industry, and that these employees were more likely to work at high-wage establishments compared to their counterparts in academia. The study provides unique insights into where research-funded Ph.D.'s go when they graduate and enter the private sector, an area for which there is little existing data but results for which could help illuminate the impact of research on the economy. While the U.S. investment in scientific research can be documented readily, the output is harder to track. To overcome this obstacle, Nikolas Zolas et al.