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A machine learning algorithm can detect signs of anxiety and depression in the speech patterns of young children, potentially providing a fast and easy way of diagnosing conditions that are difficult to spot and often overlooked in young people, according to new research published in the Journal of Biomedical and Health Informatics.

Around one in five suffer from anxiety and depression, collectively known as “internalizing disorders.” But because children under the age of eight can’t reliably articulate their emotional suffering, adults need to be able to infer their mental state, and recognise potential mental health problems. Waiting lists for appointments with psychologists, insurance issues, and failure to recognise the symptoms by parents all contribute to children missing out on vital treatment.

“We need quick, objective tests to catch kids when they are suffering,” says Ellen McGinnis, a at the University of Vermont Medical Center’s Vermont Center for Children, Youth and Families and lead author of the study. “The majority of kids under eight are undiagnosed.”

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2015

After an oil spill, the number one priority is finding a way to contain and remove the oil. Boat operators sometimes deploy physical booms to trap the oil so that it can be siphoned or burned off of the water’s surface. But, because oil in water is tricky to contain, other methods for corraling it call for adding manmade chemicals to the water.

In a technique called dispersion, chemicals and wave action break down the oil into smaller particles, which then disperse and slowly biodegrade over a large area. Then, there is chemical herding. To clean up an oil spill with a chemical herder, crews spray a compound around the perimeter of the spill. The compound stays on the surface and causes the oil to thicken. Once it’s thick enough, it can be burned off. Chemical herding requires calm water, which makes it unreliable in some spills, but, unlike mechanical removal or dispersion, it gets all the oil. The technique has been around since the 1970s, but, until now, the chemicals used to herd the oil, called soap surfectants, didn’t break down over time. After the oil burned off, they’d still be in the ecosystem.

Researchers at the City College of New York, led by chemist George John and chemical engineer Charles Maldarelli, have developed a way to clean up oil using a chemical herder made of phytol, a molecule in chlorophyll that makes algae green.

Continue reading “Scientists Find a Natural Way to Clean Up Oil Spills, With a Plant-Based Molecule” | >

Blue supergiants are the rock-and-roll stars of the universe. They are massive stars that live fast and die young which makes them rare and difficult to study, even with modern telescopes.

Before space telescopes, few blue supergiants had been observed, so our knowledge of these stars was limited.

Leading astrophysicist Dr. Tamara Rogers, from Newcastle University, UK, and her team have been working for the past five years to create simulations of stars like these to try to predict what it is that makes the surface appear the way it does.

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To kill bacteria in the blood, our immune system relies on nanomachines that can open deadly holes in their targets. UCL scientists have now filmed these nanomachines in action, discovering a key bottleneck in the process which helps to protect our own cells.

The research, published in Nature Communications, provides us with a better understanding of how the kills bacteria and why our own cells remain intact. This may guide the development of new therapies that harness the immune system against bacterial infections, and strategies that repurpose the immune system to act against other rogue cells in the body.

In earlier research, the scientists imaged the hallmarks of attack in live bacteria, showing that the immune system response results in ‘bullet holes’ spread across the cell envelopes of bacteria. The holes are incredibly small with a diameter of just 10 nanometres.

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