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Health Impact of Zika Still Felt in U.S. Territories, CDC Study Shows

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In a population of children age 1, we don't have a good background prevalence (for neurodevelopmental problems), and it really emphasizes how much more we have to learn about the full impact of Zika,

Neurodevelopmental protein Musashi-1 interacts with the Zika genome and promotes viral replication


Microcephaly has been the terrifying hallmark of the recent outbreak of Zika virus (ZIKV) in the Americas. How the virus damages brain development in the fetus is enigmatic. Chavali et al. found that in congenital microcephaly, mutations in a neural precursor protein, Musashi-1 (MSI1), impede RNA binding to neural stem cell targets, resulting in abnormal brain development (see the Perspective by Griffin). MSI1 also binds ZIKV RNA to amplify viral replication in cells. This interaction could put a pregnant woman at risk of giving birth to a microcephalic child.

To detect fake news, this AI first learned to write it – TechCrunch


One of the biggest problems in media today is so-called "fake news," which is so highly pernicious in part because it superficially resembles the real thing. AI tools promise to help identify it, but in order for it to do so, researchers have found that the best way is for that AI to learn to create fake news itself -- a double-edged sword, though perhaps not as dangerous as it sounds. Grover is a new system created by the University of Washington and Allen Institute for AI (AI2) computer scientists that is extremely adept at writing convincing fake news on myriad topics and as many styles -- and as a direct consequence is also no slouch at spotting it. The paper describing the model is available here. The idea of a fake news generator isn't new -- in fact, OpenAI made a splash recently by announcing that its own text-generating AI was too dangerous to release publicly. But Grover's creators believe we'll only get better at fighting generated fake news by putting the tools to create it out there to be studied.

Neuroscientists reverse some behavioral symptoms of Williams Syndrome


Williams Syndrome, a rare neurodevelopmental disorder that affects about 1 in 10,000 babies born in the United States, produces a range of symptoms including cognitive impairments, cardiovascular problems, and extreme friendliness, or hypersociability. In a study of mice, MIT neuroscientists have garnered new insight into the molecular mechanisms that underlie this hypersociability. They found that loss of one of the genes linked to Williams Syndrome leads to a thinning of the fatty layer that insulates neurons and helps them conduct electrical signals in the brain. The researchers also showed that they could reverse the symptoms by boosting production of this coating, known as myelin. This is significant, because while Williams Syndrome is rare, many other neurodevelopmental disorders and neurological conditions have been linked to myelination deficits, says Guoping Feng, the James W. and Patricia Poitras Professor of Neuroscience and a member of MIT's McGovern Institute for Brain Research.

How An Automated Gesture Imitation Game Can Improve Social Interactions With Teenagers With ASD Machine Learning

With the outlook of improving communication and social abilities of people with ASD, we propose to extend the paradigm of robot-based imitation games to ASD teenagers. In this paper, we present an interaction scenario adapted to ASD teenagers, propose a computational architecture using the latest machine learning algorithm Openpose for human pose detection, and present the results of our basic testing of the scenario with human caregivers. These results are preliminary due to the number of session (1) and participants (4). They include a technical assessment of the performance of Openpose, as well as a preliminary user study to confirm our game scenario could elicit the expected response from subjects.