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MIT chemists have discovered how the structure of the EmrE transporter changes as a compound moves through it. At left is the transporter structure at high pH. As the pH drops (right), the helices begin to tilt so that the channel is more open toward the outside of the cell, guiding the compound out. Credit: Courtesy of the researchers.

A new study sheds light on how a protein pumps toxic molecules out of bacterial cells.

MIT chemists have discovered the structure of a protein that can pump toxic molecules out of bacterial cells. Proteins similar to this one, which is found in E. coli, are believed to help bacteria become resistant to multiple antibiotics.

A new machine-learning technique can pinpoint potential power grid failures and cascading traffic bottlenecks, in real time.

A new machine-learning technique could pinpoint potential power grid failures or cascading traffic bottlenecks in real time.

Identifying a malfunction in the nation’s power grid can be like trying to find a needle in an enormous haystack. Hundreds of thousands of interrelated sensors spread across the U.S. capture data on electric current, voltage, and other critical information in real time, often taking multiple recordings per second.

Sounds provide important information about how well a machine is running. ETH researchers have now developed a new machine learning method that automatically detects whether a machine is “healthy” or requires maintenance.

Whether railway wheels or generators in a power plant, whether pumps or valves—they all make sounds. For trained ears, these noises even have a meaning: devices, machines, equipment or rolling stock differently when they are functioning properly compared to when they have a defect or fault.

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Neura Pod is a series covering topics related to Neuralink, Inc. Topics such as brain-machine interfaces, brain injuries, and artificial intelligence will be explored. Host Ryan Tanaka synthesizes informationopinions, and conducts interviews to easily learn about Neuralink and its future.

Epidemiological data have long linked depression with Alzheimer’s disease (AD), a neurodegenerative disease characterized by progressive dementia that affects nearly 6 million Americans. Now, a new study identifies common genetic factors in both depression and AD. Importantly, the researchers found that depression played a causal role in AD development, and those with worse depression experienced a faster decline in memory. The study appears in Biological Psychiatry, published by Elsevier.

Co-senior author Aliza Wingo, MD, of Emory University School of Medicine, Atlanta, USA, said of the work, “It raises the possibility that there are genes that contribute to both illnesses. While the shared genetic basis is small, the findings suggest a potential causal role of depression on dementia.”

The authors performed a genome-wide association study (GWAS), a technique that scans the entire genome for areas of commonality associated with particular conditions. The GWAS identified 28 brain proteins and 75 transcripts – the messages that encode proteins – that were associated with depression. Among those, 46 transcripts and 7 proteins were also associated with symptoms of AD. The data suggest a shared genetic basis for the two diseases, which may drive the increased risk for AD associated with depression.