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Alzheimer’s disease (AD) is a debilitating progressive illness that begins with mild memory loss and slowly destroys cognitive function and memory. It currently has no cure and is predicted to affect over 100 million people worldwide by 2050. In the United States, AD is the leading cause of dementia in older adults and the 7th most common cause of death, according to the National Institute on Aging.

Ongoing Alzheimer’s research is focused on two key neurotoxic proteins: amyloid beta (Aβ) and tau. Although these proteins have been shown to be associated with AD, the levels of Aβ and tau do not consistently explain or correlate with the severity of cognitive decline for some people with the disease.

Investigators at Brigham and Women’s Hospital, a founding member of the Mass General Brigham healthcare system, set out to identify other proteins that may be directly involved with fundamental aspects of AD, like synaptic loss and neurodegeneration. They exposed laboratory neurons to human brain extracts from about 40 people who either had AD, were protected from AD despite having high Aβ and tau levels, or were protected from AD with little or no Aβ and tau in their brains.

JILA and NIST Fellow James K. Thompson’s team of researchers have for the first time successfully combined two of the “spookiest” features of quantum mechanics to make a better quantum sensor: entanglement between atoms and delocalization of atoms.

Einstein originally referred to as creating spooky action at a distance—the strange effect of quantum mechanics in which what happens to one atom somehow influences another atom somewhere else. Entanglement is at the heart of hoped-for quantum computers, quantum simulators and quantum sensors.

A second rather spooky aspect of quantum mechanics is delocalization, the fact that a can be in more than one place at the same time. As described in their paper recently published in Nature, the Thompson group has combined the spookiness of both entanglement and delocalization to realize a matter-wave interferometer that can sense accelerations with a precision that surpasses the standard quantum limit (a limit on the accuracy of an experimental measurement at a quantum level) for the first time.

California produces about 90% of the nation’s strawberries, but severe drought and worker shortages are threatening the fruit. One company is hoping to change that with the power of robots.

Eric Adamson’s company is behind a strawberry robotic revolution. He said they’re programmed to think on their own, with cameras that sense texture and color.

“People think robots have been around forever, but they’re actually very, very new, especially robots that make decisions and are autonomous,” Adamson said.

Over the last several decades, obesity has rapidly grown to affect more than 2 billion people, making it one of the biggest contributors to poor health globally. Many individuals still have trouble losing weight despite decades of study on diet and exercise regimens. Researchers from Baylor College of Medicine and affiliated institutions now believe they understand why, and they argue that the emphasis should be shifted from treating obesity to preventing it.

The research team reports in the journal Science Advances that early-life molecular processes of brain development are likely a major determinant of obesity risk. Previous large human studies have shown that the genes most strongly associated with obesity are expressed in the developing brain. This most recent study in mice focused on epigenetic development. Epigenetics is a molecular bookmarking system that regulates whether genes are utilized or not in certain cell types.

“Decades of research in humans and animal models have shown that environmental influences during critical periods of development have a major long-term impact on health and disease,” said corresponding author Dr. Robert Waterland, professor of pediatrics-nutrition and a member of the USDA Children’s Nutrition Research Center at Baylor. “Body weight regulation is very sensitive to such ‘developmental programming,’ but exactly how this works remains unknown.”

If you’ve ever played the claw game at an arcade, you know how hard it is to grab and hold onto objects using robotics grippers. Imagine how much more nerve-wracking that game would be if, instead of plush stuffed animals, you were trying to grab a fragile piece of endangered coral or a priceless artifact from a sunken ship.

Most of today’s robotic grippers rely on embedded sensors, complex feedback loops, or advanced machine learning algorithms, combined with the skill of the operator, to grasp fragile or irregularly shaped objects. But researchers from the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) have demonstrated an easier way.

Taking inspiration from nature, they designed a new type of soft, robotic that uses a collection of thin tentacles to entangle and ensnare objects, similar to how jellyfish collect stunned prey. Alone, individual tentacles, or filaments, are weak. But together, the collection of filaments can grasp and securely hold heavy and oddly shaped objects. The gripper relies on simple inflation to wrap around objects and doesn’t require sensing, planning, or feedback control.