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Brains aren’t the easiest of organs to study, what with their delicate wiring and subtle whispering of neurotransmitter messages. Now, this research could be made a little easier, as we’ve learned we can swap some critical chemical systems with the host animal being none the wiser.

In a proof-of-concept study run by a team of US researchers, the microscopic worm Caenorhabditis elegans was genetically gifted pieces of a nervous system taken from a radically different creature – a curious freshwater organism known as Hydra.

The swap wasn’t unlike teaching a specific brain circuit a foreign language, and finding it performs its job just as well as before.

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Genetic information can be messy. Mapping proteins could offer a clearer view of what’s driving cancer.

Scientists have unveiled new maps of the protein networks underlying different types of cancer, offering a potentially clearer way to see what’s driving the disease and to find therapeutic targets.

Sequencing the genetic information of tumors can provide a trove of data about the mutations contained in those cancer cells. Some of those mutations help doctors figure out the best way to treat a patient, but others remain more of a mystery than a clear instruction manual. Many are exceedingly rare, or there are so many mutations it’s not clear what’s fueling the cancer.

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Researchers at McGill University have developed the strongest and toughest glass ever known. Inspired, in part, by the inner layer of mollusk shells, this glass does not shatter when hit, and acts more like plastic.

The material, once commercially viable, could be used to improve cell phone screens, among other applications in the future.

Interestingly, this may be an example of modern science rediscovering an old technology, now long lost.

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We can consider white holes and black holes to be the two sides of the same coin. A perfect pair of antonyms. White holes first found their place, like many others, in Einstein’s theory of relativity. But it was left just there until theorists began pondering over its existence quite recently.

What is a white hole?

Insight, a white hole looks exactly like a black hole. It has mass, probably a ring of dust and gas around it. But the similarities end there. According to Carlo Ravelli, a theoretical physicist at the Centre de Physique Theorique in France, “It’s only in the moment when things come out that you can say, ‘ah, this is a white hole,”.

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There can be other kinds of black holes that trap other physical phenomena, like sound waves, and these kinds of black holes, known as sonic black holes, might be critical to understanding their light-consuming counterparts in the wider universe.

Most important of all, what can sonic black holes tell us about one of modern physics’ most contentious debates, the so-called Information Paradox? A recent study attempted to find out, and its results seem to make the problem more complicated, not less.

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Developing drugs for a range of tauopathies — dr leticia toledo-sherman, senior director, drug discovery, tau consortium, rainwater charitable foundation.

Dr. Leticia Toledo-Sherman is Senior Director of Drug Discovery of the Tau Consortium (https://tauconsortium.org/) for The Rainwater Charitable Foundation (https://rainwatercharitablefoundation.org/medical-research) and also holds an appointment as Adjunct Assistant Professor of Neurology at UCLA.

Dr. Toledo-Sherman leads drug discovery activities for an international network of scientists working to develop therapies for Tauopathies, a group of neurodegenerative disorders characterized by the deposition of abnormal Tau protein in the brain.

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Intel today announced a major update to its neuromorphic computing program, including a second-generation chip called Loihi 2 and Lava, an open-source framework for developing “neuro-inspired” applications. The company is now offering two Loihi 2-based neuromorphic systems — Oheo Gulch and Kapoho Point. They will be available through a cloud service to members of the Intel Neuromorphic Research Community (INRC) and Lava via GitHub for free.

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Intel unveiled the second generation of its neuromorphic chip and claims it will be able to solve planning and optimization problems.

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November 12 2020

RESEARCH TRIANGLE PARK, N.C. — A new machine learning algorithm, developed with Army funding, can isolate patterns in brain signals that relate to a specific behavior and then decode it, potentially providing Soldiers with behavioral-based feedback.

“The impact of this work is of great importance to Army and DOD in general, as it pursues a framework for decoding behaviors from brain signals that generate them,” said Dr. Hamid Krim, program manager, Army Research Office, an element of the U.S. Army Combat Capabilities Develop Command, now known as DEVCOM, Army Research Laboratory. “As an example future application, the algorithms could provide Soldiers with needed feedback to take corrective action as a result of fatigue or stress.”

Brain signals contain dynamic neural patterns that reflect a combination of activities simultaneously. For example, the brain can type a message on a keyboard and acknowledge if a person is thirsty at that same time. A standing challenge has been isolating those patterns in brain signals that relate to a specific behavior, such as finger movements.

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