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CRISPR-Cas9 is a revolutionary gene-editing technology that offers the potential to treat diseases such as cancer, but the effects of CRISPR in patients are currently unknown. Stadtmauer et al. report a phase 1 clinical trial to assess the safety and feasibility of CRISPR-Cas9 gene editing in three patients with advanced cancer (see the Perspective by Hamilton and Doudna). They removed immune cells called T lymphocytes from patients and used CRISPR-Cas9 to disrupt three genes (TRAC, TRBC, and PDCD1) with the goal of improving antitumor immunity. A cancer-targeting transgene, NY-ESO-1, was also introduced to recognize tumors. The engineered cells were administered to patients and were well tolerated, with durable engraftment observed for the study duration. These encouraging observations pave the way for future trials to study CRISPR-engineered cancer immunotherapies.

Science, this issue p. eaba7365; see also p. 976.

A new genomics study of shark DNA, including from great white and great hammerhead sharks, reveals unique modifications in their immunity genes that may underlie the rapid wound healing and possibly higher resistance to cancers in these ocean predators. This research brings us a few steps closer to understanding, from a genetic sense, why sharks exhibit some characteristics that are highly desirable by humans.

Liz Parrish and Integrated Health Systems discuss the thymus, an organ that is essential to healthy immune function.

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When opportunity knocks, open the door: No one has taken heed of that adage like Nvidia, which has transformed itself from a company focused on catering to the needs of video gamers to one at the heart of the artificial-intelligence revolution. In 2001, no one predicted that the same processor architecture developed to draw realistic explosions in 3D would be just the thing to power a renaissance in deep learning. But when Nvidia realized that academics were gobbling up its graphics cards, it responded, supporting researchers with the launch of the CUDA parallel computing software framework in 2006.

Since then, Nvidia has been a big player in the world of high-end embedded AI applications, where teams of highly trained (and paid) engineers have used its hardware for things like autonomous vehicles. Now the company claims to be making it easy for even hobbyists to use embedded machine learning, with its US $100 Jetson Nano dev kit, which was originally launched in early 2019 and rereleased this March with several upgrades. So, I set out to see just how easy it was: Could I, for example, quickly and cheaply make a camera that could recognize and track chosen objects?

Embedded machine learning is evolving rapidly. In April 2019, Hands On looked at Google’s Coral Dev AI board which incorporates the company’s Edge tensor processing unit (TPU), and in July 2019, IEEE Spectrum featured Adafruit’s software library, which lets even a handheld game device do simple speech recognition. The Jetson Nano is closer to the Coral Dev board: With its 128 parallel processing cores, like the Coral, it’s powerful enough to handle a real-time video feed, and both have Raspberry Pi–style 40-pin GPIO connectors for driving external hardware.

NASA Administrator Jim Bridenstine signaled today that astronauts would soon be cleared to take suborbital spaceflights aboard the commercial rocket ships being tested by Virgin Galactic and by Amazon CEO Jeff Bezos’ Blue Origin space venture.

“NASA is developing the process to fly astronauts on commercial suborbital spacecraft,” Bridenstine said in a tweet. “Whether it’s suborbital, orbital or deep space, NASA will utilize our nation’s innovative commercial capabilities.”

Bridenstine said the details will be laid out in a request for information to be released next week. Efforts to get further information from NASA Headquarters weren’t immediately successful.

This post by Dr. Robert Zubrin originally appeared at National Space Society.

Mars Is The New World

Among extraterrestrial bodies in our solar system, Mars is singular in that it possesses all the raw materials required to support not only life, but a new branch of human civilization. This uniqueness is illustrated most clearly if we contrast Mars with the Earth’s Moon, the most frequently cited alternative location for extraterrestrial human colonization.

Summary: Chandelier cells have an unusual direct method of communication. Unlike other neurons, chandelier cells connect directly to the part of a target neuron that initiates a spike.

Source: CSHL

Within the intricate network of cells that make up the brain, chandelier cells stand out for their elaborate, branching structure. With an elegant shape similar to that of its namesake, a single chandelier cell reaches out to connect and communicate with more than 100 other neurons. Abnormalities in chandelier cells have been linked to epilepsy, autism, and schizophrenia, underscoring their critical role in keeping brain signaling in balance. However, these cells have been notoriously difficult to study as their numbers are few, so until recently, chandelier cells remained largely enigmatic.

Ion-based technology may enable energy-efficient simulations of the brain’s learning process, for neural network AI systems.

Teams around the world are building ever more sophisticated artificial intelligence systems of a type called neural networks, designed in some ways to mimic the wiring of the brain, for carrying out tasks such as computer vision and natural language processing.

Using state-of-the-art semiconductor circuits to simulate neural networks requires large amounts of memory and high power consumption. Now, an MIT team has made strides toward an alternative system, which uses physical, analog devices that can much more efficiently mimic brain processes.