Lifeboat Foundation

The human body can be genetically inclined to attack its own cells, destroying the beta cells in the pancreas that make insulin, which helps convert sugar into energy. Called Type 1 diabetes, this disorder can occur at any age and can be fatal if not carefully managed with insulin shots or an insulin pump to balance the body’s sugar levels.

But there may be another, personalized option on the horizon, according to Xiaojun “Lance” Lian, associate professor of biomedical engineering and biology at Penn State. For the first time, Lian and his team converted human embryonic stem cells into beta cells capable of producing insulin using only small molecules in the laboratory, making the process more efficient and cost-effective.

Stem cells can become other cell types through signals in their environment, and some mature cells can revert to stem cells—induced pluripotency. The researchers found that their approach worked for human embryonic and induced pluripotent stem cells, both derived from federally approved stem cell lines. According to Lian, the effectiveness of their approach could reduce or eliminate the need for human embryonic stem cells in future work. They published their results today (Aug. 26) in Stem Cell Reports.

Blue Origin successfully launched its 17th New Shepard suborbital spaceflight Thursday morning. The capsule flew to a peak altitude of 347,430 feet while carrying 20 payloads.

“We are thinking about volumes in millions.”

“We are thinking about volumes in millions, not the thousands that people talk about with quantum computers based on superconducting,” said Marcus Doherty, chief science officer.

Quantum Brilliance delivered its first system to the Pawsey Supercomputing Centre in Australia earlier this year and is beginning to ship to other commercial customers.

Determining the 3D shapes of biological molecules is one of the hardest problems in modern biology and medical discovery. Companies and research institutions often spend millions of dollars to determine a molecular structure—and even such massive efforts are frequently unsuccessful.

Using clever, new machine learning techniques, Stanford University Ph.D. students Stephan Eismann and Raphael Townshend, under the guidance of Ron Dror, associate professor of computer science, have developed an approach that overcomes this problem by predicting accurate structures computationally.

Most notably, their approach succeeds even when learning from only a few known structures, making it applicable to the types of molecules whose structures are most difficult to determine experimentally.

Devices in the submillimetre range – so-called “nano-supercapacitors” – allow the shrinkage of electronic components to tiny dimensions. However, they are difficult to produce and do not usually incorporate biocompatible materials. Corrosive electrolytes, for example, can quickly discharge themselves in the event of defects and contamination.

So-called “biosupercapacitors” (BSCs) offer a solution. These have two outstanding properties: full biocompatibility, which means they can be used in body fluids such as blood, and compensation for self-discharge behaviours through bio-electrochemical reactions. In other words, they can actually benefit from the body’s own reactions. This is because, in addition to typical charge storage reactions of a supercapacitor, redox enzymatic reactions and living cells naturally present in the blood can increase the performance of a device by 40%.

Shrinking these devices down to submillimetre sizes, while maintaining full biocompatibility, has been enormously challenging. Now, scientists have created a prototype that combines both essential properties.

About 11.1 million Americans are living with long COVID-19, according to new estimates from The American Academy of Physical Medicine and Rehabilitation.

Long COVID-19, or persistent symptoms up to six months after being cleared of the illness, affects around 30 percent of individuals who had COVID-19, according to two recent publications from the Journal of the American Medical Association. Symptoms of long COVID-19 are varied and may include neurological challenges, cognitive problems, shortness of breath, fatigue, pain and mobility issues.

The AAPM&R has developed a dashboard estimating long COVID-19 infections. The model assumes that 30 percent of people who recover from acute COVID-19 develop long COVID-19, but users can adjust estimates based on higher or lower percentages. U.S. case data is pulled from Baltimore-based Johns Hopkins University COVID-19 data. U.S. census data uses2019estimates.

Could the cryptocurrency’s huge electricity consumption also sink it?

Long distance quantum communication over 600 km of fiber unlocked!

Toshiba in partnership with the Japanese Tohoku University Hospital have achieved a new milestone on the road towards the quantum internet — the research team encrypted the human genome and sent it over a quantum-secure connection over 600 km of fiber.

A blockchain-based initiative from the United States Air Force will employ Constellation’s Hypergraph Network to provide data security with the Department of Defense’s commercial partners.

In a Thursday announcement, Constellation said it had been working with Kinnami Software Corporation to develop an end-to-end data security solution using blockchain encryption and distributed data management for the United States Transportation Command, Air Mobility Command’s 618th Air Operations Center, and a Civil Reserve Air Fleet partner. According to the platform, its goal is to securely exchange data with commercial partners on missions involving the operations of aircraft and ships under contract to the Department of Defense, or DoD.

The United States Transportation Command, or USTRANSCOM, allows authorities — including those in the 618th — to coordinate missions using available resources from both the military and private sector. Constellation Network’s solution may have the potential to improve the existing cybersecurity and general effectiveness.