The Ascension Products Blog.

Syringes and hollow needles have been used to deliver medication for more than a century. However, the precise implementation of these devices depends on the operator, and it can be difficult to deliver medication to delicate regions such as the suprachoroidal space at the back of the eye. Investigators from Brigham and Women's Hospital have developed a highly sensitive intelligent-injector for tissue-targeting (i2T2) that detects changes in resistance in order to properly and safely deliver medication in preclinical testing. Their results are published in Nature Biomedical Engineering.

* This article was originally published here

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Researchers identify how the bacterial replicative helicase opens to start DNA replication process

DNA replication is a complex process in which a helicase ring separates the DNA molecule's two entwined and encoded strands, allowing each to precisely reproduce its missing half. Until recently, however, researchers have not understood how the helicase—a donut-shaped enzyme composed of six identical proteins—is able to thread just one of the strands when they are bound together. Now, new research from scientists at The Graduate Center of The City University of New York, its Advanced Science Research Center (ASRC), and The City College of New York (CCNY) has solved the mystery.

* This article was originally published here

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Exposing flaws in metrics for user login systems

How good is the research on the success or failure of the system that verifies your identity when you log into a computer, smartphone or other device?

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Should you really forgive and forget?

(HealthDay)—Is forgive and forget always the right approach after hurtful behavior from your spouse or significant other?

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US keeps air pollution standard established under Obama

U.S. environmental regulators on Tuesday announced they are leaving intact an air quality standard for power plant pollution that can worsen asthma in children, despite calls by health advocates for a tougher standard.

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New AI approach bridges the 'slim-data gap' that can stymie deep learning approaches

Scientists have developed a deep neural network that sidesteps a problem that has bedeviled efforts to apply artificial intelligence to tackle complex chemistry—a shortage of precisely labeled chemical data. The new method gives scientists an additional tool to apply deep learning to explore drug discovery, new materials for manufacturing, and a swath of other applications.

* This article was originally published here