Researchers think it could play an important function in devices using IoT and medical applications.

Giving millions of patients already taking statins a new type of drug could slash their heart disease risk even further, research suggests.
Scientists claim pills that are currently under development, called lipoprotein lipase (LPL) enhancers, could prevent thousands of heart attacks.
And their study also showed the drugs — which work by lowering levels of fats in the blood — could also slash the risk of type 2 diabetes.
Today, we want to draw your attention to a new study that looks at the role of chronic age-related inflammation and the decline of nerve regeneration.
Inflammaging drives age-related loss of tissue regeneration
Inflammation can be beneficial and serves an important purpose: it spurs regeneration and immune responses while combating pathogens and other invaders. This kind of inflammation tends to be short-lived and localized to an area of injury. However, there is another form of inflammation, a chronic, smouldering kind that accompanies aging: this is often called inflammaging.
Surging productivity and the general rise in incomes it brings would be welcome, of course, but that isn’t sufficient. The same questions being raised about the advance of robotics in the workplace apply to machine learning. While new jobs would be created, many existing jobs — from doctors and financial advisers to translators and call-center operators — are susceptible to displacement or much-reduced roles. No economic law guarantees that productivity growth benefits everyone equally. Unless we thoughtfully manage the transition, some people, even a majority, are vulnerable to being left behind even as others reap billions.
Whether it’s for the better and for the many is up to human intelligence.
Recently, there has been an explosion of interest in applying artificial intelligence (AI) to medicine. Whether explicitly or implicitly, much of this interest has centered on using AI to automate decision-making tasks that are currently done by physicians. This includes two seminal papers in the Journal of the American Medical Association demonstrating that AI-based algorithms have similar or higher accuracy than physicians: one in diagnostic assessment of metastatic breast cancer compared to pathologists and the other in detecting diabetic retinopathy compared to ophthalmologists.
While promising, these applications of AI in medicine raise a number of novel regulatory and policy issues around efficacy, safety, health workforce, and payment. They have also triggered concerns from the medical and patient communities about AI replacing doctors. And, except in narrow domains of practice, general AI systems may fall far short of the hype.
We posit that the applications of AI to “augment” physicians may be more realistic and broader reaching than those that portend to replace existing health care services. In particular, with the right support from policy makers, physicians, patients, and the technology community, we see opportunities for AI to be a solution for—rather than a contributor to—burnout among physicians and achieving the quadruple aim of improving health, enhancing the experience of care, reducing cost, and attaining joy in work for health professionals.
Over its 60-year history, DARPA has played a leading role in the creation and advancement of artificial intelligence (AI) technologies that have produced game-changing capabilities for the Department of Defense. Starting in the 1960s, DARPA research shaped the first wave of AI technologies, which focused on handcrafted knowledge, or rule-based systems capable of narrowly defined tasks. While a critical step forward for the field, these systems were fragile and limited. Starting in the 1990s, DARPA helped usher in a second wave of AI machine learning technologies that created statistical pattern recognizers from large amounts of data. The agency’s funding of natural language understanding, problem solving, navigation and perception technologies has led to the creation of self-driving cars, personal assistants, and near-natural prosthetics, in addition to a myriad of critical and valuable military and commercial applications. However, these second wave AI technologies are dependent on large amounts of high quality training data, do not adapt to changing conditions, offer limited performance guarantees, and are unable to provide users with explanations of their results.
To address the limitations of these first and second wave AI technologies, DARPA seeks to explore new theories and applications that could make it possible for machines to adapt to changing situations. DARPA sees this next generation of AI as a third wave of technological advance, one of contextual adaptation. To better define a path forward, DARPA is announcing today a multi-year investment of more than $2 billion in new and existing programs called the “AI Next” campaign. Agency director, Dr. Steven Walker, officially unveiled the large-scale effort during closing remarks today at DARPA’s D60 Symposium taking place Wednesday through Friday at the Gaylord Resort and Convention Center in National Harbor, Maryland.
“With AI Next, we are making multiple research investments aimed at transforming computers from specialized tools to partners in problem-solving,” said Dr. Walker. “Today, machines lack contextual reasoning capabilities, and their training must cover every eventuality, which is not only costly, but ultimately impossible. We want to explore how machines can acquire human-like communication and reasoning capabilities, with the ability to recognize new situations and environments and adapt to them.”
This study investigated the portrayal of “personalized” and “precision” medicine (PM) in North American news over the past decade. Content analysis of print and online news was conducted to determine how PM has been defined and to identify the frames used to discuss PM, including associated topics, benefits, and concerns.
A data set was built using the FACTIVA database, searching for popular North American publications with the terms “personalized (personalised) medicine” and/or “precision medicine” from 1 January 2005 to 15 March 2016. The final set of publications totaled 774.
PM is almost exclusively defined as related to genetics and is often part of a story related to cancer. The PM story is overwhelmingly one of highlighting (potential) benefits and optimism, especially in shorter publications, and ones where PM is not the main focus. This promotional PM discourse has remained fairly consistent over the past decade.
Scientists have discovered a new family of molecules that work together to precisely remove unwanted DNA during reproduction in single-celled, freshwater organisms called ciliates.
The discovery of these new molecules has profound implications for our understanding of the mechanism of gene removal (or ‘excision’) and rearrangement which plays a crucial role in the development and evolution of many species. The findings are published in eLife.
Transposons are pieces of DNA that move around in the genome, transported by enzymes called transposases that bind to them. As transposons jump around during evolution, host organisms can acquire the genes they carry and use them to gain new functions in a process known as domestication.
Today, we are delighted to announce that we have launched a new crowdfunding campaign on Lifespan.io: the NAD+ Mouse Project by Dr. David Sinclair and his team at Harvard Medical School.
NAD+ is a vitally important molecule that is found in every cell in your body and is involved in DNA repair, tissue growth, nutrient sensing and metabolism, cell-to-cell signaling, and many other cellular processes. Quite simply, without NAD+, cells would not work and life would be impossible. If you would like to learn more about NAD+ and its role in aging, check out our articles here, here, and here.