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The New Nutrition Facts Label: Why the Makeover?

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You’re probably aware of the Nutrition Facts label on foods—it’s been around for more than 20 years. What you may not know is that the label has had a makeover—with improvements that can help you make healthy choices about the foods you and your family eat. 

Including the example above, the U.S. Food and Drug Administration (FDA) is launching a lively new education campaign to introduce you to those improvements—and how you can use them.

Lookin’ Good

Starting today and for the next year, you’ll see the campaign in action in a number of places and in a number of ways. Look for colorful advertisements on your grocery store shopping carts in eight locations across the United States, as well as on Facebook, Instagram and Pandora.

Also check out the snazzy videos on YouTube and on fda.gov.

Audience Favorites

The redesigned label has a number of new features for consumers like updated serving sizes to better match how much people eat and larger font size for calories. Also, new nutrients are listed, like Vitamin D, potassium and added sugars. FDA’s education campaign aims to reach the general population and targeted sub-populations at increased risk of nutrition-related chronic disease.

What’s in it for you? Take a look at the new, improved label and find out!

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New York researchers rush to capture 3-D data map of COVID-19 ‘surface vectors’

Credit: NYU Tandon School of Engineering

New York University researchers are in the field capturing highly detailed three-dimensional data on human movements and behaviors—particularly around medical facilities, public transportation systems, and essential services—to document the complex landscape of “surface vectors” and thus opportunities for COVID-19 transmission.

Working under a National Science Foundation Rapid Response Research (RAPID) grant for proposals with severe urgency, the team from the NYU Tandon School of Engineering and the NYU School of Global Health is advancing epidemiological analysis beyond the two-dimensional concept that has been in use since 1854, when John Snow first mapped cholera cases to identify specific contaminated wells as the infection sources of a severe local outbreak in London.

Rapid, repeated documentation and mapping of current conditions around medical and transport facilities will make it possible to investigate the implementation of social distancing regulations and predict patterns of exposure and transmission moving forward, explained the professors. The lead investigator for the project is Debra Laefer, a professor of civil and urban engineering at NYU Tandon who also serves as a professor of urban informatics and director of citizen science at its Center for Urban Science and Progress (CUSP), and the co-leader for the project is Thomas Kirchner, director of the NYU mobile health lab and an assistant professor of social and behavioral sciences at the School of Global Public Health.

This first-of-a-kind study will also lay the groundwork to build machine learning models to speed the analysis of how a virus spreads in urban areas—not just in New York, but across the United States and beyond. For instance, the project is pioneering a new way of thinking and documenting transmission locations. This type of documentation and modeling could easily be applied to airports, , and playgrounds—anywhere large groups of people come,

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Safely Using Hand Sanitizer | FDA

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Each of us can help stop the spread of COVID-19 disease by washing our hands regularly with soap and water for 20 seconds – especially after going to the bathroom, before eating, and after coughing, sneezing, or blowing your nose. If soap and water are not available, the Centers for Disease Control and Prevention recommend that consumers use alcohol-based hand sanitizers containing at least 60% alcohol.

The alcohol in hand sanitizer works best when you rub hand sanitizer all over your hands, making sure to get between your fingers and on the back of your hands. Do not wipe or rinse off the hand sanitizer before it is dry. Do not use hand sanitizer if your hands are visibly dirty or greasy; wash your hands with soap and water instead.

If you use alcohol-based hand sanitizers, please pay attention to the information below.

Hand Sanitizers Are Drugs

Hand sanitizers are regulated as over-the-counter (non-prescription) drugs by the U.S. Food and Drug Administration. If you use alcohol-based hand sanitizers, read and follow the Drug Facts label, particularly the warnings section.

Store hand sanitizer out of the reach of pets and children, and children should use it only with adult supervision.

Do not drink hand sanitizer. This is particularly important for young children, especially toddlers, who may be attracted by the pleasant smell or brightly colored bottles of hand sanitizer. Drinking even a small amount of hand sanitizer can cause alcohol poisoning in children. (However, there is no need to be concerned if your children eat with or lick their hands after using hand sanitizer.) During this coronavirus pandemic, poison control centers have had an increase in calls about accidental ingestion of hand sanitizer, so it is important that adults monitor young children’s use.

Do not allow pets to

Health Life

Artificial intelligence could help predict future diabetes cases

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A type of artificial intelligence called machine learning can help predict which patients will develop diabetes, according to an ENDO 2020 abstract that will be published in a special supplemental section of the Journal of the Endocrine Society.

Diabetes is linked to increased risks of severe health problems, including heart disease and cancer. Preventing is essential to reduce the risk of illness and death. “Currently we do not have sufficient methods for predicting which generally healthy individuals will develop diabetes,” said lead author Akihiro Nomura, M.D., Ph.D., of the Kanazawa University Graduate School of Medical Sciences in Kanazawa, Japan.

The researchers investigated the use of a type of called in diagnosing diabetes. Artificial intelligence (AI) is the development of computer systems able to perform tasks that normally require human intelligence. Machine learning is a type of AI that enables computers to learn without being explicitly programmed. With each exposure to new data, a machine-learning algorithm grows increasingly better at recognizing patterns over time.

“Using machine learning, it could be possible to precisely identify high-risk groups of future diabetes patients better than using existing risk scores,” Nomura said. “In addition, the rate of visits to might be improved to prevent future onset of diabetes.”

Nomura and colleagues analyzed 509,153 nationwide annual health checkup records from 139,225 participants from 2008 to 2018 in the city of Kanazawa. Among them, 65,505 participants without diabetes were included.

The data included physical exams, blood and urine tests and participant questionnaires. Patients without diabetes at the beginning of the study who underwent more than two annual health checkups during this period were included. New cases of diabetes were recorded during patients’ checkups.

The researchers identified a total of 4,696 new diabetes patients (7.2%) in