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A Calorie is Not a Calorie and Its Source Can Significantly Affect Body Weight
Evidence from recent research suggests that it does matter where a calorie comes from because its source influences the intake of the next calorie.

When it comes to weight loss and weight gain, energy intake is crucial. And when it comes to energy intake, the most simplistic view is - a calorie is a calorie, regardless of where it comes from (protein, fat or carbohydrates). Evidence from recent research suggests that it does matter where a calorie comes from because its source influences the intake of the next calorie. Changes in macronutrient intake (the ratio of carbohydrates, fat and protein in a diet) may significantly affect a person’s total energy intake.
Take, for example, the effect changes in macronutrient intake have had on the U.S. population. Between the 1970s and 2014 the percentage of energy intake from carbohydrates has increased from 44% to 49%, while that of protein and fat has decreased - from 17% to 16% and from 37% to 33% respectively. This change in macronutrient composition is correlated with an increase in total energy intake by approximately 235 kcal per day and an increase in the prevalence of obesity from 11.9% to 33.4% in men and from 16.6% to 36.5% in women (Source1, Source2).
One explanation why this correlation exists is the “protein leverage hypothesis”. Based on studies in a variety of animals it posits that when animals are given foods low in protein they will continue eating carb-heavy foods until these foods have supplied them with the required protein, even if the extra food surpasses their caloric requirements and results in weight gain. This protein regulation has also been observed in humans. One study found that a 1.5%E decrease in dietary protein intake increases energy intake from carbohydrates and fats by 14%. Another study found that a 1%E increase in dietary protein intake corresponded to a 31-54 kcal decrease in daily energy intake. (Source)
Moreover, it turns out that the amount of carbs and protein that one consumes affects energy metabolism and the oxidation of fat (how much of the stored fat in the body is broken down and used for fuel). It turns out that protein intake can potentially increase fat oxidation by up to 50%, while added sugar (in the form of a sugary drink) decreases it (Source).
Sugary beverages like soda have been the largest source of added sugar in the diet of Americans in the last decades. A recently published study examined how sugar-sweetened beverages (SSBs) affect the oxidation of fat and feelings of satiety when consumed with a low-protein (15%E) or a high-protein meal (30%E).
High protein meals proved to have several positive effects compared to low-protein meals - they significantly reduced the feeling of hunger in participants, decreased the appetite for savory, salty and fatty foods, as well as decreased the participants' future food intake. These positive effects were negated, however, when a sugary drink was added to the high-protein meal. The added sugar actually increased the appetite for savory and salty foods and, surprisingly, the additional calories from the drink did not result in an increased feeling of satiety. In addition, drinking a sugar-sweetened beverage with a meal high in protein decreased fat oxidation after the meal by 8%. Over time, this effect of sugary drinks, especially when paired with high protein meals, may lead to a greater tendency to store fat and increased body weight.
While bodybuilders, for decades, have known about the importance of protein in the diet and have been building their nutrition plans around its intake, the importance of this macronutrient has mostly been neglected by the popular media and the general public because of their focus on fat, carbs and calories in general. As the authors of the study point out, however, this new data “highlight the need to design strategies aimed at maximizing macronutrient balance instead of focusing on interventions that strictly target energy balance.”
How New York's largest hospital system is predicting COVID-19 spikes
Northwell Health is using insights from website traffic to forecast COVID-19 hospitalizations two weeks in the future.
- The machine-learning algorithm works by analyzing the online behavior of visitors to the Northwell Health website and comparing that data to future COVID-19 hospitalizations.
- The tool, which uses anonymized data, has so far predicted hospitalizations with an accuracy rate of 80 percent.
- Machine-learning tools are helping health-care professionals worldwide better constrain and treat COVID-19.
The value of forecasting
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Credit: Northwell Health
<p>One unique benefit of forecasting COVID-19 hospitalizations is that it allows health systems to better prepare, manage and allocate resources. For example, if the tool forecasted a surge in COVID-19 hospitalizations in two weeks, Northwell Health could begin:</p><ul><li>Making space for an influx of patients</li><li>Moving personal protective equipment to where it's most needed</li><li>Strategically allocating staff during the predicted surge</li><li>Increasing the number of tests offered to asymptomatic patients</li></ul><p>The health-care field is increasingly using machine learning. It's already helping doctors develop <a href="https://care.diabetesjournals.org/content/early/2020/06/09/dc19-1870" target="_blank">personalized care plans for diabetes patients</a>, improving cancer screening techniques, and enabling mental health professionals to better predict which patients are at <a href="https://healthitanalytics.com/news/ehr-data-fuels-accurate-predictive-analytics-for-suicide-risk" target="_blank" rel="noopener noreferrer">elevated risk of suicide</a>, to name a few applications.</p><p>Health systems around the world have already begun exploring how <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7315944/" target="_blank" rel="noopener noreferrer">machine learning can help battle the pandemic</a>, including better COVID-19 screening, diagnosis, contact tracing, and drug and vaccine development.</p><p>Cruzen said these kinds of tools represent a shift in how health systems can tackle a wide variety of problems.</p><p>"Health care has always used the past to predict the future, but not in this mathematical way," Cruzen said. "I think [Northwell Health's new predictive tool] really is a great first example of how we should be attacking a lot of things as we go forward."</p>Making machine-learning tools openly accessible
<p>Northwell Health has made its predictive tool <a href="https://github.com/northwell-health/covid-web-data-predictor" target="_blank">available for free</a> to any health system that wishes to utilize it.</p><p>"COVID is everybody's problem, and I think developing tools that can be used to help others is sort of why people go into health care," Dr. Cruzen said. "It was really consistent with our mission."</p><p>Open collaboration is something the world's governments and health systems should be striving for during the pandemic, said Michael Dowling, Northwell Health's president and CEO.</p><p>"Whenever you develop anything and somebody else gets it, they improve it and they continue to make it better," Dowling said. "As a country, we lack data. I believe very, very strongly that we should have been and should be now working with other countries, including China, including the European Union, including England and others to figure out how to develop a health surveillance system so you can anticipate way in advance when these things are going to occur."</p><p>In all, Northwell Health has treated more than 112,000 COVID patients. During the pandemic, Dowling said he's seen an outpouring of goodwill, collaboration, and sacrifice from the community and the tens of thousands of staff who work across Northwell.</p><p>"COVID has changed our perspective on everything—and not just those of us in health care, because it has disrupted everybody's life," Dowling said. "It has demonstrated the value of community, how we help one another."</p>3,000-pound Triceratops skull unearthed in South Dakota
"You dream about these kinds of moments when you're a kid," said lead paleontologist David Schmidt.
Excavation of a triceratops skull in South Dakota.
- The triceratops skull was first discovered in 2019, but was excavated over the summer of 2020.
- It was discovered in the South Dakota Badlands, an area where the Triceratops roamed some 66 million years ago.
- Studying dinosaurs helps scientists better understand the evolution of all life on Earth.
Credit: David Schmidt / Westminster College
<p style="margin-left: 20px;">"We had to be really careful," Schmidt told St. Louis Public Radio. "We couldn't disturb anything at all, because at that point, it was under law enforcement investigation. They were telling us, 'Don't even make footprints,' and I was thinking, 'How are we supposed to do that?'"</p><p>Another difficulty was the mammoth size of the skull: about 7 feet long and more than 3,000 pounds. (For context, the largest triceratops skull ever unearthed was about <a href="https://www.tandfonline.com/doi/abs/10.1080/02724634.2010.483632" target="_blank">8.2 feet long</a>.) The skull of Schmidt's dinosaur was likely a <em>Triceratops prorsus, </em>one of two species of triceratops that roamed what's now North America about 66 million years ago.</p>Credit: David Schmidt / Westminster College
<p>The triceratops was an herbivore, but it was also a favorite meal of the T<em>yrannosaurus rex</em>. That probably explains why the Dakotas contain many scattered triceratops bone fragments, and, less commonly, complete bones and skulls. In summer 2019, for example, a separate team on a dig in North Dakota made <a href="https://www.nytimes.com/2019/07/26/science/triceratops-skull-65-million-years-old.html" target="_blank">headlines</a> after unearthing a complete triceratops skull that measured five feet in length.</p><p>Michael Kjelland, a biology professor who participated in that excavation, said digging up the dinosaur was like completing a "multi-piece, 3-D jigsaw puzzle" that required "engineering that rivaled SpaceX," he jokingly told the <a href="https://www.nytimes.com/2019/07/26/science/triceratops-skull-65-million-years-old.html" target="_blank">New York Times</a>.</p>Morrison Formation in Colorado
James St. John via Flickr
Triceratops illustration
Credit: Nobu Tamura/Wikimedia Commons |
World's oldest work of art found in a hidden Indonesian valley
Archaeologists discover a cave painting of a wild pig that is now the world's oldest dated work of representational art.
Pig painting at Leang Tedongnge in Indonesia, made at 45,500 years ago.
- Archaeologists find a cave painting of a wild pig that is at least 45,500 years old.
- The painting is the earliest known work of representational art.
- The discovery was made in a remote valley on the Indonesian island of Sulawesi.
Oldest Cave Art Found in Sulawesi
<span style="display:block;position:relative;padding-top:56.25%;" class="rm-shortcode" data-rm-shortcode-id="a9734e306f0914bfdcbe79a1e317a7f0"><iframe type="lazy-iframe" data-runner-src="https://www.youtube.com/embed/b-wAYtBxn7E?rel=0" width="100%" height="auto" frameborder="0" scrolling="no" style="position:absolute;top:0;left:0;width:100%;height:100%;"></iframe></span>What can Avicenna teach us about the mind-body problem?
The Persian polymath and philosopher of the Islamic Golden Age teaches us about self-awareness.
The incredible physics behind quantum computing
Can computers do calculations in multiple universes? Scientists are working on it. Step into the world of quantum computing.
