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Hypoxia researchers win 2019 Nobel Prize in Medicine
Three scientist friends, working separately, share the prestigious prize.

- Nobel recognizes breakthrough insights into cell's perception and response to changes in oxygen levels.
- Too title oxygen is a problem. Also too much.
- Their research unveiled a genuine "textbook discovery."
The 2019 Nobel Prize in Medicine has just been awarded to three scientists from the U.S. and U.K. working independently on the same problem: How cells sense and adapt to oxygen availability. They've unveiled the series of molecular events that allow cells to assess and respond to changing levels of available oxygen, with implications in the treatment of cancer, heart attacks, strokes, anemia, and other diseases.
According to the Nobel Assembly, these seminal discoveries "revealed one of life's most essential adaptive processes." The Assembly's Randall Johnson says, "Scientists often toss around this phrase 'textbook discovery.' But I'd say this is really essentially a textbook discovery." He envisions the discovery as "something basic biology students will be learning about when they study — at aged 12 or 13 or younger — biology, and learn the fundamental ways cells work."
Three scientists with three questions
Image source: Paramonov Alexander/Shutterstock
The three scientists who received the 5 a.m. call from Stockholm are Gregg Semenza (Johns Hopkins University), Sir Peter Ratcliffe (Oxford University), and William Kaelin, Jr. (Dana-Farber Cancer Institute/Harvard University). The three shared their work informally over the years in an ongoing conversation that moved the whole field of study forward. Each had his own reason for pursuing his research area, and their interests reflect the far-ranging impact of their findings.
Semenza wondered exactly what it was that cancer cells were seeking when they spread to new areas in the body. He suspected it was oxygen.
As a kidney specialist, Ratcliffe was intrigued by the manner in which the kidney regulated the production of a particular hormone, erythropoietin (EPO), which affects the production of red, oxygen-carrying blood cells in response to changes in levels of available oxygen. Others considered this to be a not-very-interesting question, but Ratcliffe was intrigued.
For Kaelin, it was a pursuit of answers behind a rare genetic form of cancer, Von Hippel-Lindau syndrome (VHL disease), known to involve exaggerated production levels of EPO, and an excess of blood vessels. He had a hunch it was something in cells' then-mysterious oxygen-sensing mechanism malfunctioning.
Why this is important
Image source: Daniel Prudek /Shutterstock
Cells need oxygen to live, and Earth's air-breathing organisms have developed ways to ensure their cells get the amount of oxygen they need. At high altitudes, for example, we produce more red blood cells to accommodate the relative scarcity of air and combat the onset of hypoxia. While a lack of oxygen can be deadly, so too can too much — it may be that an excess of oxygen can be exploited by some cancers, among other issues.
Human bodies have developed a couple of ways to monitor and respond to changes in oxygen levels. The carotid body associated with the large vessels on both sides of the neck have unique cells that sense oxygen levels, and, as noted above, the body produces more oxygen-carrying cells to maximize delivery of what O2 there is when there's not enough. Production of these oxygen-carrying cells is triggered by the production of erythropoietin (EPO) — it's this system that the Nobel winners explored.
A technical glimpse into a three-part puzzle
Image source: DragonTiger8/Shutterstock
The research that led to the Nobel-awarded discovery began back in the 1990s when, Semenza started studying the EPO gene to learn how its production was being controlled. He identified a DNA segment near the EPO gene that appeared to be regulating its production in response to hypoxia. Most interestingly, this DNA, also spotted around the same time by Ratcliffe, wasn't only in kidney cells known to produce EPO, but in all cells.
Eventually Semenza discovered a protein complex that binds to the DNA depending on the amount of oxygen available, and named it hypoxia-inducible factor, or HIF. HIF turned out to be a pair of different DNA-binding proteins, HIF-1α and ARNT.
The amount of HIF-1α increases when oxygen levels are low, apparently due to an oxygen-related reduction in the effect of ubiquitin, a peptide that normally would bind with and quickly decay HIF-1α.
As a result of his immersion in Von Hippel-Lindau research, Ratcliffe discovered why a lack of oxygen could dampen ubiquitin's bite: HIF-1α is tagged for destruction by ubiquitin via the VHL gene. (An absence of the VHL gene causes the disease by allowing the presence of too much HIF-1α.)
This implied an unknown interaction between the VHL gene and HIF-1α and Kaelin and Ratcliffe worked it out. They realized that at normal oxygen levels, two hydroxyl groups were added to two locations in HIF-1α. Aided by oxygen-sensitive enzymes, VHL thus binds to HIF-1α and moderates the production of EPO and the number red blood cells. With either too little or too much oxygen, this balance is upset.
In all, this daisy-chained sets of research has given us a new insight about our bodies — specifically, of the series of molecular events that constantly help our cells assess and respond to changing levels of oxygen. "Textbook discovery," indeed.
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
<img type="lazy-image" data-runner-src="https://assets.rebelmouse.io/eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpbWFnZSI6Imh0dHBzOi8vYXNzZXRzLnJibC5tcy8yNTA0Njk2OC9vcmlnaW4uanBnIiwiZXhwaXJlc19hdCI6MTYyMzM2NDQzOH0.rid9regiDaKczCCKBsu7wrHkNQ64Vz_XcOEZIzAhzgM/img.jpg?width=980" id="2bb93" class="rm-shortcode" data-rm-shortcode-id="31345afbdf2bd408fd3e9f31520c445a" data-rm-shortcode-name="rebelmouse-image" data-width="1546" data-height="1056" />Northwell emergency departments use the dashboard to monitor in real time.
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 |
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.
- While today's computers—referred to as classical computers—continue to become more and more powerful, there is a ceiling to their advancement due to the physical limits of the materials used to make them. Quantum computing allows physicists and researchers to exponentially increase computation power, harnessing potential parallel realities to do so.
- Quantum computer chips are astoundingly small, about the size of a fingernail. Scientists have to not only build the computer itself but also the ultra-protected environment in which they operate. Total isolation is required to eliminate vibrations and other external influences on synchronized atoms; if the atoms become 'decoherent' the quantum computer cannot function.
- "You need to create a very quiet, clean, cold environment for these chips to work in," says quantum computing expert Vern Brownell. The coldest temperature possible in physics is -273.15 degrees C. The rooms required for quantum computing are -273.14 degrees C, which is 150 times colder than outer space. It is complex and mind-boggling work, but the potential for computation that harnesses the power of parallel universes is worth the chase.
The scent of sickness: 5 questions answered about using dogs – and mice and ferrets – to detect disease
Could medical detection animals smell coronavirus?
