Shoot for the Moon: Its Surface Contains a Pot of Gold
Here's a riddle: What do the Moon, nuclear weapons, clean energy of the future, terrorism, and lung disease all have in common?
One goal of India's upcoming space probe is to locate deposits of helium-3 that are worth trillions of dollars.
The answer is helium-3, a gas that's extremely rare on Earth but 100 million times more abundant on the Moon. This past October, the Lockheed Martin corporation announced a concept for a lunar landing craft that may return humans to the Moon in the coming decade, and yesterday China successfully landed the Change-4 probe on the far side of the Moon. Landing inside the Moon's deepest crater, the Chinese achieved a first in space exploration history.
Meanwhile, later this month, India's Chandrayaan-2 space probe will also land on the lunar surface. One of its goals is to locate deposits of helium-3 that are worth trillions of dollars, because it could be a fuel for nuclear fusion energy to generate electricity or propel a rocket.
The standard way that nuclear engineers are trying to achieve sustainable fusion uses fuels that are more plentiful on Earth: deuterium and tritium. But MIT researchers have found that adding small amounts of helium-3 to the mix could make it much more efficient, and thus a viable energy source much sooner that once thought.
Even if fusion is proven practical tomorrow, any kind of nuclear energy involves long waits for power plant construction measured in decades. However, mining helium-3 could be useful now, because of its non-energy applications. A major one is its ability to detect neutrons coming from plutonium that could be used in terrorist attacks. Here's how it works: a small amount of helium-3 is contained within a forensic instrument. When a neutron hits an atom of helium-3, the reaction produces tritium, a proton, and an electrical charge, alerting investigators to the possibility that plutonium is nearby.
Ironically, as global concern about a potential for hidden nuclear material increased in the early 2000s, so did the supply of helium-3 on Earth. That's because helium-3 comes from the decay of tritium, used in thermonuclear warheads (H-bombs). Thousands of such weapons have been dismantled from U.S. and Russian arsenals, making helium-3 available for plutonium detection, research, and other applications--including in the world of healthcare.
Helium-3 can help doctors diagnose lung diseases, since it enables imaging of the lungs in real time.
Helium-3 dramatically improves the ability of doctors to image the lungs in a range of diseases including asthma, chronic obstructive pulmonary disease and emphysema, cystic fibrosis, and bronchopulmonary dysplasia, which happens particularly in premature infants. Specifically, helium-3 is useful in magnetic resonance imaging (MRI), a procedure that creates images from within the body for diagnostic purposes.
But while a standard MRI allows doctors to visualize parts of the body like the heart or brain, it's useless for seeing the lungs. Because lungs are filled with air, which is much less dense than water or fat, effectively no signals are produced that would enable imaging.
To compensate for this problem, a patient can inhale gas that is hyperpolarized –meaning enhanced with special procedures so that the magnetic resonance signals from the lungs are finally readable. This gas is safe to breathe when mixed with enough oxygen to support life. Helium-3 is one such gas that can be hyperpolarized; since it produces such a strong signal, the MRI can literally see the air inside the lungs and in all of the airways, revealing intricate details of the bronchopulmonary tree. And it can do this in real time
The capability to show anatomic details of the lungs and airways, and the ability to display functional imaging as a patient breathes, makes helium-3 MRI far better than the standard method of testing lung function. Called spirometry, this method tells physicians how the lungs function overall, but does not home in on particular areas that may be causing a problem. Plus, spirometry requires patients to follow instructions and hold their breath, so it is not great for testing young children with pulmonary disease.
In recent years, the cost of helium-3 on Earth has skyrocketed.
Over the past several years, researchers have been developing MRI for lung testing using other hyperpolarized gases. The main alternative to helium-3 is xenon-129. Over the years, researchers have learned to overcome certain disadvantages of the latter, such as its potential to put patients to sleep. Since helium-3 provides the strongest signal, though, it is still the best gas for MRI studies in many lung conditions.
But the supply of helium-3 on Earth has been decreasing in recent years, due to the declining rate of dismantling of warheads, just as the Department of Homeland Security has required more and more of the gas for neutron detection. As a result, the cost of the gas has skyrocketed. Less is available now for medical uses – unless, of course, we begin mining it on the moon.
The question is: Are the benefits worth the 239,000-mile trip?
The Friday Five covers five stories in research that you may have missed this week. There are plenty of controversies and troubling ethical issues in science – and we get into many of them in our online magazine – but this news roundup focuses on new scientific theories and progress to give you a therapeutic dose of inspiration headed into the weekend.
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Here are the stories covered this week:
- The eyes are the windows to the soul - and biological aging?
- What bean genes mean for health and the planet
- This breathing practice could lower levels of tau proteins
- AI beats humans at assessing heart health
- Should you get a nature prescription?
Two-and-a-half year-old Huckleberry, a blue merle Australian shepherd, pulls hard at her leash; her yelps can be heard by skiers and boarders high above on the chairlift that carries them over the ski patrol hut to the top of the mountain. Huckleberry is an avalanche rescue dog — or avy dog, for short. She lives and works with her owner and handler, a ski patroller at Breckenridge Ski Resort in Colorado. As she watches the trainer play a game of hide-and-seek with six-month-old Lume, a golden retriever and avy dog-in-training, Huckleberry continues to strain on her leash; she loves the game. Hide-and-seek is one of the key training methods for teaching avy dogs the rescue skills they need to find someone caught in an avalanche — skier, snowmobiler, hiker, climber.
Lume’s owner waves a T-shirt in front of the puppy. While another patroller holds him back, Lume’s owner runs away and hides. About a minute later — after a lot of barking — Lume is released and commanded to “search.” He springs free, running around the hut to find his owner who reacts with a great amount of excitement and fanfare. Lume’s scent training will continue for the rest of the ski season (Breckenridge plans operating through May or as long as weather permits) and through the off-season. “We make this game progressively harder by not allowing the dog watch the victim run away,” explains Dave Leffler, Breckenridge's ski patroller and head of the avy dog program, who has owned, trained and raised many of them. Eventually, the trainers “dig an open hole in the snow to duck out of sight and gradually turn the hole into a cave where the dog has to dig to get the victim,” explains Leffler.
By the time he is three, Lume, like Huckleberry, will be a fully trained avy pup and will join seven other avy dogs on Breckenridge ski patrol team. Some of the team members, both human and canine, are also certified to work with Colorado Rapid Avalanche Deployment, a coordinated response team that works with the Summit County Sheriff’s office for avalanche emergencies outside of the ski slopes’ boundaries.
There have been 19 avalanche deaths in the U.S. this season, according to avalanche.org, which tracks slides; eight in Colorado. During the entirety of last season there were 17. Avalanche season runs from November through June, but avalanches can occur year-round.
High tech and high stakes
Complementing avy dogs’ ability to smell people buried in a slide, avalanche detection, rescue and recovery is becoming increasingly high tech. There are transceivers, signal locators, ground scanners and drones, which are considered “games changers” by many in avalanche rescue and recovery
For a person buried in an avalanche, the chance of survival plummets after 20 minutes, so every moment counts.
A drone can provide thermal imaging of objects caught in a slide; what looks like a rock from far away might be a human with a heat signature. Transceivers, also known as beacons, send a signal from an avalanche victim to a companion. Signal locators, like RECCO reflectors which are often sewn directly into gear, can echo back a radar signal sent by a detector; most ski resorts have RECCO detector units.
Research suggests that Ground Penetrating Radar (GPR), an electromagnetic tool used by geophysicists to pull images from inside the ground, could be used to locate an avalanche victim. A new study from the Department of Energy’s Sandia National Laboratories suggests that a computer program developed to pinpoint the source of a chemical or biological terrorist attack could also be used to find someone submerged in an avalanche. The search algorithm allows for small robots (described as cockroach-sized) to “swarm” a search area. Researchers say that this distributed optimization algorithm can help find avalanche victims four times faster than current search mechanisms. For a person buried in an avalanche, the chance of survival plummets after 20 minutes, so every moment counts.
An avy dog in training is picking up scent
Sarah McLear
While rescue gear has been evolving, predicting when a slab will fall remains an emerging science — kind of where weather forecasting science was in the 1980s. Avalanche forecasting still relies on documenting avalanches by going out and looking,” says Ethan Greene, director of the Colorado Avalanche Information Center (CAIC). “So if there's a big snowstorm, and as you might remember, most avalanches happened during snowstorms, we could have 10,000 avalanches that release and we document 50,” says Greene. “Avalanche forecasting is essentially pattern recognition,” he adds--and understanding the layering structure of snow.
However, determining where the hazards lie can be tricky. While a dense layer of snow over a softer, weaker layer may be a recipe for an avalanche, there’s so much variability in snowpack that no one formula can predict the trigger. Further, observing and measuring snow at a single point may not be representative of all nearby slopes. Finally, there’s not enough historical data to help avalanche scientists create better prediction models.
That, however, may be changing.
Last year, an international group of researchers created computer simulations of snow cover using 16 years of meteorological data to forecast avalanche hazards, publishing their research in Cold Regions Science and Technology. They believe their models, which categorize different kinds of avalanches, can support forecasting and determine whether the avalanche is natural (caused by temperature changes, wind, additional snowfall) or artificial (triggered by a human or animal).
With smell receptors ranging from 800 million for an average dog, to 4 billion for scent hounds, canines remain key to finding people caught in slides.
With data from two sites in British Columbia and one in Switzerland, researchers built computer simulations of five different avalanche types. “In terms of real time avalanche forecasting, this has potential to fill in a lot of data gaps, where we don't have field observations of what the snow looks like,” says Simon Horton, a postdoctoral fellow with the Simon Fraser University Centre for Natural Hazards Research and a forecaster with Avalanche Canada, who participated in the study. While complex models that simulate snowpack layers have been around for a few decades, they weren’t easy to apply until recently. “It's been difficult to find out how to apply that to actual decision-making and improving safety,” says Horton. If you can derive avalanche problem types from simulated snowpack properties, he says, you’ll learn “a lot about how you want to manage that risk.”
The five categories include “new snow,” which is unstable and slides down the slope, “wet snow,” when rain or heat makes it liquidly, as well as “wind-drifted snow,” “persistent weak layers” and “old snow.” “That's when there's some type of deeply buried weak layer in the snow that releases without any real change in the weather,” Horton explains. “These ones tend to cause the most accidents.” One step by a person on that structurally weak layer of snow will cause a slide. Horton is hopeful that computer simulations of avalanche types can be used by scientists in different snow climates to help predict hazard levels.
Greene is doubtful. “If you have six slopes that are lined up next to each other, and you're going to try to predict which one avalanches and the exact dimensions and what time, that's going to be really hard to do. And I think it's going to be a long time before we're able to do that,” says Greene.
What both researchers do agree on, though, is that what avalanche prediction really needs is better imagery through satellite detection. “Just being able to count the number of avalanches that are out there will have a huge impact on what we do,” Greene says. “[Satellites] will change what we do, dramatically.” In a 2022 paper, scientists at the University of Aberdeen in England used satellites to study two deadly Himalayan avalanches. The imaging helped them determine that sediment from a 2016 ice avalanche plus subsequent snow avalanches contributed to the 2021 avalanche that caused a flash flood, killing over 200 people. The researchers say that understanding the avalanches characteristics through satellite imagery can inform them how one such event increases the magnitude of another in the same area.
Avy dogs trainers hide in dug-out holes in the snow, teaching the dogs to find buried victims
Sarah McLear
Lifesaving combo: human tech and Mother Nature’s gear
Even as avalanche forecasting evolves, dogs with their built-in rescue mechanisms will remain invaluable. With smell receptors ranging from 800 million for an average dog, to 4 billion for scent hounds, canines remain key to finding people caught in slides. (Humans in comparison, have a meager 12 million.) A new study published in the Journal of Neuroscience revealed that in dogs smell and vision are connected in the brain, which has not been found in other animals. “They can detect the smell of their owner's fingerprints on a glass slide six weeks after they touched it,” says Nicholas Dodman, professor emeritus at Cummings School of Veterinary Medicine at Tufts University. “And they can track from a boat where a box filled with meat was buried in the water, 100 feet below,” says Dodman, who is also co-founder and president of the Center for Canine Behavior Studies.
Another recent study from Queens College in Belfast, United Kingdom, further confirms that dogs can smell when humans are stressed. They can also detect the smell of a person’s breath and the smell of the skin cells of a deceased person.
The emerging avalanche-predicting human-made tech and the incredible nature-made tech of dogs’ olfactory talents is the lifesaving “equipment” that Leffler believes in. Even when human-made technology develops further, it will be most efficient when used together with the millions of dogs’ smell receptors, Leffler believes. “It is a combination of technology and the avalanche dog that will always be effective in finding an avalanche victim.”