This Jarvik-7 artificial heart was used in the first bridge operation in 1985 meant to replace a failing heart while the patient waited for a donor organ.
In June, a team of surgeons at Duke University Hospital implanted the latest model of an artificial heart in a 39-year-old man with severe heart failure, a condition in which the heart doesn't pump properly. The man's mechanical heart, made by French company Carmat, is a new generation artificial heart and the first of its kind to be transplanted in the United States. It connects to a portable external power supply and is designed to keep the patient alive until a replacement organ becomes available.
Many patients die while waiting for a heart transplant, but artificial hearts can bridge the gap. Though not a permanent solution for heart failure, artificial hearts have saved countless lives since their first implantation in 1982.
What might surprise you is that the origin of the artificial heart dates back decades before, when an inventive television actor teamed up with a famous doctor to design and patent the first such device.
A man of many talents
Paul Winchell was an entertainer in the 1950s and 60s, rising to fame as a ventriloquist and guest-starring as an actor on programs like "The Ed Sullivan Show" and "Perry Mason." When children's animation boomed in the 1960s, Winchell made a name for himself as a voice actor on shows like "The Smurfs," "Winnie the Pooh," and "The Jetsons." He eventually became famous for originating the voices of Tigger from "Winnie the Pooh" and Gargamel from "The Smurfs," among many others.
But Winchell wasn't just an entertainer: He also had a quiet passion for science and medicine. Between television gigs, Winchell busied himself working as a medical hypnotist and acupuncturist, treating the same Hollywood stars he performed alongside. When he wasn't doing that, Winchell threw himself into engineering and design, building not only the ventriloquism dummies he used on his television appearances but a host of products he'd dreamed up himself. Winchell spent hours tinkering with his own inventions, such as a set of battery-powered gloves and something called a "flameless lighter." Over the course of his life, Winchell designed and patented more than 30 of these products – mostly novelties, but also serious medical devices, such as a portable blood plasma defroster.
| Ventriloquist Paul Winchell with Jerry Mahoney, his dummy, in 1951 |
A meeting of the minds
In the early 1950s, Winchell appeared on a variety show called the "Arthur Murray Dance Party" and faced off in a dance competition with the legendary Ricardo Montalban (Winchell won). At a cast party for the show later that same night, Winchell met Dr. Henry Heimlich – the same doctor who would later become famous for inventing the Heimlich maneuver, who was married to Murray's daughter. The two hit it off immediately, bonding over their shared interest in medicine. Before long, Heimlich invited Winchell to come observe him in the operating room at the hospital where he worked. Winchell jumped at the opportunity, and not long after he became a frequent guest in Heimlich's surgical theatre, fascinated by the mechanics of the human body.
One day while Winchell was observing at the hospital, he witnessed a patient die on the operating table after undergoing open-heart surgery. He was suddenly struck with an idea: If there was some way doctors could keep blood pumping temporarily throughout the body during surgery, patients who underwent risky operations like open-heart surgery might have a better chance of survival. Winchell rushed to Heimlich with the idea – and Heimlich agreed to advise Winchell and look over any design drafts he came up with. So Winchell went to work.
Winchell's heart
As it turned out, building ventriloquism dummies wasn't that different from building an artificial heart, Winchell noted later in his autobiography – the shifting valves and chambers of the mechanical heart were similar to the moving eyes and opening mouths of his puppets. After each design, Winchell would go back to Heimlich and the two would confer, making adjustments along the way to.
By 1956, Winchell had perfected his design: The "heart" consisted of a bag that could be placed inside the human body, connected to a battery-powered motor outside of the body. The motor enabled the bag to pump blood throughout the body, similar to a real human heart. Winchell received a patent for the design in 1963.
At the time, Winchell never quite got the credit he deserved. Years later, researchers at the University of Utah, working on their own artificial heart, came across Winchell's patent and got in touch with Winchell to compare notes. Winchell ended up donating his patent to the team, which included Dr. Richard Jarvik. Jarvik expanded on Winchell's design and created the Jarvik-7 – the world's first artificial heart to be successfully implanted in a human being in 1982.
The Jarvik-7 has since been replaced with newer, more efficient models made up of different synthetic materials, allowing patients to live for longer stretches without the heart clogging or breaking down. With each new generation of hearts, heart failure patients have been able to live relatively normal lives for longer periods of time and with fewer complications than before – and it never would have been possible without the unsung genius of a puppeteer and his love of science.
Avalanche rescue dogs train to find and dig out people buried in snow slides
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.”
