This Resistance Fighter Invented Dialysis in Nazi-Occupied Holland
One of the Netherlands’ most famous pieces of pop culture is “Soldier of Orange.” It’s the title of the country’s most celebrated war memoir, movie and epic stage musical, all of which detail the exploits of the nation’s resistance fighters during World War II.
Willem Johan Kolff was a member of the Dutch resistance, but he doesn’t rate a mention in the “Solider of Orange” canon. Yet his wartime toils in a rural backwater not only changed medicine, but the world.
Kolff had been a physician less than two years before Germany invaded the Netherlands in May 1940. He had been engaged in post-graduate studies at the University of Gronigen but withdrew because he refused to accommodate the demands of the Nazi occupiers. Kolff’s Jewish supervisor made an even starker choice: He committed suicide.
After his departure from the university, Kolff took a job managing a small hospital in Kampen. Located 50 miles from the heavily populated coastal region, the facility was far enough away from the prying eyes of Germans that not only could Kolff care for patients, he could hide fellow resistance fighters and even Jewish refugees in relative safety. Kolff coached many of them to feign convincing terminal illnesses so the Nazis would allow them to remain in the hospital.
Despite the demands of practicing medicine and resistance work, Kolff still found time to conduct research. He had been haunted and inspired when, not long before the Nazi invasion, one of his patients died in agony from kidney disease. Kolff wanted to find a way to save future patients.
He broke his problem down to a simple task: If he could remove 20 grams of urea from a patient’s blood in 24 hours, they would survive. He began experimenting with ways to filter blood and return it to a patient’s body. Since the war had ground all non-military manufacturing to a halt, he was mostly forced to make do with material he could find at the hospital and around Kampen. Kolff eventually built a device from a washing machine parts, juice cans, sausage casings, a valve from an old Ford automobile radiator, and even scrap from a downed German aircraft.
The world’s first dialysis machine was hardly imposing; it resembled a rotating drum for a bingo game or raffle. Yet it carried on the highly sophisticated task of moving a patient’s blood through a semi-permeable membrane (about a 50-foot length of sausage casings) into a saline solution that drew out urea while leaving the blood cells untouched.
In emigrating to the U.S. to practice medicine, Kolff's intent was twofold: Advocate for a wider adoption of dialysis, and work on new projects. He wildly succeeded at both.
Kolff began using the machine to treat patients in 1943, most of whom had lapsed into comas due to their kidney failure. But like most groundbreaking medical devices, it was not an immediate success. By the end of the war, Kolff had dialyzed more than a dozen patients, but all had died. He briefly suspended use of the device after the Allied invasion of Europe, but he continued to refine its operation and the administration of blood thinners to patients.
In September 1945, Kolff dialyzed another comatose patient, 67-year-old Sofia Maria Schafstadt. She regained consciousness after 11 hours, and would live well into the 1950s with Kolff’s assistance. Yet this triumph contained a dark irony: At the time of her treatment, Schafstadt had been imprisoned for collaborating with the Germans.
With a tattered Europe struggling to overcome the destruction of the war, Kolff and his family emigrated to the U.S. in 1950, where he began working for the Cleveland Clinic while undergoing the naturalization process so he could practice medicine in the U.S. His intent was twofold: Advocate for a wider adoption of dialysis, and work on new projects. He wildly succeeded at both.
By the mid-1950s, dialysis machines had become reliable and life-saving medical devices, and Kolff had become a U.S. citizen. About that time he invented a membrane oxygenator that could be used in heart bypass surgeries. This was a critical component of the heart-lung machine, which would make heart transplants possible and bypass surgeries routine. He also invented among the very first practical artificial hearts, which in 1957 kept a dog alive for 90 minutes.
Kolff moved to the University of Utah in 1967 to become director of its Institute for Biomedical Engineering. It was a promising time for such a move, as the first successful transplant of a donor heart to a human occurred that year. But he was interested in going a step further and creating an artificial heart for human use.
It took more than a decade of tinkering and research, but in 1982, a team of physicians and engineers led by Kolff succeeded in implanting the first artificial heart in dentist Barney Clark, whose failing health disqualified him from a heart transplant. Although Clark died in March 1983 after 112 days tethered to the device, that it kept him alive generated international headlines. While graduate student Robert Jarvik received the named credit for the heart, he was directly supervised by Kolff, whose various endeavors into artificial organ research at the University of Utah were segmented into numerous teams.
Forty years later, several artificial hearts have been approved for use by the Food and Drug Administration, although all are a “bridge” that allow patients to wait for a transplant.
Kolff continued researching and tinkering with biomedical devices – including artificial eyes and ears – until he retired in 1997 at the age of 86. When he died in 2009, the medical community acknowledged that he was not only a pioneer in biotechnology, but the “father” of artificial organs.
In today’s podcast episode, Leaps.org Deputy Editor Lina Zeldovich speaks about the health and ecological benefits of farming crickets for human consumption with Bicky Nguyen, who joins Lina from Vietnam. Bicky and her business partner Nam Dang operate an insect farm named CricketOne. Motivated by the idea of sustainable and healthy protein production, they started their unconventional endeavor a few years ago, despite numerous naysayers who didn’t believe that humans would ever consider munching on bugs.
Yet, making creepy crawlers part of our diet offers many health and planetary advantages. Food production needs to match the rise in global population, estimated to reach 10 billion by 2050. One challenge is that some of our current practices are inefficient, polluting and wasteful. According to nonprofit EarthSave.org, it takes 2,500 gallons of water, 12 pounds of grain, 35 pounds of topsoil and the energy equivalent of one gallon of gasoline to produce one pound of feedlot beef, although exact statistics vary between sources.
Meanwhile, insects are easy to grow, high on protein and low on fat. When roasted with salt, they make crunchy snacks. When chopped up, they transform into delicious pâtes, says Bicky, who invents her own cricket recipes and serves them at industry and public events. Maybe that’s why some research predicts that edible insects market may grow to almost $10 billion by 2030. Tune in for a delectable chat on this alternative and sustainable protein.
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Further reading:
More info on Bicky Nguyen
https://yseali.fulbright.edu.vn/en/faculty/bicky-n...
The environmental footprint of beef production
https://www.earthsave.org/environment.htm
https://www.watercalculator.org/news/articles/beef-king-big-water-footprints/
https://www.frontiersin.org/articles/10.3389/fsufs.2019.00005/full
https://ourworldindata.org/carbon-footprint-food-methane
Insect farming as a source of sustainable protein
https://www.insectgourmet.com/insect-farming-growing-bugs-for-protein/
https://www.sciencedirect.com/topics/agricultural-and-biological-sciences/insect-farming
Cricket flour is taking the world by storm
https://www.cricketflours.com/
https://talk-commerce.com/blog/what-brands-use-cricket-flour-and-why/
Lina Zeldovich has written about science, medicine and technology for Popular Science, Smithsonian, National Geographic, Scientific American, Reader’s Digest, the New York Times and other major national and international publications. A Columbia J-School alumna, she has won several awards for her stories, including the ASJA Crisis Coverage Award for Covid reporting, and has been a contributing editor at Nautilus Magazine. In 2021, Zeldovich released her first book, The Other Dark Matter, published by the University of Chicago Press, about the science and business of turning waste into wealth and health. You can find her on http://linazeldovich.com/ and @linazeldovich.
Autonomous, indoor farming gives a boost to crops
The glass-encased cabinet looks like a display meant to hold reasonably priced watches, or drugstore beauty creams shipped from France. But instead of this stagnant merchandise, each of its five shelves is overgrown with leaves — moss-soft pea sprouts, spikes of Lolla rosa lettuces, pale bok choy, dark kale, purple basil or red-veined sorrel or green wisps of dill. The glass structure isn’t a cabinet, but rather a “micro farm.”
The gadget is on display at the Richmond, Virginia headquarters of Babylon Micro-Farms, a company that aims to make indoor farming in the U.S. more accessible and sustainable. Babylon’s soilless hydroponic growing system, which feeds plants via nutrient-enriched water, allows chefs on cruise ships, cafeterias and elsewhere to provide home-grown produce to patrons, just seconds after it’s harvested. Currently, there are over 200 functioning systems, either sold or leased to customers, and more of them are on the way.
The chef-farmers choose from among 45 types of herb and leafy-greens seeds, plop them into grow trays, and a few weeks later they pick and serve. While success is predicated on at least a small amount of these humans’ care, the systems are autonomously surveilled round-the-clock from Babylon’s base of operations. And artificial intelligence is helping to run the show.
Babylon piloted the use of specialized cameras that take pictures in different spectrums to gather some less-obvious visual data about plants’ wellbeing and alert people if something seems off.
Imagine consistently perfect greens and tomatoes and strawberries, grown hyper-locally, using less water, without chemicals or environmental contaminants. This is the hefty promise of controlled environment agriculture (CEA) — basically, indoor farms that can be hydroponic, aeroponic (plant roots are suspended and fed through misting), or aquaponic (where fish play a role in fertilizing vegetables). But whether they grow 4,160 leafy-green servings per year, like one Babylon farm, or millions of servings, like some of the large, centralized facilities starting to supply supermarkets across the U.S., they seek to minimize failure as much as possible.
Babylon’s soilless hydroponic growing system
Courtesy Babylon Micro-Farms
Here, AI is starting to play a pivotal role. CEA growers use it to help “make sense of what’s happening” to the plants in their care, says Scott Lowman, vice president of applied research at the Institute for Advanced Learning and Research (IALR) in Virginia, a state that’s investing heavily in CEA companies. And although these companies say they’re not aiming for a future with zero human employees, AI is certainly poised to take a lot of human farming intervention out of the equation — for better and worse.
Most of these companies are compiling their own data sets to identify anything that might block the success of their systems. Babylon had already integrated sensor data into its farms to measure heat and humidity, the nutrient content of water, and the amount of light plants receive. Last year, they got a National Science Foundation grant that allowed them to pilot the use of specialized cameras that take pictures in different spectrums to gather some less-obvious visual data about plants’ wellbeing and alert people if something seems off. “Will this plant be healthy tomorrow? Are there things…that the human eye can't see that the plant starts expressing?” says Amandeep Ratte, the company’s head of data science. “If our system can say, Hey, this plant is unhealthy, we can reach out to [users] preemptively about what they’re doing wrong, or is there a disease at the farm?” Ratte says. The earlier the better, to avoid crop failures.
Natural light accounts for 70 percent of Greenswell Growers’ energy use on a sunny day.
Courtesy Greenswell Growers
IALR’s Lowman says that other CEA companies are developing their AI systems to account for the different crops they grow — lettuces come in all shapes and sizes, after all, and each has different growing needs than, for example, tomatoes. The ways they run their operations differs also. Babylon is unusual in its decentralized structure. But centralized growing systems with one main location have variabilities, too. AeroFarms, which recently declared bankruptcy but will continue to run its 140,000-square foot vertical operation in Danville, Virginia, is entirely enclosed and reliant on the intense violet glow of grow lights to produce microgreens.
Different companies have different data needs. What data is essential to AeroFarms isn’t quite the same as for Greenswell Growers located in Goochland County, Virginia. Raising four kinds of lettuce in a 77,000-square-foot automated hydroponic greenhouse, the vagaries of naturally available light, which accounts for 70 percent of Greenswell’s energy use on a sunny day, affect operations. Their tech needs to account for “outside weather impacts,” says president Carl Gupton. “What adjustments do we have to make inside of the greenhouse to offset what's going on outside environmentally, to give that plant optimal conditions? When it's 85 percent humidity outside, the system needs to do X, Y and Z to get the conditions that we want inside.”
AI will help identify diseases, as well as when a plant is thirsty or overly hydrated, when it needs more or less calcium, phosphorous, nitrogen.
Nevertheless, every CEA system has the same core needs — consistent yield of high quality crops to keep up year-round supply to customers. Additionally, “Everybody’s got the same set of problems,” Gupton says. Pests may come into a facility with seeds. A disease called pythium, one of the most common in CEA, can damage plant roots. “Then you have root disease pressures that can also come internally — a change in [growing] substrate can change the way the plant performs,” Gupton says.
AI will help identify diseases, as well as when a plant is thirsty or overly hydrated, when it needs more or less calcium, phosphorous, nitrogen. So, while companies amass their own hyper-specific data sets, Lowman foresees a time within the next decade “when there will be some type of [open-source] database that has the most common types of plant stress identified” that growers will be able to tap into. Such databases will “create a community and move the science forward,” says Lowman.
In fact, IALR is working on assembling images for just such a database now. On so-called “smart tables” inside an Institute lab, a team is growing greens and subjects them to various stressors. Then, they’re administering treatments while taking images of every plant every 15 minutes, says Lowman. Some experiments generate 80,000 images; the challenge lies in analyzing and annotating the vast trove of them, marking each one to reflect outcome—for example increasing the phosphate delivery and the plant’s response to it. Eventually, they’ll be fed into AI systems to help them learn.
For all the enthusiasm surrounding this technology, it’s not without downsides. Training just one AI system can emit over 250,000 pounds of carbon dioxide, according to MIT Technology Review. AI could also be used “to enhance environmental benefit for CEA and optimize [its] energy consumption,” says Rozita Dara, a computer science professor at the University of Guelph in Canada, specializing in AI and data governance, “but we first need to collect data to measure [it].”
The chef-farmers can choose from 45 types of herb and leafy-greens seeds.
Courtesy Babylon Micro-Farms
Any system connected to the Internet of Things is also vulnerable to hacking; if CEA grows to the point where “there are many of these similar farms, and you're depending on feeding a population based on those, it would be quite scary,” Dara says. And there are privacy concerns, too, in systems where imaging is happening constantly. It’s partly for this reason, says Babylon’s Ratte, that the company’s in-farm cameras all “face down into the trays, so the only thing [visible] is pictures of plants.”
Tweaks to improve AI for CEA are happening all the time. Greenswell made its first harvest in 2022 and now has annual data points they can use to start making more intelligent choices about how to feed, water, and supply light to plants, says Gupton. Ratte says he’s confident Babylon’s system can already “get our customers reliable harvests. But in terms of how far we have to go, it's a different problem,” he says. For example, if AI could detect whether the farm is mostly empty—meaning the farm’s user hasn’t planted a new crop of greens—it can alert Babylon to check “what's going on with engagement with this user?” Ratte says. “Do they need more training? Did the main person responsible for the farm quit?”
Lowman says more automation is coming, offering greater ability for systems to identify problems and mitigate them on the spot. “We still have to develop datasets that are specific, so you can have a very clear control plan, [because] artificial intelligence is only as smart as what we tell it, and in plant science, there's so much variation,” he says. He believes AI’s next level will be “looking at those first early days of plant growth: when the seed germinates, how fast it germinates, what it looks like when it germinates.” Imaging all that and pairing it with AI, “can be a really powerful tool, for sure.”