The Cocoanut Grove fire in Boston in 1942 tragically claimed 490 lives, but was the catalyst for several important medical advances.
On the evening of November 28, 1942, more than 1,000 revelers from the Boston College-Holy Cross football game jammed into the Cocoanut Grove, Boston's oldest nightclub. When a spark from faulty wiring accidently ignited an artificial palm tree, the packed nightspot, which was only designed to accommodate about 500 people, was quickly engulfed in flames. In the ensuing panic, hundreds of people were trapped inside, with most exit doors locked. Bodies piled up by the only open entrance, jamming the exits, and 490 people ultimately died in the worst fire in the country in forty years.
"People couldn't get out," says Dr. Kenneth Marshall, a retired plastic surgeon in Boston and president of the Cocoanut Grove Memorial Committee. "It was a tragedy of mammoth proportions."
Within a half an hour of the start of the blaze, the Red Cross mobilized more than five hundred volunteers in what one newspaper called a "Rehearsal for Possible Blitz." The mayor of Boston imposed martial law. More than 300 victims—many of whom subsequently died--were taken to Boston City Hospital in one hour, averaging one victim every eleven seconds, while Massachusetts General Hospital admitted 114 victims in two hours. In the hospitals, 220 victims clung precariously to life, in agonizing pain from massive burns, their bodies ravaged by infection.
The scene of the fire.
Boston Public Library
Tragic Losses Prompted Revolutionary Leaps
But there is a silver lining: this horrific disaster prompted dramatic changes in safety regulations to prevent another catastrophe of this magnitude and led to the development of medical techniques that eventually saved millions of lives. It transformed burn care treatment and the use of plasma on burn victims, but most importantly, it introduced to the public a new wonder drug that revolutionized medicine, midwifed the birth of the modern pharmaceutical industry, and nearly doubled life expectancy, from 48 years at the turn of the 20th century to 78 years in the post-World War II years.
The devastating grief of the survivors also led to the first published study of post-traumatic stress disorder by pioneering psychiatrist Alexandra Adler, daughter of famed Viennese psychoanalyst Alfred Adler, who was a student of Freud. Dr. Adler studied the anxiety and depression that followed this catastrophe, according to the New York Times, and "later applied her findings to the treatment World War II veterans."
Dr. Ken Marshall is intimately familiar with the lingering psychological trauma of enduring such a disaster. His mother, an Irish immigrant and a nurse in the surgical wards at Boston City Hospital, was on duty that cold Thanksgiving weekend night, and didn't come home for four days. "For years afterward, she'd wake up screaming in the middle of the night," recalls Dr. Marshall, who was four years old at the time. "Seeing all those bodies lined up in neat rows across the City Hospital's parking lot, still in their evening clothes. It was always on her mind and memories of the horrors plagued her for the rest of her life."
The sheer magnitude of casualties prompted overwhelmed physicians to try experimental new procedures that were later successfully used to treat thousands of battlefield casualties. Instead of cutting off blisters and using dyes and tannic acid to treat burned tissues, which can harden the skin, they applied gauze coated with petroleum jelly. Doctors also refined the formula for using plasma--the fluid portion of blood and a medical technology that was just four years old--to replenish bodily liquids that evaporated because of the loss of the protective covering of skin.
"Every war has given us a new medical advance. And penicillin was the great scientific advance of World War II."
"The initial insult with burns is a loss of fluids and patients can die of shock," says Dr. Ken Marshall. "The scientific progress that was made by the two institutions revolutionized fluid management and topical management of burn care forever."
Still, they could not halt the staph infections that kill most burn victims—which prompted the first civilian use of a miracle elixir that was being secretly developed in government-sponsored labs and that ultimately ushered in a new age in therapeutics. Military officials quickly realized this disaster could provide an excellent natural laboratory to test the effectiveness of this drug and see if it could be used to treat the acute traumas of combat in this unfortunate civilian approximation of battlefield conditions. At the time, the very existence of this wondrous medicine—penicillin—was a closely guarded military secret.
From Forgotten Lab Experiment to Wonder Drug
In 1928, Alexander Fleming discovered the curative powers of penicillin, which promised to eradicate infectious pathogens that killed millions every year. But the road to mass producing enough of the highly unstable mold was littered with seemingly unsurmountable obstacles and it remained a forgotten laboratory curiosity for over a decade. But Fleming never gave up and penicillin's eventual rescue from obscurity was a landmark in scientific history.
In 1940, a group at Oxford University, funded in part by the Rockefeller Foundation, isolated enough penicillin to test it on twenty-five mice, which had been infected with lethal doses of streptococci. Its therapeutic effects were miraculous—the untreated mice died within hours, while the treated ones played merrily in their cages, undisturbed. Subsequent tests on a handful of patients, who were brought back from the brink of death, confirmed that penicillin was indeed a wonder drug. But Britain was then being ravaged by the German Luftwaffe during the Blitz, and there were simply no resources to devote to penicillin during the Nazi onslaught.
In June of 1941, two of the Oxford researchers, Howard Florey and Ernst Chain, embarked on a clandestine mission to enlist American aid. Samples of the temperamental mold were stored in their coats. By October, the Roosevelt Administration had recruited four companies—Merck, Squibb, Pfizer and Lederle—to team up in a massive, top-secret development program. Merck, which had more experience with fermentation procedures, swiftly pulled away from the pack and every milligram they produced was zealously hoarded.
After the nightclub fire, the government ordered Merck to dispatch to Boston whatever supplies of penicillin that they could spare and to refine any crude penicillin broth brewing in Merck's fermentation vats. After working in round-the-clock relays over the course of three days, on the evening of December 1st, 1942, a refrigerated truck containing thirty-two liters of injectable penicillin left Merck's Rahway, New Jersey plant. It was accompanied by a convoy of police escorts through four states before arriving in the pre-dawn hours at Massachusetts General Hospital. Dozens of people were rescued from near-certain death in the first public demonstration of the powers of the antibiotic, and the existence of penicillin could no longer be kept secret from inquisitive reporters and an exultant public. The next day, the Boston Globe called it "priceless" and Time magazine dubbed it a "wonder drug."
Within fourteen months, penicillin production escalated exponentially, churning out enough to save the lives of thousands of soldiers, including many from the Normandy invasion. And in October 1945, just weeks after the Japanese surrender ended World War II, Alexander Fleming, Howard Florey and Ernst Chain were awarded the Nobel Prize in medicine. But penicillin didn't just save lives—it helped build some of the most innovative medical and scientific companies in history, including Merck, Pfizer, Glaxo and Sandoz.
"Every war has given us a new medical advance," concludes Marshall. "And penicillin was the great scientific advance of World War II."
Crickets are low on fat, high on protein, and can be farmed sustainably. They are also crunchy.
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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/
Artificial Intelligence is already helping to grow some of the food we eat.
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.”