Hyperbaric oxygen therapy has been used in the past to help people with traumatic brain injury, stroke and other conditions involving wounds to the brain. Now, researchers at Shamir Medical Center in Tel Aviv are studying how it could treat Long Covid.
Efrati came to HBOT almost by accident. The physician had seen how it had helped heal diabetic ulcers and improved the lives of other patients, but he was busy with his own research. Then the director of his Tel Aviv hospital threatened to shut down the small HBOT chamber unless Efrati took on administrative responsibility for it. He reluctantly agreed, a decision that shifted the entire focus of his research.
“The main difference between wounds in the leg and wounds in the brain is that one is something we can see, it's tangible, and the wound in the brain is hidden,” says Efrati. With fMRIs, he can measure how a limited supply of oxygen in blood is shuttled around to fuel activity in various parts of the brain. Years of research have mapped how specific areas of the brain control activity ranging from thinking to moving. An fMRI captures the brain area as it’s activated by supplies of oxygen; lack of activity after the same stimuli suggests damage has occurred in that tissue. Suddenly, what was hidden became visible to researchers using fMRI. It helped to make a diagnosis and measure response to treatment.
HBOT is not a single thing but rather a tool, a process or approach with variations depending on the condition being treated. It aims to increase the amount of oxygen that gets to damaged tissue and speed up healing. Regular air is about 21 percent oxygen. But inside the HBOT chamber the atmospheric pressure can be increased to up to three times normal pressure at sea level and the patient breathes pure oxygen through a mask; blood becomes saturated with much higher levels of oxygen. This can defuse through the damaged capillaries of a wound and promote healing.
The trial
Efrati’s clinical trials started in December 2020, barely a year after SARS-CoV-2 had first appeared in Israel. Patients who’d experienced cognitive issues after having COVID received 40 sessions in the chamber over a period of 60 days. In each session, they spent 90 minutes breathing through a mask at two atmospheres of pressure. While inside, they performed mental exercises to train the brain. The only difference between the two groups of patients was that one breathed pure oxygen while the other group breathed normal air. No one knew who was receiving which level of oxygen.
The results were striking. Before and after fMRIs showed significant repair of damaged tissue in the brain and functional cognition tests improved substantially among those who received pure oxygen. Importantly, 80 percent of patients said they felt back to “normal,” but Efrati says they didn't include patient evaluation in the paper because there was no baseline data to show how they functioned before COVID. After the study was completed, the placebo group was offered a new round of treatments using 100 percent oxygen, and the team saw similar results.
Scans show improved blood flow in a patient suffering from Long Covid.
Sagol Center for Hyperbaric Medicine
Efrati's use of HBOT is part of an emerging geroscience approach to diseases associated with aging. These researchers see systems dysfunctions that are common to several diseases, such as inflammation, which has been shown to play a role in micro infarcts, heart disease and Alzheimer’s disease. Preliminary research suggests that HBOT can retard some underlying mechanisms of aging, which might address several medical conditions. However, the drug approval process is set up to regulate individual disease, not conditions as broad as aging, and so they concentrate on treating the low hanging fruit: disorders where effective treatments currently are limited and success might be demonstrated.
The key to HBOT's effectiveness is something called the hyperoxic-hypoxic paradox where a body does not react to an increase in available oxygen, only to a decrease, regardless of the starting point. That danger signal has a powerful effect on gene expression, resulting in changes in metabolism, and the proliferation of stem cells. That occurs with each cycle of 20 minutes of pure oxygen followed by 5 minutes of regular air circulating through the masks, while the chamber remains pressurized. The high levels of oxygen in the blood provide the fuel necessary for tissue regeneration.
The hyperbaric chamber that Efrati has built can hold a dozen patients and attending medical staff. Think of it as a pressurized airplane cabin, only with much more space than even in first class. In the U.S., people think of HBOT as “a sack of air or some tube that you can buy on Amazon” or find at a health spa. “That is total bullshit,” Efrati says. “It has to be a medical class center where a physician can lose their license if they are not operating it properly.”
Shai Efrati
Alexander Charney, a research psychiatrist at the Icahn School of Medicine at Mount Sinai in New York City, calls Efrati’s study thoughtful and well designed. But it demands a lot from patients with its intense number of sessions. Those types of regimens have proven difficult to roll out to large numbers of patients. Still, the results are intriguing enough to merit additional trials.
John J. Miller, a physician and editor in chief of Psychiatric Times, has seen “many physicians that use hyperbaric oxygen for various brain disorders such as TBI.” He is intrigued by Efrati's work and believes the approach “has great potential to help patients with long COVID whose symptoms are related to brain tissue changes.”
Efrati believes so much in the power of the hyperoxic-hypoxic paradox to heal a variety of tissue injuries that he is leading the medical advisory board at Aviv Clinic, an international network of clinics that are delivering HBOT treatments based on research conducted in Israel. His goal is to silence doubters by quickly opening about 50 such clinics worldwide, based on the model of standalone dialysis clinics in the United States. Sagol Center is treating 300 patients per day, and clinics have opened in Florida and Dubai. There are plans to open another in Manhattan.
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.”
Researchers from the University of Cambridge have laid the foundations for growing synthetic embryos that could develop a beating heart, gut and brain.
The organoid revolution
In 1981, scientists discovered how to keep stem cells alive. This was a significant breakthrough, as stem cells have notoriously rigorous demands. Nevertheless, stem cells remained a relatively niche research area, mainly because scientists didn’t know how to convince the cells to turn into other cells.
Then, in 1987, scientists embedded isolated stem cells in a gelatinous protein mixture called Matrigel, which simulated the three-dimensional environment of animal tissue. The cells thrived, but they also did something remarkable: they created breast tissue capable of producing milk proteins. This was the first organoid — a clump of cells that behave and function like a real organ. The organoid revolution had begun, and it all started with a boob in Jello.
For the next 20 years, it was rare to find a scientist who identified as an “organoid researcher,” but there were many “stem cell researchers” who wanted to figure out how to turn stem cells into other cells. Eventually, they discovered the signals (called growth factors) that stem cells require to differentiate into other types of cells.
For a human embryo (and its organs) to develop successfully, there needs to be a “dialogue” between these three types of stem cells.
By the end of the 2000s, researchers began combining stem cells, Matrigel, and the newly characterized growth factors to create dozens of organoids, from liver organoids capable of producing the bile salts necessary for digesting fat to brain organoids with components that resemble eyes, the spinal cord, and arguably, the beginnings of sentience.
Synthetic embryos
Organoids possess an intrinsic flaw: they are organ-like. They share some characteristics with real organs, making them powerful tools for research. However, no one has found a way to create an organoid with all the characteristics and functions of a real organ. But Magdalena Żernicka-Goetz, a developmental biologist, might have set the foundation for that discovery.
Żernicka-Goetz hypothesized that organoids fail to develop into fully functional organs because organs develop as a collective. Organoid research often uses embryonic stem cells, which are the cells from which the developing organism is created. However, there are two other types of stem cells in an early embryo: stem cells that become the placenta and those that become the yolk sac (where the embryo grows and gets its nutrients in early development). For a human embryo (and its organs) to develop successfully, there needs to be a “dialogue” between these three types of stem cells. In other words, Żernicka-Goetz suspected the best way to grow a functional organoid was to produce a synthetic embryoid.
As described in the aforementioned Nature paper, Żernicka-Goetz and her team mimicked the embryonic environment by mixing these three types of stem cells from mice. Amazingly, the stem cells self-organized into structures and progressed through the successive developmental stages until they had beating hearts and the foundations of the brain.
“Our mouse embryo model not only develops a brain, but also a beating heart [and] all the components that go on to make up the body,” said Żernicka-Goetz. “It’s just unbelievable that we’ve got this far. This has been the dream of our community for years and major focus of our work for a decade and finally we’ve done it.”
If the methods developed by Żernicka-Goetz’s team are successful with human stem cells, scientists someday could use them to guide the development of synthetic organs for patients awaiting transplants. It also opens the door to studying how embryos develop during pregnancy.
This article originally appeared on Big Think, home of the brightest minds and biggest ideas of all time.
