This breath test can detect liver disease earlier
Every year, around two million people worldwide die of liver disease. While some people inherit the disease, it’s most commonly caused by hepatitis, obesity and alcoholism. These underlying conditions kill liver cells, causing scar tissue to form until eventually the liver cannot function properly. Since 1979, deaths due to liver disease have increased by 400 percent.
The sooner the disease is detected, the more effective treatment can be. But once symptoms appear, the liver is already damaged. Around 50 percent of cases are diagnosed only after the disease has reached the final stages, when treatment is largely ineffective.
To address this problem, Owlstone Medical, a biotech company in England, has developed a breath test that can detect liver disease earlier than conventional approaches. Human breath contains volatile organic compounds (VOCs) that change in the first stages of liver disease. Owlstone’s breath test can reliably collect, store and detect VOCs, while picking out the specific compounds that reveal liver disease.
“There’s a need to screen more broadly for people with early-stage liver disease,” says Owlstone’s CEO Billy Boyle. “Equally important is having a test that's non-invasive, cost effective and can be deployed in a primary care setting.”
The standard tool for detection is a biopsy. It is invasive and expensive, making it impractical to use for people who aren't yet symptomatic. Meanwhile, blood tests are less invasive, but they can be inaccurate and can’t discriminate between different stages of the disease.
In the past, breath tests have not been widely used because of the difficulties of reliably collecting and storing breath. But Owlstone’s technology could help change that.
The team is testing patients in the early stages of advanced liver disease, or cirrhosis, to identify and detect these biomarkers. In an initial study, Owlstone’s breathalyzer was able to pick out patients who had early cirrhosis with 83 percent sensitivity.
Boyle’s work is personally motivated. His wife died of colorectal cancer after she was diagnosed with a progressed form of the disease. “That was a big impetus for me to see if this technology could work in early detection,” he says. “As a company, Owlstone is interested in early detection across a range of diseases because we think that's a way to save lives and a way to save costs.”
How it works
In the past, breath tests have not been widely used because of the difficulties of reliably collecting and storing breath. But Owlstone’s technology could help change that.
Study participants breathe into a mouthpiece attached to a breath sampler developed by Owlstone. It has cartridges are designed and optimized to collect gases. The sampler specifically targets VOCs, extracting them from atmospheric gases in breath, to ensure that even low levels of these compounds are captured.
The sampler can store compounds stably before they are assessed through a method called mass spectrometry, in which compounds are converted into charged atoms, before electromagnetic fields filter and identify even the tiniest amounts of charged atoms according to their weight and charge.
The top four compounds in our breath
In an initial study, Owlstone captured VOCs in breath to see which ones could help them tell the difference between people with and without liver disease. They tested the breath of 46 patients with liver disease - most of them in the earlier stages of cirrhosis - and 42 healthy people. Using this data, they were able to create a diagnostic model. Individually, compounds like 2-Pentanone and limonene performed well as markers for liver disease. Owlstone achieved even better performance by examining the levels of the top four compounds together, distinguishing between liver disease cases and controls with 95 percent accuracy.
“It was a good proof of principle since it looks like there are breath biomarkers that can discriminate between diseases,” Boyle says. “That was a bit of a stepping stone for us to say, taking those identified, let’s try and dose with specific concentrations of probes. It's part of building the evidence and steering the clinical trials to get to liver disease sensitivity.”
Sabine Szunerits, a professor of chemistry in Institute of Electronics at the University of Lille, sees the potential of Owlstone’s technology.
“Breath analysis is showing real promise as a clinical diagnostic tool,” says Szunerits, who has no ties with the company. “Owlstone Medical’s technology is extremely effective in collecting small volatile organic biomarkers in the breath. In combination with pattern recognition it can give an answer on liver disease severity. I see it as a very promising way to give patients novel chances to be cured.”
Improving the breath sampling process
Challenges remain. With more than one thousand VOCs found in the breath, it can be difficult to identify markers for liver disease that are consistent across many patients.
Julian Gardner is a professor of electrical engineering at Warwick University who researches electronic sensing devices. “Everyone’s breath has different levels of VOCs and different ones according to gender, diet, age etc,” Gardner says. “It is indeed very challenging to selectively detect the biomarkers in the breath for liver disease.”
So Owlstone is putting chemicals in the body that they know interact differently with patients with liver disease, and then using the breath sampler to measure these specific VOCs. The chemicals they administer are called Exogenous Volatile Organic Compound) probes, or EVOCs.
Most recently, they used limonene as an EVOC probe, testing 29 patients with early cirrhosis and 29 controls. They gave the limonene to subjects at specific doses to measure how its concentrations change in breath. The aim was to try and see what was happening in their livers.
“They are proposing to use drugs to enhance the signal as they are concerned about the sensitivity and selectivity of their method,” Gardner says. “The approach of EVOC probes is probably necessary as you can then eliminate the person-to-person variation that will be considerable in the soup of VOCs in our breath.”
Through these probes, Owlstone could identify patients with liver disease with 83 percent sensitivity. By targeting what they knew was a disease mechanism, they were able to amplify the signal. The company is starting a larger clinical trial, and the plan is to eventually use a panel of EVOC probes to make sure they can see diverging VOCs more clearly.
“I think the approach of using probes to amplify the VOC signal will ultimately increase the specificity of any VOC breath tests, and improve their practical usability,” says Roger Yazbek, who leads the South Australian Breath Analysis Research (SABAR) laboratory in Flinders University. “Whilst the findings are interesting, it still is only a small cohort of patients in one location.”
The future of breath diagnosis
Owlstone wants to partner with pharmaceutical companies looking to learn if their drugs have an effect on liver disease. They’ve also developed a microchip, a miniaturized version of mass spectrometry instruments, that can be used with the breathalyzer. It is less sensitive but will enable faster detection.
Boyle says the company's mission is for their tests to save 100,000 lives. "There are lots of risks and lots of challenges. I think there's an opportunity to really establish breath as a new diagnostic class.”
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.
Listen on Apple | Listen on Spotify | Listen on Stitcher | Listen on Amazon | Listen on Google
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.”