Researchers have found that a mindfulness-based therapy, including savoring natural rewards, can help patients with chronic pain and opioid addiction.
Garland’s study focused on 250 adults who had received opioid therapy for chronic pain for 90 days or longer, randomly assigning them to eight weeks of either a standard psychotherapy support group or Mindfulness-Oriented Recovery Enhancement (MORE) therapy, which combines mindfulness training, cognitive-behavioral therapy (CBT) and positive psychology. Nine months after getting these treatments in primary care settings, 45 percent of patients in the MORE group were no longer misusing opioids, compared to 24 percent of those in group therapy. In fact, about a third of the patients in the MORE group were able to cut their opioid dose in half or reduce it even further.
Patients treated with MORE also experienced more significant pain relief than those in support groups, according to Garland. Conventional approaches to treating opioid addiction include 12-step programs and medically-assisted treatment using drugs like methadone and Suboxone, sometimes coupled with support groups. But patients with Opioid Use Disorder (OUD) – the official diagnosis for opioid addiction – have high relapse rates following treatment, especially if they have chronic pain.
While medically-assisted treatments help to control drug cravings, they do nothing to control chronic pain, which is where psychological therapies like MORE come in.
“For patients suffering from moderate pain and OUD, the relapse rate is three times higher than in patients without chronic pain; for those with severe chronic pain, the relapse rate is five times higher,” says Amy Wachholtz, PhD, Director of Clinical Health Psychology and associate professor at University of Colorado in Denver. “So if we don’t treat the chronic pain along with the OUD addiction simultaneously, we are setting patients up for failure.”
Unfortunately, notes Garland, the standard of care for patients with chronic pain who are misusing their prescribed painkillers is “woefully inadequate.” Many patients don’t meet the criteria for OUD, he says, but instead fall into a gray zone somewhere between legitimate opioid use and full-blown addiction. And while medically-assisted treatments help to control drug cravings, they do nothing to control chronic pain, which is where psychological therapies like MORE come in. But behavioral therapies are often not available in primary care settings, and even when clinicians do refer patients to behavioral health providers, they often prescribe CBT. A large scale study last year showed that CBT – without the added components of mindfulness training and positive psychology – reduced pain but not opioid misuse.
Psychotherapist Eric Garland teaches mindfulness.
University of Utah
Reward Circuitry Rewired
Opioids are highly physiologically addictive. Repeated and high-dose drug use causes the brain to become hypersensitive to stress, pain, and drug-related cues, such as the sight of one’s pill bottle, says Garland, while at the same time becoming increasingly insensitive to natural pleasures. “As an individual becomes more and more dependent on the opioids just to feel okay, they feel less able to extract a healthy sense of joy, pleasure and meaning out of everyday life,” he explains. “This drives them to take higher and higher doses of the opioid to maintain a dwindling sense of well-being.”
The changes are not just psychological: Chronic opioid use actually causes changes in the brain’s reward circuitry. “You can see on brain imaging,” says Garland. “The brain’s reward circuitry becomes more responsive when a person is viewing opioid related images than when they are viewing images of smiling babies, lovers holding hands, or sunsets over the beach.” MORE, he says, teaches “savoring” – a tenet of positive psychology – as a means of restructuring the reward processes in the brain so the patient becomes sensitive to pleasure from natural, healthy rewards, decreasing cravings for drug-related rewards.
Mindfulness and Addiction
Mindfulness, a form of meditation that teaches people to observe their feelings and sensations without judgement, has been increasingly applied to the treatment of addiction. By observing their pain and cravings objectively, for example, patients gain increased awareness of their responses to pain and their habits of opioid use. “They learn how to be with discomfort, whether emotional or physical, in a more compassionate way,” says Sarah Bowen, PhD, associate professor of psychology at Pacific University in Oregon. “And if your mind gives you a message like ‘Oh, I can’t handle that,’ to recognize that that’s a thought that might not be true.”
Bowen’s research is focused on Mindfulness-Based Relapse Prevention, which addresses the cravings associated with addiction. She has patients practice what she calls “urge surfing”: riding out a craving or urge rather than relying on a substance for immediate relief. “Craving will happen, so rather than fighting it, we look at understanding it better,” she says.
MORE differs from other forms of mindfulness-based therapy in that it integrates reappraisal and savoring training. Reappraisal is a technique often used in CBT in which patients learn to change negative thought patterns in order to reduce their emotional impact, while savoring helps to restructure the reward processes in the brain.
Mindfulness training not only helps patients to understand and gain control over their behavior in response to cravings and triggers like pain, says Garland, but also provides a means of pain relief. “We use mindfulness to zoom into pain and break it down into its subcomponents – feelings of heat or tightness or tingling – which reduces the impact that negative emotions have on pain processing in the brain.”
Eric Garland examines brain waves.
University of Utah
Powerful interventions
As the dangers of opioid addiction have become increasingly evident, some scientists are developing less addictive, non-opioid painkillers, but more trials are needed. Meanwhile, behavioral approaches to chronic pain relief have continued to gain traction, and researchers like Garland are probing the possibilities of integrative treatments to treat the addiction itself. Given that the number of people suffering from chronic pain and OUD have reached new heights during the COVID-19 pandemic, says Wachholtz, new treatment alternatives for patients caught in the relentless cycle of chronic pain and opioid misuse are sorely needed. “We’re trying to refine the techniques,” she says, “but we’re starting to realize just how powerful some of these mind-body interventions can be.”
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.
