Anne, Stan, and grandson Louie during vacation in Mexico, 2019. INSET: Anne post-op in 2017.
I was an artist.
I worked in mixed media, Papier-mâché, and collage, inspired by dreams, birds, mystery. I had gallery shows and participated in studio tours.
Educated in thanatology, I worked in hospice care as a volunteer and education director for Hospice Caledon, an organization that supports people facing life-limiting illness and grief.
I trained volunteers who helped people through their transition.
Parkinson's disease changed all that.
My hands and my head were not coordinating, so it was impossible to do my art.
It started as a twitch in my leg. During a hospice workshop, my right leg started vibrating in a way I hadn't experienced before. I told a friend, "This can't be good."
Over the next year, my right foot vibrated more and more. I could not sleep well. In my dreams people lurked in corners, in dark places, and behind castle doors. I knew they were there and couldn't avoid the ambush. I shrieked and woke everyone in the house.
An anxiety attack—something I had also never experienced before—came next.
During a class I was teaching, my mouth got so dry, I couldn't speak. I stood in front of the class for three or four minutes, unable to continue. I pushed through and finished the class. That's when I realized this was more than jiggling legs.
That's when I went to see a doctor.
A Diagnosis
My first doctor, when I suggested it might be Parkinson's, didn't believe me. She sent me to a neurologist who told me I had to meditate more and calm myself.
A friend from hospice told me to phone the Toronto Western Hospital Movement Disorders Clinic. In January 2010, I was diagnosed with Parkinson's disease.
The doctor, a fellow, got all my stats and asked a lot of questions. He was so excited he knew what it was, he exclaimed, "You've got Parkinson's!" like it was the best thing ever. I must say, that wasn't the best news, but at least I finally had a diagnosis.
I could choose whether to take medication or not. The doctor said, "If Parkinson's is compromising your lifestyle, you should consider taking levodopa."
"Well I can't run my classes, I can't do my art, so it's compromising me," I said. And my health was going downhill. The shaking—my whole body moved—sleeping was horrible. Two to four hours max a night was usual. I had terrible anxiety and panic attacks and had to quit work.
So I started taking levodopa. It's taken in a four-hour cycle, but the medication didn't last the full time. I developed dyskenisia, a side effect of the medication that made me experience uncontrolled, involuntary movements. I was edgy, irritable, and focused on my watch like a drug addict. I'd lie on the couch, feel crummy and tired, and wait.
The medication cycle restricted where I could go. Fearing the "off" period, I avoided interaction with lifelong friends, which increased my feeling of social isolation. They would come over and cook with me and read to me sometimes, and that was fine, as long as it was during an "on" period.
There was incontinence, constipation, and fatigue.
I lost fine motor skills, like writing. And painting. My hands and my head were not coordinating, so it was impossible to do my art.
It was a terrible time.
The worst symptoms—what pushed me to consider DBS—were the symptoms no one could see. The anxiety and depression were so bad, the sleeplessness, not eating.
I projected a lot of my discomforts onto Stan. I reacted so badly to him. I actually separated from him briefly on two separate occasions and lived in a separate space—a self-imposed isolation. There wasn't anything he could do to help me really except sit back and watch.
I tried alternative therapies—a naturopath, an osteopath, a reflexologist and a Chinese medicine practitioner—but nothing seemed to help.
I felt like I was dying. Certain parts of my life were being taken away from me. I was a perfectionist, and I felt imperfect. It was a horrible feeling, to not be in control of myself.
The DBS Decision
I was familiar with DBS, a procedure that involves a neurosurgeon drilling small holes into your skull and implanting electrical leads deep in your brain to modify neural activity, reducing involuntary movements.
But I was convinced I'd never do it. I was brought up in a family that believed 'doctors make you sick and hospitals kill you.'
I worried the room wouldn't be sterile. Someone's cutting into your brain, you don't know what's going to happen. They're putting things in your body. I didn't want to risk possible infection.
And my doctor said he couldn't promise he would actually do the operation. It might be a fellow, but he'd be in the background in case anything went wrong. I wasn't comfortable with that arrangement.
When filmmakers Taryn Southern and Elena Gaby decided to make a documentary about people whose lives were changed by cutting-edge brain implants--and I agreed to participate—my doctor said he would for sure do the operation. They couldn't risk anything happening on the operating table on camera, so most of my fears went away.
My family supported the decision. My mother had trigeminal neuralgia, which is a very painful facial condition. She also had a stroke and what we now believe to be Parkinson's. My father, a retired dentist, managed her care and didn't give her the opportunity to see a specialist.
I felt them running the knife across my scalp, and drilling two holes in my head, but only as pressure, not pain.
When we were talking about DBS, my son, Joseph, said, "How can you not do this, for the sake of your family? Because if you don't, you'll end up like Grandma, who, for the last few years of her life, just lay on a couch because she didn't get any kind of outside help. If you even have a chance to improve your life or give yourself five extra years, why wouldn't you do that, for our sake? Are we not worth that?"
That talk really affected me, and I realized I had to try. Even though it was difficult, I had to be brave for my family.
Surgery, Recovery, and Tweaking
You have to be awake for part of the procedure—I was awake enough that my subconscious could hear, because they had to know how far to insert the electrodes. DBS targets the troublemaking areas of the brain. There's a one millimeter difference between success and failure.
I felt them running the knife across my scalp, and drilling two holes in my head, but only as pressure, not pain.
Once they were inside, they asked me to move parts of my body to see whether the right neurons were activated.
They put me to sleep to put a battery-powered neurostimulator in my chest. A wire that runs behind my ear and down my neck connects the electrodes in my brain to the battery pack. The neurostimulator creates electric pulses 24 hours a day.
I was moving around almost immediately after surgery. Recovery from the stitches took a few weeks, but everything else took a lot longer.
I couldn't read. My motor skills were still impaired, and my brain and my hands weren't yet linked up. I needed the device to be programmed and tweaked. Until that happened, I needed help.
The depression and anxiety, though, went away almost immediately. From that perspective, it was like I never had Parkinson's. I was so happy.
When they calibrated the electrodes, they adjusted how much electrical current goes to any one of four contact points on the left and right sides of the brain. If they increased it too much, a leg would start shaking, a foot would start cramping, or my tongue would feel thicker. It took a while to get it calibrated correctly to control the symptoms.
First it was five sessions in five weeks, then once a month, then every three months. Now I visit every six months. As the disease progresses, they have the ability to keep making adjustments. (DBS controls the symptoms, but it doesn't cure the disease.)
Once they got the calibration right, my motor skills improved. I could walk without shuffling. My muscles weren't stiff and aching, and the dyskinesia disappeared. But if I turn off the device, my symptoms return almost immediately.
Some days I have more fatigue than others, and sometimes my brain doesn't click. And my voice got softer – that's a common side effect of this operation. But I'm doing so much better than before.
I have a quality of life I didn't have before. Before COVID-19 hit, Stan and I traveled, went to concerts, movies, galleries, and spent time with our growing family.
I cut back the levodopa from seven-and-a-half pills a day to two-and-a-half. I often forget to take my medication until I realize I'm feeling tired or anxious.
Best of all, my motivation and creative ability have clicked in.
I am an artist—again.
I'm painting every day. It's what is keeping me sane. It's my saving grace.
I'm not perfect. But I am Anne. Again.
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.
