Scientists Are Studying How to Help Dogs Have Longer Lives, in a Bid to Further Our Own
The sad eyes. The wagging tail. The frustrated whine. The excited bark. Dogs know how to get their owners to fork over the food more often.
The extra calories dogs get from feeding patterns now used by many Americans may not be good for them from a health and longevity viewpoint. In research from a large study called the Dog Aging Project, canines fed once a day had better scores on cognition tests and lower odds of developing diseases of organs throughout the body: intestinal tract, mouth and teeth, bones and joints, kidneys and bladder, and liver and pancreas.
Fewer than 1 in 10 dog owners fed their furry friends once daily, while nearly three fourths provided two daily meals.
“Most veterinarians have been led to believe that feeding dogs twice a day is optimal, but this is a relatively new idea that has developed over the past few decades with little supportive evidence from a health standpoint,” said Matt Kaeberlein, PhD, Co-Director of the Dog Aging Project, a professor of pathology and Director of the Healthy Aging and Longevity Research Institute at the University of Washington. Kaeberlein studies basic mechanisms of aging to find ways of extending the healthspan, the number of years of life lived free of disease. It’s not enough to extend the lifespan unless declines in biological function and risks of age-related diseases are also studied, he believes, hence the healthspan.
The Dog Aging Project is studying tens of thousands of dogs living with their owners in the real world, not a biology laboratory. The feeding study is the first of several reports now coming from the project based on owners’ annual reports of demographics, physical activity, environment, dog behavior, diet, medications and supplements, and health status. It has been posted on bioRxiv as it goes through peer review.
“All available evidence suggests that most biological mechanisms of aging in dogs will be conserved in humans. It just happens much faster in dogs.”
“The Dog Aging Project is one of the most exciting in the longevity space,” said David A. Sinclair, professor in the Department of Genetics and co-director of the Paul F. Glenn Center for Biology of Aging Research at Harvard Medical School. “Not only is it important to help our companions live longer and healthier, but because they are like people and share the same environment and many of the lifestyles as their owners, they are the perfect model for human longevity interventions.”
The epigenetic clock — and specifically changes in gene expression resulting from methylation of cytosine and guanine in the DNA — provides the critical connection between aging in dogs and people. “All available evidence suggests that most biological mechanisms of aging in dogs will be conserved in humans,” Kaeberlein said. “It just happens much faster in dogs.” These methylation changes, called the “methylomes,” have been associated with rates of aging in dogs, humans, and also mice.
In a 2020 study young dogs matched with young adults and aged dogs matched with older adults showed the greatest similarities in methylomes. In the Cell Systems report, Tina Wang of the University of California, San Diego, and colleagues wrote that the methylome “can be used to quantitatively translate the age-related physiology experienced by one organism (i.e., a model species like dog) to the age at which physiology in a second organism is most similar (i.e., a second model or humans).” This allows rates of aging in one species to be mapped onto aging in another species, providing “a compelling tool in the quest to understand aging and identify interventions for maximizing healthy lifespan.”
In the Dog Aging Project study, 8% of 24,238 owners fed their dogs once daily, the same as the percentage of owners serving three daily meals. Twice-daily feedings were most common (73%), and just over 1 in 10 owners (11%) “free fed” their dogs by just filling up the bowl whenever it was empty — most likely Rover’s favorite option.
“The notion of breakfast, lunch, and dinner for people in the United States is not based on large studies that compared three meals a day to two meals a day, or to four, “ said Kate E. Creevy, chief veterinary officer with the Dog Aging Project and associate professor at Texas A&M University. “It’s more about what we are accustomed to. Similarly, there are not large population studies comparing outcomes of dogs fed once, twice, or three times a day.”
“We do not recommend that people change their dogs’ diets based on this report,” Creevy emphasized. “It’s important to understand the difference between research that finds associations versus research that finds cause and effect.”
To establish cause and effect, the Dog Aging Project will follow their cohort over many years. Then, Creevy said, “We will be able to determine whether the associations we have found with feeding frequency are causes, or effects, or neither.”
While not yet actionable, the feeding findings fit with biology across a variety of animals, Kaeberlein said, including indicators that better health translates into longer healthspans. He said that caloric restriction and perhaps time-restricted eating or intermittent fasting — all ways that some human diets are structured — can have a positive impact on the biology of aging by allowing the gastrointestinal tract to have time each day to rest and repair itself, just as sleep benefits the brain through rest.
Timing of meals is also related to the concept of ketogenesis, Kaeberlein explained. Without access to glucose, animals switch over to a ketogenic state in which back-up systems produce energy through metabolic pathways that generate ketones. Mice go into this state very quickly, after a few hours or an overnight fast, while people shift to ketogenesis more slowly, from a few hours to up to 36 hours for people on typical Western diets, Kaeberlein said.
Dogs are different. They take at least two days to shift to ketogenesis, suggesting they have evolved to need fewer meals that are spaced out rather than the multiple daily meals plus snacks that people prefer.
As this relates to longevity, Kaeberlein said that a couple of studies show that mice who are fed a ketogenic diet have longer lifespans (years of life regardless of health). “For us, the next step is to analyze the composition of the dogs’ diets or the relationship of multiple daily feedings with obesity,” he said. “Maybe not being obese is related to better health.”
To learn more, the Dog Aging Project needs dogs — lots of dogs! Kaeberlein wants at least 100,000 dogs, including small dogs, large dogs, dogs of all ages. Puppies are needed for the researchers to follow across their lifespan. The project has an excellent website where owners can volunteer to participate.
Nutritional strategies are often not built around sound scientific principles, Kaeberlein said. In human nutrition, people have tried all kinds of diets over the years, including some that were completely wrong. Kaeberlein and his colleagues in the Dog Aging Project want to change that, at least for people’s canine companions, and hopefully, as a result, give dogs added years of healthy life and provide clues for human nutrition.
After that, maybe they can do something about those sad eyes and the frustrated whine.
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.”
Scientists make progress with growing organs for transplants
Story by Big Think
For over a century, scientists have dreamed of growing human organs sans humans. This technology could put an end to the scarcity of organs for transplants. But that’s just the tip of the iceberg. The capability to grow fully functional organs would revolutionize research. For example, scientists could observe mysterious biological processes, such as how human cells and organs develop a disease and respond (or fail to respond) to medication without involving human subjects.
Recently, a team of researchers from the University of Cambridge has laid the foundations not just for growing functional organs but functional synthetic embryos capable of developing a beating heart, gut, and brain. Their report was published in Nature.
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.