Tag Archives: surrogate
#439077 How Scientists Grew Human Muscles in Pig ...
The little pigs bouncing around the lab looked exceedingly normal. Yet their adorable exterior hid a remarkable secret: each piglet carried two different sets of genes. For now, both sets came from their own species. But one day, one of those sets may be human.
The piglets are chimeras—creatures with intermingled sets of genes, as if multiple entities were seamlessly mashed together. Named after the Greek lion-goat-serpent monsters, chimeras may hold the key to an endless supply of human organs and tissues for transplant. The crux is growing these human parts in another animal—one close enough in size and function to our own.
Last week, a team from the University of Minnesota unveiled two mind-bending chimeras. One was joyous little piglets, each propelled by muscles grown from a different pig. Another was pig embryos, transplanted into surrogate pigs, that developed human muscles for more than 20 days.
The study, led by Drs. Mary and Daniel Garry at the University of Minnesota, had a therapeutic point: engineering a brilliant way to replace muscle loss, especially for the muscles around our skeletons that allow us to move and navigate the world. Trauma and injury, such as from firearm wounds or car crashes, can damage muscle tissue beyond the point of repair. Unfortunately, muscles are also stubborn in that donor tissue from cadavers doesn’t usually “take” at the injury site. For now, there are no effective treatments for severe muscle death, called volumetric muscle loss.
The new human-pig hybrids are designed to tackle this problem. Muscle wasting aside, the study also points to a clever “hack” that increases the amount of human tissue inside a growing pig embryo.
If further improved, the technology could “provide an unlimited supply of organs for transplantation,” said Dr. Mary Garry to Inverse. What’s more, because the human tissue can be sourced from patients themselves, the risk of rejection by the immune system is relatively low—even when grown inside a pig.
“The shortage of organs for heart transplantation, vascular grafting, and skeletal muscle is staggering,” said Garry. Human-animal chimeras could have a “seismic impact” that transforms organ transplantation and helps solve the organ shortage crisis.
That is, if society accepts the idea of a semi-humanoid pig.
Wait…But How?
The new study took a page from previous chimera recipes.
The main ingredients and steps go like this: first, you need an embryo that lacks the ability to develop a tissue or organ. This leaves an “empty slot” of sorts that you can fill with another set of genes—pig, human, or even monkey.
Second, you need to fine-tune the recipe so that the embryos “take” the new genes, incorporating them into their bodies as if they were their own. Third, the new genes activate to instruct the growing embryo to make the necessary tissue or organs without harming the overall animal. Finally, the foreign genes need to stay put, without cells migrating to another body part—say, the brain.
Not exactly straightforward, eh? The piglets are technological wonders that mix cutting-edge gene editing with cloning technologies.
The team went for two chimeras: one with two sets of pig genes, the other with a pig and human mix. Both started with a pig embryo that can’t make its own skeletal muscles (those are the muscles surrounding your bones). Using CRISPR, the gene-editing Swiss Army Knife, they snipped out three genes that are absolutely necessary for those muscles to develop. Like hitting a bullseye with three arrows simultaneously, it’s already a technological feat.
Here’s the really clever part: the muscles around your bones have a slightly different genetic makeup than the ones that line your blood vessels or the ones that pump your heart. While the resulting pig embryos had severe muscle deformities as they developed, their hearts beat as normal. This means the gene editing cut only impacted skeletal muscles.
Then came step two: replacing the missing genes. Using a microneedle, the team injected a fertilized and slightly developed pig egg—called a blastomere—into the embryo. If left on its natural course, a blastomere eventually develops into another embryo. This step “smashes” the two sets of genes together, with the newcomer filling the muscle void. The hybrid embryo was then placed into a surrogate, and roughly four months later, chimeric piglets were born.
Equipped with foreign DNA, the little guys nevertheless seemed totally normal, nosing around the lab and running everywhere without obvious clumsy stumbles. Under the microscope, their “xenomorph” muscles were indistinguishable from run-of-the-mill average muscle tissue—no signs of damage or inflammation, and as stretchy and tough as muscles usually are. What’s more, the foreign DNA seemed to have only developed into muscles, even though they were prevalent across the body. Extensive fishing experiments found no trace of the injected set of genes inside blood vessels or the brain.
A Better Human-Pig Hybrid
Confident in their recipe, the team next repeated the experiment with human cells, with a twist. Instead of using controversial human embryonic stem cells, which are obtained from aborted fetuses, they relied on induced pluripotent stem cells (iPSCs). These are skin cells that have been reverted back into a stem cell state.
Unlike previous attempts at making human chimeras, the team then scoured the genetic landscape of how pig and human embryos develop to find any genetic “brakes” that could derail the process. One gene, TP53, stood out, which was then promptly eliminated with CRISPR.
This approach provides a way for future studies to similarly increase the efficiency of interspecies chimeras, the team said.
The human-pig embryos were then carefully grown inside surrogate pigs for less than a month, and extensively analyzed. By day 20, the hybrids had already grown detectable human skeletal muscle. Similar to the pig-pig chimeras, the team didn’t detect any signs that the human genes had sprouted cells that would eventually become neurons or other non-muscle cells.
For now, human-animal chimeras are not allowed to grow to term, in part to stem the theoretical possibility of engineering humanoid hybrid animals (shudder). However, a sentient human-pig chimera is something that the team specifically addressed. Through multiple experiments, they found no trace of human genes in the embryos’ brain stem cells 20 and 27 days into development. Similarly, human donor genes were absent in cells that would become the hybrid embryos’ reproductive cells.
Despite bioethical quandaries and legal restrictions, human-animal chimeras have taken off, both as a source of insight into human brain development and a well of personalized organs and tissues for transplant. In 2019, Japan lifted its ban on developing human brain cells inside animal embryos, as well as the term limit—to global controversy. There’s also the question of animal welfare, given that hybrid clones will essentially become involuntary organ donors.
As the debates rage on, scientists are nevertheless pushing the limits of human-animal chimeras, while treading as carefully as possible.
“Our data…support the feasibility of the generation of these interspecies chimeras, which will serve as a model for translational research or, one day, as a source for xenotransplantation,” the team said.
Image Credit: Christopher Carson on Unsplash Continue reading
Posted in Human Robots
#431599 8 Ways AI Will Transform Our Cities by ...
How will AI shape the average North American city by 2030? A panel of experts assembled as part of a century-long study into the impact of AI thinks its effects will be profound.
The One Hundred Year Study on Artificial Intelligence is the brainchild of Eric Horvitz, technical fellow and a managing director at Microsoft Research.
Every five years a panel of experts will assess the current state of AI and its future directions. The first panel, comprised of experts in AI, law, political science, policy, and economics, was launched last fall and decided to frame their report around the impact AI will have on the average American city. Here’s how they think it will affect eight key domains of city life in the next fifteen years.
1. Transportation
The speed of the transition to AI-guided transport may catch the public by surprise. Self-driving vehicles will be widely adopted by 2020, and it won’t just be cars — driverless delivery trucks, autonomous delivery drones, and personal robots will also be commonplace.
Uber-style “cars as a service” are likely to replace car ownership, which may displace public transport or see it transition towards similar on-demand approaches. Commutes will become a time to relax or work productively, encouraging people to live further from home, which could combine with reduced need for parking to drastically change the face of modern cities.
Mountains of data from increasing numbers of sensors will allow administrators to model individuals’ movements, preferences, and goals, which could have major impact on the design city infrastructure.
Humans won’t be out of the loop, though. Algorithms that allow machines to learn from human input and coordinate with them will be crucial to ensuring autonomous transport operates smoothly. Getting this right will be key as this will be the public’s first experience with physically embodied AI systems and will strongly influence public perception.
2. Home and Service Robots
Robots that do things like deliver packages and clean offices will become much more common in the next 15 years. Mobile chipmakers are already squeezing the power of last century’s supercomputers into systems-on-a-chip, drastically boosting robots’ on-board computing capacity.
Cloud-connected robots will be able to share data to accelerate learning. Low-cost 3D sensors like Microsoft’s Kinect will speed the development of perceptual technology, while advances in speech comprehension will enhance robots’ interactions with humans. Robot arms in research labs today are likely to evolve into consumer devices around 2025.
But the cost and complexity of reliable hardware and the difficulty of implementing perceptual algorithms in the real world mean general-purpose robots are still some way off. Robots are likely to remain constrained to narrow commercial applications for the foreseeable future.
3. Healthcare
AI’s impact on healthcare in the next 15 years will depend more on regulation than technology. The most transformative possibilities of AI in healthcare require access to data, but the FDA has failed to find solutions to the difficult problem of balancing privacy and access to data. Implementation of electronic health records has also been poor.
If these hurdles can be cleared, AI could automate the legwork of diagnostics by mining patient records and the scientific literature. This kind of digital assistant could allow doctors to focus on the human dimensions of care while using their intuition and experience to guide the process.
At the population level, data from patient records, wearables, mobile apps, and personal genome sequencing will make personalized medicine a reality. While fully automated radiology is unlikely, access to huge datasets of medical imaging will enable training of machine learning algorithms that can “triage” or check scans, reducing the workload of doctors.
Intelligent walkers, wheelchairs, and exoskeletons will help keep the elderly active while smart home technology will be able to support and monitor them to keep them independent. Robots may begin to enter hospitals carrying out simple tasks like delivering goods to the right room or doing sutures once the needle is correctly placed, but these tasks will only be semi-automated and will require collaboration between humans and robots.
4. Education
The line between the classroom and individual learning will be blurred by 2030. Massive open online courses (MOOCs) will interact with intelligent tutors and other AI technologies to allow personalized education at scale. Computer-based learning won’t replace the classroom, but online tools will help students learn at their own pace using techniques that work for them.
AI-enabled education systems will learn individuals’ preferences, but by aggregating this data they’ll also accelerate education research and the development of new tools. Online teaching will increasingly widen educational access, making learning lifelong, enabling people to retrain, and increasing access to top-quality education in developing countries.
Sophisticated virtual reality will allow students to immerse themselves in historical and fictional worlds or explore environments and scientific objects difficult to engage with in the real world. Digital reading devices will become much smarter too, linking to supplementary information and translating between languages.
5. Low-Resource Communities
In contrast to the dystopian visions of sci-fi, by 2030 AI will help improve life for the poorest members of society. Predictive analytics will let government agencies better allocate limited resources by helping them forecast environmental hazards or building code violations. AI planning could help distribute excess food from restaurants to food banks and shelters before it spoils.
Investment in these areas is under-funded though, so how quickly these capabilities will appear is uncertain. There are fears valueless machine learning could inadvertently discriminate by correlating things with race or gender, or surrogate factors like zip codes. But AI programs are easier to hold accountable than humans, so they’re more likely to help weed out discrimination.
6. Public Safety and Security
By 2030 cities are likely to rely heavily on AI technologies to detect and predict crime. Automatic processing of CCTV and drone footage will make it possible to rapidly spot anomalous behavior. This will not only allow law enforcement to react quickly but also forecast when and where crimes will be committed. Fears that bias and error could lead to people being unduly targeted are justified, but well-thought-out systems could actually counteract human bias and highlight police malpractice.
Techniques like speech and gait analysis could help interrogators and security guards detect suspicious behavior. Contrary to concerns about overly pervasive law enforcement, AI is likely to make policing more targeted and therefore less overbearing.
7. Employment and Workplace
The effects of AI will be felt most profoundly in the workplace. By 2030 AI will be encroaching on skilled professionals like lawyers, financial advisers, and radiologists. As it becomes capable of taking on more roles, organizations will be able to scale rapidly with relatively small workforces.
AI is more likely to replace tasks rather than jobs in the near term, and it will also create new jobs and markets, even if it’s hard to imagine what those will be right now. While it may reduce incomes and job prospects, increasing automation will also lower the cost of goods and services, effectively making everyone richer.
These structural shifts in the economy will require political rather than purely economic responses to ensure these riches are shared. In the short run, this may include resources being pumped into education and re-training, but longer term may require a far more comprehensive social safety net or radical approaches like a guaranteed basic income.
8. Entertainment
Entertainment in 2030 will be interactive, personalized, and immeasurably more engaging than today. Breakthroughs in sensors and hardware will see virtual reality, haptics and companion robots increasingly enter the home. Users will be able to interact with entertainment systems conversationally, and they will show emotion, empathy, and the ability to adapt to environmental cues like the time of day.
Social networks already allow personalized entertainment channels, but the reams of data being collected on usage patterns and preferences will allow media providers to personalize entertainment to unprecedented levels. There are concerns this could endow media conglomerates with unprecedented control over people’s online experiences and the ideas to which they are exposed.
But advances in AI will also make creating your own entertainment far easier and more engaging, whether by helping to compose music or choreograph dances using an avatar. Democratizing the production of high-quality entertainment makes it nearly impossible to predict how highly fluid human tastes for entertainment will develop.
Image Credit: Asgord / Shutterstock.com Continue reading
Posted in Human Robots