Chinese researchers report a pig kidney transplant and a first-step liver experiment
WASHINGTON (AP) — Chinese researchers are reporting new steps in the quest for animal-to-human organ transplants – with a successful pig kidney transplant and a hint Wednesday that pig livers might eventually be useful, too.
A Chinese patient is the third person in world known to be living with a gene-edited pig kidney. And the same research team also reported an experiment implanting a pig liver into a brain-dead person.
Scientists are genetically altering pigs so their organs are more humanlike in hopes of alleviating a transplant shortage. Two initial xenotransplants in the U.S. — two pig hearts and two pig kidneys – were short-lived. But two additional pig kidney recipients so far are thriving – an Alabama woman transplanted in November and a New Hampshire man transplanted in January. A U.S. clinical trial is about to begin.
Nearly three weeks after the kidney surgery the Chinese patient "is very well' and the pig kidney likewise is functioning very well, Dr. Lin Wang of Xijing Hospital of the Fourth Military Medical University in Xi'an told reporters in a briefing this week.
Wang, part of the hospital's xenotransplant team, said the kidney recipient remains in the hospital for testing. Chinese media have reported she is a 69-year-old woman diagnosed with kidney failure eight years ago.
But Wang pointed to a potential next step in xenotransplantation — learning to transplant pig livers. His team reported Wednesday in the journal Nature that a pig liver transplanted into a brain-dead person survived for 10 days, with no early signs of rejection. He said the pig liver produced bile and albumin — important for basic organ function — although not as much as human livers do.
The liver is a complex challenge because of its varied jobs, including removing waste, breaking down nutrients and medicines, fighting infection, storing iron and regulating blood clotting.
'We do find that it could function a little bit in a human being,' Wang said. He speculated that would be enough to help support a failing human liver.
In the U.S. last year, surgeons at the University of Pennsylvania attempted that sort of 'bridge' support by externally attaching a pig liver to a brain-dead human body to filter blood, much like dialysis for failing kidneys. U.S. pig developer eGenesis is studying that approach.
In China, Wang's team didn't remove the deceased person's own liver, instead implanting the pig liver near it.
That 'clouds the picture,' said Dr. Parsia Vagefi, a liver transplant surgeon at UT Southwestern Medical Center who wasn't involved with the work. 'It's hopefully a first step but it's still, a lot like any good research, more questions than answers.'
Wang said his team later replaced the human liver of another brain-dead person with a pig liver and is analyzing the outcome.
According to media reports, another Chinese hospital last year transplanted a pig liver into a living patient after a piece of his own cancerous liver was removed but it's unclear how that experiment turned out.
___
The Associated Press Health and Science Department receives support from the Howard Hughes Medical Institute's Science and Educational Media Group and the Robert Wood Johnson Foundation. The AP is solely responsible for all content.
Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
San Francisco Chronicle
35 minutes ago
- San Francisco Chronicle
AI chatbots need more books to learn from. These libraries are opening their stacks
CAMBRIDGE, Mass. (AP) — Everything ever said on the internet was just the start of teaching artificial intelligence about humanity. Tech companies are now tapping into an older repository of knowledge: the library stacks. Nearly one million books published as early as the 15th century — and in 254 languages — are part of a Harvard University collection being released to AI researchers Thursday. Also coming soon are troves of old newspapers and government documents held by Boston's public library. Cracking open the vaults to centuries-old tomes could be a data bonanza for tech companies battling lawsuits from living novelists, visual artistsand others whose creative works have been scooped up without their consent to train AI chatbots. 'It is a prudent decision to start with public domain data because that's less controversial right now than content that's still under copyright,' said Burton Davis, a deputy general counsel at Microsoft. Davis said libraries also hold 'significant amounts of interesting cultural, historical and language data' that's missing from the past few decades of online commentary that AI chatbots have mostly learned from. Supported by 'unrestricted gifts' from Microsoft and ChatGPT maker OpenAI, the Harvard-based Institutional Data Initiative is working with libraries around the world on how to make their historic collections AI-ready in a way that also benefits libraries and the communities they serve. 'We're trying to move some of the power from this current AI moment back to these institutions,' said Aristana Scourtas, who manages research at Harvard Law School's Library Innovation Lab. 'Librarians have always been the stewards of data and the stewards of information.' Harvard's newly released dataset, Institutional Books 1.0, contains more than 394 million scanned pages of paper. One of the earlier works is from the 1400s — a Korean painter's handwritten thoughts about cultivating flowers and trees. The largest concentration of works is from the 19th century, on subjects such as literature, philosophy, law and agriculture, all of it meticulously preserved and organized by generations of librarians. It promises to be a boon for AI developers trying to improve the accuracy and reliability of their systems. 'A lot of the data that's been used in AI training has not come from original sources,' said the data initiative's executive director, Greg Leppert, who is also chief technologist at Harvard's Berkman Klein Center for Internet & Society. This book collection goes "all the way back to the physical copy that was scanned by the institutions that actually collected those items,' he said. Before ChatGPT sparked a commercial AI frenzy, most AI researchers didn't think much about the provenance of the passages of text they pulled from Wikipedia, from social media forums like Reddit and sometimes from deep repositories of pirated books. They just needed lots of what computer scientists call tokens — units of data, each of which can represent a piece of a word. Harvard's new AI training collection has an estimated 242 billion tokens, an amount that's hard for humans to fathom but it's still just a drop of what's being fed into the most advanced AI systems. Facebook parent company Meta, for instance, has said the latest version of its AI large language model was trained on more than 30 trillion tokens pulled from text, images and videos. Meta is also battling a lawsuit from comedian Sarah Silverman and other published authors who accuse the company of stealing their books from 'shadow libraries' of pirated works. Now, with some reservations, the real libraries are standing up. OpenAI, which is also fighting a string of copyright lawsuits, donated $50 million this year to a group of research institutions including Oxford University's 400-year-old Bodleian Library, which is digitizing rare texts and using AI to help transcribe them. When the company first reached out to the Boston Public Library, one of the biggest in the U.S., the library made clear that any information it digitized would be for everyone, said Jessica Chapel, its chief of digital and online services. 'OpenAI had this interest in massive amounts of training data. We have an interest in massive amounts of digital objects. So this is kind of just a case that things are aligning,' Chapel said. Digitization is expensive. It's been painstaking work, for instance, for Boston's library to scan and curate dozens of New England's French-language newspapers that were widely read in the late 19th and early 20th century by Canadian immigrant communities from Quebec. Now that such text is of use as training data, it helps bankroll projects that librarians want to do anyway. 'We've been very clear that, 'Hey, we're a public library,'" Chapel said. 'Our collections are held for public use, and anything we digitized as part of this project will be made public.' Harvard's collection was already digitized starting in 2006 for another tech giant, Google, in its controversial project to create a searchable online library of more than 20 million books. Google spent years beating back legal challenges from authors to its online book library, which included many newer and copyrighted works. It was finally settled in 2016 when the U.S. Supreme Court let stand lower court rulings that rejected copyright infringement claims. Now, for the first time, Google has worked with Harvard to retrieve public domain volumes from Google Books and clear the way for their release to AI developers. Copyright protections in the U.S. typically last for 95 years, and longer for sound recordings. How useful all of this will be for the next generation of AI tools remains to be seen as the data gets shared Thursday on the Hugging Face platform, which hosts datasets and open-source AI models that anyone can download. The book collection is more linguistically diverse than typical AI data sources. Fewer than half the volumes are in English, though European languages still dominate, particularly German, French, Italian, Spanish and Latin. A book collection steeped in 19th century thought could also be 'immensely critical' for the tech industry's efforts to build AI agents that can plan and reason as well as humans, Leppert said. 'At a university, you have a lot of pedagogy around what it means to reason,' Leppert said. 'You have a lot of scientific information about how to run processes and how to run analyses.' At the same time, there's also plenty of outdated data, from debunked scientific and medical theories to racist narratives. 'When you're dealing with such a large data set, there are some tricky issues around harmful content and language," said Kristi Mukk, a coordinator at Harvard's Library Innovation Lab who said the initiative is trying to provide guidance about mitigating the risks of using the data, to 'help them make their own informed decisions and use AI responsibly.'
Yahoo
an hour ago
- Yahoo
AI chatbots need more books to learn from. These libraries are opening their stacks
CAMBRIDGE, Mass. (AP) — Everything ever said on the internet was just the start of teaching artificial intelligence about humanity. Tech companies are now tapping into an older repository of knowledge: the library stacks. Nearly one million books published as early as the 15th century — and in 254 languages — are part of a Harvard University collection being released to AI researchers Thursday. Also coming soon are troves of old newspapers and government documents held by Boston's public library. Cracking open the vaults to centuries-old tomes could be a data bonanza for tech companies battling lawsuits from living novelists, visual artistsand others whose creative works have been scooped up without their consent to train AI chatbots. 'It is a prudent decision to start with public domain data because that's less controversial right now than content that's still under copyright,' said Burton Davis, a deputy general counsel at Microsoft. Davis said libraries also hold 'significant amounts of interesting cultural, historical and language data' that's missing from the past few decades of online commentary that AI chatbots have mostly learned from. Supported by 'unrestricted gifts' from Microsoft and ChatGPT maker OpenAI, the Harvard-based Institutional Data Initiative is working with libraries around the world on how to make their historic collections AI-ready in a way that also benefits libraries and the communities they serve. 'We're trying to move some of the power from this current AI moment back to these institutions,' said Aristana Scourtas, who manages research at Harvard Law School's Library Innovation Lab. 'Librarians have always been the stewards of data and the stewards of information.' Harvard's newly released dataset, Institutional Books 1.0, contains more than 394 million scanned pages of paper. One of the earlier works is from the 1400s — a Korean painter's handwritten thoughts about cultivating flowers and trees. The largest concentration of works is from the 19th century, on subjects such as literature, philosophy, law and agriculture, all of it meticulously preserved and organized by generations of librarians. It promises to be a boon for AI developers trying to improve the accuracy and reliability of their systems. 'A lot of the data that's been used in AI training has not come from original sources,' said the data initiative's executive director, Greg Leppert, who is also chief technologist at Harvard's Berkman Klein Center for Internet & Society. This book collection goes "all the way back to the physical copy that was scanned by the institutions that actually collected those items,' he said. Before ChatGPT sparked a commercial AI frenzy, most AI researchers didn't think much about the provenance of the passages of text they pulled from Wikipedia, from social media forums like Reddit and sometimes from deep repositories of pirated books. They just needed lots of what computer scientists call tokens — units of data, each of which can represent a piece of a word. Harvard's new AI training collection has an estimated 242 billion tokens, an amount that's hard for humans to fathom but it's still just a drop of what's being fed into the most advanced AI systems. Facebook parent company Meta, for instance, has said the latest version of its AI large language model was trained on more than 30 trillion tokens pulled from text, images and videos. Meta is also battling a lawsuit from comedian Sarah Silverman and other published authors who accuse the company of stealing their books from 'shadow libraries' of pirated works. Now, with some reservations, the real libraries are standing up. OpenAI, which is also fighting a string of copyright lawsuits, donated $50 million this year to a group of research institutions including Oxford University's 400-year-old Bodleian Library, which is digitizing rare texts and using AI to help transcribe them. When the company first reached out to the Boston Public Library, one of the biggest in the U.S., the library made clear that any information it digitized would be for everyone, said Jessica Chapel, its chief of digital and online services. 'OpenAI had this interest in massive amounts of training data. We have an interest in massive amounts of digital objects. So this is kind of just a case that things are aligning,' Chapel said. Digitization is expensive. It's been painstaking work, for instance, for Boston's library to scan and curate dozens of New England's French-language newspapers that were widely read in the late 19th and early 20th century by Canadian immigrant communities from Quebec. Now that such text is of use as training data, it helps bankroll projects that librarians want to do anyway. 'We've been very clear that, 'Hey, we're a public library,'" Chapel said. 'Our collections are held for public use, and anything we digitized as part of this project will be made public.' Harvard's collection was already digitized starting in 2006 for another tech giant, Google, in its controversial project to create a searchable online library of more than 20 million books. Google spent years beating back legal challenges from authors to its online book library, which included many newer and copyrighted works. It was finally settled in 2016 when the U.S. Supreme Court let stand lower court rulings that rejected copyright infringement claims. Now, for the first time, Google has worked with Harvard to retrieve public domain volumes from Google Books and clear the way for their release to AI developers. Copyright protections in the U.S. typically last for 95 years, and longer for sound recordings. How useful all of this will be for the next generation of AI tools remains to be seen as the data gets shared Thursday on the Hugging Face platform, which hosts datasets and open-source AI models that anyone can download. The book collection is more linguistically diverse than typical AI data sources. Fewer than half the volumes are in English, though European languages still dominate, particularly German, French, Italian, Spanish and Latin. A book collection steeped in 19th century thought could also be 'immensely critical' for the tech industry's efforts to build AI agents that can plan and reason as well as humans, Leppert said. 'At a university, you have a lot of pedagogy around what it means to reason,' Leppert said. 'You have a lot of scientific information about how to run processes and how to run analyses.' At the same time, there's also plenty of outdated data, from debunked scientific and medical theories to racist narratives. 'When you're dealing with such a large data set, there are some tricky issues around harmful content and language," said Kristi Mukk, a coordinator at Harvard's Library Innovation Lab who said the initiative is trying to provide guidance about mitigating the risks of using the data, to 'help them make their own informed decisions and use AI responsibly.' ———— The Associated Press and OpenAI have a licensing and technology agreement that allows OpenAI access to part of AP's text archives.
Scientific American
2 hours ago
- Scientific American
Brain Implant Lets Man with ALS Speak and Sing with His ‘Real Voice'
A man with a severe speech disability is able to speak expressively and sing using a brain implant that translates his neural activity into words almost instantly. The device conveys changes of tone when he asks questions, emphasizes the words of his choice and allows him to hum a string of notes in three pitches. The system — known as a brain–computer interface (BCI) — used artificial intelligence (AI) to decode the participant's electrical brain activity as he attempted to speak. The device is the first to reproduce not only a person's intended words but also features of natural speech such as tone, pitch and emphasis, which help to express meaning and emotion. In a study, a synthetic voice that mimicked the participant's own spoke his words within 10 milliseconds of the neural activity that signalled his intention to speak. The system, described today in Nature, marks a significant improvement over earlier BCI models, which streamed speech within three seconds or produced it only after users finished miming an entire sentence. On supporting science journalism If you're enjoying this article, consider supporting our award-winning journalism by subscribing. By purchasing a subscription you are helping to ensure the future of impactful stories about the discoveries and ideas shaping our world today. 'This is the holy grail in speech BCIs,' says Christian Herff, a computational neuroscientist at Maastricht University, the Netherlands, who was not involved in the study. 'This is now real, spontaneous, continuous speech.' Real-time decoder The study participant, a 45-year-old man, lost his ability to speak clearly after developing amyotrophic lateral sclerosis, a form of motor neuron disease, which damages the nerves that control muscle movements, including those needed for speech. Although he could still make sounds and mouth words, his speech was slow and unclear. Five years after his symptoms began, the participant underwent surgery to insert 256 silicon electrodes, each 1.5-mm long, in a brain region that controls movement. Study co-author Maitreyee Wairagkar, a neuroscientist at the University of California, Davis, and her colleagues trained deep-learning algorithms to capture the signals in his brain every 10 milliseconds. Their system decodes, in real time, the sounds the man attempts to produce rather than his intended words or the constituent phonemes — the subunits of speech that form spoken words. 'We don't always use words to communicate what we want. We have interjections. We have other expressive vocalizations that are not in the vocabulary,' explains Wairagkar. 'In order to do that, we have adopted this approach, which is completely unrestricted.' The team also personalized the synthetic voice to sound like the man's own, by training AI algorithms on recordings of interviews he had done before the onset of his disease. The team asked the participant to attempt to make interjections such as 'aah', 'ooh' and 'hmm' and say made-up words. The BCI successfully produced these sounds, showing that it could generate speech without needing a fixed vocabulary. Freedom of speech Using the device, the participant spelt out words, responded to open-ended questions and said whatever he wanted, using some words that were not part of the decoder's training data. He told the researchers that listening to the synthetic voice produce his speech made him 'feel happy' and that it felt like his 'real voice'. In other experiments, the BCI identified whether the participant was attempting to say a sentence as a question or as a statement. The system could also determine when he stressed different words in the same sentence and adjust the tone of his synthetic voice accordingly. 'We are bringing in all these different elements of human speech which are really important,' says Wairagkar. Previous BCIs could produce only flat, monotone speech. 'This is a bit of a paradigm shift in the sense that it can really lead to a real-life tool,' says Silvia Marchesotti, a neuroengineer at the University of Geneva in Switzerland. The system's features 'would be crucial for adoption for daily use for the patients in the future.'
