Scientists are working on eye transplants for vision loss. Who will sign up?

Scientists are working on eye transplants for vision loss. Who will sign up?

Often called the window to the soul, the eyes are more sacred than other body parts, at least for some.

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Awash in a fluid finely calibrated to keep it alive, a human eye rests inside a transparent cubic device. This ECaBox, or Eyes in a Care Box, is a one-of-a-kind system built by scientists at Barcelona’s Centre for Genomic Regulation (CRG). Their goal is to preserve human eyes for transplantation and related research.

In recent years, scientists have learned to transplant delicate organs such as the liver, lungs or pancreas, but eyes are another story. Even when preserved at the average transplant temperature of 4 Centigrade, they last for 48 hours max. That's one explanation for why transplanting the whole eye isn’t possible—only the cornea, the dome-shaped, outer layer of the eye, can withstand the procedure. The retina, the layer at the back of the eyeball that turns light into electrical signals, which the brain converts into images, is extremely difficult to transplant because it's packed with nerve tissue and blood vessels.

These challenges also make it tough to research transplantation. “This greatly limits their use for experiments, particularly when it comes to the effectiveness of new drugs and treatments,” said Maria Pia Cosma, a biologist at Barcelona’s Centre for Genomic Regulation (CRG), whose team is working on the ECaBox.

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Stav Dimitropoulos
Stav Dimitropoulos's features have appeared in major outlets such as the BBC, National Geographic, Scientific American, Nature, Popular Mechanics, Science, Runner’s World, and more. Follow her on Facebook or Twitter @TheyCallMeStav.
Researchers probe extreme gene therapy for severe alcoholism

When all traditional therapeutic approaches fail for alcohol abuse disorder, a radical gene therapy might be something to try in the future.

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Story by Freethink

A single shot — a gene therapy injected into the brain — dramatically reduced alcohol consumption in monkeys that previously drank heavily. If the therapy is safe and effective in people, it might one day be a permanent treatment for alcoholism for people with no other options.

The challenge: Alcohol use disorder (AUD) means a person has trouble controlling their alcohol consumption, even when it is negatively affecting their life, job, or health.

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Kristin Houser
Kristin Houser is a staff writer at Freethink, where she covers science and tech. Her written work has appeared in Business Insider, NBC News, and the World Economic Forum’s Agenda, among other publications, and Stephen Colbert once talked about a piece on The Late Show, to her delight. Formerly, Kristin was a staff writer for Futurism and wrote several animated and live action web series.
Massive benefits of AI come with environmental and human costs. Can AI itself be part of the solution?

Generative AI has a large carbon footprint and other drawbacks. But AI can help mitigate its own harms—by plowing through mountains of data on extreme weather and human displacement.

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The recent explosion of generative artificial intelligence tools like ChatGPT and Dall-E enabled anyone with internet access to harness AI’s power for enhanced productivity, creativity, and problem-solving. With their ever-improving capabilities and expanding user base, these tools proved useful across disciplines, from the creative to the scientific.

But beneath the technological wonders of human-like conversation and creative expression lies a dirty secret—an alarming environmental and human cost. AI has an immense carbon footprint. Systems like ChatGPT take months to train in high-powered data centers, which demand huge amounts of electricity, much of which is still generated with fossil fuels, as well as water for cooling. “One of the reasons why Open AI needs investments [to the tune of] $10 billion from Microsoft is because they need to pay for all of that computation,” says Kentaro Toyama, a computer scientist at the University of Michigan. There’s also an ecological toll from mining rare minerals required for hardware and infrastructure. This environmental exploitation pollutes land, triggers natural disasters and causes large-scale human displacement. Finally, for data labeling needed to train and correct AI algorithms, the Big Data industry employs cheap and exploitative labor, often from the Global South.

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Payal Dhar
Payal is a writer based in New Delhi who has been covering science, technology, and society since 1998.