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How Taiwan’s Giant Genomics Project Is Rewriting the Future of Disease Prediction

A sweeping genomic effort in Taiwan has revealed something that global precision medicine has long overlooked, that the best way to predict disease is to study the people who will be living with its consequences. Researchers at Academia Sinica have now shown that building genetic risk tools tailored to Han Chinese populations can transform how common illnesses are forecast and understood.

In work published in Nature on October 15, 2025, scientists analyzed genomic and clinical data from more than half a million participants in the Taiwan Precision Medicine Initiative. By conducting the largest genome wide association analysis of Han Chinese individuals to date, they developed the first population specific polygenic risk score models for diseases ranging from type 2 diabetes to autoimmune disorders to heart disease, achieving markedly stronger accuracy than tools based on European data. “This project marks a milestone for precision medicine in East Asia,” said Dr. Cathy S. J. Fann, senior corresponding author at Academia Sinica. “By integrating large scale genomic and clinical data, we are building predictive models that truly reflect the real genetic architecture of our population.”

Explainable AI and turbulence: A fresh look at an unsolved physics problem

While atmospheric turbulence is a familiar culprit of rough flights, the chaotic movement of turbulent flows remains an unsolved problem in physics. To gain insight into the system, a team of researchers used explainable AI to pinpoint the most important regions in a turbulent flow, according to a Nature Communications study led by the University of Michigan and the Universitat Politècnica de València.

A clearer understanding of turbulence could improve forecasting, helping pilots navigate around turbulent areas to avoid passenger injuries or structural damage. It can also help engineers manipulate turbulence, dialing it up to help industrial mixing like water treatment or dialing it down to improve fuel efficiency in vehicles.

“For more than a century, turbulence research has struggled with equations too complex to solve, experiments too difficult to perform, and computers too weak to simulate reality. Artificial Intelligence has now given us a new tool to confront this challenge, leading to a breakthrough with profound practical implications,” said Sergio Hoyas, a professor of aerospace engineering at the Universitat Politècnica de València and co-author of the study.

Artificial spacetimes for reactive control of resource-limited robots

Not metaphorically—literally. The light intensity field becomes an artificial “gravity,” and the robot’s trajectory becomes a null geodesic, the same path light takes in warped spacetime.

By calculating the robot’s “energy” and “angular momentum” (just like planetary orbits), they mathematically prove: robots starting within 90 degrees of a target will converge exponentially, every time. No simulations or wishful thinking—it’s a theorem.

They use the Schwarz-Christoffel transformation (a tool from black hole physics) to “unfold” a maze onto a flat rectangle, program a simple path, then “fold” it back. The result: a single, static light pattern that both guides robots and acts as invisible walls they can’t cross.

npj Robot ics — Artificial spacetimes for reactive control of resource-limited robots. npj Robot 3, 39 (2025). https://doi.org/10.1038/s44182-025-00058-9

Simple molecule shows remarkable Alzheimer’s reversal in rats

Scientists have developed a new molecule that breaks down beta-amyloid plaques by binding to excess copper in the brain. The treatment restored memory and reduced inflammation in rats, while also proving non-toxic and able to cross the blood–brain barrier. Because it’s far simpler and potentially cheaper than existing drugs, researchers are now pursuing partnerships to begin human trials.

A new space radiation shield: Flexible boron nitride nanotube film shows promise

High-energy cosmic radiation damages cells and DNA, causing cancer, and secondary neutrons—generated especially from the planetary surfaces—can be up to 20 times more harmful than other radiations. Aluminum, the most widely used shielding material, has the drawback of generating additional secondary neutrons when below a certain thickness.

Consequently, (BNNTs), which are lightweight, strong, and possess excellent neutron shielding capabilities, are emerging as a promising alternative.

BNNTs are ultrafine tubular only about 5 nanometers in diameter—roughly 1/20,000 the thickness of a human hair—making them extremely light and strong, with excellent thermal neutron absorption capability. However, due to limitations in fabrication technology, they have so far only been produced into thin and brittle sheet, restricting their practical applications.

It Took Physicists 50 Years To Prove Einstein Right About This

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Over a century ago, Einstein wrote his theories of special relativity and general relativity. Within those theories, he predicted that, as an object moves faster, it slightly contracts in length. However, 50 years later Penrose and Terrell predicted that what one would see is instead that the object is rotated. In a recent experiment, physicists proved that this Penrose-Terrell effect is actually real. Let’s take a look.

Paper: https://www.nature.com/articles/s4200… to what I say: The object (frame) they used is obviously not a cube (as you can see in the photo), it has dimensions of 1 × 1 × 0.6 m. 🤓 Check out my new quiz app ➜ http://quizwithit.com/ 📚 Buy my book ➜ https://amzn.to/3HSAWJW 💌 Support me on Donorbox ➜ https://donorbox.org/swtg 📝 Transcripts and written news on Substack ➜ https://sciencewtg.substack.com/ 👉 Transcript with links to references on Patreon ➜ / sabine 📩 Free weekly science newsletter ➜ https://sabinehossenfelder.com/newsle… 👂 Audio only podcast ➜ https://open.spotify.com/show/0MkNfXl… 🔗 Join this channel to get access to perks ➜ / @sabinehossenfelder #science #sciencenews #physics #relativity.

Correction to what I say: The object (frame) they used is obviously not a cube (as you can see in the photo), it has dimensions of 1 × 1 × 0.6 m.

🤓 Check out my new quiz app ➜ http://quizwithit.com/
📚 Buy my book ➜ https://amzn.to/3HSAWJW
💌 Support me on Donorbox ➜ https://donorbox.org/swtg.
📝 Transcripts and written news on Substack ➜ https://sciencewtg.substack.com/
👉 Transcript with links to references on Patreon ➜ / sabine.
📩 Free weekly science newsletter ➜ https://sabinehossenfelder.com/newsle…
👂 Audio only podcast ➜ https://open.spotify.com/show/0MkNfXl…
🔗 Join this channel to get access to perks ➜
/ @sabinehossenfelder.

#science #sciencenews #physics #relativity

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A snapshot of relativistic motion: visualizing the Terrell-Penrose effect

The Terrell-Penrose effect states that the relativistic Lorentz contraction of fast-moving objects cannot be seen in a photograph, but it has never been verified due to the requirement of relativistic speeds of the moving object. Using femtosecond laser pulses and ultrafast photography, and virtually reducing the speed of light, the authors demonstrate the accuracy of this statement.

Scientists Reveal a Theory Suggesting Another Reality Has Been Overlapping Ours

If you think about it, physics has always advanced because of strange little clues that didn’t seem to fit. Mercury’s orbit was off by a tiny fraction; that small mismatch eventually gave us Einstein’s theory of relativity.

The ultraviolet catastrophe in blackbody radiation didn’t make sense because the crisis opened the door to quantum mechanics. So whenever something doesn’t quite add up, it’s worth paying attention. Extra dimensions enter the story because of exactly this kind of mismatch.

If extra dimensions are real, then the forces of nature might not be as separate as they look. Gravity might only appear weak because it’s spread across hidden dimensions, while the other forces are stuck to the space we can see. That would mean unification: the dream of combining all forces under one theory isn’t just possible, but natural.

Thank you for watching.

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