Topic: Biology
Evan Economo's lab created detailed 3D models of ants using a particle accelerator. This new approach is much faster than previous methods and can help digitize many organisms.
For over ten years, Evan Economo's lab has used micro CT scanners to study insect specimens. These scans provide extremely detailed 3D data about the physical structure and form of insects, also known as morphology. However, this technique is expensive and slow.
Economo and his team wanted to find a way to speed up the process. They brought together researchers from the University of Maryland and the Karlsruhe Institute of Technology (KIT) in Germany. Together, they used a particle accelerator, X-ray imaging, robotics, and artificial intelligence (AI) to create interactive digital reconstructions of 800 ant species.
This new approach is much faster than previous methods. In fact, it took only one week to scan 2,000 specimens using the particle accelerator, compared to six years with a lab-based CT scanner.
The team also developed AI tools that can adjust the scanned images so the ants appear in natural positions, similar to how they would look in the wild.
Why It Matters
This new approach can help digitize many organisms and could be used in scientific research, education, or entertainment. It's an important step towards building a digital library of ant biodiversity.
Key Facts
- The team created detailed 3D models of ants using a particle accelerator.
- This new approach is much faster than previous methods.
- It took only one week to scan 2,000 specimens using the particle accelerator.
- The team developed AI tools that can adjust the scanned images so the ants appear in natural positions.
- The research could be used in scientific research, education, or entertainment.
Key Terms
- Particle Accelerator
- A machine that uses high-energy particles to create intense X-ray beams.
Implications
This new approach can help digitize many organisms and could be used in scientific research, education, or entertainment. It's an important step towards building a digital library of ant biodiversity.
Source: https://www.sciencedaily.com/releases/2026/03/260310223603.htm
Journal Reference:
- Julian Katzke, Francisco Hita Garcia, Philipp D. Lösel, Fumika Azuma, Tomáš Faragó, Lazzat Aibekova, Alexandre Casadei-Ferreira, Shubham Gautam, Adrian Richter, Evropi Toulkeridou, Sabine Bremer, Elias Hamann, Jenny Hein, Janes Odar, Chandan Sarkar, Marcus Zuber, Jacobus J. Boomsma, Rodrigo M. Feitosa, Lukas Schrader, Guojie Zhang, Sándor Csősz, Minsoo Dong, Olivia Evangelista, Georg Fischer, Brian L. Fisher, Jaime A. Florez-Fernandez, Serge Aron, Abel Bernadou, Martin Bollazzi, Raphaël Boulay, Sylvia Cremer, Heike Feldhaar, Susanne Foitzik, Erik T. Frank, Jürgen Gadau, Daniele Giannetti, Stephane de Greef, Heikki Helanterä, Ana Ješovnik, Fredrick Larabee, Bálint Markó, David Nash, Jérôme Orivel, Jes Søe Pedersen, Frédéric Petitclerc, Stephen Rehner, Morten Schiøtt, András Tartally, Kazuki Tsuji, Irene Villalta, Herbert C. Wagner, Fede García, Kiko Gómez, Donato A. Grasso, Stephane de Greef, Benoit Guénard, Peter G. Hawkes, Robert A. Johnson, Roberto A. Keller, Rasmus S. Larsen, Timothy A. Linksvayer, Cong Liu, Arthur Matte, Masako Ogasawara, Hao Ran, Juanita Rodriguez, Enrico Schifani, Ted R. Schultz, Jonathan Z. Shik, Jeffrey Sosa-Calvo, Chao Tong, Leonardo Tozetto, Seonwoo Yoon, Masashi Yoshimura, Jie Zhao, Tilo Baumbach, Evan P. Economo, Thomas van de Kamp. High-throughput phenomics of global ant biodiversity. Nature Methods, 2026; DOI: 10.1038/s41592-026-03005-0
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