Microalgae‑based architecture could soon come to Western Australia.
A team from Murdoch University is working on a project to integrate microalgae-filled photobioreactors into everyday structures like houses, apartments, mining dongas, and urban designs.
If adapted, it could improve energy efficiency and environmental health.
McGill University engineers have developed new ultra-thin materials that can be programmed to move, fold and reshape themselves, much like animated origami. They open the door to softer, safer and more adaptable robots that could be used in medical tools that gently move inside the body, wearable devices that change shape on the skin or smart packaging that reacts to its environment.
The research, jointly led by the laboratories of Hamid Akbarzadeh in the Department of Bioresource Engineering and Marta Cerruti in the Department of Mining and Material Engineering, shows how simple, paper-like sheets made from folded graphene oxide (GO) can be turned into tiny devices that walk, twist, flip and sense their own motion. Two related studies demonstrate how these materials can be made at scale, programmed to change shape and controlled either by humidity or magnetic fields.
The studies are published in Materials Horizons and Advanced Science.
In this Review, Emilio Hirsch discuss the mechanisms and therapeutic strategies for cardiotoxicity caused by chemotherapy, targeted agents, and immune modulators.
1Department of Molecular Biotechnology and Health Sciences, Molecular Biotechnology Center “Guido Tarone”, University of Torino, Torino, Italy.
2University of Arizona College of Medicine, Tucson, Arizona, USA.
Address correspondence to: Emilio Hirsch or Alessandra Ghigo, Via Nizza 52, 10126, Turin, Italy. Phone: 39.011.670.6425; Email: [email protected] (EH). Phone: 39.011.670.6335; Email: [email protected] (AG). Or to: Hossein Ardehali, 3,838 North Campbell Avenue, Building 2, Tucson, Arizona 85,719, USA. Phone: 520.626.6453; Email: [email protected].
“We saw some peculiar brain activity in the model,” Miller says. “There was a group of neurons that predicted the wrong answer, yet they kept getting stronger as the model learned. So we went back to the original macaque data, and the same signal was there, hiding in plain sight. It wasn’t a quirk of the model — the monkeys’ brains were doing it too. Even as their performance improved, both the real and simulated brains maintained a reserve of neurons that continued to predict the incorrect answer.”
The new work, published in Nature Communications, puts a name to these overlooked signals: incongruent neurons, or ICNs, and explores theories as to why a primate brain might want to keep alternate options in mind, even if they’re not the right ones at the moment.
Beyond identifying a previously unrecognized class of neurons involved in learning, the study shows that the model behaves like a brain and generates realistic brain activity, even without being trained on neural data. The findings could have major implications for testing potential neurological drugs and for using computational models to investigate how cognition emerges and functions.
