Motion correction in live imaging has long posed a critical challenge, as the rhythmic pulsations caused by breathing, heartbeat, and limb movements induce complex rigid and non-rigid deformations that severely compromise high-fidelity, long-term monitoring of large-scale neuronal populations. Now, through the development of an adaptive motion correction framework, a research team from Zhejiang University and Hangzhou City University has successfully overcome the accuracy and computational bottlenecks of traditional algorithms. The discovery is published in the journal PhotoniX.

A group of scientists have shown that brain organoids can pass on signals that correspond to Braille letters, an essential step towards developing the energy-efficient biohybrid computers of the future. The brain organoids, remotely connected to a sensor that recorded tactile signals from different Braille letters, produced signals that were different for each letter, allowing a decoder to distinguish between the different letters the organoids had been given. Although individual brain organoids provided accurately decodable signals 61% of the time, a team of three performed significantly better, producing an accurate signal 83% of the time. The team of three was also better at distinguishing the signals from artificial noise than the decoder working directly on the obscured signals, without the organoids’ involvement.  

A world-first study by Australian researchers compared three mRNA-LNP vaccine platforms in human blood samples, generating findings that could revolutionise cancer treatment and vaccine design.

- Endowed Chair Professor Buhm Soon Park of the Graduate School of Science and Technology Policy and an international research team propose a definition of the Anthropocene and directions for its application

- The team proposes 1952 as the starting point, focusing on the rapid changes to the Earth since the mid-20th century

- The concept is expected to serve as a common language connecting the Earth sciences, the humanities and social sciences, and policy

Researchers have developed a new tool that pairs machine learning with advanced DNA sequencing to find regions that are crucial for gene regulation. Their new tool, called FIRE, could help researchers pinpoint the DNA changes behind hereditary diseases—a key step toward genetic medicines—and provides an unprecedented look at previously mysterious regions of the genome.