Variation in tissue mechanical properties play an important role in generating animal body shape diversity, as a new study from EMBL researchers and their collaborators has shown. Using a combination of theoretical modelling and experimental perturbations, the researchers showed how a combination of such properties results in a unique 'mechanotype’ for a species. Mechanotypes can help us predict body shape, and the scientists hypothesise that evolution might act on mechanotypes to give rise to the diversity of animal body shapes that we see around us today.

A research team has successfully developed a deep neural network (DNN) model capable of predicting nuclear charge density distributions with high precision. Trained on advanced theoretical data, this model outperforms existing methods in accuracy and has yielded a comprehensive global dataset of charge densities spanning a wide range of nuclides. This achievement provides invaluable data support for research in nuclear physics, atomic and molecular physics, and related fundamental fields.

Advanced Scientific Instruments (ASI), a new interdisciplinary open-access journal, has published its inaugural issue. The journal is dedicated to the art and science of instrumentation—from fundamental principles and system architecture to advanced applications. It is published by Science China Press and KeAi, under the auspices of the Chinese Academy of Sciences.

Seamless integration between electronics and the human body is the goal, and Ga-LMs are key to this transformation. Essential properties,such as, fluidity, conductivity, and biocompatibility, enable Ga-LMs to form stretchable, self-healing circuits, paving the way for advanced wearables, soft robotics, and medical implants that promise to redefine human-machine interaction.

In the macro world, building a robot is straightforward: you connect motors to joints and follow the laws of physics. But at the nanoscale—where machines are a billion times smaller—how to build a robot? Scientists are now engineering DNA to perform complex tasks at the nanoscale, building machines that move, grip, and even process information. In a new review published in SmartBot, Professor Lifeng Zhou of Peking University, along with Academician Jian S. Dai from Southern University of Science and Technology, takes us through the cutting-edge world of DNA nanorobots and explores the transition from static DNA structures to dynamic, programmable machines.