Researchers at Istituto Italiano di Tecnologia (IIT-Italian Institute of Technology) have developed an innovative microscopy technique capable of improving the observation of living cells. The study, published in the journal Optics Letters, paves the way for a more in-depth analysis of numerous biological processes without the need for contrast agents. The next step will be to enhance this technique using artificial intelligence, opening the door to a new generation of optical microscopy methods capable of combining direct imaging with innovative molecular information.

Osaka Metropolitan University researchers have developed a polymerization technology that enables the synthesis of degradable polymer capsules in aqueous solvents without any initiators or catalysts by irradiating light-reactive monomers derived from natural products.

TU Graz is launching the COMET project AutoForst for digitalisation and automation of the forestry value chain. The research project has a budget of 6 million euros and is being implemented in collaboration with three other universities and more than 20 industrial partners.

This study presents a transfer learning–based method for predicting train-induced environmental vibration. The method applies data fusion to combine physics-based numerical simulations and limited measurement data within a neural network. It reduces the heavy reliance of conventional machine learning–based models on scarce and costly field measurements while achieving improved prediction accuracy.

Light-emitting semiconductors are used throughout everyday life in TVs, smartphones, and lighting. However, many technical barriers remain in developing environmentally friendly semiconductor materials. In particular, nanoscale semiconductors that are tens of thousands of times smaller than the width of a human hair (about 100,000 nanometers) are theoretically capable of emitting bright light, yet in practice have suffered from extremely weak emission. KAIST researchers have now developed a new surface-control technology that overcomes this limitation.

Data from a major U.S. clinical trial from the Alliance for Clinical Trials in Oncology has uncovered a genetic factor that may inform how to optimize the dosing of abiraterone, a widely used hormone treatment for advanced prostate cancer. Published in Clinical and Translational Science, this secondary analysis of Alliance A032201 could lead to more personalized treatments for patients.

Using advanced first-principles simulations, a team led by Prof. Maryam Ghazisaeidi at The Ohio State University and Prof. Giulia Galli at the University of Chicago Pritzker School of Molecular Engineering (UChicago PME) and Chemistry Department demonstrated that nitrogen-vacancy (NV) centers in diamond, a leading solid-state qubit platform, can be attracted to dislocations and retain — and in some cases improve — their quantum properties when positioned near these line defects.