Peer-reviewed study confirming strong predictive performance of patient-specific lung digital twins, validated against clinical imaging data

Whole-lung, physics-based modeling enables locally resolved prediction of drug deposition, addressing a central challenge in inhaled drug development

Validated lung digital twin technology forms the foundation of Ebenbuild’s platform applications, supporting translational research today and regulated clinical use in the future

Previously known as Food and Ecological Systems Modelling Journal (FESMJ), the now rebranded journal, Agricultural and Environmental Modelling (AEM), expands its scope and deepens its Open Science commitment, offering a publishing platform to cover the full lifecycle of agricultural, food systems, and environmental modelling research.

A team of scientists from Nanyang Technological University, Singapore (NTU Singapore) has developed a new biochip that, when paired with Artificial Intelligence (AI), can detect quickly and accurately extremely small amounts of microRNAs, which are tiny genetic markers linked to diseases such as heart disease.

 

Published in the scientific journal Advanced Materials, the new biosensing platform combines a specially designed nanophotonic chip with AI-automated image analysis.

 

With a tiny drop of blood loaded into the chip, it can rapidly detect multiple microRNA biomarkers. With its integrated AI imaging function, thousands of microRNA signals can be imaged and analysed in a single snapshot.

 

Compared with the current gold standard of detecting microRNA – PCR (polymerase chain reaction) detects tiny amounts of genetic material by copying them many times – the new device can cut detection time from hours to 20 minutes.

SWIFTT is a forest management platform that combines the rich Copernicus Sentinel satellite data and powerful machine learning models. It helps foresters identify changes in tree health, map dieback in their forests and coordinate sanitary cuts, map windthrow damage, and identify areas at high risk of and damaged by wildfires.

Researchers at China Agricultural University have developed an ovarian follicle-based angiogenesis microphysiological system, or OF-AMPS, for rapid and quantitative screening of anti-angiogenic compounds. The platform uses growing ovarian follicles as natural angiogenic microphysiological units and forms complex 3D vascular networks within 24 hours without exogenous VEGF. In a screen of 406 small molecules, OF-AMPS identified compounds with selective anti-angiogenic activity, predicted in vivo efficacy, and helped prioritize Ki8751, which later suppressed tumor growth in a human xenograft model.

A new review examines how insertion and deletion (indel) errors disrupt data synchronization in modern communication systems. By surveying both traditional and Deep Learning-driven approaches, the study provides a comprehensive overview of existing solutions and outlines future directions for more reliable communication in 6G, satellite networks, and beyond.

Researchers have succeeded in improving mobility efficiency by having the snake-like robot move using an “undulating motion” on uneven terrain and a “rolling motion” on level ground.

Researchers are investigating how 3D printers could achieve unprecedented levels of precision when creating batteries, opening the door for new innovations.