Multi-omics AI model boosts preterm birth prediction accuracy to nearly 90%
Peer-Reviewed Publication
Updates every hour. Last Updated: 14-Dec-2025 20:11 ET (15-Dec-2025 01:11 GMT/UTC)
A recent study developed a highly accurate risk prediction framework for preterm birth (PTB) that could broaden the potential of AI-driven multi-omics applications in precision obstetrics and biomedical research.
The model, deeply integrating genomics, transcriptomics, and large language models (LLMs) for the first time for PTB risk prediction, has shown its effectiveness and clinical application prospects.
The research was conducted by a collaborative team led by BGI Genomics, together with Professor Huang Hefeng's team, Shenzhen Longgang Maternal and Child Health Hospital, Fujian Maternity and Child Health Hospital, and OxTium Technology. The research was published in npj Digital Medicine on August 20th.
Researchers at The University of Osaka and collaborating institutions have developed a cryo-optical microscopy technique that rapidly freezes live cells with millisecond precision during optical imaging. This enables detailed quantitative imaging of fast cellular events via optical microscopy techniques, including super-resolution fluorescence and Raman microscopy. With near-instant immobilization, a single time point in the cells can then be visualized with multiple imaging techniques, providing new insights across cell biology, biophysics, and medical research.
A study on calcium bioavailability by researchers with the Arkansas Agricultural Experiment Station show that two calcium availability tests — a classic approach and a newer, speedier test — offer reliable results that can help poultry producers optimize calcium digestibility.
A new article in Veterinary Pathology introduces a 9-point checklist designed to improve the reporting quality of studies that use artificial intelligence (AI)-based automated image analysis (AIA). As AI tools become more widely used in pathology-based research, concerns have emerged about the reproducibility and transparency of published findings.
Fat metabolism in Caenorhabditis elegans is commonly studied, but linking fat molecules to specific body structures has remained difficult. Now, researchers have developed a microfluidics-based method that preserves internal anatomy while preparing worm sections for imaging. Using mass spectrometry imaging and fat-specific staining, they visualized the spatial distribution of lipids across organs like the intestine and embryos. This technique also enables 3D reconstruction, revealing how fat molecules are organized within individual worms in remarkable detail.