Cell-free DNA (cfDNA) is an emerging biomarker detectable in various bodily fluids, with promising implications across a wide range of clinical domains. Its minimally invasive nature, short half-life, and ability to reflect tissue-specific genetic an... read more
American journal of medical genetics. Part A
Mar 11, 2026
RASopathies are a group of genetic disorders caused by pathogenic variants in the RAS-mitogen-activated protein kinase (RAS-MAPK) signaling pathway, often presenting with congenital heart defects, craniofacial dysmorphisms, and developmental delays. ... read more
The food industry is witnessing the emergence of specialized protein-based functional ingredients for the use as gelling, thickening, and/or emulsifying agents in various food applications. Different sources of protein including species and cultivars... read more
Artificial Intelligence models pose serious challenges to intensive computing and high-bandwidth communication for conventional electronic circuit-based computing clusters. Silicon photonic technologies, due to their high speed, low latency, large ba... read more
Wildfires are becoming more frequent and severe under the influence of climate change, posing increasing risks to ecosystems, human health, and infrastructure. Accurate spatiotemporal data on wildfire propagation is essential for advancing fire behav... read more
Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality globally, and accurate classification of liver lesions using ultrasound remains challenging. We present SMC-LUD (Samsung Medical Center - Liver Ultrasound Dataset), a publi... read more
We present a first global high-resolution map (30 m x 30 m) of high-altitudinal wetlands in the world's major mountain regions, i.e. the Andes, Rocky Mountains, Alps and High Mountain Asia. To map these wetlands, we employed a supervised classificati... read more
Diagnosing diseases from medical images and reporting them at the paragraph level is a significant challenge for deep learning-based autonomous systems. Existing work primarily focuses on achieving high accuracy, often paying less attention to the co... read more
We introduce CG-Vec, a crystal graph-to-vector framework that replaces iterative message passing with compact, interpretable descriptors coupled to conventional machine learning. Across diverse datasets, CG-Vec matches the accuracy of deep graph netw... read more
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