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http://dx.doi.org/10.1186/s12967-025-06601-4 | DOI Listing |
Discov Nano
September 2025
Department of Rehabilitation Medicine, Rehabilitation Medical Center, Key Laboratory of Rehabilitation Medicine in Sichuan Province, West China Hospital, Sichuan University, Chengdu, 610041, People's Republic of China.
Immunoelectron Microscopy (IEM) is a technique that combines specific immunolabeling with high-resolution electron microscopic imaging to achieve precise spatial localization of biomolecules at the subcellular scale (< 10 nm) by using high-electron-density markers such as colloidal gold and quantum dots. As a core tool for analyzing the distribution of proteins, organelle interactions, and localization of disease pathology markers, it has irreplaceable value, especially in synapse research, pathogen-host interaction mechanism, and tumor microenvironment analysis. According to the differences in labeling sequence and sample processing, the IEM technology system can be divided into two categories: the first is pre-embedding labeling, which optimizes the labeling efficiency through the pre-exposure of antigenic epitopes and is especially suitable for the detection of low-abundance and sensitive antigens; the second is post-embedding labeling, which relies on the low-temperature resin embedding (e.
View Article and Find Full Text PDFRadiology
September 2025
Department of Biomedical Informatics, Harvard Medical School, 10 Shattuck St, Boston, MA 02115.
Despite the rapid growth of Food and Drug Administration-cleared artificial intelligence (AI)- and machine learning-enabled medical devices for use in radiology, current tools remain limited in scope, often focusing on narrow tasks and lacking the ability to comprehensively assist radiologists. These narrow AI solutions face limitations in financial sustainability, operational efficiency, and clinical utility, hindering widespread adoption and constraining their long-term value in radiology practice. Recent advances in generative and multimodal AI have expanded the scope of image interpretation, prompting discussions on the development of generalist medical AI.
View Article and Find Full Text PDFInt J Nanomedicine
September 2025
Department of Orthopedics, Honghui Hospital, Xi'an Jiaotong University, Xi'an, Shaanxi, People's Republic of China.
Peptide-based fluorescent probes have found widespread applications in biomedical research, including bio-imaging, disease diagnosis, drug discovery, and image-guided surgery. Their favorable properties-such as small molecular size, low toxicity, minimal immunogenicity, and high targeting specificity-have contributed to their growing utility in both basic research and translational medicine. This review provides a comprehensive overview of recent advances in peptide-based fluorescent probes, emphasizing design strategies, biological targets, and diverse functional applications.
View Article and Find Full Text PDFJ Obes Metab Syndr
September 2025
Department of Medicine, College of Medicine, Kyung Hee University, Seoul, Korea.
Although the prevalence of obesity is increasing worldwide, related treatment remains a complex challenge that requires multidimensional approaches. Recent advancements in artificial intelligence (AI) have led to the development of multimodal methods capable of integrating diverse types of data. These AI approaches utilize both multimodal data integration and multidimensional feature representations, enabling personalized, data-driven strategies for obesity management.
View Article and Find Full Text PDFNurs Sci Q
October 2025
DePaul University, Chicago, IL, USA.
The authors describe the methodological strategies used to effectively recruit a diverse sample of nurses in a qualitative study. Adequate representation of diverse populations is necessary to advance science and health equity. A multimodal research approach (research team composition, flyers, social media, and purposive sampling) was used.
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