ArticleNature methods2026
All-optical multimodal mapping of single-cell-type-specific metabolic activities via REDCAT.
Article in Nature methods, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- 3D multi-omics tumour atlases: from technology to biology and clinical translation.Nature reviews. Cancer · 2026Review
- Integration of imaging-based and sequencing-based spatial omics mapping on the same tissue section via DBiTplus.Nature methods · 2026Article
- A multimodal, all-optical platform for linking cell identity to metabolic function in intact tissues.Nature methods · 2026Article
- A spatial multi-omics atlas of immunosenescence reveals germinal-center B cell dysfunction in human lymph nodes.Cell press blue · 2026Article
- Illuminating aging with multimodal optical metabolic imaging.Science advances · 2026Review
- Spatial instruction of tissue immunity.ImmunoHorizons · 2026Review
- Light and metabolism: label-free optical imaging of metabolic activities in biological systems [Invited].Biomedical optics express · 2025Review
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18 authors.
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Abstract
Metabolism is fundamental to cell function, yet its activities vary across tissue environments. Resolving these processes in situ at single-cell resolution is crucial for understanding physiology in health and disease. However, existing methods lack biochemical specificity or direct linkage to cell identity. Here we report a method, Raman Enhanced Delineation of Cell Atlases in Tissues (REDCAT), an all-optical platform integrating Raman scattering microscopy and high-plex immunofluorescence to co-map metabolism and cell types. REDCAT achieves subcellular profiling of protein, lipid, nuclear metabolites and redox metabolism in human tissues. In lymph nodes, it revealed cell-type-specific metabolic specialization. In lymphoma, REDCAT uncovered profound reprogramming and transitional states during tumor transformation. In the liver, it resolved zonation-dependent metabolic gradients. By linking cell identity to spatial metabolic states, REDCAT provides a framework for studying immunity and cancer, offering a path to deciphering the metabolic basis of disease.
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