ReviewACS nano medicine2026
Visualizing Metabolism: Lipid-Based Raman Nanoreporters as an Enabling Platform for Metabolic Imaging and Precision Medicine.
Review in ACS nano medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
6 authors.
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Abstract
Lipid-based Raman reporters represent a promising but still developing class of metabolic sensors. This review reports lipid nanoparticles and lipid conjugated inorganic nanoparticles as Raman-active systems capable of decoding cellular metabolism with spatial and chemical specificity. It is demonstrated how bioorthogonal reporters operating in the Raman-silent window were incorporated across various modalities such as spontaneous Raman, coherent anti-Stokes Raman spectroscopy, stimulated Raman scattering, surface enhanced Raman spectroscopy, spatially offset Raman spectroscopy, and tip-enhanced Raman spectroscopy. Furthermore, strategies are presented for achieving multiplexed and barcoded Raman imaging using isotopic encoding and other molecular tags. The hybrid integration of Raman with other imaging modulation such as photoacoustic, magnetic resonance imaging, and positron emission tomography is evaluated to overcome inherent limitations in penetration depth and sensitivity. Additionally, the application of Raman reporters is characterized into
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