Label-free multimodal optical biopsy reveals biomolecular and morphological features of diabetic kidney tissue in 2D and 3D
Anthony A. Fung,
Zhi Li,
Craig Boote,
Petar Markov,
Joseph P. Gaut,
Sanjay Jain () and
Lingyan Shi ()
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Anthony A. Fung: University of California San Diego
Zhi Li: University of California San Diego
Craig Boote: Cardiff University
Petar Markov: EMBL c/o DESY
Joseph P. Gaut: Washington University School of Medicine, Department of Pathology and Immunology
Sanjay Jain: Washington University in St. Louis
Lingyan Shi: University of California San Diego
Nature Communications, 2025, vol. 16, issue 1, 1-13
Abstract:
Abstract Kidney disease, the ninth leading cause of death in the United States, suffers from poor diagnostic efficiency (10%). Traditional biopsies use molecular reagents to enhance diagnostic power but are limited by overlapping spatial and chromatic signals, product quality variability, and additional processing. To address these challenges without disrupting routine diagnostics, we implement label-free imaging modalities—stimulated Raman scattering (SRS), second harmonic generation (SHG), and two-photon fluorescence (TPF)—within a single setup. We identify morphological, lipidomic, and metabolic biomarkers in control and diabetic kidney samples at subcellular resolution. Label-free Stimulated Raman Histology (SRH) reveals distinct collagen morphology, mesangial-glomerular volumes, lipid saturation, redox status, and lipid-protein concentrations previously unrecognized in kidney diseases. Using the same tissue section enhances diagnostic value without compromising limited tissue. These multimodal biomarkers broadly deepen the understanding of kidney disease progression by integrating lipidomic, fibrotic, and metabolic data.
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-59163-w
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DOI: 10.1038/s41467-025-59163-w
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