ArticleOptics letters2020
K-means clustering of coherent Raman spectra from extracellular vesicles visualized by label-free multiphoton imaging.
Article in Optics letters, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed, 16 citations in OpenAlex.
- Research on a rapid and accurate diagnosis platform for liver fibrosis based on machine learning-assisted SERS technology.Biomedical optics express · 2026Article
- Machine learning for extracellular vesicles enables diagnostic and therapeutic nanobiotechnology.Journal of nanobiotechnology · 2026Review
- Advanced Multipurpose Spectroscopic Nanobio-Device for Concurrent Lab-on-a-Chip Label-Free Separation and Detection of Extracellular Vesicles as Key-Biomarkers for Point-of-Care Cardiovascular Disease Diagnostics.Advanced healthcare materials · 2025Article
- Machine learning empowered coherent Raman imaging and analysis for biomedical applications.Communications engineering · 2025Review
- Weakly Supervised Identification and Localization of Drug Fingerprints Based on Label-Free Hyperspectral CARS Microscopy.Analytical chemistry · 2023Article
- A Review of Labeling Approaches Used in Small Extracellular Vesicles Tracing and Imaging.International journal of nanomedicine · 2023Review
- Label-free optical redox ratio from urinary extracellular vesicles as a screening biomarker for bladder cancer.American journal of cancer research · 2022Article
- Label-free characterization of single extracellular vesicles using two-photon fluorescence lifetime imaging microscopy of NAD(P)H.Scientific reports · 2021Article
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
Extracellular vesicles (EVs) have emerged as potential biomarkers in cancer research and for clinical diagnosis. Little is known, however, about their spatial distributions in tissue and the different subpopulations that may exist. Here we report the use of label-free nonlinear optical imaging techniques to provide spatially resolved chemical information of EVs within untreated tissues. A multimodal nonlinear optical imaging system incorporating multiphoton autofluorescence and hyperspectral coherent anti-Stokes Raman scattering (CARS) imaging was built to visualize the spatial tissue distribution and probe the spectra of EVs. K-means clustering is performed on the CARS spectra from EVs in rat mammary tissues and human breast tumor tissue to reveal both the spatial distribution of EV clusters and their different chemical signatures. Correlations are identified between EV clusters and metabolic information.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.