ArticleCommunications biology2022
In vivo simultaneous nonlinear absorption Raman and fluorescence (SNARF) imaging of mouse brain cortical structures.
Article in Communications biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.
- Accuracy of Raman spectroscopy in the diagnosis of Alzheimer's disease.Frontiers in psychiatry · 2023Pooled it
- Quantitative Optical Imaging of Oxygen in Brain Vasculature.The journal of physical chemistry. B · 2024Review
- Innovative Approaches for Drug Discovery: Quantifying Drug Distribution and Response with Raman Imaging.Analytical chemistry · 2024Review
- Computational conjugate adaptive optics microscopy for longitudinal through-skull imaging of cortical myelin.Nature communications · 2023Article
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
Abstract
Label-free multiphoton microscopy is a powerful platform for biomedical imaging. Recent advancements have demonstrated the capabilities of transient absorption microscopy (TAM) for label-free quantification of hemoglobin and stimulated Raman scattering (SRS) microscopy for pathological assessment of label-free virtual histochemical staining. We propose the combination of TAM and SRS with two-photon excited fluorescence (TPEF) to characterize, quantify, and compare hemodynamics, vessel structure, cell density, and cell identity in vivo between age groups. In this study, we construct a simultaneous nonlinear absorption, Raman, and fluorescence (SNARF) microscope with the highest reported in vivo imaging depth for SRS and TAM at 250-280 μm to enable these multimodal measurements. Using machine learning, we predict capillary-lining cell identities with 90% accuracy based on nuclear morphology and capillary relationship. The microscope and methodology outlined herein provides an exciting route to study several research topics, including neurovascular coupling, blood-brain barrier, and neurodegenerative diseases.
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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.