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Related Experiment Video

Updated: Jun 10, 2026

Biobanking of Human Aqueous and Vitreous Liquid Biopsies for Molecular Analyses
14:54

Biobanking of Human Aqueous and Vitreous Liquid Biopsies for Molecular Analyses

Published on: September 11, 2023

Robust Heterojunction Nanoconstructs Enable Precise Decipherment of Aqueous Humor Metabolic Profiles in Multiple

Hairu Lin1, Yuxiang Hu2, Jia Qi1

  • 1Center for Medical Research and Innovation, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, Department of Chemistry, Institutes of Biomedical Sciences, Fudan University, Shanghai 201399, China.

Analytical Chemistry
|June 9, 2026
PubMed
Summary

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Investigative ophthalmology & visual science·2026

Researchers developed a cost-effective nanomaterial for aqueous humor analysis, enabling accurate detection of retinal diseases (RD) like AMD, DR, and RVO using machine learning. This diagnostic tool shows promise for early vision impairment detection.

Area of Science:

  • Ophthalmology
  • Biomedical Engineering
  • Analytical Chemistry

Background:

  • Retinal diseases (RD) cause irreversible vision loss and require advanced diagnostic methods.
  • Aqueous humor metabolic analysis offers a promising avenue for investigating ocular conditions.
  • Current diagnostic tools for RD often fall short, necessitating innovative approaches.

Purpose of the Study:

  • To develop a cost-effective, high-performance nanoconstruct for analyzing aqueous humor.
  • To utilize mass spectrometry and machine learning for metabolic profiling of RD patients.
  • To identify specific metabolic signatures for diagnosing and differentiating RD.

Main Methods:

  • Synthesis of a novel heterojunction nanoconstruct (MZ-D) with high reproducibility.

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Last Updated: Jun 10, 2026

Biobanking of Human Aqueous and Vitreous Liquid Biopsies for Molecular Analyses
14:54

Biobanking of Human Aqueous and Vitreous Liquid Biopsies for Molecular Analyses

Published on: September 11, 2023

Ex Vivo OCT-Based Multimodal Imaging of Human Donor Eyes for Research into Age-Related Macular Degeneration
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Ex Vivo OCT-Based Multimodal Imaging of Human Donor Eyes for Research into Age-Related Macular Degeneration

Published on: May 26, 2023

  • High-throughput mass spectrometry for aqueous humor metabolic profiling.
  • Machine learning algorithms for analyzing metabolic data and classifying ocular conditions.

    • Main Results:

    • The MZ-D nanoconstruct achieved 92.87% accuracy in distinguishing RD from cataract (CA).
    • Metabolic profiling accurately differentiated between age-related macular degeneration (AMD), diabetic retinopathy (DR), and retinal vein occlusion (RVO) with 86.59% accuracy.
    • Retinaldehyde and 2-hydroxylauroylcarnitine identified as key metabolic biomarkers for RD.

    Conclusions:

    • Nanomaterial-enabled analysis of aqueous humor metabolites can accurately diagnose and differentiate RD.
    • The developed diagnostic approach shows potential for clinical translation in ophthalmology.
    • This method offers a cost-effective and high-performance solution for ocular metabolic diagnostics.