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February 11, 2026Critical Reviews in Analytical Chemistry1 citations

Recent Advancement of Matrix-Assisted Laser Desorption Ionization Mass Spectrometry for Biomedical Applications

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YZYanli ZhuJingchu University of TechnologyYWYì WángBGI Group (China)

Key Points

  • The aim is to review advancements in matrix-assisted laser desorption ionization mass spectrometry for biomedical applications.
  • Review of matrix materials used in LDI MS
  • Analysis of synthesis methods and analytical mechanisms
  • Overview of applications in detecting small molecules, analyzing biological macromolecules, and microbial identification
  • Discussion of challenges and future perspectives in LDI MS-based biomedical analysis
  • Improved sensitivity and resolution in LDI MS techniques
  • Effective detection of small molecules and biological macromolecules
  • Enhanced capabilities for microbial identification
  • Highlighting challenges and proposing future research directions in the field.

Abstract

Advances in high sensitivity, resolution, and rapidity have accelerated the application of laser desorption ionization mass spectrometry (LDI MS) to biomedical analysis. This review outlines the recent matrix materials of LDI MS and a comprehensive overview of application in biomedical analysis fields. The review also emphasizes the synthesis methods, analytical mechanisms, and diverse applications of various matrix materials, including organic molecules, carbon-based materials, silicon-based materials, metal particles and oxides, as well as organic frameworks. In the review we summarize the value of LDI MS information in modern biomedical applications such as small molecules detection, biological macromolecules analysis and microbial identification. Finally, it discusses the current challenges in LDI MS-based biomedical analysis and proposes perspectives for further research in this field. It is anticipated that LDI MS will assume a more pivotal role in biomedicine and make substantial contributions to human health.

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Cite This Study

Zhu et al. (2026) studied this question.

synapsesocial.com/papers/698c1c22267fb587c655e567https://doi.org/10.1080/10408347.2026.2623491
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