ArticleScientific reports2015
Multi-dimensional TOF-SIMS analysis for effective profiling of disease-related ions from the tissue surface.
Article in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 19 citations in OpenAlex.
- Composition of Human Meibomian Gland Secretions: Insights from TOF-SIMS Analysis.International journal of molecular sciences · 2026Article
- Machine Learning for Individual EV Classification Based on Highly Sensitive Multiplexed Mass Spectrometry Measurements.Journal of the American Society for Mass Spectrometry · 2026Article
- Multimodal Ion Beam Imaging to Correlate Elements and Metabolites at the Micron Scale Using Water Cluster Secondary Ion Mass Spectrometry and MeV Ion Beam Analysis.Analytical chemistry · 2025Article
- PCA, PC-CVA, and Random Forest of GCIB-SIMS Data for the Elucidation of Bacterial Envelope Differences in Antibiotic Resistance Research.Analytical chemistry · 2024Article
- Screening of important metabolites and KRAS genotypes in colon cancer using secondary ion mass spectrometry.Bioengineering & translational medicine · 2021Article
- Biological tissue sample preparation for time-of-flight secondary ion mass spectrometry (ToF-SIMS) imaging.Nano convergence · 2018Review
- The Chemistry of Plant-Microbe Interactions in the Rhizosphere and the Potential for Metabolomics to Reveal Signaling Related to Defense Priming and Induced Systemic Resistance.Frontiers in plant science · 2018Review
- An unsupervised MVA method to compare specific regions in human breast tumor tissue samples using ToF-SIMS.The Analyst · 2016Article
Corrections and comments
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Authors and funding
10 authors at 6 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Time-of-flight secondary ion mass spectrometry (TOF-SIMS) emerges as a promising tool to identify the ions (small molecules) indicative of disease states from the surface of patient tissues. In TOF-SIMS analysis, an enhanced ionization of surface molecules is critical to increase the number of detected ions. Several methods have been developed to enhance ionization capability. However, how these methods improve identification of disease-related ions has not been systematically explored. Here, we present a multi-dimensional SIMS (MD-SIMS) that combines conventional TOF-SIMS and metal-assisted SIMS (MetA-SIMS). Using this approach, we analyzed cancer and adjacent normal tissues first by TOF-SIMS and subsequently by MetA-SIMS. In total, TOF- and MetA-SIMS detected 632 and 959 ions, respectively. Among them, 426 were commonly detected by both methods, while 206 and 533 were detected uniquely by TOF- and MetA-SIMS, respectively. Of the 426 commonly detected ions, 250 increased in their intensities by MetA-SIMS, whereas 176 decreased. The integrated analysis of the ions detected by the two methods resulted in an increased number of discriminatory ions leading to an enhanced separation between cancer and normal tissues. Therefore, the results show that MD-SIMS can be a useful approach to provide a comprehensive list of discriminatory ions indicative of disease states.
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