Uncovering new challenges in bio-analysis with ToF-SIMS

Fletcher, John S.; Henderson, Alex; Biddulph, Gregory X.; Vaidyanathan, Seetharaman; Lockyer, Nicholas P.; Vickerman, John C.

doi:10.1016/j.apsusc.2008.05.253

Cited by 30 publications

(36 citation statements)

References 29 publications

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“…In addition, for TOF SIMS heavier elements, like cesium, are preferred for their higher sputter yield. In particular the use of TOF SIMS in the life sciences requires projectiles heavier than Ga [3]. Unfortunately this goes at the expense of spatial resolution, which can only be reached at present with the Ga-based LMIS FIB.…”

mentioning

confidence: 99%

Low-Energy-Spread Ion Bunches from a Trapped Atomic Gas

et al. 2009

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confidence: 99%

Low-Energy-Spread Ion Bunches from a Trapped Atomic Gas

et al. 2009

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“…The frog egg was very large (approximately 1.2 mm diameter) compared to usual SIMS samples and as such the entire egg was not analyzed. 29,30 However, lipid related species over several hundred Dalton were detected as 10 s of micrometers of material were removed, and, perhaps most importantly, lipid signals not present on the surface of the sample appeared after etching. Figure 3(c) shows a 3D reconstruction of the frog egg data published in Ref.…”

Section: Biological Samplesmentioning

confidence: 99%

“…Reshaping SIMS data based on atomic force microscopy (AFM) data is relatively simple using image processing software assuming the same cell can be imaged with both techniques. 30 Recently, combined SIMS and in vacuum AFM systems have been built that allow correct 3D reconstruction of samples to be performed. 39 This works well for room temperature samples; however, AFM measurements of frozen samples in vacuum is a significant challenge.…”

Section: D Reconstruction Of Tof-sims Datamentioning

confidence: 99%

Latest applications of 3D ToF-SIMS bio-imaging

Fletcher

2015

Biointerphases

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Time-of-flight secondary ion mass spectrometry (ToF-SIMS) is a rapidly developing technique for the characterization of a wide range of materials. Recently, advances in instrumentation and sample preparation approaches have provided the ability to perform 3D molecular imaging experiments. Polyatomic ion beams, such as C60, and gas cluster ion beams, often Arn (n = 500–4000), substantially reduce the subsurface damage accumulation associated with continued bombardment of organic samples with atomic beams. In this review, the capabilities of the technique are discussed and examples of the 3D imaging approach for the analysis of model membrane systems, plant single cell, and tissue samples are presented. Ongoing challenges for 3D ToF-SIMS imaging are also discussed along with recent developments that might offer improved 3D imaging prospects in the near future.

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“…), the analyst is presented with the additional challenges of low ion yields and the lack of molecular specificity of many of the resulting peaks. [1][2][3] Low ion yields are the result of the low ionization efficiencies of ToF-SIMS. Typically less than 1% of the material removed from the surface during the primary ion bombardment is ionized.…”

Section: Introductionmentioning

confidence: 99%

“…1,[3][4][5]8,[18][19][20][21][23][24][25][26] For this work, ToF-SIMS analysts have used a variety of methods to process and understand their data. These include a combination of traditional manual analysis and the application of multivariate analysis (MVA) methods.…”

Section: Introductionmentioning

confidence: 99%

Image and Spectral Processing for ToF-SIMS Analysis of Biological Materials

Graham

Castner

2013

Mass Spectrometry

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Time-of-flight secondary ion mass spectrometry (ToF-SIMS) instruments can rapidly produce large complex data sets. Within each spectrum, there can be hundreds of peaks. A typical 256×256 pixel image contains 65,536 spectra. If this is extended to a 3D image, the number of spectra in a given data set can reach the millions. The challenge becomes how to process these large data sets while taking into account the changes and differences between all the peaks in the spectra. This is particularly challenging for biological materials that all contain the same types of proteins and lipids, just in varying concentrations and spatial distributions. This data analysis challenge is further complicated by the limitations in the ion yield of higher mass, more chemically specific species, and potentially by the processing power of typical computers. Herein we briefly discuss analysis methodologies including univariate analysis, multivariate analysis (MVA) methods, and some of the limitations of ToF-SIMS analysis of biological materials.

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Uncovering new challenges in bio-analysis with ToF-SIMS

Cited by 30 publications

References 29 publications

Low-Energy-Spread Ion Bunches from a Trapped Atomic Gas

Low-Energy-Spread Ion Bunches from a Trapped Atomic Gas

Latest applications of 3D ToF-SIMS bio-imaging

Image and Spectral Processing for ToF-SIMS Analysis of Biological Materials

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