10 developed faster algorithms that allowed PCA to be performed on large 2D data sets. 9 on a relatively small 3D ToF-SIMS image with a size of 256 × 256 × 10 pixels. 5 As a result, up until now the only published application of PCA on a 3D ToF-SIMS dataset was reported by Fletcher et al. 8 While PCA already proved useful for 2D ToF-SIMS image analysis, 3D ToF-SIMS data sets are typically very large and unsuitable for MVA using the processing power of standard desk top computers. With these limitations in mind, powerful data analysis is of the essence, which is why the SIMS community has embraced multivariate analysis (MVA) methods such as PCA. Finally, biological samples can show curvature and surface topography to the extent, where they affect the secondary ion yield. The compounds of interest also usually generate high-mass species, which have a poor signal-to-noise ratio. At the same time, cellular features are relatively small (sub-micrometer range) compared to current ToF-SIMS lateral resolution limits (commonly in the μm range although sub-μm is possible). Because of their inherent complexity and the close chemical similarities of most of the compounds of interest (proteins, lipids and carbohydrates), biological samples require a high mass resolution. ![]() 7 The analysis of biological samples is particularly affected by these limitations. 6 There are also complications involving the secondary ion yield, when the sample material has a curvature or a surface topography in excess of several tens of μm. Additionally, the ion images of high-mass molecular species often have a poor signal-to-noise ratio due to the low ion count per pixel. The low duty cycle of the pulsed ion beam leads to long depth profiling experiments, which frequently causes samples to be analysed well below the static limit as well, in order to save time. Analysis in the static regime limits the signal-to-noise ratio as no more than 1% of the surface can be bombarded with primary ions in order to avoid hitting sites damaged by the analysis beam, which means only a very small fraction of the sample is used for analysis. 5 Chief among these is the intrinsic trade-off between high mass resolution and high spatial resolution. 2 In particular, the research on 3D ToF-SIMS imaging of single cells has progressed to the point where the intracellular uptake and location of non-native compounds such as bromodeoxyuridine 3 and amiodarone 4 can be imaged.ĭespite the increasing capabilities of ToF-SIMS instruments, typical ToF-SIMS measurements have a number of fundamental limitations that make data acquisition and interpretation challenging. The technique has proven its ability to characterise surfaces and coatings of inorganic and organic materials, 1 and is increasingly used for pharmaceutical applications. Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS) is capable of generating 3D chemical-composition images by combining label-free, 2D molecular imaging with depth profiling via ion beam sputtering. The method readily provides access to sample component information and significantly improves the images’ signal-to-noise ratio (SNR). ![]() Here, we demonstrate that by using a training set approach principal components analysis (PCA) can be performed on large 3D ToF-SIMS images of neuronal cell cultures. Advanced data analysis tools are crucial for the application of ToF-SIMS analysis to biological samples.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |