![](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjp1WMfAyKkoGFLFmoXRDE7FhRvL5MzkVuBUzbh90445nSkAkuYA9ld4cOaLoeVaggVzparVIpGenI2YkX2s7pDZliH3Tv4TjEhU4lLWqfaEQ57NQ5_lbkGNv5MSKDYKMx6NEmA2i1S850/s1600/cell-3DSIMS.jpg)
Sebastiaan and Mischa recently published a
communication titled ‘Multivariate analysis of 3D ToF-SIMS images: method validation and
application to cultured neuronal networks’ in
Analyst with Christopher
Parmenter, David Scurr and Noah Russell as their co-authors. They 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. The method
readily p
rovides access to sample component information and significantly
improves the images’ signal-to-noise ratio (SNR).