PMID- 32233419
OWN - NLM
STAT- PubMed-not-MEDLINE
DCOM- 20200818
LR  - 20230816
IS  - 1520-6882 (Electronic)
IS  - 0003-2700 (Print)
IS  - 0003-2700 (Linking)
VI  - 92
IP  - 9
DP  - 2020 May 5
TI  - ToF-SIMS and Machine Learning for Single-Pixel Molecular Discrimination of an 
      Acrylate Polymer Microarray.
PG  - 6587-6597
LID - 10.1021/acs.analchem.0c00349 [doi]
AB  - Combinatorial approaches to materials discovery offer promising potential for the 
      rapid development of novel polymer systems. Polymer microarrays enable the 
      high-throughput comparison of material physical and chemical properties-such as 
      surface chemistry and properties like cell attachment or protein adsorption-in 
      order to identify correlations that can progress materials development. A 
      challenge for this approach is to accurately discriminate between highly similar 
      polymer chemistries or identify heterogeneities within individual polymer spots. 
      Time-of-flight secondary ion mass spectrometry (ToF-SIMS) offers unique potential 
      in this regard, capable of describing the chemistry associated with the outermost 
      layer of a sample with high spatial resolution and chemical sensitivity. However, 
      this comes at the cost of generating large scale, complex hyperspectral imaging 
      data sets. We have demonstrated previously that machine learning is a powerful 
      tool for interpreting ToF-SIMS images, describing a method for color-tagging the 
      output of a self-organizing map (SOM). This reduces the entire hyperspectral data 
      set to a single reconstructed color similarity map, in which the spectral 
      similarity between pixels is represented by color similarity in the map. Here, we 
      apply the same methodology to a ToF-SIMS image of a printed polymer microarray 
      for the first time. We report complete, single-pixel molecular discrimination of 
      the 70 unique homopolymer spots on the array while also identifying intraspot 
      heterogeneities thought to be related to intermixing of the polymer and the pHEMA 
      coating. In this way, we show that the SOM can identify layers of similarity and 
      clusters in the data, both with respect to polymer backbone structures and their 
      individual side groups. Finally, we relate the output of the SOM analysis with 
      fluorescence data from polymer-protein adsorption studies, highlighting how 
      polymer performance can be visualized within the context of the global topology 
      of the data set.
FAU - Gardner, Wil
AU  - Gardner W
AD  - Centre for Materials and Surface Science and Department of Chemistry and Physics, 
      La Trobe University, Melbourne, Victoria 3086, Australia.
AD  - La Trobe Institute for Molecular Sciences, La Trobe University, Melbourne, 
      Victoria 3086, Australia.
AD  - CSIRO Manufacturing, Clayton, Victoria 3168, Australia.
FAU - Hook, Andrew L
AU  - Hook AL
AD  - Advanced Materials and Healthcare Technologies, School of Pharmacy, University of 
      Nottingham, Nottingham NG7 2RD, U.K.
FAU - Alexander, Morgan R
AU  - Alexander MR
AD  - Advanced Materials and Healthcare Technologies, School of Pharmacy, University of 
      Nottingham, Nottingham NG7 2RD, U.K.
FAU - Ballabio, Davide
AU  - Ballabio D
AUID- ORCID: 0000-0002-5748-147X
AD  - Milano Chemometrics and QSAR Research Group, Department of Earth and 
      Environmental Sciences, University of Milano-Bicocca, P.zza della Scienza 1, 
      20126 Milano, Italy.
FAU - Cutts, Suzanne M
AU  - Cutts SM
AUID- ORCID: 0000-0002-6055-0405
AD  - La Trobe Institute for Molecular Sciences, La Trobe University, Melbourne, 
      Victoria 3086, Australia.
FAU - Muir, Benjamin W
AU  - Muir BW
AUID- ORCID: 0000-0002-8858-3217
AD  - CSIRO Manufacturing, Clayton, Victoria 3168, Australia.
FAU - Pigram, Paul J
AU  - Pigram PJ
AUID- ORCID: 0000-0002-7972-492X
AD  - Centre for Materials and Surface Science and Department of Chemistry and Physics, 
      La Trobe University, Melbourne, Victoria 3086, Australia.
LA  - eng
GR  - WT_/Wellcome Trust/United Kingdom
GR  - 103882/WT_/Wellcome Trust/United Kingdom
GR  - 103884/WT_/Wellcome Trust/United Kingdom
GR  - 103882/WT_/Wellcome Trust/United Kingdom
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20200413
PL  - United States
TA  - Anal Chem
JT  - Analytical chemistry
JID - 0370536
SB  - IM
PMC - PMC7611022
MID - EMS127622
COIS- Conflicts of interest The authors declare no conflicts of interest.
EDAT- 2020/04/03 06:00
MHDA- 2020/04/03 06:01
PMCR- 2021/06/21
CRDT- 2020/04/03 06:00
PHST- 2020/04/03 06:00 [pubmed]
PHST- 2020/04/03 06:01 [medline]
PHST- 2020/04/03 06:00 [entrez]
PHST- 2021/06/21 00:00 [pmc-release]
AID - 10.1021/acs.analchem.0c00349 [doi]
PST - ppublish
SO  - Anal Chem. 2020 May 5;92(9):6587-6597. doi: 10.1021/acs.analchem.0c00349. Epub 
      2020 Apr 13.