Multivariate ToF-SIMS image analysis of polymer microarrays and protein adsorption
The complexity of hyperspectral time of flight secondary ion mass spectrometry (ToF-SIMS) datasets makes their subsequent analysis and interpretation challenging, and is often an impasse to the identification of trends and differences within large sample-sets. The application of multivariate data an...
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American Vacuum Society
2015
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| Online Access: | https://eprints.nottingham.ac.uk/32452/ |
| _version_ | 1848794409980657664 |
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| author | Hook, Andrew L. Williams, Philip M. Alexander, Morgan R. Scurr, David J. |
| author_facet | Hook, Andrew L. Williams, Philip M. Alexander, Morgan R. Scurr, David J. |
| author_sort | Hook, Andrew L. |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | The complexity of hyperspectral time of flight secondary ion mass spectrometry (ToF-SIMS) datasets makes their subsequent analysis and interpretation challenging, and is often an impasse to the identification of trends and differences within large sample-sets. The application of multivariate data analysis has become a routine method to successfully deconvolute and analyze objectively these datasets. The advent of high-resolution large area ToF-SIMS imaging capability has enlarged further the data handling challenges. In this work, a modified multivariate curve resolution image analysis of a polymer microarray containing 70 different poly(meth)acrylate type spots (over a 9.2 × 9.2 mm area) is presented. This analysis distinguished key differences within the polymer library such as the differentiation between acrylate and methacrylate polymers and variance specific to side groups. Partial least squares (PLS) regression analysis was performed to identify correlations between the ToF-SIMS surface chemistry and the protein adsorption. PLS analysis identified a number of chemical moieties correlating with high or low protein adsorption, including ions derived from the polymer backbone and polyethylene glycol side-groups. The retrospective validation of the findings from the PLS analysis was also performed using the secondary ion images for those ions found to significantly contribute to high or low protein adsorption. |
| first_indexed | 2025-11-14T19:15:45Z |
| format | Article |
| id | nottingham-32452 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:15:45Z |
| publishDate | 2015 |
| publisher | American Vacuum Society |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-324522020-05-04T17:02:59Z https://eprints.nottingham.ac.uk/32452/ Multivariate ToF-SIMS image analysis of polymer microarrays and protein adsorption Hook, Andrew L. Williams, Philip M. Alexander, Morgan R. Scurr, David J. The complexity of hyperspectral time of flight secondary ion mass spectrometry (ToF-SIMS) datasets makes their subsequent analysis and interpretation challenging, and is often an impasse to the identification of trends and differences within large sample-sets. The application of multivariate data analysis has become a routine method to successfully deconvolute and analyze objectively these datasets. The advent of high-resolution large area ToF-SIMS imaging capability has enlarged further the data handling challenges. In this work, a modified multivariate curve resolution image analysis of a polymer microarray containing 70 different poly(meth)acrylate type spots (over a 9.2 × 9.2 mm area) is presented. This analysis distinguished key differences within the polymer library such as the differentiation between acrylate and methacrylate polymers and variance specific to side groups. Partial least squares (PLS) regression analysis was performed to identify correlations between the ToF-SIMS surface chemistry and the protein adsorption. PLS analysis identified a number of chemical moieties correlating with high or low protein adsorption, including ions derived from the polymer backbone and polyethylene glycol side-groups. The retrospective validation of the findings from the PLS analysis was also performed using the secondary ion images for those ions found to significantly contribute to high or low protein adsorption. American Vacuum Society 2015-02-06 Article PeerReviewed Hook, Andrew L., Williams, Philip M., Alexander, Morgan R. and Scurr, David J. (2015) Multivariate ToF-SIMS image analysis of polymer microarrays and protein adsorption. Biointerphases, 10 . 019005/1-019005/8. ISSN 1559-4106 Least-squares regression; Ion mass spectrometry; Embryonic stem cells; Surfaces; Adhesion; Systems; Growth; Biomaterials; Formulations; Wettability http://scitation.aip.org/content/avs/journal/bip/10/1/10.1116/1.4906484 doi:10.1116/1.4906484 doi:10.1116/1.4906484 |
| spellingShingle | Least-squares regression; Ion mass spectrometry; Embryonic stem cells; Surfaces; Adhesion; Systems; Growth; Biomaterials; Formulations; Wettability Hook, Andrew L. Williams, Philip M. Alexander, Morgan R. Scurr, David J. Multivariate ToF-SIMS image analysis of polymer microarrays and protein adsorption |
| title | Multivariate ToF-SIMS image analysis of polymer microarrays and protein adsorption |
| title_full | Multivariate ToF-SIMS image analysis of polymer microarrays and protein adsorption |
| title_fullStr | Multivariate ToF-SIMS image analysis of polymer microarrays and protein adsorption |
| title_full_unstemmed | Multivariate ToF-SIMS image analysis of polymer microarrays and protein adsorption |
| title_short | Multivariate ToF-SIMS image analysis of polymer microarrays and protein adsorption |
| title_sort | multivariate tof-sims image analysis of polymer microarrays and protein adsorption |
| topic | Least-squares regression; Ion mass spectrometry; Embryonic stem cells; Surfaces; Adhesion; Systems; Growth; Biomaterials; Formulations; Wettability |
| url | https://eprints.nottingham.ac.uk/32452/ https://eprints.nottingham.ac.uk/32452/ https://eprints.nottingham.ac.uk/32452/ |