Cargando…
Multivariate Curve Resolution for 2D Solid-State NMR spectra
[Image: see text] We present a processing method, based on the multivariate curve resolution approach (MCR), to denoise 2D solid-state NMR spectra, yielding a substantial S/N ratio increase while preserving the lineshapes and relative signal intensities. These spectral features are particularly impo...
Autores principales: | , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical
Society
2020
|
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7997113/ https://www.ncbi.nlm.nih.gov/pubmed/32069028 http://dx.doi.org/10.1021/acs.analchem.9b05420 |
_version_ | 1783670253539033088 |
---|---|
author | Bruno, Francesco Francischello, Roberto Bellomo, Giovanni Gigli, Lucia Flori, Alessandra Menichetti, Luca Tenori, Leonardo Luchinat, Claudio Ravera, Enrico |
author_facet | Bruno, Francesco Francischello, Roberto Bellomo, Giovanni Gigli, Lucia Flori, Alessandra Menichetti, Luca Tenori, Leonardo Luchinat, Claudio Ravera, Enrico |
author_sort | Bruno, Francesco |
collection | PubMed |
description | [Image: see text] We present a processing method, based on the multivariate curve resolution approach (MCR), to denoise 2D solid-state NMR spectra, yielding a substantial S/N ratio increase while preserving the lineshapes and relative signal intensities. These spectral features are particularly important in the quantification of silicon species, where sensitivity is limited by the low natural abundance of the (29)Si nuclei and by the dilution of the intrinsic protons of silica, but can be of interest also when dealing with other intermediate-to-low receptivity nuclei. This method also offers the possibility of coprocessing multiple 2D spectra that have the signals at the same frequencies but with different intensities (e.g.: as a result of a variation in the mixing time). The processing can be carried out on the time-domain data, thus preserving the possibility of applying further processing to the data. As a demonstration, we have applied Cadzow denoising on the MCR-processed FIDs, achieving a further increase in the S/N ratio and more effective denoising also on the transients at longer indirect evolution times. We have applied the combined denoising on a set of experimental data from a lysozyme–silica composite. |
format | Online Article Text |
id | pubmed-7997113 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | American Chemical
Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-79971132021-03-29 Multivariate Curve Resolution for 2D Solid-State NMR spectra Bruno, Francesco Francischello, Roberto Bellomo, Giovanni Gigli, Lucia Flori, Alessandra Menichetti, Luca Tenori, Leonardo Luchinat, Claudio Ravera, Enrico Anal Chem [Image: see text] We present a processing method, based on the multivariate curve resolution approach (MCR), to denoise 2D solid-state NMR spectra, yielding a substantial S/N ratio increase while preserving the lineshapes and relative signal intensities. These spectral features are particularly important in the quantification of silicon species, where sensitivity is limited by the low natural abundance of the (29)Si nuclei and by the dilution of the intrinsic protons of silica, but can be of interest also when dealing with other intermediate-to-low receptivity nuclei. This method also offers the possibility of coprocessing multiple 2D spectra that have the signals at the same frequencies but with different intensities (e.g.: as a result of a variation in the mixing time). The processing can be carried out on the time-domain data, thus preserving the possibility of applying further processing to the data. As a demonstration, we have applied Cadzow denoising on the MCR-processed FIDs, achieving a further increase in the S/N ratio and more effective denoising also on the transients at longer indirect evolution times. We have applied the combined denoising on a set of experimental data from a lysozyme–silica composite. American Chemical Society 2020-02-18 2020-03-17 /pmc/articles/PMC7997113/ /pubmed/32069028 http://dx.doi.org/10.1021/acs.analchem.9b05420 Text en Permits the broadest form of re-use including for commercial purposes, provided that author attribution and integrity are maintained (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Bruno, Francesco Francischello, Roberto Bellomo, Giovanni Gigli, Lucia Flori, Alessandra Menichetti, Luca Tenori, Leonardo Luchinat, Claudio Ravera, Enrico Multivariate Curve Resolution for 2D Solid-State NMR spectra |
title | Multivariate Curve Resolution for 2D Solid-State NMR
spectra |
title_full | Multivariate Curve Resolution for 2D Solid-State NMR
spectra |
title_fullStr | Multivariate Curve Resolution for 2D Solid-State NMR
spectra |
title_full_unstemmed | Multivariate Curve Resolution for 2D Solid-State NMR
spectra |
title_short | Multivariate Curve Resolution for 2D Solid-State NMR
spectra |
title_sort | multivariate curve resolution for 2d solid-state nmr
spectra |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7997113/ https://www.ncbi.nlm.nih.gov/pubmed/32069028 http://dx.doi.org/10.1021/acs.analchem.9b05420 |
work_keys_str_mv | AT brunofrancesco multivariatecurveresolutionfor2dsolidstatenmrspectra AT francischelloroberto multivariatecurveresolutionfor2dsolidstatenmrspectra AT bellomogiovanni multivariatecurveresolutionfor2dsolidstatenmrspectra AT giglilucia multivariatecurveresolutionfor2dsolidstatenmrspectra AT florialessandra multivariatecurveresolutionfor2dsolidstatenmrspectra AT menichettiluca multivariatecurveresolutionfor2dsolidstatenmrspectra AT tenorileonardo multivariatecurveresolutionfor2dsolidstatenmrspectra AT luchinatclaudio multivariatecurveresolutionfor2dsolidstatenmrspectra AT raveraenrico multivariatecurveresolutionfor2dsolidstatenmrspectra |