Singular spectrum analysis for an automated solvent artifact removal and baseline correction of 1D NMR spectra

Sanctis, Silvia De; Malloni, Wilhelm M.; Kremer, Werner; Tomé, Ana Maria; Lang, Elmar; Neidig, Klaus-Peter; Kalbitzer, Hans Robert

doi:10.1016/j.jmr.2011.03.001

Cited by 10 publications

(4 citation statements)

References 20 publications

(29 reference statements)

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“…1). However, it is well know the disturbances that solvent suppression schemes promotes within vicinal frequencies and the increment of these artefacts when several signals are simultaneously suppressed [16]. Triple suppression Figure 5.…”

Section: Resultsmentioning

confidence: 99%

The “Wine-T₁” NMR experiment for novel wine-metabolome fingerprinting with nuclear-spin relaxation

et al. 2019

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In agreement with the draft resolution OENO-SCMA 17-618 at step 5 “Quantitation of glucose, malic acid, acetic acid, fumaric acid, shikimic acid and sorbic acid in wine using proton nuclear magnetic resonance spectroscopy (1H NMR)” said technique has been recently accepted within the OIV chair as a primary quantitative analytical technique for beverage analysis such as wine. However, poor chemical shift dispersion in 1H NMR spectra severely penalizes quantification within overlapped or crowded regions. To outflank said penalization and quantify metabolites in signal overcrowding situations, the novel “Wine-T1” experiment is proposed. The novel scheme comprises the addition of a second dimension, wherein the proton spin-lattice relaxation times (T1-{1H}) of each metabolite's spin-system is correlated to a chemical-shift dimension. The new experiment includes a water and ethanol signal pre-saturation module, prior to the T1 saturation-inversion recovery dimension in order to maximize signal-to-noise ratio of wine metabolome NMR spectra. “Wine-T1” pulse sequence can be adapted to all commercial spectrometers (Bruker, Varian/Agilent, Jeol) and with acquisition times in the order of minutes, it should be considered as a fast repetition method to produce a robust metabolome fingerprint that has not been described before, to the best of our knowledge.

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Section: Resultsmentioning

confidence: 99%

The “Wine-T₁” NMR experiment for novel wine-metabolome fingerprinting with nuclear-spin relaxation

et al. 2019

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“…The software suites XWINNMR 2.6 and TOPSPIN 3.1 were used during the acquisition and the processing stages of the NMR data. SSA for solvent suppression and the ALS for baseline correction implemented in the program AUREMOL were applied to all spectra before performing the automated assignment to improve the spectral quality and reveal some resonances superposed by the solvent signal (Malloni et al, 2010;De Sanctis et al, 2011). The TALOS+ program (Corneliescu et al, 1999) was used to predict the secondary structure from the detected chemical shifts of C a , C b , C 0 , H a , and H N atoms yielding 4 and c dihedral angle restraints.…”

Section: Nmr Data Evaluationmentioning

confidence: 99%

PSCD Domains of Pleuralin-1 from the Diatom Cylindrotheca fusiformis : NMR Structures and Interactions with Other Biosilica-Associated Proteins

et al. 2016

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Diatoms are eukaryotic unicellular algae characterized by silica cell walls and associated with three unique protein families, the pleuralins, frustulins, and silaffins. The NMR structure of the PSCD4 domain of pleuralin-1 from Cylindrotheca fusiformis contains only three short helical elements and is stabilized by five unique disulfide bridges. PSCD4 contains two binding sites for Ca(2+) ions with millimolar affinity. NMR-based interaction studies show an interaction of the domain with native silaffin-1A as well as with α-frustulins. The interaction sites of the two proteins mapped on the PSCD4 structure are contiguous and show only a small overlap. A plausible functional role of pleuralin could be to bind simultaneously silaffin-1A located inside the cell wall and α-frustulin coating the cell wall, thus connecting the interfaces between hypotheca and epitheca at the girdle bands. Restrained molecular dynamics calculations suggest a bead-chain-like structure of the central part of pleuralin-1.

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“…SSA also has been applied to process biomedical signals with different goals: eliminating high-amplitude artifacts [5], suppressing noise contributions or extracting informative components [22,8]. The elimination of high-amplitude artifacts is naturally related to the components associated with the largest eigenvalues.…”

Section: Introductionmentioning

confidence: 99%

“…The elimination of high-amplitude artifacts is naturally related to the components associated with the largest eigenvalues. Therefore, the number of eigenvalues is always discussed but in most of the applications eliminating the component related with the largest eigenvalue reduces significantly the artifact-related interference without distorting the underlying signal [5,23]. On the contrary, reducing white noise interferences usually is addressed by eliminating components related with small eigenvalues [8].…”

Section: Introductionmentioning

confidence: 99%

On the use of Singular Spectrum Analysis

Tomé¹,

Malafaia²,

Teixeira³

et al. 2018

Preprint

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Singular Spectrum Analysis (SSA) or Singular Value Decomposition (SVD) are often used to de-noise univariate time series or to study their spectral profile. Both techniques rely on the eigendecomposition of the correlation matrix estimated after embedding the signal into its delayed coordinates. In this work we show that the eigenvectors can be used to calculate the coefficients of a set of filters which form a filter bank. The properties of these filters are derived. In particular we show that their outputs can be grouped according to their frequency response. Furthermore, the frequency at the maximum of each frequency response and the corresponding eigenvalue can provide a power spectrum estimation of the time series. Two different applications illustrate how both characteristics can be applied to analyze wideband signals in order to achieve narrow-band signals or to infer their frequency occupation.

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Singular spectrum analysis for an automated solvent artifact removal and baseline correction of 1D NMR spectra

Cited by 10 publications

References 20 publications

The “Wine-T₁” NMR experiment for novel wine-metabolome fingerprinting with nuclear-spin relaxation

The “Wine-T₁” NMR experiment for novel wine-metabolome fingerprinting with nuclear-spin relaxation

PSCD Domains of Pleuralin-1 from the Diatom Cylindrotheca fusiformis : NMR Structures and Interactions with Other Biosilica-Associated Proteins

On the use of Singular Spectrum Analysis

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Singular spectrum analysis for an automated solvent artifact removal and baseline correction of 1D NMR spectra

Cited by 10 publications

References 20 publications

The “Wine-T1” NMR experiment for novel wine-metabolome fingerprinting with nuclear-spin relaxation

The “Wine-T1” NMR experiment for novel wine-metabolome fingerprinting with nuclear-spin relaxation

PSCD Domains of Pleuralin-1 from the Diatom Cylindrotheca fusiformis : NMR Structures and Interactions with Other Biosilica-Associated Proteins

On the use of Singular Spectrum Analysis

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The “Wine-T₁” NMR experiment for novel wine-metabolome fingerprinting with nuclear-spin relaxation

The “Wine-T₁” NMR experiment for novel wine-metabolome fingerprinting with nuclear-spin relaxation