New supervised alignment method as a preprocessing tool for chromatographic data in metabolomic studies

Struck, Wiktoria; Wiczling, Paweł; Waszczuk-Jankowska, Małgorzata; Kaliszan, Roman; Markuszewski, Michał J.

doi:10.1016/j.chroma.2012.07.084

Cited by 13 publications

(7 citation statements)

References 20 publications

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“…Subsequently, retention times of the fragments between the aforementioned peaks are linearly interpolated. A full description of this method has been explained in detail in the work of Struck et al ( 2012 ). The chromatograms before and after SA are presented in Figure 2 .…”

Section: Resultsmentioning

confidence: 99%

An Approach Based on HPLC-Fingerprint and Chemometrics to Quality Consistency Evaluation of Matricaria chamomilla L. Commercial Samples

et al. 2016

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Chamomile has been used as an herbal medication since ancient times and is still popular because it contains various bioactive phytochemicals that could provide therapeutic effects. In this study, a simple and reliable HPLC method was developed to evaluate the quality consistency of nineteen chamomile samples through establishing a chromatographic fingerprint, quantification of phenolic compounds and determination of antioxidant activity. For fingerprint analysis, 12 peaks were selected as the common peaks to evaluate the similarities of commercial samples of chamomile obtained from different manufacturers. A similarity analysis was performed to assess the similarity/dissimilarity of chamomile samples where values varied from 0.868 to 0.990 what indicating that samples from different manufacturers were consistent. Additionally, simultaneous quantification of five phenolic acids (gallic, caffeic, syringic, p-coumaric, ferulic) and four flavonoids (rutin, myricetin, quercetin and keampferol) was performed to interpret the quality consistency. In quantitative analysis, the nine individual phenolic compounds showed good regression (r > 0.9975). Inter- and intra-day precisions for all analyzed compounds expressed as relative standard deviation (CV) ranged from 0.05% to 3.12%. Since flavonoids and other polyphenols are commonly recognized as natural antioxidants, the antioxidant activity of chamomile samples was evaluated using 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical scavenging activity and ferric reducing/antioxidant power (FRAP) assay. Correlation analysis was used to assess the relationship between antioxidant activity and phenolic composition, and multivariate analysis (PCA and HCA) were applied to distinguish chamomile samples. Results shown in the study indicate high similarity of chamomile samples among them, widely spread in the market and commonly used by people as infusions or teas, as well as that there were no statistically significant differences among them, which in turn is a proof of high quality of commercially available samples of chamomile. The study indicated that the combination of chromatographic fingerprint and quantitative analysis can be readily utilized as a quality consistency method for chamomile and related medicinal preparations. Moreover, the applied strategy seems to be the most promising for the assessment of the investigated plant material.

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Section: Resultsmentioning

confidence: 99%

An Approach Based on HPLC-Fingerprint and Chemometrics to Quality Consistency Evaluation of Matricaria chamomilla L. Commercial Samples

et al. 2016

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“…Likely an aromatic molecular ion for C 14 -alkylbenzene (normally observed in heavy distillates or vinyl pyrolysis) Overall, with the exception of Sample 90, all of the false positives detected could still be reasonably identified as positive, in that these samples all contained some evidence of a petroleum product, just not a product that could be confidently identified as gasoline.…”

Section: False Positive Resultsmentioning

confidence: 93%

“…The size of the data files may be a technical hurdle for some computers; however, the need to account for sample‐to‐sample shifts in retention times coupled with the highly unpredictable and inconsistent chromatographic patterns present in the data presents a significant fundamental challenge. Due to a lack of consistent intrinsic retention time markers, algorithms that require landmarks or anchors struggle with fire debris chromatograms. Algorithms such as correlation optimized warping (COW) , interval correlated shifting (Icoshift) , and recursive alignment by fast Fourier transform (RAFFT) are similarly defeated by the inherent lack of correlation between fire debris chromatograms.…”

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confidence: 99%

Total Ion Spectra versus Segmented Total Ion Spectra as Preprocessing Tools for Gas Chromatography – Mass Spectrometry Data

Adutwum

Abel

Harynuk

2017

Journal of Forensic Sciences

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Alignment of fire debris data from GC-MS for chemometric analysis is challenged by highly variable, uncontrolled sample and matrix composition. The total ion spectrum (TIS) obviates the need for alignment but loses all separation information. We introduce the segmented total ion spectrum (STIS), which retains the advantages of TIS while retaining some retention information. We compare the performance of STIS with TIS for the classification of casework fire debris samples. TIS and STIS achieve good model prediction accuracies of 96% and 98%, respectively. Baseline removal improved model prediction accuracies for both TIS and STIS to 97% and 99%, respectively. The importance of maintaining some chromatographic information to aid in deciphering the underlying chemistry of the results and reasons for false positive/negative results was also examined.

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“…As chromatographic analyses often face problems connected with incomplete analyte separation, presence of interfering substances and matrix effects, the preliminary action in data interpretation is often based on pretreatment of raw data or its binning and alignment to obtain reliable models in further analyses. Different chemometric strategies such as correlation optimized warping [Nielsen et al., ], Gaussian binning [Anderson et al., ], or supervised alignment [Struck et al., ] serve such purposes and improve the quality of so‐called second‐order chromatographic signals as a result.…”

Section: An Overview Of Chemometric Methods Most Commonly Used In CLImentioning

confidence: 99%

Application of Chemometric Techniques in Search of Clinically Applicable Biomarkers of Disease

Kotłowska

2014

Drug Development Research

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Metabolomics deals with the global assessment of the metabolites present in a biological system to evaluate the progress of the disease, select potential biomarkers, and provide insights into the underlying pathophysiology. As metabolomic analysis generates large quantities of data, multivariate data analysis techniques and chemometrics are often used to interpret experimental results. The present overreview describes various chemometric methods that are frequently used in clinical biomarker studies, with emphasis on data analysis strategies and validation of classification and prognostic models. Moreover, an overview of most interesting recent biomarker discovery publications is provided to highlight the clinical applications of chemometric techniques used for bioanalytical data interpretation.

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New supervised alignment method as a preprocessing tool for chromatographic data in metabolomic studies

Cited by 13 publications

References 20 publications

An Approach Based on HPLC-Fingerprint and Chemometrics to Quality Consistency Evaluation of Matricaria chamomilla L. Commercial Samples

An Approach Based on HPLC-Fingerprint and Chemometrics to Quality Consistency Evaluation of Matricaria chamomilla L. Commercial Samples

Total Ion Spectra versus Segmented Total Ion Spectra as Preprocessing Tools for Gas Chromatography – Mass Spectrometry Data

Application of Chemometric Techniques in Search of Clinically Applicable Biomarkers of Disease

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