Literature DB >> 21298727

Application of the stochastic resonance algorithm to the simultaneous quantitative determination of multiple weak peaks of ultra-performance liquid chromatography coupled to time-of-flight mass spectrometry.

Haishan Deng1, Erxin Shang, Bingren Xiang, Shaofei Xie, Yuping Tang, Jin-ao Duan, Ying Zhan, Yumei Chi, Defei Tan.   

Abstract

The stochastic resonance algorithm (SRA) has been developed as a potential tool for amplifying and determining weak chromatographic peaks in recent years. However, the conventional SRA cannot be applied directly to ultra-performance liquid chromatography/time-of-flight mass spectrometry (UPLC/TOFMS). The obstacle lies in the fact that the narrow peaks generated by UPLC contain high-frequency components which fall beyond the restrictions of the theory of stochastic resonance. Although there already exists an algorithm that allows a high-frequency weak signal to be detected, the sampling frequency of TOFMS is not fast enough to meet the requirement of the algorithm. Another problem is the depression of the weak peak of the compound with low concentration or weak detection response, which prevents the simultaneous determination of multi-component UPLC/TOFMS peaks. In order to lower the frequencies of the peaks, an interpolation and re-scaling frequency stochastic resonance (IRSR) is proposed, which re-scales the peak frequencies via linear interpolating sample points numerically. The re-scaled UPLC/TOFMS peaks could then be amplified significantly. By introducing an external energy field upon the UPLC/TOFMS signals, the method of energy gain was developed to simultaneously amplify and determine weak peaks from multi-components. Subsequently, a multi-component stochastic resonance algorithm was constructed for the simultaneous quantitative determination of multiple weak UPLC/TOFMS peaks based on the two methods. The optimization of parameters was discussed in detail with simulated data sets, and the applicability of the algorithm was evaluated by quantitative analysis of three alkaloids in human plasma using UPLC/TOFMS. The new algorithm behaved well in the improvement of signal-to-noise (S/N) compared to several normally used peak enhancement methods, including the Savitzky-Golay filter, Whittaker-Eilers smoother and matched filtration.
Copyright © 2011 John Wiley & Sons, Ltd.

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Year:  2011        PMID: 21298727     DOI: 10.1002/rcm.4890

Source DB:  PubMed          Journal:  Rapid Commun Mass Spectrom        ISSN: 0951-4198            Impact factor:   2.419


  2 in total

1.  An adaptive single-well stochastic resonance algorithm applied to trace analysis of clenbuterol in human urine.

Authors:  Wei Wang; Suyun Xiang; Shaofei Xie; Bingren Xiang
Journal:  Molecules       Date:  2012-02-15       Impact factor: 4.411

2.  The application of multiobjective genetic algorithm to the parameter optimization of single-well potential stochastic resonance algorithm aimed at simultaneous determination of multiple weak chromatographic peaks.

Authors:  Haishan Deng; Shaofei Xie; Bingren Xiang; Ying Zhan; Wei Li; Xiaohua Li; Caiyun Jiang; Xiaohong Wu; Dan Liu
Journal:  ScientificWorldJournal       Date:  2014-01-12
  2 in total

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