Optimal gradient operation in comprehensive liquid chromatography×liquid chromatography systems with limited orthogonality

Bedani, Filippo; Kok, Wim Th.; Janssen, Hans‐Gerd

doi:10.1016/j.aca.2009.06.042

Cited by 50 publications

(30 citation statements)

References 21 publications

(27 reference statements)

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“…When orthogonal columns cannot be used, the loss in peak capacity compared to a fully orthogonal system can be limited if the second dimension gradient operation is adapted to the degree of orthogonality. This can result either in an improved peak capacity or in decreasing total analysis time, depending on the final goal of the experiment [103]. …”

Section: Development Of Mdlc In Proteomicsmentioning

confidence: 99%

Multi-dimensional liquid chromatography in proteomics—A review

Zhang

Fang

Riley

et al. 2010

Analytica Chimica Acta

162

108

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Proteomics is the large-scale study of proteins, particularly their expression, structures and functions. This still-emerging combination of technologies aims to describe and characterize all expressed proteins in a biological system. Because of upper limits on mass detection of mass spectrometers, proteins are usually digested into peptides and the peptides are then separated, identified and quantified from this complex enzymatic digest. The problem in digesting proteins first and then analyzing the peptide cleavage fragments by mass spectrometry is that huge numbers of peptides are generated that overwhelm direct mass spectral analyses. The objective in the liquid chromatography approach to proteomics is to fractionate peptide mixtures to enable and maximize identification and quantification of the component peptides by mass spectrometry. This review will focus on existing multidimensional liquid chromatographic (MDLC) platforms developed for proteomics and their application in combination with other techniques such as stable isotope labeling. We also provide some perspectives on likely future developments.

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Section: Development Of Mdlc In Proteomicsmentioning

confidence: 99%

Multi-dimensional liquid chromatography in proteomics—A review

Zhang

Fang

Riley

et al. 2010

Analytica Chimica Acta

162

108

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“…Obviously, in view of the f coverage factor in Eq. 1 increasing orthogonality will raise the effective peak capacity in a practical LC×LC system [37]; Jandera et al explored this approach by choice of the proper columns and the careful optimization of the mobile phase and gradient for each dimension [18–20]. Schoenmakers et al proposed a protocol to establish the optimal conditions including column length and diameter, particle size, flow rate, and second dimension loop size [21].…”

Section: Introductionmentioning

confidence: 99%

Peak capacity optimization in comprehensive two dimensional liquid chromatography: A practical approach

Huang

Carr

2011

Journal of Chromatography A

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In this work we develop a practical approach to optimization in comprehensive two dimensional liquid chromatography (LC×LC) which incorporates the important under-sampling correction and is based on the previously developed gradient implementation of the Poppe approach to optimizing peak capacity. The Poppe method allows the determination of the column length, flow rate as well as initial and final eluent compositions that maximize the peak capacity at a given gradient time. It was assumed that gradient elution is applied in both dimensions and that various practical constraints are imposed on both the initial and final mobile phase composition in the first dimension separation. It was convenient to consider four different classes of solute sets differing in their retention properties. The major finding of this study is that the under-sampling effect is very important and causes some unexpected results including the important counter-intuitive observation that under certain conditions the optimum effective LC×LC peak capacity is obtained when the first dimension is deliberately run under sub-optimal conditions.

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“…The LC×LC separation of wine polyphenols was optimized using the standard mixture, at first, in There are some examples in the literature demonstrating how a tailored 2 D gradient program leads to a greater coverage of the available separation space [18,33]; the total analysis time may also be reduced [34] and the modulation time reduced accordingly, resulting in a better fractionation of the a narrower organic solvent range was adopted, spanning from 0% to 20%, so that retention was stronger on the 2 D column, and the separation improved.…”

Section: Lc×lc-pda-ms Analyses Of Red Winementioning

confidence: 99%