In pursuit of resolution in time‐of‐flight mass spectrometry: A historical perspective

Radionova, Anna; Filippov, Igor V.; Derrick, Peter J.

doi:10.1002/mas.21470

Cited by 38 publications

(29 citation statements)

References 155 publications

(184 reference statements)

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“…30 Currently, the application of metabolomics to urine samples has been successful in nding potential biomarkers for diseases. [35][36][37][38][39] Our ndings have dened a panel of molecules whose levels are altered in the urine of RA patients. The urine biomarkers identied in this study exhibited satisfactory diagnostic performance.…”

Section: Discussionmentioning

confidence: 99%

Exploration of metabolite signatures using high-throughput mass spectrometry coupled with multivariate data analysis

Zhang

Liu

et al. 2017

RSC Adv.

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Section: Discussionmentioning

confidence: 99%

Exploration of metabolite signatures using high-throughput mass spectrometry coupled with multivariate data analysis

Zhang

Liu

et al. 2017

RSC Adv.

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“…In this section, formulas for the first and second order space foci of two‐stage ion sources and ion reflectors are deduced. For comparison see Mamyrin et al (), furthermore, consider Schlag (), Guilhaus (), Grotemeyer (), Wollnik (), Radionova, Filippov, & Derrick () and references, cited herein. In the following, unified parameters are introduced which can be applied to both systems and allow a simplified way of deduction of such formulas.…”

Section: Space Focus Of Two‐stage Ion Sources and Ion Reflectorsmentioning

confidence: 99%

“…Most citations are given to provide examples or further information rather than complete reviews of the field. For such reviews and further information, see Schlag (1994), Guilhaus (1995), Cotter (1997), Grotemeyer (2001), Wollnik (2013), Radionova, Filippov, & Derrick (2015).…”

Section: Introductionmentioning

confidence: 99%

Time-of-flight mass spectrometry: Introduction to the basics

Boesl

2016

Mass Spec Rev

104

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The intention of this tutorial is to introduce into the basic concepts of time-of-flight mass spectrometry, beginning with the most simple single-stage ion source with linear field-free drift region and continuing with two-stage ion sources combined with field-free drift regions and ion reflectors-the so-called reflectrons. Basic formulas are presented and discussed with the focus on understanding the physical relations of geometric and electric parameters, initial distribution of ionic parameters, ion flight times, and ion flight time incertitude. This tutorial is aimed to help the applicant to identify sources of flight time broadening which limit good mass resolution and sources of ion losses which limit sensitivity; it is aimed to stimulate creativity for new experimental approaches by discussing a choice of instrumental options and to encourage those who toy with the idea to build an own time-of-flight mass spectrometer. Large parts of mathematics are shifted into a separate chapter in order not to overburden the text with too many mathematical deviations. Rather, thumbrule formulas are supplied for first estimations of geometry and potentials when designing a home-built instrument, planning experiments, or searching for sources of flight time broadening.

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“…The transfer cell is operated at lower pressure than the IM cell and ions therefore travel with the TW rather than falling over the wave as they might do in IM. 14,21,66,67 Therefore, assuming an ion entering the transfer cell had insufficient kinetic energy to overtake the TW in the transfer cell, and ignoring phase effects of the TW, the maximum amount of time an ion could spend in the transfer cell ( t transfer ) would be equal to the length of the cell ( d t ) divided by the transfer cell wave velocity ( v t ): 11

t_{transfer} = \frac{d_{t}}{v_{t}}

For a cell length of 100 mm (0.1 m) and transfer cell wave velocity of 248 m/s (as used in our experiments), the maximum time an ion should spend in the transfer cell (under our experimental conditions) is ~0.40 ms. Based on these simple estimations, under our experimental conditions, we should expect shift factors between ~0.10 × 10 −2 ms (minimum TOF variation for fragment and precursor ions) 68 and ~0.40 ms (maximum transfer cell time).…”

Section: Resultsmentioning

confidence: 84%

Determination of ion mobility collision cross sections for unresolved isomeric mixtures using tandem mass spectrometry and chemometric deconvolution

Harper

Neumann

Stow

et al. 2016

Analytica Chimica Acta

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Ion mobility (IM) is an important analytical technique for determining ion collision cross section (CCS) values in the gas-phase and gaining insight into molecular structures and conformations. However, limited instrument resolving powers for IM may restrict adequate characterization of conformationally similar ions, such as structural isomers, and reduce the accuracy of IM-based CCS calculations. Recently, we introduced an automated technique for extracting “pure” IM and collision-induced dissociation (CID) mass spectra of IM overlapping species using chemometric deconvolution of post-IM/CID mass spectrometry (MS) data [J. Am. Soc. Mass Spectrom., 2014, 25, 1810–1819]. Here we extend those capabilities to demonstrate how extracted IM profiles can be used to calculate accurate CCS values of peptide isomer ions which are not fully resolved by IM. We show that CCS values obtained from deconvoluted IM spectra match with CCS values measured from the individually analyzed corresponding peptides on uniform field IM instrumentation. We introduce an approach that utilizes experimentally determined IM arrival time (AT) “shift factors” to compensate for ion acceleration variations during post-IM/CID and significantly improve the accuracy of the calculated CCS values. Also, we discuss details of this IM deconvolution approach and compare empirical CCS values from traveling wave (TW)IM-MS and drift tube (DT)IM-MS with theoretically calculated CCS values using the projected superposition approximation (PSA). For example, experimentally measured deconvoluted TWIM-MS mean CCS values for doubly-protonated RYGGFM, RMFGYG, MFRYGG, and FRMYGG peptide isomers were 288.8 Å2, 295.1 Å2, 296.8 Å2, and 300.1 Å2; all four of these CCS values were within 1.5% of independently measured DTIM-MS values.

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In pursuit of resolution in time‐of‐flight mass spectrometry: A historical perspective

Cited by 38 publications

References 155 publications

Exploration of metabolite signatures using high-throughput mass spectrometry coupled with multivariate data analysis

Exploration of metabolite signatures using high-throughput mass spectrometry coupled with multivariate data analysis

Time-of-flight mass spectrometry: Introduction to the basics

Determination of ion mobility collision cross sections for unresolved isomeric mixtures using tandem mass spectrometry and chemometric deconvolution

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