Evidence map›Paper›PMID 25960696›Full record

ArticleMetabolomics : Official journal of the Metabolomic Society2015

Correction of precursor and product ion relative abundances in order to standardize CID spectra and improve Ecom

Ritvik Dubey, Dennis W Hill, Steven Lai, Chen Ming-Hui, David F Grant

Abstract read
In one paragraph

Article in Metabolomics : Official journal of the Metabolomic Society, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Quantitative Comparison of Tandem Mass Spectra Obtained on Various Instruments.Journal of the American Society for Mass Spectrometry · 2016
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Ritvik DubeyDepartment of Pharmaceutical Sciences, University of Connecticut, 69 North Eagleville Road, Storrs, CT 06269 USA.
Dennis W HillDepartment of Pharmaceutical Sciences, University of Connecticut, 69 North Eagleville Road, Storrs, CT 06269 USA.
Steven LaiWaters Corporation, 100 Cummings Center, Beverly, MA 01915, USA.
Chen Ming-HuiDepartment of Statistics, University of Connecticut, 215 Glenbrook Road, Storrs, CT 06269 USA.
David F GrantDepartment of Pharmaceutical Sciences, University of Connecticut, 69 North Eagleville Road, Storrs, CT 06269 USA.

Funding

Metabolomics Tools for BiomedicineR01GM087714 · NIGMS · UNIVERSITY OF CONNECTICUT STORRS · PI GRANT, DAVID FRANKLIN · 2010 to 2018
$3.1M
NIGMS NIH HHS R01 GM087714
6 · The paper itself

Abstract

Quantitative biases in the abundance of precursor and product ions due to mass discrimination in RF-only ion guides results in inaccurate collision induced dissociation (CID) spectra. We evaluated the effects of collision cell RF voltage and collision energy on CID spectra using ten singly protonated compounds (46-854 Da) in an orthogonal acceleration time-of-flight mass spectrometer. The relative ion transfer efficiency, i.e. the relative amount of ions transferred through the ion guide at any particular RF voltage was shown to be dependent on the ion's m/z. We developed an algorithm to correct for the mass discriminating effects of RF voltage on CID spectra. The algorithm was tested for both precursor and product ions at multiple RF voltages and collision energies in order to ensure reliability. Our results suggest that compounds that generate major product ions with m/z values <150 have peak intensities that deviate substantially from their actual abundance. This has implications for small molecule metabolomics research, particularly for studies that rely on CID spectra matching methods for structure identification.

Identifiers

PMID25960696
PMCPMC4422648

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.