Evidence map›Paper›PMID 22351295›Full record

ArticleJournal of the American Society for Mass Spectrometry2012

MS(M), an efficient workflow for metabolite identification using hybrid linear ion trap Orbitrap mass spectrometer.

Robert Cho, Yingying Huang, Jae C Schwartz, Yan Chen, Timothy J Carlson, Ji Ma

Abstract read
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In one paragraph

Article in Journal of the American Society for Mass Spectrometry, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Absorption, distribution, metabolism, and excretion of [Pharmacology research & perspectives · 2017
    Article
  2. Review
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

6 authors.

Robert ChoDepartment of Pharmacokinetics and Drug Metabolism, Amgen Inc., South San Francisco, CA 94080, USA.
Yingying Huang
Jae C Schwartz
Yan Chen
Timothy J Carlson
Ji Ma

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Identification of drug metabolites can often yield important information regarding clearance mechanism, pharmacologic activity, or toxicity for drug candidate molecules. Additionally, the identification of metabolites can provide beneficial structure-activity insight to help guide lead optimization efforts towards molecules with optimal metabolic profiles. There are challenges associated with detecting and identifying metabolites in the presence of complex biological matrices, and new LC-MS technologies have been developed to meet these challenges. In this report, we describe the development of an experimental approach that applies unique features of the hybrid linear ion trap Orbitrap mass spectrometer to streamline in vitro and in vivo metabolite identification experiments. The approach, referred to as MS(M), utilizes multiple collision cells, dissociation methods, mass analyzers, and detectors. With multiple scan types and different dissociation modes built into one experimental method, along with flexible post-acquisition analysis options, the MS(M) workflow offers an attractive option to fast and reliable identification of metabolites in different kinds of in vitro and in vivo samples. The MS(M) workflow was successfully applied to metabolite identification analysis of verapamil in both in vitro rat hepatocyte incubations and in vivo rat bile samples.

Indexed as

AnimalsBileChromatography, LiquidHepatocytesMaleMass SpectrometryPharmaceutical PreparationsPharmacokineticsRatsRats, Sprague-DawleyVerapamilPharmaceutical PreparationsVerapamil

Identifiers

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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.