Evidence map›Paper›PMID 27150507›Full record

ArticleJournal of the American Society for Mass Spectrometry2016

Characteristics of Ion Activation and Collision Induced Dissociation Using Digital Ion Trap Technology.

Fuxing Xu, Qiankun Dang, Xinhua Dai, Xiang Fang, Yuanyuan Wang, Li Ding, Chuan-Fan Ding

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Article in Journal of the American Society for Mass Spectrometry, 2016. 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

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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. 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

7 authors.

Fuxing XuDepartment of Electric Engineering, Fudan University, Shanghai, China.
Qiankun DangShanghai Key Laboratory of Molecular Catalysis and Functional Material, Department of Chemistry and Laser Chemistry Institute, Fudan University, Shanghai, China.
Xinhua DaiNational Institute of Metrology, Beijing, China.
Xiang FangNational Institute of Metrology, Beijing, China. fangxiang@china.com.
Yuanyuan WangDepartment of Electric Engineering, Fudan University, Shanghai, China.
Li DingShanghai Key Laboratory of Molecular Catalysis and Functional Material, Department of Chemistry and Laser Chemistry Institute, Fudan University, Shanghai, China.
Chuan-Fan DingShanghai Key Laboratory of Molecular Catalysis and Functional Material, Department of Chemistry and Laser Chemistry Institute, Fudan University, Shanghai, China. cfding@fudan.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Collision induced dissociation (CID) is one of the most established techniques for tandem mass spectrometry analysis. The CID of mass selected ion could be realized by ion resonance excitation with a digital rectangular waveform. The method is simple, and highly efficient CID result could be obtained by optimizing the experimental parameters, such as digital waveform voltage, frequency, and q value. In this work, the relationship between ion trapping waveform voltage and frequency at preselected q value, the relationship between waveform frequency and the q value at certain ion trapping voltage for optimum CID efficiency were investigated. Experiment results showed that the max CID efficiency of precursor reserpine ions can be obtained at different trapping waveform voltage and frequency when q and β are different. Based on systematic experimental analysis, the optimum experimental conditions for high CID efficiency can be calculated at any selected β or q. By using digital ion trap technology, the CID process and efficient fragmentation of parent ions can be realized by simply changing the trapping waveform amplitude, frequency, and the β values in the digital ion trap mass spectrometry. The technology and method are simple. It has potential use in ion trap mass spectrometry. Graphical Abstract ᅟ.

Indexed as

CID efficiencyCollision induced dissociationDigital ion trapIon trap waveform frequencyIon trap waveform voltageq Value

Identifiers

PMID27150507

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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.