Evidence map›Paper›PMID 34786679›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2022

GC-MS/MS Profiling of Plant Metabolites.

Feroza Kaneez Choudhury, Prajita Pandey, Ron Meitei, Dwain Cardona, Amit C Gujar, Vladimir Shulaev

Abstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Review
  2. Review
  3. Leveraging metabolic similarity in aScientific reports · 2026
    Article
  4. Review
  5. Review
  6. Review
  7. Article
  8. Review
  9. Article
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  12. An Innovative Approach to a Potential NeuroprotectiveInternational journal of molecular sciences · 2024
    Article
  13. 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

6 authors.

Feroza Kaneez ChoudhuryDepartment of Biological Sciences, College of Science, University of North Texas, Denton, TX, USA.
Prajita PandeyDepartment of Biological Sciences, College of Science, University of North Texas, Denton, TX, USA.
Ron MeiteiDivision of Plant Sciences and Interdisciplinary Plant Group, College of Agriculture, Food, and Natural Resources, Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO, USA.
Dwain CardonaThermo Fisher Scientific, Austin, TX, USA.
Amit C GujarThermo Fisher Scientific, Austin, TX, USA.
Vladimir ShulaevDepartment of Biological Sciences and Advanced Environmental Research Institute, College of Science, University of North Texas, Denton, TX, USA. shulaev@unt.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gas chromatography coupled to electron ionization (EI) quadrupole mass spectrometry (GC-MS) is currently one of the most developed and robust metabolomics technologies. This approach allows for simultaneous measurements of large number of chemically diverse compounds including organic acids, amino acids, sugars, sugar alcohols, aromatic amines, and fatty acids. Untargeted GC-MS profiling based on full scan data acquisition requires complicated raw data processing and sometime provides ambiguous metabolite identifications. Targeted analysis using GC-MS/MS can provide better specificity, increase sensitivity, and simplify data processing and compound identification but wider application of targeted GC-MS/MS approach in metabolomics is hampered by the lack of extensive databases of MRM transitions for non-derivatized and derivatized endogenous metabolites. The focus of this chapter is the automation of GC-MS/MS method development which makes it feasible to develop quantitative methods for several hundred metabolites and use this strategy for plant metabolomics applications.

Indexed as

MetabolomicsTandem Mass SpectrometryAmino AcidsGas Chromatography-Mass SpectrometryPlantsAmino AcidsArabidopsisAutoSRMGC-MS /MSMetabolomics

Identifiers

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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 Socratic graph.