Evidence map›Paper›PMID 39713036›Full record

ArticleACS measurement science au2024

Rapid and Robust Workflows Using Different Ionization, Computation, and Visualization Approaches for Spatial Metabolome Profiling of Microbial Natural Products in

Jian Yu, Haidy Metwally, Jennifer Kolwich, Hailey Tomm, Martin Kaufmann, Rachel Klotz, Chang Liu, J C Yves Le Blanc, Thomas R Covey, John Rudan and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in ACS measurement science au, 2024. 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. Review
  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

12 authors.

Jian YuDepartment of Chemistry, Queen's University, Kingston, Ontario, Canada K7K 0C2.
Haidy MetwallyDepartment of Chemistry, Queen's University, Kingston, Ontario, Canada K7K 0C2.
Jennifer KolwichDepartment of Chemistry, Queen's University, Kingston, Ontario, Canada K7K 0C2.
Hailey TommDepartment of Chemistry, Queen's University, Kingston, Ontario, Canada K7K 0C2.
Martin KaufmannDepartment of Surgery, Queen's University, Kingston, Ontario, Canada K7L 2V7.
Rachel KlotzDepartment of Chemistry, Queen's University, Kingston, Ontario, Canada K7K 0C2.
Chang LiuSCIEX, 71 Four Valley Drive, Concord, Ontario, Canada L4K 4V8.ORCID https://orcid.org/0000-0003-0508-4357
J C Yves Le BlancSCIEX, 71 Four Valley Drive, Concord, Ontario, Canada L4K 4V8.ORCID https://orcid.org/0000-0002-3801-3590
Thomas R CoveySCIEX, 71 Four Valley Drive, Concord, Ontario, Canada L4K 4V8.
John RudanDepartment of Surgery, Queen's University, Kingston, Ontario, Canada K7L 2V7.
Avena C RossDepartment of Chemistry, Queen's University, Kingston, Ontario, Canada K7K 0C2.ORCID https://orcid.org/0000-0002-9845-729X
Richard D OleschukDepartment of Chemistry, Queen's University, Kingston, Ontario, Canada K7K 0C2.ORCID https://orcid.org/0000-0003-2783-7532

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ambient mass spectrometry (MS) technologies have been applied to spatial metabolomic profiling of various samples in an attempt to both increase analysis speed and reduce the length of sample preparation. Recent studies, however, have focused on improving the spatial resolution of ambient approaches. Finer resolution requires greater analysis times and commensurate computing power for more sophisticated data analysis algorithms and larger data sets. Higher resolution provides a more detailed molecular picture of the sample; however, for some applications, this is not required. A liquid microjunction surface sampling probe (LMJ-SSP) based MS platform combined with unsupervised multivariant analysis based hyperspectral visualization is demonstrated for the metabolomic analysis of marine bacteria from the genus

Identifiers

PMID39713036
PMCPMC11659995

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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 OpenQuestion graph.