Evidence map›Paper›PMID 22807360›Full record

ArticleJournal of separation science2012

Neuropeptide analysis with liquid chromatography-capillary electrophoresis-mass spectrometric imaging.

Zichuan Zhang, Chenxi Jia, Lingjun Li

Open access · greenAbstract readEvaluation Study
In one paragraph

Article in Journal of separation science, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.9field-weighted citation impact, top 15% of its field
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

11 citing papers in PubMed, 22 citations in OpenAlex.

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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

3 authors at 1 institution in 1 country.

Zichuan ZhangSchool of Pharmacy, University of Wisconsin, Madison, Wisconsin 53705, USA.
Chenxi Jia
Lingjun Li
University of Wisconsin–Madison · US

Funding

WISCONSIN CENTER ON MENTAL RETARDATION: CORE SUPPORTP30HD003352 · NICHD · UNIVERSITY OF WISCONSIN-MADISON · PI MESSING, ALBEE · 1985 to 2015
$25.2M
Mass Spectrometric Studies of Neuropeptides in FeedingR01DK071801 · NIDDK · UNIVERSITY OF WISCONSIN-MADISON · PI LINGJUN LI · 2006 to 2026
$6.7M
Mass Spectrometric Studies of Neuropeptides in FeedingR56DK071801 · NIDDK · UNIVERSITY OF WISCONSIN-MADISON · PI LI, LINGJUN · 2011 to 2011
$216k
NICHD NIH HHS P30 HD003352NIDDK NIH HHS 1R01DK071801NIDDK NIH HHS 1R56DK071801NIDDK NIH HHS R01 DK071801NIDDK NIH HHS R56 DK071801
6 · The paper itself

Abstract

Herein we report the first attempt of coupling multidimensional separations to matrix-assisted laser desorption/ionization (MALDI) mass spectrometric imaging detection. Complex neuropeptide mixtures extracted from crustaceans were first fractionated by reversed-phase liquid chromatography (RPLC), and then subjected to a capillary electrophoresis-mass spectrometric imaging platform. With a specific focus on orcokinin family neuropeptides, we demonstrated that these trace-level analytes from complex neural tissue samples can be fully separated from chemical noise and interfering components and visualized as mass spectrometric imaging signals. A total of 19 putative orcokinins were detected, with highly efficient separations within the family being achieved for the first time. The results indicate that two-dimensional separation coupling to mass spectrometric imaging can serve as a novel and powerful tool in proteomics and peptidomics studies.

Indexed as

Amino Acid SequenceAnimalsBrachyuraChromatography, LiquidElectrophoresis, CapillaryMolecular Sequence DataNeuropeptidesPeptide MappingSpectrometry, Mass, Matrix-Assisted Laser Desorption-IonizationNeuropeptides

Identifiers

PMID22807360
PMCPMC3638723
OpenAlexW2143582958

What OpenQuestion holds

Textmetadata
LicenceTDM
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 OpenQuestion graph.