Evidence map›Paper›PMID 28031966›Full record

ArticleFuture science OA2016

Comparison of commercial nanoliquid chromatography columns for fast, targeted mass spectrometry-based proteomics.

Tore Vehus, Kristina Erikstad Seterdal, Stefan Krauss, Elsa Lundanes, Steven R Wilson

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Future science OA, 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

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. Article
  2. 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

5 authors.

Tore VehusDepartment of Chemistry, University of Oslo, P.O. 1033 Blindern, NO-0315 Oslo, Norway; Department of Chemistry, University of Oslo, P.O. 1033 Blindern, NO-0315 Oslo, Norway.
Kristina Erikstad SeterdalDepartment of Chemistry, University of Oslo, P.O. 1033 Blindern, NO-0315 Oslo, Norway; Department of Chemistry, University of Oslo, P.O. 1033 Blindern, NO-0315 Oslo, Norway.
Stefan KraussUnit for Cell Signaling, SFI-CAST Biomedical Innovation Center, Oslo University Hospital, Rikshospitalet, NO-0027 Oslo, Norway; Unit for Cell Signaling, SFI-CAST Biomedical Innovation Center, Oslo University Hospital, Rikshospitalet, NO-0027 Oslo, Norway.
Elsa LundanesDepartment of Chemistry, University of Oslo, P.O. 1033 Blindern, NO-0315 Oslo, Norway; Department of Chemistry, University of Oslo, P.O. 1033 Blindern, NO-0315 Oslo, Norway.
Steven R WilsonDepartment of Chemistry, University of Oslo, P.O. 1033 Blindern, NO-0315 Oslo, Norway; Department of Chemistry, University of Oslo, P.O. 1033 Blindern, NO-0315 Oslo, Norway.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimWe compared four commonly used, commercially available reverse phase nanoLC columns for identification/determination of Wnt/β-catenin-related pathway proteins. MATERIALS &

methodsThe columns were: Chromolith

resultsThe peak capacity of the columns varied from 100 (Pepswift) to 190 (Accucore) (for 30 min gradients). All columns enabled identification/detection of GSK3β and β-catenin in the complex samples. However, even the columns with higher peak capacities could not enable detection of the somewhat less abundant proteins AXIN2 and TNKS2. The monoliths were more prone to retention time instability when sample complexity increased.

conclusionWe find that commercial nanoLC columns, although featuring different morphologies and peak capacities, provided surprisingly few practical differences for relatively fast, targeted determination of proteins.

Indexed as

Chromatographymass spectrometryparallel reaction monitoringSILACtargeted proteomics

Identifiers

PMID28031966
PMCPMC5137844

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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.