Evidence map›Paper›PMID 27396364›Full record

ReviewBioanalysis2016

Mass spectrometric immunoassays for discovery, screening and quantification of clinically relevant proteoforms.

Olgica Trenchevska, Randall W Nelson, Dobrin Nedelkov

Abstract readReview
In one paragraph

Review in Bioanalysis, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. 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

3 authors.

Olgica TrenchevskaThe Biodesign Institute at Arizona State University, Tempe, AZ, USA.
Randall W NelsonThe Biodesign Institute at Arizona State University, Tempe, AZ, USA.
Dobrin NedelkovThe Biodesign Institute at Arizona State University, Tempe, AZ, USA.

Funding

Team Approach to Translate Novel Biomarkers for DiabetesR24DK090958 · NIDDK · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI NELSON, RANDALL W, PEARSON, JAMES DAVID · 2011 to 2014
$4.5M
Population-Based Proteomic Investigation of Type 2 Diabetes MellitusR01DK082542 · NIDDK · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI NELSON, RANDALL W · 2010 to 2014
$3.0M
NIDDK NIH HHS R01 DK082542NIDDK NIH HHS R24 DK090958
6 · The paper itself

Abstract

Human proteins can exist as multiple proteoforms with potential diagnostic or prognostic significance. MS top-down approaches are ideally suited for proteoforms identification because there is no prerequisite for a priori knowledge of the specific proteoform. One such top-down approach, termed mass spectrometric immunoassay utilizes antibody-derivatized microcolumns for rapid and contained proteoforms isolation and detection via MALDI-TOF MS. The mass spectrometric immunoassay can also provide quantitative measurement of the proteoforms through inclusion of an internal reference standard into the analytical sample, serving as normalizer for all sample processing and data acquisition steps. Reviewed here are recent developments and results from the application of mass spectrometric immunoassays for discovery of clinical correlations of specific proteoforms for the protein biomarkers RANTES, retinol binding protein, serum amyloid A and apolipoprotein C-III.

Indexed as

AnimalsApolipoprotein C-IIIChemokine CCL5Chromatography, AffinityHumansProtein IsoformsProteinsRetinol-Binding ProteinsSerum Amyloid A ProteinSpectrometry, Mass, Matrix-Assisted Laser Desorption-IonizationApolipoprotein C-IIIChemokine CCL5Protein IsoformsProteinsRetinol-Binding ProteinsSerum Amyloid A ProteinimmunoaffinityMALDIMSplasmaproteoform

Identifiers

PMID27396364
PMCPMC4964736

What OpenQuestion holds

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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.