Evidence map›Paper›PMID 35702551›Full record

ArticleRSC advances2019

Immunocapture sample clean-up in determination of low abundant protein biomarkers - a feasibility study of peptide capture by anti-protein antibodies.

Maren C S Levernæs, Bassem Farhat, Inger Oulie, Sazan S Abdullah, Elisabeth Paus, Léon Reubsaet, Trine G Halvorsen

Abstract read
In one paragraph

Article in RSC advances, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Is this the end of dried blood spots as we know it?Analytical science advances · 2023
    Article
  3. 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

7 authors.

Maren C S LevernæsDepartment Pharmacy, University of Oslo P. O. Box 1068 Blindern 0316 Oslo Norway trinegha@farmasi.uio.no +47 22854402 +47 22855735.
Bassem FarhatDepartment Pharmacy, University of Oslo P. O. Box 1068 Blindern 0316 Oslo Norway trinegha@farmasi.uio.no +47 22854402 +47 22855735.
Inger OulieDepartment Pharmacy, University of Oslo P. O. Box 1068 Blindern 0316 Oslo Norway trinegha@farmasi.uio.no +47 22854402 +47 22855735.
Sazan S AbdullahDepartment Pharmacy, University of Oslo P. O. Box 1068 Blindern 0316 Oslo Norway trinegha@farmasi.uio.no +47 22854402 +47 22855735.
Elisabeth PausDepartment of Medical Biochemistry, Norwegian Radium Hospital, Oslo University Hospital Norway.
Léon ReubsaetDepartment Pharmacy, University of Oslo P. O. Box 1068 Blindern 0316 Oslo Norway trinegha@farmasi.uio.no +47 22854402 +47 22855735.ORCID https://orcid.org/0000-0001-5165-2701
Trine G HalvorsenDepartment Pharmacy, University of Oslo P. O. Box 1068 Blindern 0316 Oslo Norway trinegha@farmasi.uio.no +47 22854402 +47 22855735.ORCID https://orcid.org/0000-0002-2545-3474

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Immunocapture in mass spectrometry based targeted protein analysis using a bottom-up workflow is nowadays mainly performed by target protein extraction using anti-protein antibodies followed by tryptic digestion. Already available monoclonal antibodies (mAbs) which were developed against intact target proteins (anti-protein antibodies) can capture proteotypic epitope containing peptides after tryptic digestion of the sample. In the present paper considerations when developing a method for targeted protein quantitation through capture of epitope containing peptides are discussed and a method applying peptide capture by anti-protein antibodies is compared with conventional immunocapture MS. The model protein used for this purpose was progastrin releasing peptide (ProGRP), a validated low abundant biomarker for Small Cell Lung Cancer with reference values in serum in the pg mL

Identifiers

PMID35702551
PMCPMC9097496

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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.