Evidence map›Paper›PMID 21477312›Full record

ArticleProteome science2011

Targeted quantitative mass spectrometric immunoassay for human protein variants.

Olgica Trenchevska, Dobrin Nedelkov

Open access · goldAbstract read
In one paragraph

Article in Proteome science, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
1.8field-weighted citation impact, top 17% 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

17 citing papers in PubMed, 33 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

2 authors at 1 institution in 1 country.

Olgica TrenchevskaIntrinsic Bioprobes, 2155 E, Conference Dr, Suite 104, Tempe, AZ 85284, USA. dnedelkov@intrinsicbio.com.
Dobrin Nedelkov
Intrinsic LifeSciences (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPost-translational modifications and genetic variations give rise to protein variants that significantly increase the complexity of the human proteome. Modified proteins also play an important role in biological processes. While sandwich immunoassays are routinely used to determine protein concentrations, they are oblivious to protein variants that may serve as biomarkers with better sensitivity and specificity than their wild-type proteins. Mass spectrometry, coupled to immunoaffinity separations, can provide an efficient mean for simultaneous detection and quantification of protein variants.

resultsPresented here is a mass spectrometric immunoassay method for targeted quantitative proteomics analysis of protein modifications. Cystatin C, a cysteine proteinase inhibitor and a potential marker for several pathological processes, was used as a target analyte. An internal reference standard was incorporated into the assay, serving as a normalization point for cystatin C quantification. The precision, linearity, and recovery characteristics of the assay were established. The new assay was also benchmarked against existing cystatin C ELISA. In application, the assay was utilized to determine the individual concentration of several cystatin C variants across a cohort of samples, demonstrating the ability to fully quantify individual forms of post-translationally modified proteins.

conclusionsThe mass spectrometric immunoassays can find use in quantifying specific protein modifications, either as a part of a specific protein biomarker discovery/rediscovery effort to delineate the role of these variants in the onset of the disease, progression, and response to therapy, or in a more systematic study to delineate and understand human protein diversity.

Identifiers

PMID21477312
PMCPMC3080279
OpenAlexW2123900066

What OpenQuestion holds

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LicenceCC BY
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.