Evidence map›Paper›PMID 28510014›Full record

ReviewBiophysical reviews2016

Biosensor binding data and its applicability to the determination of active concentration.

Robert Karlsson

Abstract readReview
In one paragraph

Review in Biophysical reviews, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Fluidic Interface for Surface-based DNA Origami Studies.ACS applied materials & interfaces · 2024
    Article
  3. Article
  4. Article
  5. Article
  6. VHH characterization. Comparison of recombinant with chemically synthesized anti-HER2 VHH.Protein science : a publication of the Protein Society · 2019
    Article
  7. Article
  8. Article
  9. Review
  10. 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

1 author.

Robert KarlssonGE Healthcare Bio-Sciences AB, Björkgatan 30, 753 23, Uppsala, Sweden. robert.karlsson@ge.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Protein concentration data are required for understanding protein interactions and are a prerequisite for the determination of affinity and kinetic properties. It is vital for the judgment of protein quality and for monitoring the effect of therapeutic agents. Protein concentration values are typically obtained by comparison to a standard and derived from a standard curve. The use of a protein standard is convenient, but may not give reliable results if samples and standards behave differently. In other cases, a standard preparation may not be available and has to be established and validated. Using surface plasmon resonance (SPR) biosensors, an alternative concentration method is possible. This method is called calibration-free concentration analysis (CFCA); it generates active concentration data directly and without the use of a standard. The active concentration of a protein is defined through its interaction with its binding partner. This concentration can differ from the total protein concentration if some protein fraction is incapable of binding. If a protein has several different binding sites, active concentration data can be established for each binding site using site-specific interaction partners. This review will focus on CFCA analysis. It will reiterate the theory of CFCA and describe how CFCA has been applied in different research segments. The major part of the review will, however, try to set expectations on CFCA and discuss how CFCA can be further developed for absolute and relative concentration measurements.

Indexed as

BiomarkerCFCAProtein qualitySimulationSPRVaccine

Identifiers

PMID28510014
PMCPMC5418478

What OpenQuestion holds

Textmetadata
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.