Evidence map›Paper›PMID 39898999›Full record

ArticleAnalytical chemistry2025

Everything's under Control: Maximizing Biosensor Performance through Negative Control Probe Selection.

Joseph Bucukovski, Benjamin L Miller

Abstract read
In one paragraph

Article in Analytical chemistry, 2025. 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. Review
  2. Article
  3. 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

2 authors.

Joseph BucukovskiDepartment of Biochemistry and Biophysics, University of Rochester, Rochester, New York 14627, United States.
Benjamin L MillerDepartment of Biochemistry and Biophysics, University of Rochester, Rochester, New York 14627, United States.ORCID 0000-0001-9168-8047

Funding

A microphysiological system of tendon inflammation and fibrosis for drug screening and efficacy testingUH3TR003281 · NCATS · UNIVERSITY OF ROCHESTER · PI AWAD, HANI A, MCGRATH, JAMES L · 2022 to 2024
$2.2M
NCATS NIH HHS UH3 TR003281
6 · The paper itself

Abstract

The rapid rise of label-free biosensing technologies has led to multiple creative strategies for the detection of macromolecules in complex biological solutions for disease state monitoring, drug discovery, and basic science research. A challenge with these techniques is that assays conducted in complex media such as serum suffer from nonspecific binding of matrix constituents. In label-free biosensors, it is virtually impossible to distinguish these nonspecific interactions without the use of a reference (negative control) probe. Only with reference subtraction can the specific binding signal be faithfully reported. To date, this has been a sparsely studied area in the biosensing field. Here, we report an FDA-inspired framework for optimum control probe selection and a systematic analysis for determining the optimal negative control probe given two monoclonal antibody capture probes on photonic ring resonator sensors. Briefly, while the differences in assay performance for IL-17A and CRP were found to be subtle, the best-scoring reference control based on the bioanalytical parameters of linearity, accuracy, and selectivity differed for each analyte. In the IL-17A assay, BSA scored the highest at 83%, while mouse IgG1 isotype control antibody placed a close second with 75%. With respect to the CRP assay, the rat IgG1 isotype control antibody scored the highest at 95%, while anti-FITC scored the second highest at 89%. These results suggest that although isotype-matching to the capture antibody may be tempting, the best on-chip reference control must be optimized on a case-by-case basis using the framework we report.

Indexed as

Biosensing TechniquesC-Reactive ProteinInterleukin-17AnimalsAntibodies, MonoclonalHumansImmunoglobulin GMiceAntibodies, MonoclonalC-Reactive ProteinImmunoglobulin GInterleukin-17

Identifiers

PMID39898999
PMCPMC11840803

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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.