Evidence map›Paper›PMID 39959045›Full record

ReviewACS omega2025

A Review on Perception of Binding Kinetics in Affinity Biosensors: Challenges and Opportunities.

Benjamin McCann, Brandon Tipper, Sepeedeh Shahbeigi, Morteza Soleimani, Masoud Jabbari, Mohammad Nasr Esfahani

Abstract readReview
In one paragraph

Review in ACS omega, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Review
  6. Article
  7. Article
  8. Article
  9. Review
  10. Review
  11. Review
  12. 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

6 authors.

Benjamin McCannSchool of Physics, Engineering and Technology, University of York, York YO10 5DD, U.K.
Brandon TipperSchool of Physics, Engineering and Technology, University of York, York YO10 5DD, U.K.
Sepeedeh ShahbeigiDepartment of Computer Science, University of York, York YO10 5DD, U.K.
Morteza SoleimaniWMG, University of Warwick, Coventry CV4 7AL, U.K.
Masoud JabbariSchool of Mechanical Engineering, University of Leeds, Leeds LS2 9JT, U.K.ORCID https://orcid.org/0000-0003-3615-969X
Mohammad Nasr EsfahaniSchool of Physics, Engineering and Technology, University of York, York YO10 5DD, U.K.ORCID https://orcid.org/0000-0002-6973-2205

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There are challenges associated with design and development of affinity biosensors due to the complicated multiphysics nature of the system. Understanding the binding interaction between target molecules and immobilized receptors and its kinetics is a crucial step to develop robust and reliable biosensor technologies. Evaluation of binding kinetics in biosensors becomes more important and challenging for clinical samples with a complex matrix. Despite drastic advancements in biosensor technologies, having a practical perception of the binding kinetics has remained a critical bottleneck due to limited fundamental understanding. This Review aims to provide a comprehensive discussion on concepts and advances developed so far for the perception of binding kinetics in affinity biosensors. Here, modeling approaches and measurement techniques are presented to characterize the binding interactions in biosensor technologies, while the effect of fouling and secondary factors in the binding interactions will be discussed in the concept of kinetics. This Review will investigate the existing research gaps and potential opportunities in the perception of binding kinetics and challenges to develop robust and reliable biosensors.

Identifiers

PMID39959045
PMCPMC11822510

What OpenQuestion holds

Textmetadata
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.