Evidence map›Paper›PMID 34735605›Full record

ReviewAnalytical and bioanalytical chemistry2022

Biochemistry strategies for label-free optical sensor biofunctionalization: advances towards real applicability.

Maria Soler, Laura M Lechuga

Abstract readReview
In one paragraph

Review in Analytical and bioanalytical chemistry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

  1. Streptavidin-DisplayingSensors (Basel, Switzerland) · 2026
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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.

Maria SolerNanobiosensors and Bioanalytical Applications Group (NanoB2A), Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC, BIST, and CIBER-BBN, Bellaterra, 08193, Barcelona, Spain. maria.soler@icn2.cat.
Laura M LechugaNanobiosensors and Bioanalytical Applications Group (NanoB2A), Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC, BIST, and CIBER-BBN, Bellaterra, 08193, Barcelona, Spain.

Funding

Ministerio de Ciencia e Innovación PGC-2018-099870
6 · The paper itself

Abstract

Label-free biosensors, and especially those based on optical transducers like plasmonic or silicon photonic systems, have positioned themselves as potential alternatives for rapid and highly sensitive clinical diagnostics, on-site environmental monitoring, and for quality control in foods or other industrial applications, among others. However, most of the biosensor technology has not yet been transferred and implemented in commercial products. Among the several causes behind that, a major challenge is the lack of standardized protocols for sensor biofunctionalization. In this review, we summarize the most common methodologies for sensor surface chemical modification and bioreceptor immobilization, discussing their advantages and limitations in terms of analytical sensitivity and selectivity, reproducibility, and versatility. Special focus is placed on the suggestions of innovative strategies towards antifouling and biomimetic functional coatings to boost the applicability and reliability of optical biosensors in clinics and biomedicine. Finally, a brief overview of research directions in the area of device integration, automation, and multiplexing will give a glimpse of the future perspectives for label-free optical biosensors.

Indexed as

Biosensing TechniquesOptics and PhotonicsReproducibility of ResultsSiliconTransducersSiliconAntibody immobilizationAntifouling coatingBiochemical cross-linkingLipid membraneSilicon photonicsSurface plasmon resonance

Identifiers

PMID34735605
PMCPMC9242939

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.