Evidence map›Paper›PMID 42000709›Full record

ArticleNature communications2026

Single-molecule readout of reversible nanoswitches enables continuous monitoring of low biomarker concentrations.

Chris Vu, Selina A J Janssen, Arthur M de Jong, Menno W J Prins

Abstract read
In one paragraph

Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

4 authors.

Chris VuDepartment of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.ORCID http://orcid.org/0000-0001-9863-2855
Selina A J JanssenDepartment of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.ORCID http://orcid.org/0009-0007-4689-3640
Arthur M de JongInstitute for Complex Molecular Systems (ICMS), Eindhoven University of Technology, Eindhoven, The Netherlands.ORCID http://orcid.org/0000-0001-6019-7333
Menno W J PrinsDepartment of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands. m.w.j.prins@tue.nl.ORCID http://orcid.org/0000-0002-9788-7298

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Continuous sensing technologies are expected to change how dynamic bioprocesses will be monitored and controlled in the future. However, a fundamental challenge in the field of biomolecular sensing is that low concentrations invariably cause slow sensor responses. In this paper, we explain how continuous sensors can be developed for quantifying very low biomarker concentrations with fast sensor response times. The measurement concept is based on combining reversible affinity-based nanoswitches with single-molecule readout. A generalizable rate-based simulation model was developed and validated on experimental data of a sandwich-based nanoswitch. The results show how the nanoswitch design and the sensing acquisition parameters control the amplitude and stochastic variations of the sensor response, and how these affect the precision of the concentration determination. We show that the measurement precision is limited by the counting statistics of molecular sandwich events. Using realistic design parameters, we predict limits-of-quantification in the low picomolar range within measurement timescales of minutes. These results pave the way for the development of intrinsically reversible nanoswitch sensors that can access unexplored concentration-time spaces of dynamic biosystems.

Indexed as

BiomarkersBiosensing TechniquesNanotechnologySingle Molecule ImagingBiomarkers

Identifiers

PMID42000709
PMCPMC13280497

What OpenQuestion holds

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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.