Evidence map›Paper›PMID 40277542›Full record

ArticleBiosensors2025

Stamp-Imprinted Polymer EIS Biosensor for Amyloid-Beta Detection: A Novel Approach Towards Alzheimer's Screening.

Chloé E D Davidson, Ravi Prakash

Abstract read
In one paragraph

Article in Biosensors, 2025. 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. 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

2 authors.

Chloé E D DavidsonDepartment of Electronics Engineering, Carleton University, Ottawa, ON K1S 5B6, Canada.ORCID 0009-0009-0550-0411
Ravi PrakashDepartment of Electronics Engineering, Carleton University, Ottawa, ON K1S 5B6, Canada.ORCID 0000-0001-7934-425X

Funding

Natural Sciences and Engineering Research Council Discovery Grant
6 · The paper itself

Abstract

Surface-imprinted polymers (SIPs) represent an exciting and cost-effective alternative to antibodies for electrochemical impedance spectroscopy (EIS)-based biosensing. They can be produced using simple printing techniques and have shown high efficacy in detecting large biomolecules and microorganisms. Stamp imprinting, a novel SIP method, creates the target analyte's imprint using a soft lithography mask of the analyte matrix, thereby reducing material complexities and eliminating the need for cross-linking, which makes the process more scalable than the conventional SIPs. In this work, we demonstrate a stamp-imprinted EIS biosensor using a biocompatible polymer, polycaprolactone (PCL), for quantifying amyloid beta-42 (Aβ-42), a small peptide involved in the pathophysiology of Alzheimer's disease. The evaluated SIP-EIS biosensors showed a detection limit close to 10 fg/mL, and a detection range covering the physiologically relevant concentration range of the analyte in blood serum (from 10 fg/mL to 10 μg/mL). The device sensitivity, which is found to be comparable to antibody-based EIS devices, demonstrates the potential of SIP-EIS biosensors as an exciting alternative to conventional antibody-based diagnostic approaches. We also evaluate the viability of analyzing these proteins in complex media, notably in the presence of serum albumin proteins, which cause biofouling and non-specific interactions. The combination of high sensitivity, selectivity, and ease of fabrication makes SIP-EIS biosensors particularly suited for portable and point-of-care applications.

Indexed as

Alzheimer DiseaseAmyloid beta-PeptidesBiosensing TechniquesDielectric SpectroscopyHumansLimit of DetectionMolecular ImprintingPolyestersPolymersAmyloid beta-PeptidespolycaprolactonePolyestersPolymersAlzheimer’s detectionamyloid-betaSIP-EIS biosensorsurface imprinting

Identifiers

PMID40277542
PMCPMC12025068

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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.