ArticleHeliyon2024
Development of a graphene field effect transistor-based immersible biosensor for immunodetection of the birch pollen allergen Bet v 1 in air samples.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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.
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Who cites it
1 citing paper in PubMed.
- Plasmonic ELISA for Biomarker Detection: A Review of Mechanisms, Functionalization Strategies, and Emerging Modalities.ACS applied bio materials · 2025Review
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Pollen traps, the current gold standard to determine pollen load and thereby the allergy season, are not sufficient to determine the allergenic risk. Therefore, the establishment of highly sensitive assays for allergen measurement is of highest interest. Herein, a graphene field-effect transistor (GFET) was constructed on an interdigitated electrodes chip to develop an immersible biosensor, which was used to detect the major birch pollen allergen Bet v 1. Graphene was wet-transferred on interdigitated electrodes that contain a reference electrode used as a liquid gate in the GFET. Using a standard ELISA protocol, two different anti-Bet v 1 antibodies were chosen and immobilized on graphene for the specific capture of the target allergen. The sensitivity of the GFET biosensor was evaluated using a standard Ag/AgCl liquid gate electrode and a reference electrode when the chip was immersed in Bet v 1-containing solutions. The results showed a higher performance and sensitivity for Bet v 1 detection compared to a mediator release method, one of the most sensitive assays for allergen detection. Compared with conventional methods of allergen detection, these immersible biosensors significantly improved the speed and level of detection providing the foundation of a point-of-need platform for in-field application. Furthermore, the proposed technique provides both a new biosensor for allergen detection and a strategy for designing low-cost integrated biosensors.
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