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Dataset for: Monitoring PSA levels as chemical state-variables in metal-oxide memristors

Dataset for: Monitoring PSA levels as chemical state-variables in metal-oxide memristors
Dataset for: Monitoring PSA levels as chemical state-variables in metal-oxide memristors
Dataset supports: Tzouvadaki, I., Stathopoulos, S., Abbey, T., Michalas, L., & Prodromakis, T. (2020). Monitoring PSA levels as chemical state-variables in metal-oxide memristors. Scientific Reports. Medical interventions increasingly rely on biosensors that can provide reliable quantitative information. A longstanding bottleneck in realizing this, is various non-idealities that generate offsets and variable responses across sensors. Current mitigation strategies involve the calibration of sensors, performed in software or via auxiliary compensation circuitry thus constraining real-time operation and integration efforts. Here, we show that bio-functionalized metal-oxide memristors can be utilized for directly transducing biomarker concentration levels to discrete memory states. The introduced chemical state-variable is found to be dependent on the devices’ initial resistance, with its response to chemical stimuli being more pronounced for higher resistive states. We leverage this attribute along with memristors’ inherent state programmability for calibrating a biosensing array to render a homogeneous response across all cells. Finally, we demonstrate the application of this technology in detecting Prostate Specific Antigen in clinically relevant levels (ng/ml), paving the way towards applications in large multi-panel assays.
University of Southampton
Tzouvadaki, Ioulia
a1025ec1-7606-453d-bc71-1f732a4c1f78
Stathopoulos, Spyros
98d12f06-ad01-4708-be19-a97282968ee6
Abbey, Thomas
64fcf5bd-e20e-4fb8-9ec4-391ad8a0a7a8
Michalas, Loukas
25d00d54-5900-485e-bd52-d3505fe881a7
Prodromakis, Themistoklis
d58c9c10-9d25-4d22-b155-06c8437acfbf
Tzouvadaki, Ioulia
a1025ec1-7606-453d-bc71-1f732a4c1f78
Stathopoulos, Spyros
98d12f06-ad01-4708-be19-a97282968ee6
Abbey, Thomas
64fcf5bd-e20e-4fb8-9ec4-391ad8a0a7a8
Michalas, Loukas
25d00d54-5900-485e-bd52-d3505fe881a7
Prodromakis, Themistoklis
d58c9c10-9d25-4d22-b155-06c8437acfbf

Tzouvadaki, Ioulia (2020) Dataset for: Monitoring PSA levels as chemical state-variables in metal-oxide memristors. University of Southampton doi:10.5258/SOTON/D1439 [Dataset]

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Abstract

Dataset supports: Tzouvadaki, I., Stathopoulos, S., Abbey, T., Michalas, L., & Prodromakis, T. (2020). Monitoring PSA levels as chemical state-variables in metal-oxide memristors. Scientific Reports. Medical interventions increasingly rely on biosensors that can provide reliable quantitative information. A longstanding bottleneck in realizing this, is various non-idealities that generate offsets and variable responses across sensors. Current mitigation strategies involve the calibration of sensors, performed in software or via auxiliary compensation circuitry thus constraining real-time operation and integration efforts. Here, we show that bio-functionalized metal-oxide memristors can be utilized for directly transducing biomarker concentration levels to discrete memory states. The introduced chemical state-variable is found to be dependent on the devices’ initial resistance, with its response to chemical stimuli being more pronounced for higher resistive states. We leverage this attribute along with memristors’ inherent state programmability for calibrating a biosensing array to render a homogeneous response across all cells. Finally, we demonstrate the application of this technology in detecting Prostate Specific Antigen in clinically relevant levels (ng/ml), paving the way towards applications in large multi-panel assays.

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Published date: 2020

Identifiers

Local EPrints ID: 443458
URI: http://eprints.soton.ac.uk/id/eprint/443458
PURE UUID: ddb2f45b-941e-4d5f-9074-fdf24cde4d86
ORCID for Spyros Stathopoulos: ORCID iD orcid.org/0000-0002-0833-6209
ORCID for Themistoklis Prodromakis: ORCID iD orcid.org/0000-0002-6267-6909

Catalogue record

Date deposited: 26 Aug 2020 16:34
Last modified: 05 May 2023 16:40

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Contributors

Creator: Ioulia Tzouvadaki
Contributor: Spyros Stathopoulos ORCID iD
Contributor: Thomas Abbey
Contributor: Loukas Michalas
Research team head: Themistoklis Prodromakis ORCID iD

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