ArticleBiosensors2023
Vertical Graphene-Based Printed Electrochemical Biosensor for Simultaneous Detection of Four Alzheimer's Disease Blood Biomarkers.
Article in Biosensors, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it, 31 citations in OpenAlex.
- Stage-Wise IoT Solutions for Alzheimer's Disease: A Systematic Review of Detection, Monitoring, and Assistive Technologies.Sensors (Basel, Switzerland) · 2025Pooled it
- Blood-based multiplex nanobiosensing of Alzheimer's disease biomarkers: from nanoengineered ınterfaces to clinical translation.Metabolic brain disease · 2026Review
- Overview in Electrochemical and Electrical Biosensors for Determining Blood Protein Biomarkers of Alzheimer's Disease.Biosensors · 2026Review
- Electrochemical Detection of Aβ42 and Aβ40 at Attomolar Scale via Optimised Antibody Loading on Pyr-NHS-Functionalised 3D Graphene Foam Electrodes.Biosensors · 2025Article
- Redox-Active Polyphenol Red Molecularly Imprinted Polymers on Porous Gold Electrodes for Ultrasensitive, AI-Assisted Detection of Alzheimer's Biomarkers in Undiluted Biofluids.Advanced healthcare materials · 2025Article
- Biological applications of graphene-based nanomaterials in neurodegenerative diseases.Materials today. Bio · 2025Review
- Electrochemical Technology for the Detection of Tau Proteins as a Biomarker of Alzheimer's Disease in Blood.Biosensors · 2025Review
- Light-Triggered Graphene/Black Phosphorus Heterostructure FET Platform for Ultrasensitive Detection of Alzheimer's Disease Biomarkers at the Zeptomole Level.Research (Washington, D.C.) · 2025Article
- Identification of Autophagy-Related Candidate Genes in the Early Diagnosis of Alzheimer's Disease and Exploration of Potential Molecular Mechanisms.Molecular neurobiology · 2024Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
Early detection and timely intervention play a vital role in the effective management of Alzheimer's disease. Currently, the diagnostic accuracy for Alzheimer's disease based on a single blood biomarker is relatively low, and the combined use of multiple blood biomarkers can greatly improve diagnostic accuracy. Herein, we report a printed electrochemical biosensor based on vertical graphene (VG) modified with gold nanoparticles (VG@nanoAu) for the simultaneous detection of four Alzheimer's disease blood biomarkers. The printed electrochemical electrode array was constructed by laser etching and inkjet printing. Then gold nanoparticles were modified onto the working electrode surface via electrodeposition to further improve the sensitivity of the sensor. In addition, the entire printed electrochemical sensing system incorporates an electrochemical micro-workstation and a smartphone. The customized electrochemical micro-workstation incorporates four electro-chemical control chips, enabling the sensor to simultaneously analyze four biomarkers. Consequently, the printed electrochemical sensing system exhibits excellent analytical performance due to the large surface area, biocompatibility, and good conductivity of VG@nanoAu. The detection limit of the sensing system for Aβ40, Aβ42, T-tau, and P-tau181 was 0.072, 0.089, 0.071, and 0.051 pg/mL, respectively, which meets the detection requirements of Alzheimer's disease blood biomarkers. The printed electrochemical sensing system also exhibits good specificity and stability. This work has great value and promising prospects for early Alzheimer's disease diagnosis using blood biomarkers.
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Registered trials
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.