ArticleSmall (Weinheim an der Bergstrasse, Germany)2022
Enhanced Enzymatically Amplified Metallization on Nanostructured Surfaces for Multiplexed Point-of-Care Electrical Detection of COVID-19 Biomarkers.
Article in Small (Weinheim an der Bergstrasse, Germany), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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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.
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
10 citing papers in PubMed, 15 citations in OpenAlex.
- Biomaterials for biomarker imaging and detection.Journal of advanced research · 2026Review
- Inexpensive High-Throughput Multiplexed Cytokine Detection for Tuberculosis Diagnostics Using Amplified Enzymatic Metallization.ACS sensors · 2026Article
- Article
- Next-generation clinically relevant antibody detection: Unlocking electrochemical biosensors for critical disease management.Acta pharmaceutica Sinica. B · 2025Review
- Ultrasensitive Electrochemical Immunoassays of IgG and CA125 Based on Glucose Oxidase-Catalyzed Signal Amplification with Gold Staining.Biosensors · 2025Article
- Deep humoral profiling coupled to interpretable machine learning unveils diagnostic markers and pathophysiology of schistosomiasis.Science translational medicine · 2024Article
- Article
- Inexpensive High-Throughput Multiplexed Biomarker Detection Using Enzymatic Metallization with Cellphone-Based Computer Vision.ACS sensors · 2023Article
- Regulating the microenvironment with nanomaterials: Potential strategies to ameliorate COVID-19.Acta pharmaceutica Sinica. B · 2023Review
- Enhanced Enzymatically Amplified Metallization on Nanostructured Surfaces for Multiplexed Point-of-Care Electrical Detection of COVID-19 Biomarkers.Small (Weinheim an der Bergstrasse, Germany) · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 1 institution in 1 country.
Funding
Abstract
Inexpensive yet sensitive and specific biomarker detection is a critical bottleneck in diagnostics, monitoring, and surveillance of infectious diseases such as COVID-19. Multiplexed detection of several biomarkers can achieve wider diagnostic applicability, accuracy, and ease-of-use, while reducing cost. Current biomarker detection methods often use enzyme-linked immunosorbent assays (ELISA) with optical detection which offers high sensitivity and specificity. However, this is complex, expensive, and limited to detecting only a single analyte at a time. Here, it is found that biomarker-bound enzyme-labeled probes act synergistically with nanostructured catalytic surfaces and can be used to selectively reduce a soluble silver substrate to generate highly dense and conductive, localized surface silver metallization on microelectrode arrays. This enables a sensitive and quantitative, simple, direct electronic readout of biomarker binding without the use of any intermediate optics. Furthermore, the localized and dry-phase stable nature of the metallization enables multiplexed electronic measurement of several biomarkers from a single drop (<10 µL) of sample on a microchip.This method is applied for the multiplexed point-of-care (POC) quantitative detection of multiple COVID-19 antigen-specific antibodies. Combining a simple microchip and an inexpensive, cellphone-interfaced, portable reader, the detection and discrimination of biomarkers of prior infection versus vaccination is demonstrated.
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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.