ArticleACS omega2023
Electronic Immunoassay Using Enzymatic Metallization on Microparticles.
Article in ACS omega, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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.
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.
Who cites it
6 citing papers in PubMed, 10 citations in OpenAlex.
- Microparticle-enabled single cell multiparameter electronic immunophenotyping for selective electroporation.Lab on a chip · 2026Article
- Inexpensive High-Throughput Multiplexed Cytokine Detection for Tuberculosis Diagnostics Using Amplified Enzymatic Metallization.ACS sensors · 2026Article
- Article
- Overview in Machine-Learning-Assisted Sensing Techniques for Monitoring COVID-19.Micromachines · 2026Review
- Recent advances in bio-microsystem integration and Lab-on-PCB technology.Microsystems & nanoengineering · 2025Review
- Deep humoral profiling coupled to interpretable machine learning unveils diagnostic markers and pathophysiology of schistosomiasis.Science translational medicine · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
We present here an inexpensive method for generating a sensitive direct electronic readout in bead-based immunoassays without the use of any intermediate optical instrumentation (e.g., lasers, photomultipliers, etc.). Analyte binding to capture antigen-coated beads or microparticles is converted to probe-directed enzymatically amplified silver metallization on microparticle surfaces. Individual microparticles are then rapidly characterized in a high-throughput manner via single-bead multifrequency electrical impedance spectra captured using a simple and inexpensive microfluidic impedance spectrometry system we develop here, where they flow through a three-dimensional (3D)-printed plastic microaperture sandwiched between plated through-hole electrodes on a printed circuit board. Metallized microparticles are found to have unique impedance signatures distinguishing them from unmetallized ones. Coupled with a machine learning algorithm, this enables a simple electronic readout of the silver metallization density on microparticle surfaces and hence the underlying analyte binding. Here, we also demonstrate the use of this scheme to measure the antibody response to the viral nucleocapsid protein in convalescent COVID-19 patient serum.
Identifiers
What OpenQuestion holds
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.