Evidence map›Paper›PMID 40788688›Full record

ArticleACS nano2025

Nanoparticle-Supported, Rapid, and Electronic Detection of SARS-CoV-2 Antibodies and Antigens at the Subfemtomolar Level.

Yeji Choi, Seyedsina Mirjalili, Md Ashif Ikbal, Sean McClure, Maziyar Kalateh Mohammadi, Scott Clemens, Jose Solano, John Heggland, Tingting Zhang, Jiawei Zuo and 1 more

Abstract read
In one paragraph

Article in ACS nano, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Yeji ChoiSchool of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, Arizona 85287, United States.ORCID 0000-0002-0379-6783
Seyedsina MirjaliliSchool of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, Arizona 85287, United States.ORCID 0000-0001-5854-7867
Md Ashif IkbalSchool of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, Arizona 85287, United States.
Sean McClureSchool of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, Arizona 85287, United States.
Maziyar Kalateh MohammadiSchool of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, Arizona 85287, United States.
Scott ClemensSchool of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, Arizona 85287, United States.
Jose SolanoSchool of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, Arizona 85287, United States.
John HegglandSchool of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, Arizona 85287, United States.
Tingting ZhangSchool of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, Arizona 85287, United States.
Jiawei ZuoSchool of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, Arizona 85287, United States.
Chao WangSchool of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, Arizona 85287, United States.ORCID 0000-0001-5020-961X

Funding

Integrated Nano-Opto-Fluidic System on Sapphire towards Single-Molecule Protein SequencingDP2GM149552 · NIGMS · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI WANG, CHAO · 2022 to 2025
$2.2M
High-Throughput, Rapid, and Epitope-Specific Quantification of Neutralizing Antibodies Using Digital Nanoparticle SensorsR21AI169098 · NIAID · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI WANG, CHAO · 2022 to 2023
$418k
NIAID NIH HHS R21 AI169098NIGMS NIH HHS DP2 GM149552
6 · The paper itself

Abstract

Major challenges remain to precisely detect low-abundance proteins rapidly and cost-effectively from diverse biofluids. Here, we present a gold nanoparticle (AuNP)-supported, rapid electronic detection (NasRED) platform with subfemtomolar sensitivity and high specificity. Surface-functionalized AuNPs act as multivalent detectors to recognize target antigens and antibodies through high-affinity binding, subsequently forming aggregates precipitated in a microcentrifuge tube and producing a solution color change. The residual floating AuNPs' optical extinction is digitized using customized circuitry incorporating inexpensive optoelectronics and feedback mechanisms for stabilized readout. NasRED introduces active fluidic forces through engineered centrifugation and vortex agitation, effectively promoting low-concentration protein detection and accelerating signal transduction. Using SARS-CoV-2 as a demonstration, NasRED enables detection of both antibodies and antigens from a small sample volume (6 μL), distinguishes the viral antigens from those of human coronaviruses, and delivers test results in <15 min. The limits of detection (LoDs) for antibody detection are approximately 49 aM (7 fg/mL) in phosphate-buffered saline (PBS), or >3000 times more sensitive than enzyme-linked immunosorbent assay (ELISA), ∼76 aM (11 fg/mL) in human pooled serum and in the femtomolar range in diluted whole blood. For nucleocapsid protein detection, NasRED LoDs are ∼190 aM (10 fg/mL) in human saliva and ∼2 fM (100 fg/mL) in nasal fluid. Unlike centralized platforms, NasRED is a one-pot, in-solution assay without the needs for washing, labeling, expensive instrumentation, or highly trained operators. With low reagent costs and a compact system footprint, this modular digital platform is well-suited for accurate, near-patient diagnosis and screening of a wide range of infectious and chronic diseases.

Indexed as

Antibodies, ViralAntigens, ViralBiosensing TechniquesCOVID-19Metal NanoparticlesSARS-CoV-2COVID-19 Serological TestingGoldHumansLimit of DetectionSalivaAntibodies, ViralAntigens, ViralGoldantibody detectiongold nanoparticlespoint of carerapid antigen detectionSARS-CoV-2subfemtomolar sensitivity

Identifiers

PMID40788688
PMCPMC12927652

What OpenQuestion holds

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Registered trials

None linked

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.