Evidence map›Paper›PMID 38441485›Full record

ArticleACS sensors2024

Antigen-Mimic Nanoparticles in Ultrasensitive on-Chip Integrated Anti-p53 Antibody Quantification.

Shaoyu Kang, Daohe Yuan, Robert Barber, Jason J Davis

Open access · hybridAbstract read
In one paragraph

Article in ACS sensors, 2024. 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
1.4field-weighted citation impact, top 20% of its field
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, 6 citations in OpenAlex.

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

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Shaoyu KangDepartment of Chemistry, University of Oxford, South Parks Road, Oxford OX1 3QZ, U.K.
Daohe YuanDepartment of Chemistry, University of Oxford, South Parks Road, Oxford OX1 3QZ, U.K.
Robert BarberDepartment of Chemistry, University of Oxford, South Parks Road, Oxford OX1 3QZ, U.K.
Jason J DavisDepartment of Chemistry, University of Oxford, South Parks Road, Oxford OX1 3QZ, U.K.ORCID 0000-0001-7734-1709
University of Oxford · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As a tumor-suppressing protein, p53 plays a crucial role in preventing cancer development. Its utility as an early cancer detection tool is significant, potentially enabling clinicians to forestall disease advancement and improve patient prognosis. In response to the pathological overexpression of this antigen in tumors, the prevalence of anti-p53 antibodies increases in serum, in a manner quantitatively indicative of cancer progression. This spike can be detected through techniques, such as Western blotting, immunohistochemistry, and immunoprecipitation. In this study, we present an electrochemical approach that supports ultrasensitive and highly selective anti-p53 autoantibody quantification without the use of an immuno-modified electrode. We specifically employ antigen-mimicking and antibody-capturing peptide-coated magnetic nanoparticles, along with an AC magnetic field-promoted sample mixing, prior to the presentation of Fab-captured targets to simple lectin-modified sensors. The subfemtomolar assays are highly selective and support quantification from serum-spiked samples within minutes.

Indexed as

Antigens, NeoplasmAutoantibodiesMagnetite NanoparticlesMolecular MimicryNeoplasmsTumor Suppressor Protein p53Biosensing TechniquesEarly Detection of CancerHumansAntigens, NeoplasmAutoantibodiesMagnetite NanoparticlesTumor Suppressor Protein p53antigen-mimicking peptidecancer detectionelectrochemical enzyme-amplified assaynanoparticle-assisted immunoisolationp53

Identifiers

PMID38441485
PMCPMC10964233
OpenAlexW4392456025

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.