Evidence map›Paper›PMID 39337777›Full record

ArticleMicromachines2024

A Route to the Colorimetric Detection of Alpha-Fetoprotein Based on a Smartphone.

Junjie Liu, Qingfubo Geng, Zhaoxin Geng

Abstract read
In one paragraph

Article in Micromachines, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
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  5. Article
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

3 authors.

Junjie LiuSchool of Information Engineering, Minzu University of China, Beijing 100081, China.
Qingfubo GengSchool of Information Engineering, Minzu University of China, Beijing 100081, China.
Zhaoxin GengSchool of Information Engineering, Minzu University of China, Beijing 100081, China.ORCID 0000-0003-0917-0391

Funding

the Beijing Natural Science Foundation 4232075the National Key Research and Development Plan of China, grant number 2023YFB3210400the National Natural Science Foundation of China 62274191
6 · The paper itself

Abstract

Alpha-fetoprotein (AFP) is a key marker for early cancer detection and assessment. However, the current detection methods struggle to balance accuracy with the need for decentralized medical treatment. To address this issue, a new AFP analysis platform utilizing digital image colorimetry has been developed. Functionalized gold nanoparticles act as colorimetric agents, changing from purple-red to light gray-blue when exposed to different AFP concentrations. A smartphone app captures these color changes and calculates the AFP concentration in the sample. To improve detection accuracy, a hardware device ensures uniform illumination. Testing has confirmed that this system can quantitatively analyze AFP using colorimetry. The limit of detection reached 0.083 ng/mL, and the average accuracy reached 90.81%. This innovative method enhances AFP testing by offering portability, precision, and low cost, making it particularly suitable for resource-limited areas.

Indexed as

biosensorcolorimetric detectionmicrofluidics

Identifiers

PMID39337777
PMCPMC11433964

What OpenQuestion holds

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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.