Evidence map›Paper›PMID 38297148›Full record

ArticleScientific reports2024

A digital image colorimetry system based on smart devices for immediate and simultaneous determination of enzyme-linked immunosorbent assays.

Shaghayegh Mirhosseini, Aryanaz Faghih Nasiri, Fatemeh Khatami, Akram Mirzaei, Seyed Mohammad Kazem Aghamir, Mohammadreza Kolahdouz

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.8field-weighted citation impact, top 10% 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

7 citing papers in PubMed, 15 citations in OpenAlex.

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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

6 authors at 2 institutions in 1 country.

Shaghayegh MirhosseiniSchool of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran.
Aryanaz Faghih NasiriSchool of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran.
Fatemeh KhatamiUrology Research Center, Tehran University of Medical Sciences, Tehran, Iran.
Akram MirzaeiUrology Research Center, Tehran University of Medical Sciences, Tehran, Iran.
Seyed Mohammad Kazem AghamirUrology Research Center, Tehran University of Medical Sciences, Tehran, Iran. mkaghamir@tums.ac.ir.
Mohammadreza KolahdouzSchool of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran. kolahdouz@ut.ac.ir.
Tehran University of Medical Sciences · IRUniversity of Tehran · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Standard enzyme-linked immunosorbent assays based on microplates are frequently utilized for various molecular sensing, disease screening, and nanomedicine applications. Comparing this multi-well plate batched analysis to non-batched or non-standard testing, the diagnosis expenses per patient are drastically reduced. However, the requirement for rather big and pricey readout instruments prevents their application in environments with limited resources, especially in the field. In this work, a handheld cellphone-based colorimetric microplate reader for quick, credible, and novel analysis of digital images of human cancer cell lines at a reasonable price was developed. Using our in-house-developed app, images of the plates are captured and sent to our servers, where they are processed using a machine learning algorithm to produce diagnostic results. Using FDA-approved human epididymis protein of ovary IgG (HE4), prostate cancer cell line (PC3), and bladder cancer cell line (5637) ELISA tests, we successfully examined this mobile platform. The accuracies for the HE4, PC3, and 5637 tests were 93%, 97.5%, and 97.2%, respectively. By contrasting the findings with the measurements made using optical absorption EPOCH microplate readers and optical absorption Tecan microplate readers, this approach was found to be accurate and effective. As a result, digital image colorimetry on smart devices offered a practical, user-friendly, affordable, precise, and effective method for quickly identifying human cancer cell lines. Thus, healthcare providers might use this portable device to carry out high-throughput illness screening, epidemiological investigations or monitor vaccination campaigns.

Indexed as

Cell PhoneProstatic NeoplasmsCell LineColorimetryEnzyme-Linked Immunosorbent AssayHumansMale

Identifiers

PMID38297148
PMCPMC10830485
OpenAlexW4391403553

What OpenQuestion holds

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Registered trials

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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.