Evidence map›Paper›PMID 38081872›Full record

ArticleScientific reports2023

Smartphone based colorimetric approach for quantitative determination of uric acid using Image J.

Samar H Elagamy, Latifa Adly, Mohamed Ahmed Abdel Hamid

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

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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

10 citing papers in PubMed.

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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

3 authors.

Samar H ElagamyDepartment of Pharmaceutical Analytical Chemistry, Faculty of Pharmacy, Tanta University, Tanta, Egypt. samar.elagamy@pharm.tanta.edu.eg.
Latifa AdlyDepartment of Pharmaceutical Analytical Chemistry, Faculty of Pharmacy, Tanta University, Tanta, Egypt.
Mohamed Ahmed Abdel HamidDepartment of Pharmaceutical Analytical Chemistry, Faculty of Pharmacy, Tanta University, Tanta, Egypt.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recently, significant attention has been directed towards digital image colorimetry DIC using mobile applications or available software programs, which offer the advantage of analyzing samples without the need for sophisticated instruments. One such image processing program is Image J, widely used for obtaining quantitative information from scientific images. Image J could measure the color intensities by quantifying of the RGB (red-green-blue) gray levels across the images of colored substances. These values are correlated to the color intensities through conversion to CMY (cyan-magenta-yellow) values which are proportional to the color intensities. The objective of this study is to develop an innovative analytical method for the quantitative determination of uric acid using Image J for color quantification. Image J was utilized to analyze images captured by smart phone for successive concentrations of uric acid that were previously treated with phosphotungstate to develop a blue color. The proposed method has been applied for determination of uric acid in real urine using standard addition method and the results were compared with UV/VIS spectrophotometry as a reference method. In this research, we will also assess the effectiveness of quantitative analysis using Image J in comparison to a mobile application, namely RGB Color Detector.

Indexed as

ColorimetryMobile ApplicationsSmartphoneSpectrophotometryUric AcidUric Acid

Identifiers

PMID38081872
PMCPMC10713523

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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.