ArticleRSC advances2024
A point of care sensor for detection of alcohols, aldehydes and esters in urinary metabolites of war veterans injured by sulfur mustard.
Article in RSC advances, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Rapid detection of urinary tract infection by analyzing the dried spots of biological fluids using convolutional neural networks.Scientific reports · 2026Article
- A point of care sensor for detection of alcohols, aldehydes and esters in urinary metabolites of war veterans injured by sulfur mustard.RSC advances · 2024Article
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
To discriminate between different alcoholic, aldehyde, and ester species of urine samples, a colorimetric sensor array consisting of dopamine-capped copper-silver bimetallic nanoparticles (Ag@Cu BMNPs) combined with 12 organic dyes is introduced. Based on the sensing mechanism, the nanozyme catalyzed the reactions of oxidation, dehydrogenation, and hydrolysis of volatile organic compounds. The products could alter the amount of hydronium ions in the detection media, making a variation in the color intensity of pH-sensitive indicators. Also, they could be connected to other organic dyes through nucleophilic/electrophilic or H-bonding interactions in order to form new complexes. The colorimetric responses of the sensor were visible to the naked eye and evaluated by image analysis software, thereby obtaining a unique detection pattern for each sample. The statistical data indicated that the sensor can completely distinguish between compounds with different functional groups. As a practical study, the efficiency of the sensor was investigated for the identification of the war veterans who injured by sulfur mustard in Iran-Iraq war and their differentiation from control people. Based on the output of the assay, the sensor was found to create a special color pattern for each studied group, achieving a total accuracy of 78.0% for this discrimination. The color change of the proposed sensor has a good correlation with the severity of the injury, being independent of the metabolic changes caused by the age of the participants. Accordingly, the fabricated sensor array can be a suitable tool to detect oxygen-containing compounds in environmental or biological samples.
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Registered trials
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