ArticleRSC advances2026
Medicinal chemistry meets nanotechnology: machine learning assisted colorimetric sensing platform for oxalic acid based on drug mediated copper oxide nanoparticles.
Article in RSC advances, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
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.
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Who cites it
1 citing paper in PubMed.
- Green Synthesis of CuO Nanoparticles Using Beta vulgaris L. Extract for Removal of Methyl Violet Dye.TheScientificWorldJournal · 2026Article
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Increased levels of oxalic acid are associated with an increased risk of kidney stone formation, which can lead to renal failure. In addition, its high concentration in the blood can lead to cardiovascular diseases. Therefore, it is vital to detect and quantify oxalic acid economically and rapidly. Copper oxide nanoparticles (CuONPs) are gaining importance as colorimetric nanosensors due to their intrinsic color change, cost-effectiveness, and easy synthesis. Paracetamol-mediated CuO NPs were synthesized through a new approach and characterized through various spectroscopic and morphological techniques. UV-visible spectroscopy confirmed the synthesis of CuO NPs through surface plasmon resonance at 225 nm. The peak at 850 cm
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Registered trials
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