ArticlePharmaceutics2024
Chemical Composition and Bioactivity Dataset Integration to Identify Antiproliferative Compounds in
Article in Pharmaceutics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
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Authors and funding
3 authors.
Funding
Abstract
BACKGROUND/
objectives
methodsThe integration of liquid chromatography-mass spectrometry (LC-MS)-based chemical composition data with antiproliferative activity against three cancer cell lines-PC-3 (prostate adenocarcinoma), SiHa (cervical carcinoma), and A549 (lung carcinoma)-as well as a normal mouse fibroblast line (L929) was performed by covariate analysis. These compounds were subsequently isolated and structurally characterized using spectroscopic methods.
resultsThrough covariate statistics, seven
conclusionsThese findings highlight the potential of
Indexed as
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Registered trials
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