Evidence map›Paper›PMID 41241661›Full record

ArticleMetabolomics : Official journal of the Metabolomic Society2025

Bioactive compound identification without fractionation: an Ocimum spp. case study.

Evelyn J Abraham, Kelsey Custer, R Teal Jordan, Joshua J Kellogg

Abstract read
In one paragraph

Article in Metabolomics : Official journal of the Metabolomic Society, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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

1 citing paper in PubMed.

  1. Review
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

4 authors.

Evelyn J AbrahamIntercollege Graduate Degree Program in Plant Biology, Pennsylvania State University, University Park, PA, 16802, USA.
Kelsey CusterDepartment of Veterinary and Biomedical Sciences, Pennsylvania State University, University Park, PA, 16802, USA.
R Teal JordanDepartment of Veterinary and Biomedical Sciences, Pennsylvania State University, University Park, PA, 16802, USA.
Joshua J KelloggIntercollege Graduate Degree Program in Plant Biology, Pennsylvania State University, University Park, PA, 16802, USA. jjk6146@psu.edu.

Funding

Multivariate Statistics and Machine Learning for Quality Control of Dried Ocimum ProductsF31AT012139 · NCCIH · PENNSYLVANIA STATE UNIVERSITY, THE · PI ABRAHAM, EVELYN · 2023 to 2024
$82k
NCCIH NIH HHS F31 AT012139USDA Hatch Project No. PEN04956, Accession No. 7006496
6 · The paper itself

Abstract

introductionIdentifying the phytochemistry underpinning a plant's observed therapeutic benefits is essential for understanding mechanisms of action and developing novel therapeutics. More recent efforts fusing global metabolomics and multivariate predictive modeling have improved compound discovery; however, these models rely on chemical variations between samples, which often necessitates at least one round of fractionation and may result in compound loss or degradation.

objectivesThis study uses multiple whole botanical extracts to explore whether a metabolome-wide association study approach can accurately identify bioactive phytochemicals without prior fractionation.

methodsWe employed 40 Ocimum extracts with a range of IC

resultsThe metabolomic profiles resulted in ca. 1600 metabolite features; implementing source-based filters, followed by LASSO dimension reduction, improved the reliability of Partial Least Squares (PLS) bioactivity predictions. The resulting model highlighted four biomarkers positively correlated with activity, one of which was putatively identified as gallic acid. Gallic acid's cytotoxicity against HT-29 cells was confirmed with the purified compound.

conclusionThis study results demonstrated that predictive modeling of botanicals using a metabolome-wide association study of extracts with no fractionation was capable of identifying biologically active compounds.

Indexed as

MetabolomicsOcimumPhytochemicalsPlant ExtractsChromatography, High Pressure LiquidHT29 CellsHumansMetabolomeTandem Mass SpectrometryPhytochemicalsPlant ExtractsBasilBiochemometricsCytotoxicityLASSO regressionMachine learningMetabolomicsOcimum

Identifiers

PMID41241661
PMCPMC12619805

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.