Evidence map›Paper›PMID 42009731›Full record

ArticleScientific reports2026

Impact of extraction methods on Monte Carlo based dietary health risk assessment of potentially harmful elements in edible plants.

Agata Stolecka, Agnieszka Gruszecka-Kosowska

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Agata StoleckaDepartment of Environmental Protection, Faculty of Geology, Geophysics and Environmental Protection, AGH University of Krakow, Al. Mickiewicza 30, Kraków, 30-059, Poland. agata.wodkowska@agh.edu.pl.
Agnieszka Gruszecka-KosowskaDepartment of Environmental Protection, Faculty of Geology, Geophysics and Environmental Protection, AGH University of Krakow, Al. Mickiewicza 30, Kraków, 30-059, Poland.

Funding

AGH University of Kraków "Excellence initiative-research university" 4046
6 · The paper itself

Abstract

Accurate assessment of health risks from potentially harmful elements (PHEs) in edible plants is critical for public health. This study evaluated carcinogenic and non-carcinogenic risks of arsenic (As), cadmium (Cd), chromium (Cr), nickel (Ni), lead (Pb), antimony (Sb), tin (Sn), and thallium (Tl) in commonly consumed plants, emphasizing the impact of extraction method selection on risk estimates. Seven extraction procedures, namely TC, BCR, USEPA, ISO, UBM, SBET, and PBET, were applied to reflect different bioaccessibility scenarios. Monte Carlo simulations using Polish dietary consumption data quantified exposure and associated risks. The TC method consistently produced the highest risk values, potentially overestimating risk, whereas bioaccessibility-based methods yielded more realistic estimates. Gastric-phase extractions resulted in higher non-carcinogenic risk (HQ) values than intestinal-phase extractions. Sensitivity analysis identified PHE concentration as the main contributor to risk variability, with ingestion rate having a smaller but notable effect. These results demonstrate that health risk estimates vary substantially with extraction method and highlight the value of combining bioaccessibility-based and probabilistic modeling to improve accuracy and reduce uncertainty in dietary risk assessment of PHEs.

Indexed as

DietFood ContaminationPlants, EdibleArsenicCadmiumDietary ExposureHumansMonte Carlo MethodRisk AssessmentArsenicCadmiumBioaccessibility assaysCarcinogenic riskElemental speciationFood productsNon-carcinogenic riskProbabilistic modeling

Identifiers

PMID42009731
PMCPMC13096188

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Registered trials

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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.