Evidence map›Paper›PMID 41149749›Full record

ArticleJournal of xenobiotics2025

Advanced Characterization of Environmental Pollutant Metabolism in Human Skin.

Rafael Reis, Martine Zanini, Guillaume Lereaux, Ariane Dimitrov, Samia Boudah

Abstract read
In one paragraph

Article in Journal of xenobiotics, 2025. 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

5 authors.

Rafael ReisDepartment of Environmental Toxicology, Eawag, Swiss Federal Institute of Aquatic Science and Technology, 8600 Dübendorf, Switzerland.
Martine ZaniniExposome Discovery Domain, L'Oreal Research & Innovation, 93600 Aulnay sous Bois, France.
Guillaume LereauxADME Laboratory, L'Oréal Research & Innovation, 93600 Aulnay sous Bois, France.
Ariane DimitrovExposome Discovery Domain, L'Oreal Research & Innovation, 93600 Aulnay sous Bois, France.
Samia BoudahAnalytical Chemistry Department, L'Oréal Research & Innovation, 93600 Aulnay sous Bois, France.ORCID 0000-0002-1801-1416

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ultrafine particles (UFPs) containing polycyclic aromatic hydrocarbons (PAHs) benzo[a]pyrene (BaP), are linked to pollution-induced health concerns, with skin being highly susceptible to contamination. Understanding the metabolic fate of these environmental pollutants in the skin is crucial. Moreover, traditional in vitro models often lack metabolic competency, while animal testing raises ethical concerns. This study introduces a novel approach combining stable isotope labeling (SIL) and liquid chromatography-high-resolution mass spectrometry (LC-HRMS) to investigate BaP metabolism. The physiologically relevant 3D reconstructed human epidermis (RHE) model was used. RHE models were exposed to BaP and deuterium-labeled BaP (BaP-d12). These analyses, followed by data analysis incorporating stable isotope filtering, revealed the presence of five distinct BaP phase I metabolites, including mono-hydroxylated, dihydroxylated, and quinone derivatives. This study demonstrates the power of coupling stable isotope labeling with LC-HRMS for the comprehensive characterization of BaP metabolic pathways in human skin. The identification of specific metabolites enhances our understanding of BaP detoxification mechanisms and their potential adverse effects. This analytical approach holds promise for investigating the metabolic fate of various other environmental pollutants.

Indexed as

data miningisotope labelingLC-HRMSPAHskin metabolism

Identifiers

PMID41149749
PMCPMC12565309

What OpenQuestion holds

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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.