Analysis of plastic-related chemical contaminants in human milk using targeted and non-targeted screening
Notice bibliographique
Résumé
Human milk, which is vital for infant growth and development, may contain various xenobiotics, highlighting the need for its comprehensive biomonitoring on a regular basis. While traditional targeted approaches are widely employed for monitoring contaminants in biological samples around the world, numerous unknown chemicals are often overlooked. Plastic-related contaminants (PRCs), ubiquitous in the environment, represent one of the most extensive contaminants detected in human milk; bisphenols are one of the dominant classes of PRCs that have been studied. Despite the abundance of studies, however, data are lacking with respect to the levels of these contaminants in certain matrices and geographical regions. Furthermore, the use of targeted analysis (TA) limits the detection of previously underreported or unknown PRCs (i.e. preservatives, UV filters, synthetic antioxidants), suggesting the need to develop innovative tools such as non-targeted analysis (NTA) coupled with high-resolution mass spectrometry to detect these substances.The purpose of this study was to detect and identify the presence of classes of PRCs, focusing on bisphenols and parabens, that may be present in human milk. Specifically, the goal was to quantitatively assess and compare bisphenol types and levels across regions, to identify related unknowns along with other common and unusual parabens, as well as to evaluate their conjugation potential in human milk by employing both TA and NTA. There is a detailed review of all detected environmental contaminants in human milk, as well as highlights of all previous studies conducted on PRCs in Chapter 2. Limitations of the predominant use of TA, obstructing risk assessment and toxicity evaluation for chemicals present in human milk in terms of chemical mixtures, are also described. Evidently, there is a need for further data to fill data gaps with respect to the PRCs, such as bisphenols, in specific countries. To address this, bisphenols were detected in human milk from Canada and South Africa (Vhembe and Pretoria), a country where data are scarce (Chapter 3). An efficient QuEChERS extraction method was developed for the TA of 9 selected bisphenols in human milk. BPA was the predominant bisphenol detected in South African human milk, followed by BPS and BPAF. BPS was the exclusive bisphenol detectable in milk from Montreal, suggesting differences in exposure to bisphenols in these two countries and providing crucial insights for future investigations by health officials. The TA of human milk in Chapter 3 also reinforced the need for NTA as a valuable emerging tool to detect and identify different unknown contaminants. A customized database library for the detection of bisphenol-related unknowns using NTA is introduced in Chapter 4. Successful workflow implementation, with the extracted data using the same extraction method as in Chapter 3, was used to identify different bisphenol S related-unknowns that are used in thermal labels, along with different synthetic antioxidants and UV absorbers. Among these compounds, 2 synthetic antioxidants-related unknowns (including 1 metabolite) have not been reported previously in human milk studies.In Chapter 5, the use of NTA is extended for the identification of common and unusual parabens, along with other PRCs of interest. Seven parabens, various phthalate metabolites, and per- and polyfluoroalkyl substances were detected in human milk, including a unique paraben exclusive to South Africa. The detection of these different and unexpected PRCs highlights the usefulness of applying NTA in human milk biomonitoring. Together, this research has demonstrated that integrating TA with NTA in human milk biomonitoring can facilitate the detection of unexpected contaminants and is both cost effective and time efficient. This research also emphasizes the significance of applying NTA for the detection of family-specific contaminants, providing regulatory agencies with essential information on their presence for regular human milk biomonitoring
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».