Patterns of PCB-138 Occurrence in the Breast Milk of Primiparae and Multiparae Using SHapley Additive exPlanations Analysis
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Authors
Jovanović, GordanaMatek Sarić, Marijana
Herceg Romanić, Snježana
Stanišić, Svetlana M.
Mitrović Dankulov, Marija
Popović, Aleksandar R.

Perišić, Mirjana
Pap, Endre
Book part (Published version)

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Breastfeeding provides numerous health benefits for newborns by meeting infants’ nutritional needs and supporting associated immunological protection. Maternal milk is high in fat, and therefore, represents a very suitable medium for the bioaccumulation of lipophilic pollutants, such as organochlorine pesticides (OCPs) and polychlorinated biphenyls (PCBs). This makes breast milk the infant’s primary source of postnatal exposure to persistent toxic xenobiotics. In this study, we applied a novel SHapley Additive exPlanations (SHAP) method to examine the key parameters that govern the distribution of PCB-138, an indicator of non-dioxin congeners, in the mother’s milk. According to the accuracy metrics, the eXtreme Gradient Boosting regression was employed successfully, with a predicted/observed relative error below 20% and a high correlation coefficient (r === 0.97), for modeling the relationships between PCB-138 and other non-dioxin congeners, the mother’s age, and the number of births. ...According to the results, PCB-156, PCB-180, HCB, HCH and PCB-118 have a major impact, while PCB-28, PCB-52 and PCB-189 have a minor impact on PCB-138 distribution in breast milk. Similar contaminant behaviors, which belong to both the indicator congener group (−28, −52, −180) and the toxicologically relevant PCBs (−118, −189), were also noted. The SHAP conclusions were only partially consistent with the results of the correlation analysis suggesting that POPs exhibit non-linear dynamics and interrelations. Therefore, current knowledge on the contamination of complex biomatrices would benefit from further detailed analyses of pollutant intermittent relationships.
Keywords:
Human biomonitoring / Organochlorine pesticides (OCPs) / Persistent organic pollutants (POPs) / Polychlorinated biphenyls (PCBs) / SHapley Additive exPlanations (SHAP)Source:
Artificial Intelligence: Theory and Applications, 2021, 191-206Publisher:
- Springer International Publishing
Funding / projects:
- ATLAS - Artificial Intelligence Theoretical Foundations for Advanced Spatial-Temporal Modelling of Data and Processing (RS-6524105)
- Bilateral project between Serbia and Croatia (No. 337-00-205/2019-09/22)
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Institution/Community
Hemijski fakultet / Faculty of ChemistryTY - CHAP AU - Jovanović, Gordana AU - Matek Sarić, Marijana AU - Herceg Romanić, Snježana AU - Stanišić, Svetlana M. AU - Mitrović Dankulov, Marija AU - Popović, Aleksandar R. AU - Perišić, Mirjana AU - Pap, Endre PY - 2021 UR - https://cherry.chem.bg.ac.rs/handle/123456789/4743 AB - Breastfeeding provides numerous health benefits for newborns by meeting infants’ nutritional needs and supporting associated immunological protection. Maternal milk is high in fat, and therefore, represents a very suitable medium for the bioaccumulation of lipophilic pollutants, such as organochlorine pesticides (OCPs) and polychlorinated biphenyls (PCBs). This makes breast milk the infant’s primary source of postnatal exposure to persistent toxic xenobiotics. In this study, we applied a novel SHapley Additive exPlanations (SHAP) method to examine the key parameters that govern the distribution of PCB-138, an indicator of non-dioxin congeners, in the mother’s milk. According to the accuracy metrics, the eXtreme Gradient Boosting regression was employed successfully, with a predicted/observed relative error below 20% and a high correlation coefficient (r === 0.97), for modeling the relationships between PCB-138 and other non-dioxin congeners, the mother’s age, and the number of births. According to the results, PCB-156, PCB-180, HCB, HCH and PCB-118 have a major impact, while PCB-28, PCB-52 and PCB-189 have a minor impact on PCB-138 distribution in breast milk. Similar contaminant behaviors, which belong to both the indicator congener group (−28, −52, −180) and the toxicologically relevant PCBs (−118, −189), were also noted. The SHAP conclusions were only partially consistent with the results of the correlation analysis suggesting that POPs exhibit non-linear dynamics and interrelations. Therefore, current knowledge on the contamination of complex biomatrices would benefit from further detailed analyses of pollutant intermittent relationships. PB - Springer International Publishing T2 - Artificial Intelligence: Theory and Applications T1 - Patterns of PCB-138 Occurrence in the Breast Milk of Primiparae and Multiparae Using SHapley Additive exPlanations Analysis SP - 191 EP - 206 DO - 10.1007/978-3-030-72711-6_11 ER -
@inbook{ author = "Jovanović, Gordana and Matek Sarić, Marijana and Herceg Romanić, Snježana and Stanišić, Svetlana M. and Mitrović Dankulov, Marija and Popović, Aleksandar R. and Perišić, Mirjana and Pap, Endre", year = "2021", abstract = "Breastfeeding provides numerous health benefits for newborns by meeting infants’ nutritional needs and supporting associated immunological protection. Maternal milk is high in fat, and therefore, represents a very suitable medium for the bioaccumulation of lipophilic pollutants, such as organochlorine pesticides (OCPs) and polychlorinated biphenyls (PCBs). This makes breast milk the infant’s primary source of postnatal exposure to persistent toxic xenobiotics. In this study, we applied a novel SHapley Additive exPlanations (SHAP) method to examine the key parameters that govern the distribution of PCB-138, an indicator of non-dioxin congeners, in the mother’s milk. According to the accuracy metrics, the eXtreme Gradient Boosting regression was employed successfully, with a predicted/observed relative error below 20% and a high correlation coefficient (r === 0.97), for modeling the relationships between PCB-138 and other non-dioxin congeners, the mother’s age, and the number of births. According to the results, PCB-156, PCB-180, HCB, HCH and PCB-118 have a major impact, while PCB-28, PCB-52 and PCB-189 have a minor impact on PCB-138 distribution in breast milk. Similar contaminant behaviors, which belong to both the indicator congener group (−28, −52, −180) and the toxicologically relevant PCBs (−118, −189), were also noted. The SHAP conclusions were only partially consistent with the results of the correlation analysis suggesting that POPs exhibit non-linear dynamics and interrelations. Therefore, current knowledge on the contamination of complex biomatrices would benefit from further detailed analyses of pollutant intermittent relationships.", publisher = "Springer International Publishing", journal = "Artificial Intelligence: Theory and Applications", booktitle = "Patterns of PCB-138 Occurrence in the Breast Milk of Primiparae and Multiparae Using SHapley Additive exPlanations Analysis", pages = "191-206", doi = "10.1007/978-3-030-72711-6_11" }
Jovanović, G., Matek Sarić, M., Herceg Romanić, S., Stanišić, S. M., Mitrović Dankulov, M., Popović, A. R., Perišić, M.,& Pap, E.. (2021). Patterns of PCB-138 Occurrence in the Breast Milk of Primiparae and Multiparae Using SHapley Additive exPlanations Analysis. in Artificial Intelligence: Theory and Applications Springer International Publishing., 191-206. https://doi.org/10.1007/978-3-030-72711-6_11
Jovanović G, Matek Sarić M, Herceg Romanić S, Stanišić SM, Mitrović Dankulov M, Popović AR, Perišić M, Pap E. Patterns of PCB-138 Occurrence in the Breast Milk of Primiparae and Multiparae Using SHapley Additive exPlanations Analysis. in Artificial Intelligence: Theory and Applications. 2021;:191-206. doi:10.1007/978-3-030-72711-6_11 .
Jovanović, Gordana, Matek Sarić, Marijana, Herceg Romanić, Snježana, Stanišić, Svetlana M., Mitrović Dankulov, Marija, Popović, Aleksandar R., Perišić, Mirjana, Pap, Endre, "Patterns of PCB-138 Occurrence in the Breast Milk of Primiparae and Multiparae Using SHapley Additive exPlanations Analysis" in Artificial Intelligence: Theory and Applications (2021):191-206, https://doi.org/10.1007/978-3-030-72711-6_11 . .