Introducing of modeling techniques in the research of POPs in breast milk – A pilot study
Samo za registrovane korisnike
2019
Autori
Jovanović, GordanaHerceg Romanić, Snježana
Stojić, Andreja
Klinčić, Darija
Matek Sarić, Marijana
Grzunov Letinić, Judita
Popović, Aleksandar R.
Članak u časopisu (Objavljena verzija)
Metapodaci
Prikaz svih podataka o dokumentuApstrakt
This study used advanced statistical and machine learning methods to investigate organochlorine pesticides (OCPs) and polychlorinated biphenyls (PCBs) in breast milk, assuming that in a complex biological mixture, the pollutants emitted from the same source or with similar properties are statistically interrelated and possibly exhibit non-linear dynamics. The elaborated analyses such as Unmix source apportionment characterized individual source groups, while guided regularized random forest indicated the pollutant dependence on the ortho-chlorine atom attached to the congener's phenyl ring and mother's age. Mutual associations among PCBs were further discussed, but the results implied they were mostly not related to child delivery. PCB congeners −153, −180, −170, −118, −156, −105, and −138 appeared to be compounds of the outmost importance for mutual prediction with reference to their interrelations regarding chemical structure and metabolic processes in the mother's body. Finally, mac...hine learning methods, which provided prediction relative errors lower than 30% and correlation coefficients higher than 0.90, suggested a possible strong non-linear relationship among the pollutants and consequently, the complexity of their pathways in the breast milk.
Ključne reči:
Age / Feature selection / Machine learning / Parity / Persistent organic pollutants (POPs) / UnmixIzvor:
Ecotoxicology and Environmental Safety, 2019, 172, 341-347Izdavač:
- Elsevier
Finansiranje / projekti:
- Croatian Science Foundation (Project OPENTOX, No. 8366)
- Istraživanje klimatskih promena i njihovog uticaja na životnu sredinu - praćenje uticaja, adaptacija i ublažavanje (RS-MESTD-Integrated and Interdisciplinary Research (IIR or III)-43007)
- Primene niskotemperaturnih plazmi u biomedicini, zaštiti čovekove okoline i nanotehnologijama (RS-MESTD-Integrated and Interdisciplinary Research (IIR or III)-41011)
DOI: 10.1016/j.ecoenv.2019.01.087
ISSN: 0147-6513
WoS: 000460196000045
Scopus: 2-s2.0-85060897792
Kolekcije
Institucija/grupa
Hemijski fakultet / Faculty of ChemistryTY - JOUR AU - Jovanović, Gordana AU - Herceg Romanić, Snježana AU - Stojić, Andreja AU - Klinčić, Darija AU - Matek Sarić, Marijana AU - Grzunov Letinić, Judita AU - Popović, Aleksandar R. PY - 2019 UR - https://cherry.chem.bg.ac.rs/handle/123456789/2836 AB - This study used advanced statistical and machine learning methods to investigate organochlorine pesticides (OCPs) and polychlorinated biphenyls (PCBs) in breast milk, assuming that in a complex biological mixture, the pollutants emitted from the same source or with similar properties are statistically interrelated and possibly exhibit non-linear dynamics. The elaborated analyses such as Unmix source apportionment characterized individual source groups, while guided regularized random forest indicated the pollutant dependence on the ortho-chlorine atom attached to the congener's phenyl ring and mother's age. Mutual associations among PCBs were further discussed, but the results implied they were mostly not related to child delivery. PCB congeners −153, −180, −170, −118, −156, −105, and −138 appeared to be compounds of the outmost importance for mutual prediction with reference to their interrelations regarding chemical structure and metabolic processes in the mother's body. Finally, machine learning methods, which provided prediction relative errors lower than 30% and correlation coefficients higher than 0.90, suggested a possible strong non-linear relationship among the pollutants and consequently, the complexity of their pathways in the breast milk. PB - Elsevier T2 - Ecotoxicology and Environmental Safety T1 - Introducing of modeling techniques in the research of POPs in breast milk – A pilot study VL - 172 SP - 341 EP - 347 DO - 10.1016/j.ecoenv.2019.01.087 ER -
@article{ author = "Jovanović, Gordana and Herceg Romanić, Snježana and Stojić, Andreja and Klinčić, Darija and Matek Sarić, Marijana and Grzunov Letinić, Judita and Popović, Aleksandar R.", year = "2019", abstract = "This study used advanced statistical and machine learning methods to investigate organochlorine pesticides (OCPs) and polychlorinated biphenyls (PCBs) in breast milk, assuming that in a complex biological mixture, the pollutants emitted from the same source or with similar properties are statistically interrelated and possibly exhibit non-linear dynamics. The elaborated analyses such as Unmix source apportionment characterized individual source groups, while guided regularized random forest indicated the pollutant dependence on the ortho-chlorine atom attached to the congener's phenyl ring and mother's age. Mutual associations among PCBs were further discussed, but the results implied they were mostly not related to child delivery. PCB congeners −153, −180, −170, −118, −156, −105, and −138 appeared to be compounds of the outmost importance for mutual prediction with reference to their interrelations regarding chemical structure and metabolic processes in the mother's body. Finally, machine learning methods, which provided prediction relative errors lower than 30% and correlation coefficients higher than 0.90, suggested a possible strong non-linear relationship among the pollutants and consequently, the complexity of their pathways in the breast milk.", publisher = "Elsevier", journal = "Ecotoxicology and Environmental Safety", title = "Introducing of modeling techniques in the research of POPs in breast milk – A pilot study", volume = "172", pages = "341-347", doi = "10.1016/j.ecoenv.2019.01.087" }
Jovanović, G., Herceg Romanić, S., Stojić, A., Klinčić, D., Matek Sarić, M., Grzunov Letinić, J.,& Popović, A. R.. (2019). Introducing of modeling techniques in the research of POPs in breast milk – A pilot study. in Ecotoxicology and Environmental Safety Elsevier., 172, 341-347. https://doi.org/10.1016/j.ecoenv.2019.01.087
Jovanović G, Herceg Romanić S, Stojić A, Klinčić D, Matek Sarić M, Grzunov Letinić J, Popović AR. Introducing of modeling techniques in the research of POPs in breast milk – A pilot study. in Ecotoxicology and Environmental Safety. 2019;172:341-347. doi:10.1016/j.ecoenv.2019.01.087 .
Jovanović, Gordana, Herceg Romanić, Snježana, Stojić, Andreja, Klinčić, Darija, Matek Sarić, Marijana, Grzunov Letinić, Judita, Popović, Aleksandar R., "Introducing of modeling techniques in the research of POPs in breast milk – A pilot study" in Ecotoxicology and Environmental Safety, 172 (2019):341-347, https://doi.org/10.1016/j.ecoenv.2019.01.087 . .