Literature DB >> 30117187

An assessment of applicability of existing approaches to predicting the bioaccumulation of conventional substances in nanomaterials.

Wells Utembe1, Victor Wepener2, Il Je Yu3, Mary Gulumian1,4.   

Abstract

The experimental determination of bioaccumulation is challenging, and a number of approaches have been developed for its prediction. It is important to assess the applicability of these predictive approaches to nanomaterials (NMs), which have been shown to bioaccumulate. The octanol/water partition coefficient (KOW ) may not be applicable to some NMs that are not found in either the octanol or water phases but rather are found at the interface. Thus the KOW values obtained for certain NMs are shown not to correlate well with the experimentally determined bioaccumulation. Implementation of quantitative structure-activity relationships (QSARs) for NMs is also challenging because the bioaccumulation of NMs depends on nano-specific properties such as shape, size, and surface area. Thus there is a need to develop new QSAR models based on these new nanodescriptors; current efforts appear to focus on digital processing of NM images as well as the conversion of surface chemistry parameters into adsorption indices. Water solubility can be used as a screening tool for the exclusion of NMs with short half-lives. Adaptation of fugacity/aquivalence models, which include physicochemical properties, may give some insights into the bioaccumulation potential of NMs, especially with the addition of a biota component. The use of kinetic models, including physiologically based pharmacokinetic models, appears to be the most suitable approach for predicting bioaccumulation of NMs. Furthermore, because bioaccumulation of NMs depends on a number of biotic and abiotic factors, it is important to take these factors into account when one is modeling bioaccumulation and interpreting bioaccumulation results. Environ Toxicol Chem 2018;37:2972-2988.
© 2018 SETAC. © 2018 SETAC.

Entities:  

Keywords:  Bioaccumulation; Modeling; Nanomaterials

Mesh:

Substances:

Year:  2018        PMID: 30117187     DOI: 10.1002/etc.4253

Source DB:  PubMed          Journal:  Environ Toxicol Chem        ISSN: 0730-7268            Impact factor:   3.742


  4 in total

1.  Can an InChI for Nano Address the Need for a Simplified Representation of Complex Nanomaterials across Experimental and Nanoinformatics Studies?

Authors:  Iseult Lynch; Antreas Afantitis; Thomas Exner; Martin Himly; Vladimir Lobaskin; Philip Doganis; Dieter Maier; Natasha Sanabria; Anastasios G Papadiamantis; Anna Rybinska-Fryca; Maciej Gromelski; Tomasz Puzyn; Egon Willighagen; Blair D Johnston; Mary Gulumian; Marianne Matzke; Amaia Green Etxabe; Nathan Bossa; Angela Serra; Irene Liampa; Stacey Harper; Kaido Tämm; Alexander CØ Jensen; Pekka Kohonen; Luke Slater; Andreas Tsoumanis; Dario Greco; David A Winkler; Haralambos Sarimveis; Georgia Melagraki
Journal:  Nanomaterials (Basel)       Date:  2020-12-11       Impact factor: 5.076

2.  Accumulation, Chronicity, and Induction of Oxidative Stress Regulating Genes Through Allium cepa L. Functionalized Silver Nanoparticles in Freshwater Common Carp (Cyprinus carpio).

Authors:  Rajkumar Krishnasamy Sekar; Ramkumar Arunachalam; Murugadas Anbazhagan; Sivagaami Palaniyappan; Srinivasan Veeran; Arun Sridhar; Thirumurugan Ramasamy
Journal:  Biol Trace Elem Res       Date:  2022-02-23       Impact factor: 3.738

Review 3.  Current Approaches and Techniques in Physiologically Based Pharmacokinetic (PBPK) Modelling of Nanomaterials.

Authors:  Wells Utembe; Harvey Clewell; Natasha Sanabria; Philip Doganis; Mary Gulumian
Journal:  Nanomaterials (Basel)       Date:  2020-06-29       Impact factor: 5.076

Review 4.  Meta-analysis of Bioaccumulation Data for Nondissolvable Engineered Nanomaterials in Freshwater Aquatic Organisms.

Authors:  Yuanfang Zheng; Bernd Nowack
Journal:  Environ Toxicol Chem       Date:  2022-03-30       Impact factor: 4.218

  4 in total

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