Effects of Mixtures of Engineered Nanoparticles and Metallic Pollutants on Aquatic Organisms

Abstract

In aquatic environment, engineered nanoparticles (ENPs) are present as complex mixtures with other pollutants, such as trace metals, which could result in synergism, additivity or antagonism of their combined effects. Despite the fact that the toxicity and environmental risk of the ENPs have received extensive attention in the recent years, the interactions of ENPs with other pollutants and the consequent effects on aquatic organisms represent an important challenge in (nano)ecotoxicology. The present review provides an overview of the state-of-the-art and critically discusses the existing knowledge on combined effects of mixtures of ENPs and metallic pollutants on aquatic organisms. The specific emphasis is on the adsorption of metallic pollutants on metal-containing ENPs, transformation and bioavailability of ENPs and metallic pollutants in mixtures. Antagonistic, additive and synergistic effects observed in aquatic organisms co-exposed to ENPs and metallic pollutants are discussed in the case of “particle-proof” and “particle-ingestive” organisms. This knowledge is important in developing efficient strategies for sound environmental impact assessment of mixture exposure in complex environments.

A density gradient centrifugation method for rapid separation of nanoTiO2 and TiO2 aggregates from microalgal cells in complex mixtures with mercury

“…In the aquatic environments, contaminants are found as complex mixtures [7 , 10] . Due to the extensive use of engineered nanomaterials (ENMs) in industry and consumer products, a variety of ENMs is inevitably disposed or released into the environment [5 , 6] , including titanium dioxide nanoparticles (nanoTiO 2 ) [11 , 12] .…”

Improving Suppression of Hemipteran Vectors and Bacterial Pathogens of Citrus and Solanaceous Plants: Advances in Antisense Oligonucleotides (FANA)

“…Advances in medical applications includes nanoparticle-assisted delivery is rapidly developing a wide variety of molecules (Hammond et al, 2021;Mendonça et al, 2021). These novel materials may provide greater utility of biopesticide products in agriculture (Vega-Vásquez et al, 2020), aided by bioengineering and novel production methods to reduce costs or to add unique traits (Hochella et al, 2019), providing benefits across the environmental sciences (Lespes et al, 2020;Li et al, 2020;Slaveykova et al, 2020). Combined all these technological advances support the movement toward that day when FANA biopesticide are used to suppress invasive arthropod pests and insect vectors of pathogens to reduce threats to food security, or health of human and animal populations (Jiang et al, 2019;Adeyinka et al, 2020;Berber et al, 2020;Fletcher et al, 2020;He and Creasey Krainerm, 2020;Huang et al, 2020;Kleter, 2020;Mesterházy et al, 2020;Vega-Vásquez et al, 2020).…”

Aquatic Toxicity Effects and Risk Assessment of ‘Form Specific’ Product-Released Engineered Nanomaterials

“…Since SUN1, CA1 and SK1's NEPs of SUN1, CA1, and SK1 released binary PR-ENMs [15], the principal toxicant between the two or combined toxicity contribution of the binary PR-ENMs was determined using a predictive model described elsewhere [123,124]. Briefly, the predictive model is based on probability theory, defined as P(E) = P (x) + P (y) − (P x *P y /100), where P x and P y are the inhibition induced by chemical x and y, respectively [123,124]. The procedure compares the effects measured in the experiment, referred to as the observed effect, P(O), with the theoretically expected/predicted effect P(E) [123,124].…”

“…Briefly, the predictive model is based on probability theory, defined as P(E) = P (x) + P (y) − (P x *P y /100), where P x and P y are the inhibition induced by chemical x and y, respectively [123,124]. The procedure compares the effects measured in the experiment, referred to as the observed effect, P(O), with the theoretically expected/predicted effect P(E) [123,124]. The results were considered to have a synergistic or antagonistic effect when the observed effects [P(O)] and the theoretical effects [P(E] were found to be significantly different (p < 0.05).…”