The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Direct and Indirect Toxic Effects of Engineered Nanoparticles on Algae: Role of Natural Organic Matter
Abstract
In order to assess the overall risk posed by engineered nanoparticles (ENPs), the biological effects of this emergent pollutant to aquatic ecosystems must be evaluated. We present findings from studies conducted with a diversity of ENPs (metallic, quantum dots) on a variety of freshwater and marine algae (phytoplankton) illustrating both their direct and indirect effects. We show that in general, while the surface properties of ENPs govern their aggregation behavior and ionic strength controls their dissolution, exopolymeric substances (EPS) produced by algae determine their potential to be toxic and thereby movement through the water column and food web. The production of EPS reduces the impact of ENPs (bioavailability and toxicity) and/or their ions on cellular activities of algae. It does not however directly reduce the aggregation and/or solubility of ENPs but rather affects their stability. Complicating understanding of these interactions is the great assortment of surface coatings for ENPs. This perspective is intended to highlight our current knowledge and the need for future research particularly focused on determining the fate and transport of ENPs in the aquatic environment.
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Cites
Toxic potential of materials at the nanolevel
Nel, A., Xia, T., Mädler, L., & Li, N. (2006) · Science · doi:10.1126/science.1114397 · Cited by 9,324
The Global Carbon Cycle: A Test of Our Knowledge of Earth as a System
Falkowski, P., Scholes, R. J., Boyle, E., Canadell, J., Canfield, D., Elser, J., Gruber, N., Hibbard, K., Högberg, P., Linder, S., et al. (2000) · Science · doi:10.1126/science.290.5490.291 · Cited by 2,177
Jiao, N., Herndl, G. J., Hansell, D. A., Benner, R., Kattner, G., Wilhelm, S. W., Kirchman, D. L., Weinbauer, M. G., Luo, T., Chen, F., et al. (2010) · Nature Reviews Microbiology · doi:10.1038/nrmicro2386 · Cited by 1,780
Xiao, G. G., Wang, M., Li, N., Loo, J. A., & Nel, A. E. (2003) · Journal of Biological Chemistry · doi:10.1074/jbc.m306423200 · Cited by 428
Evolutionary inheritance of elemental stoichiometry in phytoplankton
Quigg, A., Irwin, A. J., & Finkel, Z. V. (2011) · Proceedings of the Royal Society B: Biological Sciences · doi:10.1098/rspb.2010.1356 · Cited by 144
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Cited by
Schwab, F., Zhai, G., Kern, M., Turner, A., Schnoor, J. L., & Wiesner, M. R. (2016) · Nanotoxicology · doi:10.3109/17435390.2015.1048326 · Cited by 872
Natural inorganic nanoparticles – formation, fate, and toxicity in the environment
Sharma, V. K., Filip, J., Zboril, R., & Varma, R. S. (2015) · Chemical Society Reviews · doi:10.1039/c5cs00236b · Cited by 488
Bergami, E., Pugnalini, S., Vannuccini, M. L., Manfra, L., Faleri, C., Savorelli, F., Dawson, K. A., & Corsi, I. (2017) · Aquatic Toxicology · doi:10.1016/j.aquatox.2017.06.008 · Cited by 423
Fu, D., Zhang, Q., Fan, Z., Qi, H., Wang, Z., & Peng, L. (2019) · Aquatic Toxicology · doi:10.1016/j.aquatox.2019.105319 · Cited by 322
Characteristics of Pine Gasification Ash and its Effects on Chlamydomonas debaryana Growth
Li, R., Zhang, B., Xiu, S., Wang, H., Boaten, N. A. B., Holmes, B. M., Wang, L., & Shahbazi, A. (2016) · BioResources · doi:10.15376/biores.11.1.1919-1929 · Cited by 5
Metadata
- Authors
- Quigg, A., Chin, W.-C., Chen, C.-S., Zhang, S., Jiang, Y., Miao, A.-J., Schwehr, K. A., Xu, C., & Santschi, P. H.
- Venue
- ACS Sustainable Chemistry & Engineering
- Publisher
- American Chemical Society (ACS)
- Published
- 2013-06-03
- Volume
- 1
- Issue
- 7
- Pages
- 686-702
- ISSN
- 2168-0485 (ISSN-L)
- OpenAlex
- W2323944449
- Cited by
- 196
- References
- 5
- FWCI
- 5.77
- Type
- journal article
- Language
- en
- Open access
- closed
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- Quigg, A., Chin, W.-C., Chen, C.-S., Zhang, S., Jiang, Y., Miao, A.-J., Schwehr, K. A., Xu, C., & Santschi, P. H. (2013). Direct and Indirect Toxic Effects of Engineered Nanoparticles on Algae: Role of Natural Organic Matter. ACS Sustainable Chemistry & Engineering. https://doi.org/10.1021/sc400103x
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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