CoChat
Sign Up
Cited by 83

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

A functional assay-based strategy for nanomaterial risk forecasting

Hendren, Christine Ogilvie, Lowry, Gregory V., Unrine, Jason M., Wiesner, Mark R.·2015·Science of The Total Environment
DOI 10.1016/j.scitotenv.2015.06.100
Open this paper in CoChat — free account

Abstract

The study of nanomaterial impacts on environment, health and safety (nanoEHS) has been largely predicated on the assumption that exposure and hazard can be predicted from physical-chemical properties of nanomaterials. This approach is rooted in the view that nanoöbjects essentially resemble chemicals with additional particle-based attributes that must be included among their intrinsic physical-chemical descriptors. With the exception of the trivial case of nanomaterials made from toxic or highly reactive materials, this approach has yielded few actionable guidelines for predicting nanomaterial risk. This article addresses inherent problems in structuring a nanoEHS research strategy based on the goal of predicting outcomes directly from nanomaterial properties, and proposes a framework for organizing data and designing integrated experiments based on functional assays (FAs). FAs are intermediary, semi-empirical measures of processes or functions within a specified system that bridge the gap between nanomaterial properties and potential outcomes in complex systems. The three components of a functional assay are standardized protocols for parameter determination and reporting, a theoretical context for parameter application and reference systems. We propose the identification and adoption of reference systems where FAs may be applied to provide parameter estimates for environmental fate and effects models, as well as benchmarks for comparing the results of FAs and experiments co…

Overview

Integrity signals

Registry

Crossref · 10.1016/j.scitotenv.2015.06.100

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Citations

Cites

Show all 1 references

Research works printed but not linked: 60

  1. Alvarez, 2009, Research priorities to advance eco-responsible nanotechnology, ACS Nano, 3, 1616, 10.1021/nn9006835 · DOI
  2. Barton, 2014, Theory and methodology for determining nanoparticle affinity for heteroaggregation in environmental matrices using batch measurements, Environ. Eng. Sci., 31, 421, 10.1089/ees.2013.0472 · DOI
  3. Bertani, 2004, Lysogeny at mid-twentieth century: P1, P2 and other experimental systems, J. Bacteriol., 186, 595, 10.1128/JB.186.3.595-600.2004 · DOI
  4. Boeije, 1999, Adaptation of the CAS test system and synthetic sewage for biological nutrient removal: part I: development of a new synthetic sewage, Chemosphere, 38, 699, 10.1016/S0045-6535(98)00311-7 · DOI
  5. Bone, 2012, Biotic and abiotic interactions in aquatic microcosms determine fate and toxicity of Ag nanoparticles: part 2 — toxicity and chemical speciation, Environ. Sci. Technol., 46, 6925, 10.1021/es204683m · DOI
  6. Boverhof, 2010, Nanomaterial characterization: considerations and needs for hazard assessment and safety evaluation, Anal. Bioanal. Chem., 396, 953, 10.1007/s00216-009-3103-3 · DOI
  7. Dale, 2013, Modeling nanosilver transformations in freshwater sediments, Environ. Sci. Technol., 47, 12920, 10.1021/es402341t · DOI
  8. Dobias, 2013, Silver release from silver nanoparticles in natural waters, Environ. Sci. Technol., 47, 4140, 10.1021/es304023p · DOI
  9. Elimelech, 1990, Effect of particle size on collision efficiency in the deposition of brownian particles with electrostatic energy barriers, Langmuir, 6, 1153, 10.1021/la00096a023 · DOI
  10. Ernstberger, 2002, Measurement and dynamic modeling of trace metal mobilization in soils using DGT and DIFS, Environ. Sci. Technol., 36, 349, 10.1021/es010917d · DOI
  11. Ernstberger, 2005, Desorption kinetics of Cd, Zn, and Ni measured in soils by DGT, Environ. Sci. Technol., 39, 1591, 10.1021/es048534d · DOI
  12. Fabrega, 2011, Silver nanoparticles: behaviour and effects in the aquatic environment, Environ. Int., 37, 517, 10.1016/j.envint.2010.10.012 · DOI
  13. Gal, 2001, About a synthetic saliva for in vitro studies, Talanta, 53, 1103, 10.1016/S0039-9140(00)00618-4 · DOI
  14. Gondikas, 2012, Cysteine-induced modifications of zero-valent silver nanomaterials: implications for particle surface chemistry, aggregation, dissolution, and silver speciation, Environ. Sci. Technol., 46, 7037, 10.1021/es3001757 · DOI
  15. Harper, 1998, Kinetics of metal exchange between solids and solutions in sediments and soils interpreted from DGT measured fluxes, Geochim. Cosmochim. Acta, 62, 2757, 10.1016/S0016-7037(98)00186-0 · DOI
  16. Harper, 2000, DIFS—a modelling and simulation tool for DGT induced trace metal remobilisation in sediments and soils, Environ. Model Softw., 15, 55, 10.1016/S1364-8152(99)00027-4 · DOI
  17. Hendren, 2013, Modeling nanomaterial fate in wastewater treatment: Monte Carlo simulation of silver nanoparticles (nano-Ag), Sci. Total Environ., 449, 418, 10.1016/j.scitotenv.2013.01.078 · DOI
  18. Jassby, 2012, Impact of aggregate size and structure on the photocatalytic properties of TiO2 and ZnO nanoparticles, Environ. Sci. Technol., 46, 6934, 10.1021/es202009h · DOI
  19. Judy, 2011, Evidence for biomagnification of gold nanoparticles within a terrestrial food chain, Environ. Sci. Technol., 45, 776, 10.1021/es103031a · DOI
  20. Kaegi, 2011, Behavior of metallic silver nanoparticles in a pilot wastewater treatment plant, Environ. Sci. Technol., 45, 3902, 10.1021/es1041892 · DOI
  21. Kandlikar, 2007, Health risk assessment for nanoparticles: a case for using expert judgement, J. Nanoparticle Res., 9, 137, 10.1007/s11051-006-9154-x · DOI
  22. Keller, 2010, Stability and aggregation of metal oxide nanoparticles in natural aqueous matrices, Environ. Sci. Technol., 44, 1962, 10.1021/es902987d · DOI
  23. Kent, 2012, Controlled evaluation of silver nanoparticle dissolution using atomic force microscopy, Environ. Sci. Technol., 46, 6977, 10.1021/es203475a · DOI
  24. Klaine, 2008, Nanomaterials in the environment: behavior, fate, bioavailability, and effects, Environ. Toxicol. Chem., 27, 1825, 10.1897/08-090.1 · DOI
  25. Klaine, 2012, Paradigms to assess the environmental impact of manufactured nanomaterials, Environ. Toxicol. Chem., 31, 3, 10.1002/etc.733 · DOI
  26. Kulthong, 2010, Determination of silver nanoparticle release from antibacterial fabrics into artificial sweat, Part. Fibre Toxicol., 7, 10.1186/1743-8977-7-8 · DOI
  27. Lamsal, 2011, Application of silver nanoparticles for the control of colletotrichum species in vitro and pepper anthracnose disease in field, Mycobiology, 39, 194, 10.5941/MYCO.2011.39.3.194 · DOI
  28. Lecoanet, 2004, Laboratory assessment of the mobility of nanomaterials in porous media, Environ. Sci. Technol., 38, 5164, 10.1021/es0352303 · DOI
  29. Levard, 2011, Sulfidation processes of PVP-coated silver nanoparticles in aqueous solution: impact on dissolution rate, Environ. Sci. Technol., 45, 5260, 10.1021/es2007758 · DOI
  30. Li, 2015, Sulfidation as a natural antidote to metallic nanoparticles is overestimated: CuO sulfidation yields CuS nanoparticles with increased toxicity in Medaka (Oryzias latipes) embryos, Environ. Sci. Technol., 49, 2486, 10.1021/es505878f · DOI
  31. Liu, 2010, Controlled release of biologically active silver from nanosilver surfaces, ACS Nano, 4, 6903, 10.1021/nn102272n · DOI
  32. Lombi, 2013, Transformation of four silver/silver chloride nanoparticles during anaerobic treatment of wastewater and post-processing of sewage sludge, Environ. Pollut., 176, 193, 10.1016/j.envpol.2013.01.029 · DOI
  33. Lowry, 2012, Transformations of nanomaterials in the environment, Environ. Sci. Technol., 46, 6893, 10.1021/es300839e · DOI
  34. Lynch, 2014, A strategy for grouping nanomaterials based on key physico-chemical descriptors as a basis for safer-by-design NMs, Nano Today, 9, 266, 10.1016/j.nantod.2014.05.001 · DOI
  35. Ma, 2012, Size-controlled dissolution of organic-coated silver nanoparticles, Environ. Sci. Technol., 46, 752, 10.1021/es201686j · DOI
  36. Ma, 2013, Fate of zinc oxide and silver nanoparticles in a pilot wastewater treatment plant and in processed biosolids, Environ. Sci. Technol., 48, 104, 10.1021/es403646x · DOI
  37. Ma, 2013, Sulfidation mechanism for zinc oxide nanoparticles and the effect of sulfidation on their solubility, Environ. Sci. Technol., 47, 2527, 10.1021/es3035347 · DOI
  38. Ma, 2014, Sulfidation of copper oxide nanoparticles and properties of resulting copper sulfide, Environ. Sci.: Nano, 1, 347
  39. Mayrovitz, 2001, Biophysical effects of water and synthetic urine on skin, Adv. Skin Wound Care, 14, 302, 10.1097/00129334-200111000-00013 · DOI
  40. Moore, 1977, Culture media for human cells—RPMI 1603, RPMI 1634, RPMI 1640 and GEM 1717, TCA Man. / Tissue Cult. Assoc., 3, 503, 10.1007/BF00918753 · DOI
  41. Nowack, 2012, Potential scenarios for nanomaterial release and subsequent alteration in the environment, Environ. Toxicol. Chem., 31, 50, 10.1002/etc.726 · DOI
  42. Park, 2013, Stability of citrate-capped silver nanoparticles in exposure media and their effects on the development of embryonic zebrafish (Danio rerio), Arch. Pharm. Res., 36, 125, 10.1007/s12272-013-0005-x · DOI
  43. Praetorius, 2012, Development of environmental fate models for engineered nanoparticles—a case study of TiO2 nanoparticles in the Rhine River, Environ. Sci. Technol., 46, 6705, 10.1021/es204530n · DOI
  44. Quadros, 2013, Release of silver from nanotechnology-based consumer products for children, Environ. Sci. Technol., 47, 8894, 10.1021/es4015844 · DOI
  45. Quik, 2015, Spatially explicit fate modelling of nanomaterials in natural waters, Water Res., 80, 200, 10.1016/j.watres.2015.05.025 · DOI
  46. Saleh, 2015, Research strategy to determine when novel nanohybrids pose unique environmental risks, Environ. Sci.: Nano, 2, 11
  47. Sawinska, 2014, Use of silver nanoparticles as a fungicide, Przem. Chem., 93, 1472
  48. Scheringer, 2008, Nanoecotoxicology: environmental risks of nanomaterials, Nat. Nanotechnol., 3, 322, 10.1038/nnano.2008.145 · DOI
  49. Sekine, 2015, Speciation and lability of Ag-, AgCl-, and Ag2S-nanoparticles in soil determined by X-ray absorption spectroscopy and diffusive gradients in thin films, Environ. Sci. Technol., 49, 897, 10.1021/es504229h · DOI
  50. Sotiriou, 2014, Engineering safer-by-design silica-coated ZnO nanorods with reduced DNA damage potential, Environ. Sci.: Nano, 1, 144
  51. Starnes, 2015, Impact of sulfidation on the bioavailability and toxicity of silver nanoparticles to Caenorhabditis elegans, Environ. Pollut., 196, 239, 10.1016/j.envpol.2014.10.009 · DOI
  52. Stone, 2010, Nanomaterials for environmental studies: classification, reference material issues, and strategies for physico-chemical characterisation, Sci. Total Environ., 408, 1745, 10.1016/j.scitotenv.2009.10.035 · DOI
  53. Tandy, 2011, The use of DGT for prediction of plant available copper, zinc and phosphorus in agricultural soils, Plant Soil, 346, 167, 10.1007/s11104-011-0806-y · DOI
  54. Therezien, 2014, Importance of heterogeneous aggregation for NP fate in natural and engineered systems, Sci. Total Environ., 485–486, 309, 10.1016/j.scitotenv.2014.03.020 · DOI
  55. Thomas, 2006, Research strategies for safety evaluation of nanomaterials, part VIII: international efforts to develop risk-based safety evaluations for nanomaterials, Toxicol. Sci., 92, 23, 10.1093/toxsci/kfj211 · DOI
  56. Unrine, 2012, Biotic and abiotic interactions in aquatic microcosms determine fate and toxicity of ag nanoparticles. Part 1. Aggregation and dissolution, Environ. Sci. Technol., 46, 6915, 10.1021/es204682q · DOI
  57. Unrine, 2012, Trophic transfer of Au nanoparticles from soil along a simulated terrestrial food chain, Environ. Sci. Technol., 46, 9753, 10.1021/es3025325 · DOI
  58. Westerhoff, 2012, Searching for global descriptors of engineered nanomaterial fate and transport in the environment, Acc. Chem. Res., 46, 844, 10.1021/ar300030n · DOI
  59. Whitley, 2013, Behavior of Ag nanoparticles in soil: effects of particle surface coating, aging and sewage sludge amendment, Environ. Pollut., 182, 141, 10.1016/j.envpol.2013.06.027 · DOI
  60. Zhang, 2011, Modeling the primary size effects of citrate-coated silver nanoparticles on their ion release kinetics, Environ. Sci. Technol., 45, 4422, 10.1021/es104205a · DOI

Cited by

Sorted by citations

See all 83

Metadata

Authors
Hendren, C. O., Lowry, G. V., Unrine, J. M., & Wiesner, M. R.
Venue
Science of The Total Environment
Publisher
Elsevier BV
Published
2015-12
Volume
536
Pages
1029-1037
ISSN
0048-9697
DOI
10.1016/j.scitotenv.2015.06.100
Cited by
83
References
1
Language
en
Licence
Funders
  • National Science FoundationNational Science Foundation (NSF)
  • Environmental Protection Agency (EPA) under NSFEnvironmental Protection Agency (EPA) under NSF (EF-0830093, DBI-1266252)

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: A functional assay-based strategy for nanomaterial risk forecasting. https://app.cochat.ai/papers/10.1016/j.scitotenv.2015.06.100
The paper
Hendren, C. O., Lowry, G. V., Unrine, J. M., & Wiesner, M. R. (2015). A functional assay-based strategy for nanomaterial risk forecasting. Science of The Total Environment. https://doi.org/10.1016/j.scitotenv.2015.06.100