A Safe‐by‐Design Principle Aligned Mixture INteraction TOXicity (MINTOX) Framework for Predicting the Joint Toxicity Effects in Metal Oxide Nanoparticle–Metal Ion Binary Mixtures: Toward Assessment of Innovative Advanced Materials
Source abstract
Abstract
ABSTRACT Toxicity assessment in Innovative Advanced Materials is challenging owing to complex interactions between components. Here we present MINTOX as a proof‐of‐concept framework developed and demonstrated on binary mixtures of metal oxide nanoparticles and dissolved metal ions. The MINTOX integrated dose–response modeling based on four complementary toxicity indices to predict the nonlinear joint toxicity effects of nanomaterial–ion mixtures, and its application to 18 binary mixtures (TiO 2 , ZnO, Fe 3 O 4 × Cu 2 ⁺/Ag⁺/Zn 2 ⁺) in Daphnia magna acute toxicity assays showed that it accurately classified 56% of mixture outcomes based on concentration‐addition metrics and 50% based on the model deviation ratio index, revealing predominantly antagonistic interactions (notably for TiO 2 –Cu 2 ⁺) and distinct synergy “hotspots” (TiO 2 –Ag⁺ and ZnO–Ag⁺). Mechanistic analysis attributed antagonism, which limited ion bioavailability, to nanoparticle (NP) surface adsorption and heteroaggregation, whereas synergy was attributed to NP‐mediated ROS generation. We propose this workflow as an early‐stage screening tool that can support future assessment of IAM‐like multicomponent systems, but the present study is restricted to nanoparticle–ion binary mixtures.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Nanoparticles: synthesis and applications · Environmental Toxicology and Ecotoxicology · Computational Drug Discovery Methods
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Group of Environmental Chemometrics Faculty of Chemistry University of Gdansk Gdansk Poland
QSAR Lab Ltd Gdansk Poland
Digital Chemistry Research Center Korea Research Institute of Chemical Technology Daejeon Republic of Korea
References (53)
Show source-provided references
1. 10.1039/c9nr01162e10.1039/c9nr01162e ↗
2. 10.5772/intechopen.8332610.5772/intechopen.83326 ↗
3. Wohlleben W. · 2017 · 411
4. Sharma G. · 2021
5. 10.1080/10601325.2019.158643910.1080/10601325.2019.1586439 ↗
6. 10.1021/acsami.9b2207210.1021/acsami.9b22072 ↗
7. 10.1002/smll.20080155010.1002/smll.200801550 ↗
8. 10.1002/anie.20221006710.1002/anie.202210067 ↗
9. 10.1515/bnm‐2015‐003010.1515/bnm‐2015‐0030 ↗
10. E.Commission “A Framework Strategy for a Resilient Energy Union with a Forward‐Looking Climate Change Policy ”COM(2015) 80 final Brussels(2015).
11. 10.1002/smll.20230558110.1002/smll.202305581 ↗
12. 10.1007/bf0195225710.1007/bf01952257 ↗
13. 10.1111/j.1744‐7348.1939.tb06990.x10.1111/j.1744‐7348.1939.tb06990.x ↗
14. 10.1111/j.2517‐6161.1952.tb00108.x10.1111/j.2517‐6161.1952.tb00108.x ↗
15. Guidelines for the Health Risk Assessment of Chemical Mixtures
16. U. S. Envirnonmental Protection Agency “Technical Support Document on Risk Assessment of Chemical Mixtures ”U.S. EPA Washington DC EPA/600/8‐90/064.
17. U. S. Environmental Protection Agency “Supplementary Guidance for Conducting Health Risk Assessment of Chemical Mixtures ”U.S. EPAWashington (2000) EPA/630/R‐00/002 https://assessments.epa.gov/risk/document/%26deid%3D20533.
18. European Commission: Directorate general for Health and Consumers: Toxicity and assessment of chemical mixtures. European Commission SBN: 978‐92‐79‐30700‐3 Brussels(2012) https://doi/org/10.2772/21444.
19. 10.1007/s11157‐012‐9286‐710.1007/s11157‐012‐9286‐7 ↗
20. Kortenkamp A. · 2009
21. 10.1080/1062936x.2014.98462710.1080/1062936x.2014.984627 ↗
22. 10.1139/f64‐00310.1139/f64‐003 ↗
23. 10.1897/01‐38610.1897/01‐386 ↗
24. 10.1016/0300‐483x(81)90130‐x10.1016/0300‐483x(81)90130‐x ↗
25. 10.1002/ieam.563003030710.1002/ieam.5630030307 ↗
26. 10.1016/0160‐5402(86)90009‐410.1016/0160‐5402(86)90009‐4 ↗
27. OECD Test No.202: Daphnia sp. Acute Immobilisation TestOECD Publishing Paris(2004) https://doi.org/10.1787/9789264069947‐en.
28. 10.1021/es506243d10.1021/es506243d ↗
29. 10.1155/2012/39872010.1155/2012/398720 ↗
30. 10.1007/s11051‐019‐4606‐210.1007/s11051‐019‐4606‐2 ↗
31. 10.1007/s13273‐019‐0035‐710.1007/s13273‐019‐0035‐7 ↗
32. 10.1016/j.envpol.2010.11.03010.1016/j.envpol.2010.11.030 ↗
33. 10.1139/f65‐04210.1139/f65‐042 ↗
34. Marking L. L. · 1977
35. ECETOC “Aquatic Toxicity of Mixtures ”Technical Report no. 80Brussels Belgium July (2001).
36. Ecotoxicological combined effects from chemical mixtures Part 1: Relevance and adequate consideration in environmental risk assessment of plant protection products and biocides
37. 10.1371/journal.pone.009658010.1371/journal.pone.0096580 ↗
38. 10.1021/acs.chemrestox.8b0016410.1021/acs.chemrestox.8b00164 ↗
39. 10.3390/ijerph1602020810.3390/ijerph16020208 ↗
40. 10.1016/j.aquatox.2022.10633210.1016/j.aquatox.2022.106332 ↗
41. 10.1002/ieam.459510.1002/ieam.4595 ↗
42. 10.1016/j.watres.2023.11998110.1016/j.watres.2023.119981 ↗
43. 10.1039/d2en00672c10.1039/d2en00672c ↗
44. Rossum G. V. · 2009
45. R. C.Team “R: A Language and Environment for Statistical Computing ”2021 Vienna Austria (2025) https://www.R‐project.org/.
46. 10.1371/journal.pone.014602110.1371/journal.pone.0146021 ↗
47. Seber G. A. F. · 1989
48. 10.1021/acs.est.2c0333310.1021/acs.est.2c03333 ↗
49. 10.1007/s10661‐020‐08444‐610.1007/s10661‐020‐08444‐6 ↗
50. 10.1016/j.comtox.2022.10025110.1016/j.comtox.2022.100251 ↗
51. 10.1021/acs.est.7b0562910.1021/acs.est.7b05629 ↗
52. 10.1016/s0166‐445x(02)00133‐910.1016/s0166‐445x(02)00133‐9 ↗
53. 10.1039/d1ra04583k10.1039/d1ra04583k ↗