Matches in SemOpenAlex for { <https://semopenalex.org/work/W3039308217> ?p ?o ?g. }
- W3039308217 endingPage "100234" @default.
- W3039308217 startingPage "100234" @default.
- W3039308217 abstract "Nanomaterials (NMs) can be manufactured in plenty of variants differing in their physicochemical properties. Functional assays can be highly useful to cope with the enormous variability by supporting prioritization and categorization. Oxidative potential (OP) seems to be in particular important in this context and different assays are available. However, their reliability and predictivity are not well-characterized. This study compares four different test methods for measuring NM OP. Reactive oxygen species (ROS) generation was measured on a set of 35 different materials, all extensively characterized with respect to physicochemical properties and most of them with respect to toxicity. Different acellular assays were applied, namely electron spin resonance (ESR) spectroscopy using CPH spin probe and DMPO spin trap, and the ferric reduction ability of serum (FRAS) assay. In addition, protein carbonylation as a marker for oxidative protein damage was analyzed in NRK-52E cells. All assays were assessed individually for their predictivity compared to established toxicological endpoints. We also aimed to identify the optimal assay combination using multivariate logistic regression and other statistical measures. BET surface area-based doses were more suitable to relate surface reactivity to toxicity. In addition, normalization to the deposited dose was advantageous for cellular assays as it improved the predictivity for in vitro as well as in vivo toxicity. The carbonylation assay, potentially in combination with ESR (DMPO spin trap) or FRAS assay, led to the best predictive performance. In summary, we propose a testing strategy for NM OP and demonstrated the applicability in an extended case study on 35 materials. This work is an important contribution towards reliable grouping and testing strategies for NMs. • Nanomaterial oxidative potential (OP) is important for prioritization and ranking as well as for categorization and grouping. • This study compares four different OP assays and their predictivity towards in vitro and in vivo toxicity endpoints. • The predictivity was assessed for each assay alone as well as for combinations of them using univariate and multivariate logistic regression models. • Prediction accuracy was best when combining the cellular protein carbonylation assay with acellular ESR using DMPO spin trap or FRAS assay. • Surface-based dosimetry resulted in better predictivity than mass-based dosimetry. Predictivity of the cellular assay was improved when considering deposited doses." @default.
- W3039308217 created "2020-07-10" @default.
- W3039308217 creator A5007700138 @default.
- W3039308217 creator A5014619914 @default.
- W3039308217 creator A5024188748 @default.
- W3039308217 creator A5024542005 @default.
- W3039308217 creator A5025215980 @default.
- W3039308217 creator A5042291694 @default.
- W3039308217 creator A5049879087 @default.
- W3039308217 date "2020-07-01" @default.
- W3039308217 modified "2023-09-29" @default.
- W3039308217 title "Nanomaterial categorization by surface reactivity: A case study comparing 35 materials with four different test methods" @default.
- W3039308217 cites W1879099706 @default.
- W3039308217 cites W1965351120 @default.
- W3039308217 cites W1977913875 @default.
- W3039308217 cites W1983937216 @default.
- W3039308217 cites W1985031521 @default.
- W3039308217 cites W1999921360 @default.
- W3039308217 cites W2005675920 @default.
- W3039308217 cites W2006451106 @default.
- W3039308217 cites W2017527731 @default.
- W3039308217 cites W2027912899 @default.
- W3039308217 cites W2041634593 @default.
- W3039308217 cites W2042791400 @default.
- W3039308217 cites W2056008941 @default.
- W3039308217 cites W2059826080 @default.
- W3039308217 cites W2062430935 @default.
- W3039308217 cites W2076202551 @default.
- W3039308217 cites W2078129874 @default.
- W3039308217 cites W2080323087 @default.
- W3039308217 cites W2086561195 @default.
- W3039308217 cites W2087292928 @default.
- W3039308217 cites W2088467325 @default.
- W3039308217 cites W2091619250 @default.
- W3039308217 cites W2098811469 @default.
- W3039308217 cites W2102429044 @default.
- W3039308217 cites W2110605441 @default.
- W3039308217 cites W2115215892 @default.
- W3039308217 cites W2116384075 @default.
- W3039308217 cites W2129146157 @default.
- W3039308217 cites W2130920625 @default.
- W3039308217 cites W2133378107 @default.
- W3039308217 cites W2134724878 @default.
- W3039308217 cites W2149790826 @default.
- W3039308217 cites W2151988198 @default.
- W3039308217 cites W2153584068 @default.
- W3039308217 cites W2171528132 @default.
- W3039308217 cites W2178548726 @default.
- W3039308217 cites W2195616206 @default.
- W3039308217 cites W2204750929 @default.
- W3039308217 cites W2289506341 @default.
- W3039308217 cites W2290248210 @default.
- W3039308217 cites W2342851231 @default.
- W3039308217 cites W2343635104 @default.
- W3039308217 cites W2476100260 @default.
- W3039308217 cites W2621031125 @default.
- W3039308217 cites W2621884880 @default.
- W3039308217 cites W2755434307 @default.
- W3039308217 cites W2775802685 @default.
- W3039308217 cites W2776704451 @default.
- W3039308217 cites W2776885897 @default.
- W3039308217 cites W2792449792 @default.
- W3039308217 cites W2969875029 @default.
- W3039308217 cites W2973573826 @default.
- W3039308217 cites W3001373118 @default.
- W3039308217 doi "https://doi.org/10.1016/j.impact.2020.100234" @default.
- W3039308217 hasPublicationYear "2020" @default.
- W3039308217 type Work @default.
- W3039308217 sameAs 3039308217 @default.
- W3039308217 citedByCount "23" @default.
- W3039308217 countsByYear W30393082172020 @default.
- W3039308217 countsByYear W30393082172021 @default.
- W3039308217 countsByYear W30393082172022 @default.
- W3039308217 countsByYear W30393082172023 @default.
- W3039308217 crossrefType "journal-article" @default.
- W3039308217 hasAuthorship W3039308217A5007700138 @default.
- W3039308217 hasAuthorship W3039308217A5014619914 @default.
- W3039308217 hasAuthorship W3039308217A5024188748 @default.
- W3039308217 hasAuthorship W3039308217A5024542005 @default.
- W3039308217 hasAuthorship W3039308217A5025215980 @default.
- W3039308217 hasAuthorship W3039308217A5042291694 @default.
- W3039308217 hasAuthorship W3039308217A5049879087 @default.
- W3039308217 hasBestOaLocation W30393082171 @default.
- W3039308217 hasConcept C12554922 @default.
- W3039308217 hasConcept C138631740 @default.
- W3039308217 hasConcept C150903083 @default.
- W3039308217 hasConcept C151730666 @default.
- W3039308217 hasConcept C171250308 @default.
- W3039308217 hasConcept C178790620 @default.
- W3039308217 hasConcept C185592680 @default.
- W3039308217 hasConcept C192562407 @default.
- W3039308217 hasConcept C207001950 @default.
- W3039308217 hasConcept C2779343474 @default.
- W3039308217 hasConcept C29730261 @default.
- W3039308217 hasConcept C86803240 @default.
- W3039308217 hasConceptScore W3039308217C12554922 @default.
- W3039308217 hasConceptScore W3039308217C138631740 @default.
- W3039308217 hasConceptScore W3039308217C150903083 @default.