Reactive Oxygen Species Formed by Metal and Metal Oxide Nanoparticles in Physiological Media—A Review of Reactions of Importance to Nanotoxicity and Proposal for Categorization
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Diffusely dispersed metal and metal oxide nanoparticles (NPs) can adversely affect living organisms through various mechanisms and exposure routes. One mechanism behind their toxic potency is their ability to generate reactive oxygen species (ROS) directly or indirectly to an extent that depends on the dose, metal speciation, and exposure route. This review provides an overview of the mechanisms of ROS formation associated with metal and metal oxide NPs and proposes a possible way forward for their future categorization. Metal and metal oxide NPs can form ROS via processes related to corrosion, photochemistry, and surface defects, as well as via Fenton, Fenton-like, and Haber–Weiss reactions. Regular ligands such as biomolecules can interact with metallic NP surfaces and influence their properties and thus their capabilities of generating ROS by changing characteristics such as surface charge, surface composition, dissolution behavior, and colloidal stability. Interactions between metallic NPs and cells and their organelles can indirectly induce ROS formation via different biological responses. H2O2 can also be generated by a cell due to inflammation, induced by interactions with metallic NPs or released metal species that can initiate Fenton(-like) and Haber–Weiss reactions forming various radicals. This review discusses these different pathways and, in addition, nano-specific aspects such as shifts in the band gaps of metal oxides and how these shifts at biologically relevant energies (similar to activation energies of biological reactions) can be linked to ROS production and indicate which radical species forms. The influences of kinetic aspects, interactions with biomolecules, solution chemistry (e.g., Cl− and pH), and NP characteristics (e.g., size and surface defects) on ROS mechanisms and formation are discussed. Categorization via four tiers is suggested as a way forward to group metal and metal oxide NPs based on the ROS reaction pathways that they may undergo, an approach that does not include kinetics or environmental variations. The criteria for the four tiers are based on the ability of the metallic NPs to induce Fenton(-like) and Haber–Weiss reactions, corrode, and interact with biomolecules and their surface catalytic properties. The importance of considering kinetic data to improve the proposed categorization is highlighted.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it