Acellular oxidative potential assay for screening of amorphous silica nanoparticles
Bibliographic record
Abstract
, -PEG) of 5 different sizes: (15, 30, 50, 75, 100 nm) for their oxidative potential using an acellular assay. The assay is based on oxidation of dithiothreitol (DTT) by reactive oxygen species and can serve as a surrogate test for oxidative stress. These materials were characterized for size distribution, aggregation, crystallinity, surface area, surface modification, surface charge and metal content. Tests for association between oxidative potential of SiNPs and their physicochemical properties were carried out using analysis of variance and correlation analyses. These test results suggest that the size of amorphous SiNPs influenced their oxidative potential irrespective of the surface modification, with 15 nm exhibiting relatively higher oxidative potential compared to the other sizes. Furthermore, SiNP surface area, surface modification and agglomeration in solution also appeared to affect oxidative potential of these SiNPs. These findings indicate that physicochemical properties are critical in influencing the oxidative behaviour of amorphous SiNPs, with potential to trigger cellular oxidative stress and thus toxicity, when exposed. This information advances our understanding of potential toxicities of these amorphous SiNPs and supports risk assessment efforts and the design of safer forms of silica nanomaterials.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".