Effects of polymer-coated metal oxide nanoparticles on goldfish (<i>Carassius auratus</i>L.) neutrophil viability and function
Bibliographic record
Abstract
Exposure effects from polyacrylic acid (PAA) metal-oxide nanoparticles (TiO2, CeO2, Fe2O3, ZnO) on fish neutrophil viability and effector functions (degranulation, respiratory burst, inflammatory gene expression) were investigated using primary kidney goldfish (Carassius auratus L.) neutrophils as a model. Several studies have reported cytotoxic effects of NPs but there are limited reports on their potential to perturb the innate immune system of aquatic organisms. PAA-TiO2 significantly decreased neutrophil viability in a time and dose-dependent manner at all measured time points (0-48 h) and concentrations (0-200 µg/mL). Maximum viability decreased by (mean ± SEM): 67.1 ± 3.3%, 78.4 ± 4.2% and 74.9 ± 5.0% when exposed to 50, 100 and 200 µg/mL for 48 h, respectively. PAA-ZnO also significantly decreased neutrophil viability but only at 48 h exposures at higher concentrations. Neutrophil degranulation increased by approximately 3% after 30 min and by 8% after 4 h when exposed to sublethal doses (10 µg/mL) of PAA-CeO2 or PAA-Fe2O3. All PAA-NPs induced an increase in neutrophil respiratory burst when exposed to 10 µg/mL for 30 and 60 min, however, PAA-Fe2O3 was the only NP where the response was significant. Lastly, NPs altered the expression of a number of pro-inflammatory and immune genes, where PAA-TiO2 most significantly increased the mRNA levels of pro-inflammatory genes (il-1b, ifng) in neutrophils by 3 and 2.5 times, respectively. Together, these data demonstrate that goldfish neutrophils can be negatively affected from exposures to PAA-coated NPs and are functionally responsive to specific core-material properties at sublethal doses. These changes could perturb the innate response and affect the ability of fish to respond to pathogens.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 source (direct Gemma or distilled Codex), 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".