Toxicity of Nickel Oxide Nanoparticles on a Freshwater Green Algal Strain of<i>Chlorella vulgaris</i>
Bibliographic record
Abstract
A freshwater microalga strain ofChlorella vulgariswas used to investigate toxic effects induced by nickel oxide nanoparticles (NiO-NPs) in suspension. Algal cells were exposed during 96 h to 0–100 mg L−1of NiO-NPs and analyzed by flow cytometry. Physicochemical characterization of nanoparticles in tested media showed a soluble fraction (free Ni2+) of only 6.42% for 100 mg L−1of NiO-NPs, indicating the low solubility capacity of these NPs. Toxicity analysis showed cellular alterations which were related to NiO-NPs concentration, such as inhibition in cell division (relative cell size and granularity), deterioration of the photosynthetic apparatus (chlorophyll synthesis and photochemical reactions of photosynthesis), and oxidative stress (ROS production). The change in cellular viability demonstrated to be a very sensitive biomarker of NiO-NPs toxicity with EC50of 13.7 mg L−1. Analysis by TEM and X-ray confirmed that NiO-NPs were able to cross biological membranes and to accumulate inside algal cells. Therefore, this study provides a characterization of both physicochemical and toxicological properties of NiO-NPs suspensions in tested media. The use of the freshwater strain ofC. vulgarisdemonstrated to be a sensitive bioindicator of NiO-NPs toxicity on the viability of green algae.
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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".