Evaluation of Copper Oxide Nanoparticles Toxicity Using Chlorophyll <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>a</mml:mi></mml:math> Fluorescence Imaging in <i>Lemna gibba</i>
Bibliographic record
Abstract
Copper oxide nanoparticles (CuO NPs), used in antifouling paints of boats, are released in the environment and can induce toxicity to aquatic organisms. In this report, we used chlorophyll a fluorescence imaging to evaluate CuO NPs toxicity in Lemna gibba . This approach allowed to evaluate the differential effect of CuO NPs on photosynthesis of whole L. gibba plants. Exposure to 0.1 to 0.4 g/L CuO NPs during 48h induced strong inhibition of photosynthetic processes resulting in a decrease of plant growth. By using fluorescence imaging, different photosynthetic parameters were evaluated simultaneously in microplate conditions. Imaging of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mtext>F</mml:mtext><mml:mtext>O</mml:mtext></mml:msub></mml:math> fluorescence yield showed the decrease of leaf photosynthetic active surface for whole plants exposed to CuO NPs. This method showed that CuO NPs inhibited photosystem II maximal, photosystem II operational quantum yields, and photochemical quenching of fluorescence associated with electron transport. Nonphotochemical fluorescence quenching as an indicator of energy dissipation not used in photosynthesis was shown to be increased by the effect of CuO NPs. Such approach in microplate conditions provides synchronous high repetition measurements for numerous plants. This study may give a reliable methodological approach to evaluate toxicity risk of NPs in aquatic ecosystems.
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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 | 0.004 | 0.001 |
| 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 | 0.001 |
| 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".