Biochemical responses of the aquatic higher plant <i>Lemna gibba</i> to a mixture of copper and 1,2-dihydroxyanthraquinone: Synergistic toxicity via reactive oxygen species
Bibliographic record
Abstract
Metals and polycyclic aromatic hydrocarbons (PAHs) are known to be toxic to plants. Because metals and PAHs often are cocontaminants in the environment, plants can be subjected to damage caused by their combined effects. We recently found that copper and an oxygenated PAH (1,2-dihydroxyanthraquinone [1,2-dhATQ]) synergistically are toxic to plants. This synergistic toxicity was linked indirectly to production of reactive oxygen species (ROS). In this study, plant growth, chlorophyll pigments, protein accumulation, and ROS production were chosen as endpoints to assess the mechanism of toxicity of copper and 1,2-dhATQ to Lemna gibba in more detail. Because copper and PAHs can generate ROS, we assayed for specific antioxidant enzymes: Superoxide dismutase (SOD), glutathione reductase (GR), and ascorbate peroxidase (APX). Copper treatment at a concentration that did not cause growth inhibition resulted in upregulation of Mn SOD, Cu-Zn SOD, and APX. At a level that moderately was toxic to plants, 1,2-dhATQ did not alter significantly the levels of these antioxidant enzymes. However, a synergistically toxic mixture of copper plus 1,2-dhATQ upregulated Cu-Zn SOD, Mn SOD, and GR, although APX activity was downregulated. When plants were treated with the ROS scavenger dimethyl thiourea (DMTU), enhanced toxicity and formation of ROS caused by the mixture both were diminished substantially. However, 1,2-dhATQ toxicity was not affected significantly by DMTU. Based on this study, the toxicity caused by the mixture of copper plus 1,2-dhATQ directly can be connected to elevated levels of ROS.
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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) | 0.001 | 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) | 0.001 | 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".