Synergistic Toxicity of a Mixture of 1,2-dihydroxyanthraquinone and Copper on the Aquatic Plant <i>Lemna gibba</i>
Bibliographic record
Abstract
Polycyclic aromatic hydrocarbons (PAHs) and metals are toxic to animals, plants and microorganisms. Both these groups of contaminants coexist in the industrialized environments. Therefore, it is important to study the mixture toxicity of such pollutants on biological systems. In the present study, we have used the aquatic higher plant Lemna gibba as a test organism to study the mixture toxicity of an oxy-PAH 1,2-dihydroxyanthraquinone (1,2-dhATQ), and the metal copper. 3 μ,Ml,2-dhATQ inhibited photosynthetic electron transport downstream of photosystem II at the cytochrome b6/f complex. Such an inhibition results in the alteration of the redox status of the chloroplast to a reduced state because the plastoquinone pool goes to a net reduced state. Under such circumstances, when 4 μM CuSO4 was administered to L. gibba, there was a synergistic inhibition of growth and protein expression. We infer from these results that the synergistic toxicity caused by the mixture of 1,2-dhATQ plus CuSO4 is due to the catalytic transfer of electrons by Cu2+ from the reduced plastoquinone pool to O2. Such a mediation of electrons leads to the generation of reactive oxygen species, which could cause greater toxicity of 1,2-dhATQ. Polycyclic aromatic hydrocarbons (PAHs) and metals are common contaminants in industrialized environments. Both these groups of chemicals are highly toxic to a variety of biological organisms (Martineau et al. 1994, McConkey et al. 1997, Wetzel and Werner 1995). In addition to their direct effects on biological systems, most PAHs have been shown to undergo photomodification under sunlight and they have an increased toxicity following photomodification (Arfsten et al. 1996, Huang et al. 1997b).
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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) | 0.001 | 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".