Synergistic effects of a photooxidized polycyclic aromatic hydrocarbon and copper on photosynthesis and plant growth: Evidence that in vivo formation of reactive oxygen species is a mechanism of copper toxicity
Bibliographic record
Abstract
Abstract Heavy metals and polycyclic aromatic hydrocarbons (PAHs) are often cocontaminants in industrialized environments, yet little is known about either the extent or mechanisms of their cotoxicity. To address this shortfall, the combined effects of an oxygenated PAH, 1,2-dihydroxyanthraquinone (1,2-dhATQ), and a heavy metal, Cu2+, on photosynthesis and growth of the duckweed (Lemna gibba) were evaluated. Using assays of chlorophyll a fluorescence and photosystem I activity, 1,2-dhATQ inhibited electron transport at the cytochrome b6/f complex. Conversely, Cu2+ alone (at low concentrations) had little effect on photosynthesis. When Cu2+ was combined with 1,2-dhATQ, an increase in transient and steady-state chlorophyll a fluorescence quenching occurred relative to 1,2-dhATQ alone. Treatment of isolated thylakoid membranes with 1,2-dhATQ inhibited whole-chain linear electron transport, measured as O2 consumption using methyl viologen as the electron acceptor. However, Cu2+ plus 1,2-dhATQ resulted in active O2 consumption with or without methyl viologen as an electron acceptor. From these data, we conclude that 1,2-dhATQ renders the plastoquinone pool to a highly reduced state by inhibiting at cytochrome b6/f Then, Cu2+ is able to mediate the transfer of electrons from reduced plastoquinone to O2, forming reactive oxygen species. At the whole-organism level, when Cu2+ and 1,2-dhATQ were mixed at concentrations that resulted in the above-mentioned impacts on photosynthesis, synergistic inhibition of plant growth was observed. This suggests a catalytic mechanism of toxicity for redox active metals, a process that could be instrumental in explaining their impacts at low concentrations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 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".