Similar Stress Responses are Elicited by Copper and Ultraviolet Radiation in the Aquatic Plant Lemna gibba: Implication of Reactive Oxygen Species as Common Signals
Bibliographic record
Abstract
Metals and ultraviolet (UV) radiation are two environmental stressors that can cause damage to plants. These two types of stressors often impact simultaneously on plants and both are known to promote reactive oxygen species (ROS) production. However, little information is available on the potential parallel stress responses elicited by metals and UV radiation. Using the aquatic plant Lemna gibba, we found that copper and simulated solar radiation (SSR, a light source containing photosynthetically active radiation (PAR) and UV radiation) induced similar responses in the plants. Both copper and SSR caused ROS formation. The ROS levels were higher when copper was combined with SSR than when applied with PAR. Higher concentrations of copper plus PAR caused toxicity as monitored by diminished growth and chlorophyll content. This toxicity was more pronounced when copper was combined with SSR. Because the generation of ROS was also higher when copper was combined with SSR, we attributed this enhanced toxicity to elevated levels of ROS. In comparison to PAR-grown plants, SSR treated plants exhibited elevated levels of superoxide dismutase (SOD) and glutathione reductase (GR). These enzyme levels were further elevated under both PAR and SSR when copper was added at concentrations that generated ROS. Interestingly, copper treatment in the absence of SSR (i.e. copper plus PAR) induced synthesis of the same flavonoids as those observed in SSR without copper. Finally, addition of either dimethyl thiourea or GSH (two common ROS scavengers) lowered in vivo ROS production, alleviated toxicity and diminished induction of GR as well as accumulation of UV absorbing compounds. Thus, the potential of ROS being a common signal for acclimation to stress by both copper and UV can be considered.
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 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) | 0.001 | 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 | 0.001 | 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".