Identification of six differentially expressed genes in response to copper exposure in the aquatic plant <i>Lemna gibba</i> (duckweed)
Bibliographic record
Abstract
Aquatic plants are susceptible to metal pollution and provide an entry point for metals, such as copper, into the aquatic biosphere. Exposure of the aquatic plant Lemna gibba to copper has been associated with the production of reactive oxygen species (ROS) and oxidative damage, caused in large part by the ability of this metal to redox cycle. In particular, copper-mediated production of ROS, a known group of signaling molecules, triggers numerous defense responses in L. gibba. Therefore, the objective of the present study was to examine to what extent acute copper exposure alters gene expression. First, the kinetics of copper uptake was assessed to determine if assimilation occurred within the short exposures needed to induce gene expression. Subsequently, using differential display polymerase chain reaction, we identified six genes with expressions that were putatively altered in response to copper. Differential expression was confirmed by northern hybridization analysis and showed that copper causes an accumulation of transcripts that encode for callose synthase, heat shock protein 90, serine decarboxylase, and the biotin carboxylase subunit of acetyl-coenzyme A carboxylase. Conversely, copper caused a decline in transcript levels for genes encoding the HAP5 subunit of the heme-activated protein (HAP) transcription factor in addition to the chloroplast nucleoid DNA-binding protein CND41. Interestingly, the expressions of these genes are sensitive to cellular ROS levels. We believe that these gene products provide valuable information regarding the molecular mechanisms of copper toxicity.
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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".