Identification and characterization of copper-responsive proteins in arabidopsis
Bibliographic record
Abstract
For the successful development of a hyperaccumulating plant sufficient for use in phytoremediation strategies, a thorough understanding of the mechanism of hyperaccumulation is required.A proteomic survey of the response of plants to metal exposure is a step towards this understanding.The frd3-3 metal accumulating mutant of Arabidopsis thaliana and its nonaccumulating wildtype parental ecotype, Columbia, were grown hydroponically in growth chamber experiments and exposed to copper in the growth medium.The responses of the global and copper-targeted proteomes were examined both spatially and temporally.Exposure to copper caused a general increase in protein abundance, however, a prolonged exposure to copper that approached toxicity caused a decrease in protein abundance.The protein species differed between the roots of the two genotypes, with more defense-and stress-related proteins, and fewer transport and storage proteins identified in the mutant when compared to the wildtype.Proteomic evidence suggests that in the mutant the uptake and transport of copper ions to the aerial tissues is regulated.The protein expression patterns over time demonstrate a constitutive expression of defense-and stress-related proteins in the mutant, whereas the wildtype expression was one of induction.The constitutive expression of key defense proteins suggests a "state-ofreadiness" for metal exposure in the mutant.The plant response to reactive oxygen species, as a consequence of copper exposure, is important in the overall metal accumulation mechanism.A suppression of the oxidative burst produced upon exposure to heavy metals is suggested by the proteomic evidence.
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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 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".