Analysis of Gene Expression Associated with Copper Toxicity in White Birch (Betula papyrifera) Populations from a Mining Region
Bibliographic record
Abstract
The Greater Sudbury Region (GSR) is one of the most ecologically disturbed regions of Canada.Recent studies have shown that Betula papyrifera accumulate metals in roots or leaves.The main objectives of the present study were to 1) determine the effects of copper treatment on B. papyrifera under controlled conditions and 2) assess the level of expression of genes associated with copper resistance in B. papyrifera populations from metal-contaminated and uncontaminated areas.Significant differences for damage rating were observed among copper dosages after eight days of treatment.There was also a trend of reduced plant growth as the dosage increased.RT-qPCR analysis showed 2x to 25x increase in leaves compared to roots of the expression of the gene for Multi-drug resistance associated protein (MRP4) belonging to the subfamily of ATPbinding cassette (ABC) transporters.A significant upregulation (ranging from 3x to 8 x increase) of Original Research Articlethe Metallothioneins (MT2B) gene in leaves compared to roots was also observed in three of the five sites studied.There were significant differences in expression of MRP4 and MT2 genes among sites, but no association between metal contamination and gene expression was identified.Likewise, no difference in expression of targeted genes was observed among the copper dosages used in growth chamber experiments.
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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 | 0.001 | 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 | 0.000 |
| 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".