Nickel and copper translocation in Pinus resinosa (red pine) and their effects on the expression of genes associated with nickel and copper resistance
Bibliographic record
Abstract
Metals are required in plant tissues at small concentrations for several physiological processes; \nhowever, excess metal can cause toxicity. The City of Greater Sudbury Region (CGS) has a rich \nmining history that has resulted in contaminating emissions that damaged surrounding ecosystems. \nThe main objectives were to 1) investigate metal accumulation and translocation in Pinus spp., 2) \nevaluate the effects of different concentrations of nickel and copper on P. resinosa genotypes, and 3) \ndetermine the effects of different concentrations of nickel and copper on gene expression in Pinus \nresinosa. Soil, roots, and shoots of P. resinosa were sampled in the CGS. Additionally, seedlings were \ntreated with different concentrations of nickel nitrate and copper sulphate and corresponding salt \ncontrols in growth chamber screening tests. P. resinosa accumulate nickel and copper in roots and \nshoots. Susceptibility to nickel exposure increased with seedling age. Resistance to copper on the \nother hand increased in old genotypes. The expression of genes associated with nickel resistance \nincluding 1-aminocyclopropane-1-carboxylic acid deaminase (ACC deaminase), glutathione-Stransferase (GST), High-affinity Ni transporter (NiCoT or AT2G16800), natural resistance-associated \nmacrophage protein 3 (NRAMP3) and Serine acetyltransferase (SAT) were analyzed using qPCR. \nEach gene was downregulated in genotypes treated with the 1,600 mg/kg nickel, while GST \nexpression was increased six folds compared to the water control. The expression of MRP4 and RAN1 \ngenes associated with copper resistance was also investigated. Only the lowest concentrations (13 \nmg/kg) of copper ions suppressed the expression of these genes while higher concentrations had no \neffects. This research suggests that P. resinosa is in general resistant to nickel and copper \ncontaminants. Nickel and copper ions affect gene expression, even at low concentrations.
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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 | 0.001 |
| 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".