Transcription of genes associated with nickel resistance induced by different doses of nickel nitrate in <i>Quercus rubra</i>
Bibliographic record
Abstract
Knowledge of the mechanism of genetic resistance to nickel (Ni) toxicity in red oak (Quercus rubra) is limited. The main objective of the present study was to evaluate the level of transcription of genes associated with nickel resistance in Q. rubra plants exposed to different doses of potassium nitrate and nickel nitrate. All the Q. rubra genotypes screened were highly resistant to nickel nitrate and potassium nitrate. An unexpected high level of transcription of (ACC) deaminase was induced in leaves by the low dose of potassium nitrate (150 mg/kg). This gene response decreased as the dose was increased to reach the lowest level at the high dose (1600 mg/kg). On the other hand, nickel induced significantly higher level of ACC deaminase transcription only for 1600 mg/kg of nickel nitrate. This transcription was higher in leaves compared to roots. For serine acetyltransferase (SAT) gene, the transcription was higher in roots than in leaves. Surprisingly, potassium nitrate (a common plant fertiliser) induced an upregulation of nicotianamine synthase (NAS3) gene in leaves of samples exposed to 150 mg/kg dose and a downregulation for the 1600 mg/kg treatment. An opposite trend attributed to nickel was observed with nickel nitrate treatments.
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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".