Bioremediation of arsenic and cadmium in a Populus tremula x Populus alba mutant
Bibliographic record
Abstract
The use of plants to remediate contaminated lands is of growing interest to the scientific community because of its ease of implementation, cost effectiveness and ability to stabilize contaminated soils. A novel Populus tremula x Populus alba mutant named fuzzy with an increased trichome density, an elevated growth rate, enhanced pest resistance and a predicted root phenotype was investigated for its ability to tolerate and accumulate arsenic and cadmium in soil. The chlorophyll, hydrogen peroxide and proline contents of fuzzy tissues were assayed, its tissue metal content was measured using ICP-MS and its wet biomass was quantified. Transgenic Arabidopsis thaliana overexpressing homologous gene of that overexpressed in the fuzzy poplar were grown on gel media and their roots were measured to corroborate the root phenotype of fuzzy poplars. The fuzzy poplar was found to have lower levels of hydrogen peroxide in its tissues after arsenic and cadmium exposure than control poplars, suggesting it has a reduced oxidative stress response when exposed to high levels of arsenic and cadmium. This low hydrogen peroxide content was not due to reduced arsenic and cadmium accumulation in fuzzy trees, as they did not accumulate different amounts of arsenic or cadmium than control plants. Proline and chlorophyll levels were not significantly different between metal treatments, or between fuzzy and control poplars. fuzzy poplars exhibited significantly higher root biomass than control poplars, and transgenic Arabidopsis thaliana overexpressing a homologous gene to the one that causes the fuzzy phenotype had significantly longer roots than control plants. All poplars exposed to arsenic and cadmium in this trial contained the majority of these compounds in their tissues in roots. The root biomass phenotype, low hydrogen peroxide content and root metal accumulation in the fuzzy poplar make it an ideal candidate for bioremediation and soil stabilization of contaminated soils.
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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".