Differential response of <i>Senna occidentalis</i> L. to arsenic and cadmium contaminated soil
Bibliographic record
Abstract
Abstract We investigated the phytoremediation potential of Senna occidentalis L., a pantropical plant that has been associated with tolerance to heavy metal-contaminated soils around mining sites. Seedlings of S. occidentalis were exposed to cadmium chloride (CdCl 2 ) and sodium arsenate (Na 3 AsO 4 ) at concentrations of 200, 300, and 400 mg L -1 under greenhouse conditions. Heavy metal tolerance was assessed by comparing biomass and stress indicators such as chlorophyll, proline, and hydrogen peroxide content. Arsenic treatment had more toxic effects than cadmium on Senna physiology. Regardless of concentration of arsenic applied, the biomass decreased by 50% as compared to control and cadmium-treated plants. Chlorophyll content decreased with exposure to both heavy metals. Higher concentration of Cd and As (400 mg L -1 ) resulted in 50% reduction in chlorophyll content. Proline and hydrogen peroxide levels were higher in arsenic-treated plants compared to controls and cadmium-treated plants, indicating an enhanced stress response when exposed to arsenic. When heavy metal content was measured, there was a significant accumulation of arsenic in the leaves, stems, and roots, indicating that arsenic in these tissues was responsible for the profound changes in biomass, proline, and hydrogen peroxide content. In contrast, although significant, there was less cadmium uptake by Senna and tolerance can be seen, which was reflected by normal biomass, proline, and hydrogen peroxide levels. High translocation of metals from soil into roots and low translocation from root to shoot tissues suggests the potential for S. occidentalis to be used for phytostabilization of arsenic- and cadmium-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".