Cd and Ni transport and accumulation in the halophyte Sesuvium portulacastrum: implication of organic acids in these processes
Bibliographic record
Abstract
The implication of organic acids in Cd and Ni translocation was studied in the halophyte species Sesuvium portulacastrum. Citric, fumaric, malic, and ascorbic acids were separated and quantified by HPLC technique in shoots, roots and xylem saps of plants grown on nutrient solutions added with 50 μM Cd, 100 μM Ni and the combination of 50 μM Cd + 100 μM Ni. Results showed that Cd had no significant impact on biomass production while Ni and the combination of both metals drastically affected plant development. Cadmium and Ni concentrations in tissues and xylem sap were higher in plants subjected to individual metal application than those subjected to the combined effect of Cd and Ni suggesting a possible competition between these metals for absorption. Both metals applied separately or in combination induced an increase in citrate concentration in shoots and xylem sap but a decrease of this concentration in the roots. However, a minor relationship was observed between metal application and fumaric, malic, and ascorbic acids. Both observations suggest the implication of citric acid in Cd, Ni translocation and shoot accumulation in S. portulacastrum. The relatively high accumulation of citric acid in xylem sap and shoot of S. portulacastrum could be involved in metal chelation and thus contributes to heavy metal tolerance in this species.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".