Tolerance and biosorption of copper and zinc by<i>Pseudomonas putida</i>CZ1 isolated from metal-polluted soil
Bibliographic record
Abstract
A strain of Pseudomonas sp. CZ1, which was isolated from the rhizosphere of Elsholtzia splendens obtained from the heavy-metal-contaminated soil in the north-central region of the Zhejiang province of China, has been studied for tolerance to copper (Cu) and zinc (Zn) and its capacities for biosorption of these metals. Based on 16S ribosomal DNA sequencing, the microorganism was closely related to Pseudomonas putida. It exhibited high minimal inhibitory concentration values (about 3 mmol Cu.L-1 and 5 mmol Zn.L-1) for metals and antibiotic resistance to ampicillin but not to kanamycin. Based on the results of heavy metal toxicity screening, inhibitory concentrations in solid media were lower than those in liquid media. Moreover, it was found that the toxicity of Cu was higher than that of Zn. Pseudomonas putida CZ1 was capable of removing about 87.2% of Cu and 99.8% of Zn during the active growth cycle, with specific biosorption capacities of 24.2 and 26.0 mg x L-1, respectively. Although at low concentrations, Cu and Zn slightly damage the surface of some cells, P. putida demonstrated high capacities for biosorption of Cu and Zn. Since P. putida CZ1 could grow in the presence of significant concentrations of metals and because of its high metal uptake capacity in aerobic conditions, this bacterium may be potentially applicable in bioreactors or in situ bioremediation of heavy-metal-contaminated aqueous or soil systems.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".