Characterization and Heavy Metal Bioremediation Potential of <i>Halomonas</i> Isolates from the Bolivian Altiplano
Bibliographic record
Abstract
The Bolivian Altiplano has an ongoing history of heavy metal pollution due to years of uncontrolled mining in this region. Heavy metals are a threat to natural environments such as lakes and soils with cultural and economic importance for the local communities. The extreme environmental conditions of the Bolivian Altiplano translate into alkaline soils with high concentration of minerals, high radiation and considerable daily temperature oscillations. Halophilic and halotolerant microorganisms isolated from such environments have interesting biotechnological applications including bioremediation of metal polluted waters and soils. Here, bacterial strains from the Bolivian Altiplano were characterized and biosorption capacity evaluated for three heavy metals (Pb+2, Cd+2 and Zn+2) in variable concentrations. Four strains were able to grow in multimetal medium with a final concentration of 100 mg. L-1, with a higher tolerance to Pb+2. The four isolates were selected for further characterization and were identified as different species of Halomonas genus. The best heavy metal biosorption rates for the four isolates were found at pH 7 and 37°C. Additionally, the fastest uptake rate for all three metals was under 120 minutes in the four chosen isolates. The biosorption process was best described by Langmuir isotherm for all isolates exposed to the three metals separately. The four Halomonas isolates showed a bioremediation potential for heavy metal polluted substrates, although the highest biosorption capacity values were from isolate Ss_is3 notably for Pb+2. This study provides new information about the potential biotechnological capacities of Halomonas strains isolated from mineral soils in the Andes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".