Efficient biodegradation of cyanide and ferrocyanide by Na-alginate beads immobilized with fungal cells of <i>Trichoderma koningii</i>
Bibliographic record
Abstract
Cyanide or metal cyanide contaminations have become serious environmental and food-health problems. A fungal mutant of Trichoderma koningii, TkA8, constructed by restriction enzyme-mediated integration, has been verified to have a high cyanide degradation ability in our previous study. In this study, the mutant cells were entrapped in sodium-alginate (Na-alginate) immobilization beads to degrade cyanide and ferrocyanide in a liquid mineral medium. The results showed that the fungus in immobilization beads consisting of 3% Na-alginate and 3% CaCl2 could degrade cyanide more efficiently than a nonimmobilized fungal culture. For maximum degradation efficiency, the optimal ratio of Na-alginate and wet fungal biomass was 20:1 (m/m) and the initial pH was 6.5. In comparison, cell immobilization took at least 3 and 8 days earlier, respectively, to completely degrade cyanide and ferrocyanide. In addition, we showed that the immobilized beads could be easily recovered from the medium and reused for up to 5 batches without significant losses of fungal remediation abilities. The results of this study provide a promising alternative method for the large-scale remediation of soil or water systems from cyanide contamination.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".