Laccase immobilization and insolubilization: from fundamentals to applications for the elimination of emerging contaminants in wastewater treatment
Bibliographic record
Abstract
Over the last few decades many attempts have been made to use biocatalysts for the biotransformation of emerging contaminants in environmental matrices. Laccase, a multicopper oxidoreductase enzyme, has shown great potential in oxidizing a large number of phenolic and non-phenolic emerging contaminants. However, laccases and more broadly enzymes in their free form are biocatalysts whose applications in solution have many drawbacks rendering them currently unsuitable for large scale use. To circumvent these limitations, the enzyme can be immobilized onto carriers or entrapped within capsules; these two immobilization techniques have the disadvantage of generating a large mass of non-catalytic product. Insolubilization of the free enzymes as cross-linked enzymes (CLEAs) is found to yield a greater volume ratio of biocatalyst while improving the characteristics of the biocatalyst. Ultimately, novel techniques of enzymes insolubilization and stabilization are feasible with the combination of cross-linked enzyme aggregates (combi-CLEAs) and enzyme polymer engineered structures (EPESs) for the elimination of emerging micropollutants in wastewater. In this review, fundamental features of laccases are provided in order to elucidate their catalytic mechanism, followed by different chemical aspects of the immobilization and insolubilization techniques applicable to laccases. Finally, kinetic and reactor design effects for enzymes in relation with the potential applications of laccases as combi-CLEAs and EPESs for the biotransformation of micropollutants in wastewater treatment are discussed.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".