Utilization of cross‐linked laccase aggregates in a perfusion basket reactor for the continuous elimination of endocrine‐disrupting chemicals
Bibliographic record
Abstract
A perfusion basket reactor (BR) was developed for the continuous utilization of insolubilized laccase as cross-linked enzyme aggregates (CLEAs). The BR consisted of an unbaffled basket made of a metallic filtration module filled with CLEAs and continuously agitated by a 3-blade marine propeller. The agitation conditions influenced both the apparent laccase activity in the reactor and the stability of the biocatalyst. Optimal laccase activity was obtained at a rotational speed of 12.5 rps and the highest stability was reached at speeds of 1.7 rps or lower. The activity and stability of the biocatalyst were affected drastically upon the appearance of vortices in the reaction medium. This reactor was used for the continuous elimination of the endocrine disrupting chemicals (EDCs) nonylphenol (NP), bisphenol A (BPA), and triclosan (TCS). Optimization of EDC elimination by laccase CLEAs as a function of temperature and pH was achieved by response surface methodology using a central composite factorial design. The optimal conditions of pH and temperature were, respectively, 4.8 and 40.3 degrees C for the elimination of p353NP (a branched isomer of NP), 4.7 and 48.0 degrees C for BPA, and 4.9 and 41.2 degrees C for TCS. Finally, the BR was used for the continuous elimination of these EDCs from a 5 mg L(-1) aqueous solution using 1 mg of CLEAs at pH 5 and room temperature. Our results showed that at least 85% of these EDCs could be eliminated with a hydraulic retention time of 325 min. The performances of the BR were quite stable over a 7-day period of continuous treatment. Furthermore, this system could eliminate the same EDCs from a 100 mg L(-1) solution. Finally, a mathematical model combining the Michaelis-Menten kinetics of the laccase CLEAs and the continuous stirred tank reactor behavior of the BR was developed to predict the elimination of these xenobiotics.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".