Enhancement of Lytic Activity of HEWL Adsorbed on Biochar by the Optimization of Adsorption Conditions
Bibliographic record
Abstract
We have found that HEWL (hen egg white lysozyme) is effectively immobilized on biochar through adsorption, and the amount of HEWL adsorbed on biochar is strongly dependent on the pH value of adsorption solutions. The structure of HEWL adsorbed on biochar changed by the pH value of adsorption solutions and became similar to that of native HEWL at acidic pH value, although the structure of HEWL solubilized in the solution was the same in the range between pH 4 and 9. On the other hand, the lytic activity of biochar-adsorbed HEWL toward Micrococcus lysodeikticus was markedly influenced by the pH value of adsorption solutions and increased with decreasing the pH value. Moreover, the addition of KCl to adsorption solutions enhanced the lytic activity of biochar-adsorbed HEWL.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 teacher head, 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".