Matrix physicochemical properties affect activity of entrapped chlorophyllase
Bibliographic record
Abstract
Abstract Chlorophyllase, a membrane glycoprotein, was entrapped in various matrices, including alginate, alginate–silicate mixed gel, TMOS‐based sol–gel, and their hydrophobically‐modified counterparts. Chlorophyllase activity was affected by the physicochemical properties of the matrix, demonstrating lower activity in organically‐modified matrices compared with the corresponding hydrophilic matrices. The advantage of adopting organically‐modified matrices to facilitate the transfer of hydrophobic substrate is likely compromised by detrimental interaction between chlorophyllase and the hydrophobic components. This hypothesis is at least partly substantiated by the negligible activity demonstrated by free chlorophyllase in hydrophobic micellar media. Even though activity yields exceeded 50% in alginate beads, the release profile reveals that alginate matrix is too porous to retain chlorophyllase. Although alginate–silicate mixed gel more effectively confined chlorophyllase in the matrix, only 16% of the activity was recovered. In contrast, inorganic sol–gel yielded a chlorophyllase preparation with mass yield above 90%, and activity yield above 50%. Doping additives did not improve activity yield, which could be explained by the lower specific surface area and pore volume, and hence possible restricted accessibility of chlorophyllase by its substrate. Water/silane ratio was found to affect the sol–gel‐entrapped chlorophyllase activity by influencing the gelation time and physical properties of the gel. Copyright © 2005 Society of Chemical Industry
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".