Modified alginate matrices for the immobilization of bioactive agents
Bibliographic record
Abstract
Bioactive agents (catalase - an enzyme, and nisin - a bacteriocin) were covalently immobilized on alginate activated with sodium periodate (oxidatively converting 2,3-dihydroxy groups into dialdehyde residues), followed or preceded by ionotropic gelation. For the same protein coupling yield, the retained enzyme activity of the immobilized enzyme (ImE) can be markedly increased by diminishing the bead diameter, a phenomenon that illustrates the role of substrate/product diffusion through the bead gel layer. When the amount of enzyme introduced for coupling was about 15 mg/100 mg of support and the bead diameter was about 100 microm, a high retained specific activity (95-98%) was obtained. Diffusion phenomena can be markedly decreased by enzyme immobilization on the surface of microbeads (obtained by gelation of activated alginate prior to immobilization). In this case, the retained activity was approx. 75% of that of the free enzyme. A slightly higher K (m) value of ImE suggested that the enzyme-substrate affinity was almost maintained. The profiles of ImE activities at various pH values, at various temperatures and when undergoing proteolysis showed a overall higher stability for the immbolized than that for the free enzyme. Nisin immobilized on the microbead surface, when submitted to proteolysis, conserved its bacteriocin activity, strongly inhibiting the growth of Lactobacillus sake when subjected to an agar spot test, whereas free nisin totally lost its activity.
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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 | 0.000 | 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".