Development of Macroporous Titania Monoliths by a Biocompatible Method. Part 2: Enzyme Entrapment Studies
Bibliographic record
Abstract
Although sol−gel-derived silica materials have been extensively used as a matrix to immobilize enzymes and other proteins, the poor pH stability and fragility of silica limits its utility in applications that require operation at pH >8. Herein, we report an alternative matrix, sol−gel-derived monolithic titania, for protein entrapment. The material is prepared from biocompatible precursors using aqueous processing conditions involving the formation of a glycerol−titania composite sol followed by titania condensation and can be made macroporous by the addition of poly(ethylene oxide). The clinically relevant protein γ-glutamyl transpeptidase (γ-GT) was entrapped in monolithic titania, and the effects of the titania sol−gel processing parameters on the retention (leaching), catalytic constant ( k cat ), Michaelis constant ( K M ), and long-term stability of entrapped γ-GT were investigated. It was found that the retention of γ-GT within the monolith was strongly related to the glycerol and PEO concentrations in the starting sol. Under optimal conditions, up to 70% of enzyme initially added to the titania sol was retained in the gel even after copious washing. Entrapped γ-GT demonstrated a higher K M and lower k cat value than in solution, indicating that substrate turnover was limited by partitioning effects and/or diffusion through the titania matrix. The entrapped enzyme demonstrated better long-term stability than in solution, likely because of protection from unfolding within a rigid titania pocket as well as the liberation of the biocompatible reagent glycerol during the sol−gel process. The entrapped enzyme did not show any loss of activity after storage at 4 °C for 3 weeks, but did show a loss in activity beyond this time. Potential applications of protein-doped titania are described.
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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) | 0.001 | 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".