The mechanism of catalase loading into porous vaterite CaCO<sub>3</sub> crystals by co-synthesis
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Bibliographic record
Abstract
Porous vaterite CaCO3 crystals are nowadays extensively used as high-capacity bio-friendly sacrificial templates for the fabrication of such protein-containing nano- and micro-particles as capsules and beads. The first step in the protein encapsulation is performed through loading of the protein molecules into the crystals. Co-synthesis is one of the most useful and simple methods proven to effectively load crystals with proteins; however, the loading mechanism is still unknown. To understand the mechanism, in this study, we focus on the loading of a model protein catalase into the crystals by means of adsorption into pre-formed crystals (ADS) and co-synthesis (COS). Analysis of the physico-chemical characteristics of the protein in solution and during the loading and simulation of the protein packing into the crystals are performed. COS provides more effective loading than ADS giving protein contents in the crystals of 20.3 and 3.5 w/w%, respectively. Extremely high loading for COS providing a local protein concentration of about 550 mg mL-1 is explained by intermolecular protein interactions, i.e. formation of protein aggregates induced by CaCl2 during the co-synthesis. This is supported by a lower equilibrium constant obtained for COS (5 × 105 M-1) than for ADS (23 × 105 M-1), indicating a higher affinity of single protein molecules rather than aggregates to the crystal surface. Fitting the adsorption isotherms by classical adsorption models has shown that the Langmuir and BET models describe the adsorption phenomenon better than the Freundlich model, proving the aggregation in solution followed by adsorption of the aggregates into the crystals. We believe that this study will be useful for protein encapsulation through CaCO3 crystals using the COS method.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it