Comparison of Drying Techniques to Produce Stable and Bioavailable Encapsulated ACE-2 Nanoparticles
Bibliographic record
Abstract
Background/Objectives: COVID-19 infection continues globally, with frequent emergence of unfamiliar SARS-CoV-2 variants acting to impair immunity. The competitive binding of SARS-CoV-2 spike proteins and angiotensin-converting enzyme 2 (ACE-2) can decrease the binding of the virus on native ACE-2 receptors on healthy human cells. It remains a practical approach to lessen viral spread. In this study, a method to encapsulate ACE-2 in the form of chitosan/tripolyphosphate cross-linked nanoparticles (NPs) was developed with emphasis placed on the best dehydration method to secure functional ACE-2 nanoparticles. Methods: Methods: Preparation conditions were assessed by varying pH (4.0–6.5) and the ratio between chitosan and ACE-2 mixing ratios (1:1, 1.5:1, 2:1, 2.5:1, and 3:1). The formulated NPs were then dehydrated using different approaches that included spray-drying (SD), freeze-drying (FD), and spray-freeze drying (SFD) and used varying mannitol concentrations (0, 1:1, and 5:1 of total weight). The mannitol was served as a cryoprotectant in this study. Results: The best formulation achieved used a pH 5.5 with a mixing chitosan–ACE-2 ratio of 2:1, where ACE-2-loaded NPs had an average particle size of 303.7 nm, polydispersity index (PDI) of 0.21, encapsulation efficiency (EE) of 98.4%, and ACE-2 loading content (LC) of 28.4%. After reconstitution, all SD samples had a relatively low yield rate, but the ACE-2 NPs dehydrated specifically using SFD required a lower amount of added mannitol (1:1 of its total weight) and produced a higher yield rate (p < 0.05) and similar PDI and EE values, along with relatively good particle size and LC. This formulation also produced a high ACE-2 release and uptake in differentiated Caco-2 cells, thus representing an effective ACE-2 encapsulation procedure for use with dry powders. Conclusions: This work showed that spray-freeze drying was the best method to dehydrate ACE-2 NPs, using less cryoprotectant to create a significant advantage in terms of greater loading capacity with lower additive requirements.
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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".