Encapsulation of Recombinant ACE-2 in Chitosan Nanoparticles for Treatment of SARS-CoV-2 Infection
Bibliographic record
Abstract
COVID-19 infection continues globally with frequent emergence of unfamiliar SARS-CoV-2 variants acting to impair immunity conferred by vaccines. The competitive binding of SARS-CoV-2 spike proteins by angiotensin-converting enzyme 2 (ACE-2) to mimetic and act as a de-coy over that by native ACE-2 receptors on healthy human cells re-mains a practical approach to lessen viral spread. In this study, a therapeutic strategy was developed that targeted gastrointestinal SARS-CoV-2 infection using ACE-2 encapsulated in chi-tosan/tripolyphosphate cross-linked nanoparticles (NPs). Optimization conditions were determined by varying pH (4.0-6.5) and chitosan: ACE-2 mixing ratios (1:1, 1.5:1, 2:1, 2.5:1, 3:1), followed by choice of spray-drying (SD), freeze-drying (FD), or spray-freeze drying (SFD) with varying mannitol concentrations (0, 1:1, and 5:1 of total weight). The optimal formulation was achieved using 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, encapsula-tion efficiency (EE) of 98.4%, zeta potential of 6.8 mV, and ACE-2 loading content (LC) of 28.4%. In general, all drying methods main-tained the spherical shape of the NPs with varying mannitol concen-tration having a significant (P<0.05) effect. After reconstitution, all SD samples had a relatively low yield rate, but the ACE-2 NPs dehydrated specifically by 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 en-capsulation procedure for use with dry powders.
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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 | 0.001 | 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 | 0.001 | 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".