Erythropoietin Encapsulation in Chitosan Nanoparticles and Kinetics of Drug Release
Bibliographic record
Abstract
Recombinant human erythropoietin (rHu-EPO) is a glycoprotein, which is produced commercially from Chinese hamster ovary (CHO) cells. It is used for the therapy of renal anemia and chemotherapy-induced anemia in cancer patients. Recent evidence suggests that rHu-EPO exerts tissue protective effects via multiple mechanisms which include inhibition of apoptosis, promotion of angiogenesis and decreased inflammation. After intravenous (i.v.) injection, the blood concentration of rHu-EPO rapidly decreases due to proteolysis resulting in a relatively short half-life of 8.5 h, which necessitates regular dosing with intervals that do not exceed 7 days. It would be desirable to develop an encapsulated formulation providing controlled release of rHu-EPO to maintain therapeutic concentrations in plasma, and for potential tissue protective applications to maintain high local therapeutic concentrations in tissue while minimizing potential unwanted systemic effects such as polycythemia and platelet activation, both of which can predispose to intravascular thrombosis. Nanoparticle encapsulation of rHu-EPO can also allow for direct injection at sites of injury in specific tissues/organs, again minimizing systemic exposure of the drug. In this paper, we report the production of biopolymer nanoparticles by ionotropic gelation of chitosan with tripolyphosphate (TPP). The nanoparticle size distribution in aqueous solution was determined and rates of rHu-EPO release from chitosan-TPP nanoparticles were measured in PBS at 37°C. It was observed that almost 30% of the encapsulated rHu-EPO was released within the first 48 hours and thereafter a linear release profile was observed for up to 2 weeks. Total drug release over 15 days was 63% of the initial amount.
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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) | 0.000 | 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) | 0.001 | 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".