Synthesis of nano‐niosomal deferoxamine and evaluation of its functional characteristics to apply as an iron‐chelating agent
Bibliographic record
Abstract
Abstract Deferoxamine has been widely used as an iron‐chelating agent in patients with primary or secondary iron overload deficiency. Deferoxamine is typically administered subcutaneously, intramuscularly, or intravenously by the constant infusion of the drug over 8–12 h. This process is lengthy and uncomfortable for the patients. A nano‐niosomal form of deferoxamine was prepared using the reverse phase evaporation method and evaluated on the basis of morphology, drug release, cytotoxicity, and iron‐chelating efficacy to compare with free drug formulation. The unique structure of niosome enables sustained release of the drug over extended periods. The average particle size was 136 nm and the entrapment efficiency was about 96 %. The biocompatibility of the drug‐loaded nanoparticles showed that the encapsulation of the drug in nano‐niosomes reduces the toxicity of the drug significantly. Our results indicate that the iron‐chelating ability of the entrapped deferoxamine in hepatocytes is higher than the free drug. The nano‐niosomal drug form showed more efficacies versus the free one and it could be a promising clinical intravenous system for delivery of iron‐chelating drugs such as deferoxamine.
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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".