SALICYLIC ACID INCORPORATION IN Fe3O4-BSA NANOPARTICLES FOR DRUG RELEASE
Bibliographic record
Abstract
The controlled release of Salicylic Acid (SA) influences the concentration and collateral effects of the drug. This release refers to the matrix in which the SA is incorporated. Among the matrices, Fe3O4 nanoparticles (NPs) stand out, for transporting drugs to specific sites. The functionalization of Fe3O4 by bovine serum albumin (BSA) can improve colloidal and chemical stability, in addition to increasing interactions with drugs. Thus, understanding the release kinetics of the AS incorporated in Fe3O4-BSA is essential to improve the controlled release. The study aimed the synthesis, characterization and release of the SA into the Fe3O4-BSA NPs. The results showed the functionalization of the Fe3O4-BSA NPs was effective and the average size was below 30 nm. The NPs showed colloidal stability above the pH of 7.5 which can be used as a drug carrier in blood plasma. Drug encapsulation into the NPs system was efficient (~91%) with about 30% of drug loading capability. The kinetic results showed the SA release mechanism was controlled by diffusion. The conclusion is that the incorporation of SA in Fe3O4-BSA NPs led to a release of SA in the first six hours, reaching equilibrium at 0.265 mg mL-1 and 1.83 mg.
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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".