NANOSTRUCTURED LIPID CARRIERS AS A PROMISING DERMAL DELIVERY PLATFORM FOR ST. JOHN'S WORT EXTRACT: PRELIMINARY STUDIES
Bibliographic record
Abstract
urpose: Nanostructured lipid carriers (NLC) can improve the stability of various phytochemicals, so this research aimed to develop and employ such delivery systems for Hypericum perforatum extract containing the light- and oxygen-sensitive phloroglucinol hyperforin. Materials and methods: By varying the processing parameters and the solid and liquid lipids used, different NLC models were obtained via emulsification, followed by high-shear homogenization and ultrasonication. After characterization of the elaborated nanocarriers, those that exhibited optimal properties were loaded with St. John's wort extract by incorporating it in the lipid phase before emulsification and also studied. Results: The NLC models developed by prolonged ultrasonication demonstrated favorable characteristics regarding particle size, polydispersity index (PDI), and zeta potential (ZP). The physically stable during long-term storage nanosystems, which also showed a reduced degree of crystallinity of the solid lipid included, were loaded with St. John's wort extract. Of the carriers so-obtained, those developed by ultrasonication at ambient temperatures can be described as acceptably uniform systems (PDI from 0.23±0.01 to 0.27±0.01), comprising particles with dimensions below 200 nm, favorable ZP values (ζ > |30 mV|), and superior entrapment efficacy (EE) greater than 85%. Conclusion: In this research, different stable NLC dispersions were successfully developed. After the inclusion of the St. John's wort extract, the model possessing the highest EE (87.77±0.64%) was chosen as a carrier to conduct further studies evaluating its wound-healing potential.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".