Oleogels for the Promotion of Healthy Skin Care Products: Synthesis and Characterization of Allantoin Containing Moringa-based Oleogel
Bibliographic record
Abstract
Background: Oleogelation is an efficient and emerging approach for obtaining biocompatible and biodegradable elastic semisolid crystals to be used in various cosmetic and pharmaceutical formulations. Recently, drug incorporation in oil structuring has been a promising strategy under consideration due to the effectiveness of this method. Plant oils have very beneficial characteristics for skin care and wound healing due to the presence of certain antioxidants. Methods: In this study, the oleogels of Moringa oleifera seed oil with natural polysaccharides, including pectin, chitosan, and xanthan gum, were prepared using the emulsion template method. Moringa oil was selected because it can hydrate and moisturize the skin and has great antioxidant activity. Also, the natural polysaccharides, i.e., pectin and chitosan, exhibited good gelling properties. Allantoin, which is a wound healer and eucalyptus leaf oil with antioxidant potential, was incorporated into the emulsion-based-oleogels to enhance the antioxidant and antimicrobial activity of the oleogels. Results: Allantoin and eucalyptus-loaded oleogels exhibited good antibacterial activity against E. coli. The FTIR spectra of moringa-based oleogels in the range between 3226-3422 cm-1 indicate the presence of hydrogen bonding in oleogels. Conclusion: The antioxidant potential of allantoin and eucalyptus-containing oleogel was maximized, and an IC50 value of 0.9719 μM was found. Maximum release of allantoin from oleogel was observed in the first hour.
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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) | 0.000 | 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 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".