Lipid-Based Delivery Systems for Flavonoids and Flavonolignans: Liposomes, Nanoemulsions, and Solid Lipid Nanoparticles
Bibliographic record
Abstract
Herbal chemicals with a long history in medicine have attracted a lot of attention. Flavonolignans and flavonoids are considered as two classes of the above-mentioned compounds with different functional groups which exhibit several therapeutic capabilities such as antimicrobial, anti-inflammatory, antioxidant, antidiabetic, and anticancer activities. Based on the studies, high hydrophobic properties of the aforementioned compounds limit their bioavailability inside the human body and restrict their wide application. Nanoscale formulations such as solid lipid nanoparticles, liposomes, and other types of lipid-based delivery systems have been introduced to overcome the above-mentioned challenges. This approach allows the aforementioned hydrophobic therapeutic compounds to be encapsulated between hydrophobic structures, resulting in improving their bioavailability. The above-mentioned enhanced delivery system improves delivery to the targeted sites and reduces the daily required dosage. Lowering the required daily dose improves the performance of the drug by diminishing its side effects on non-targeted tissues. The present study aims to highlight the recent improvements in implementing lipid-based nanocarriers to deliver flavonolignans and flavonoids.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".