Effect of particle size on the oral absorption of isoliquiritigenin nanocrystals
Bibliographic record
Abstract
Abstract As one of the most promising formulations for poorly water-soluble drugs, nanocrystals have been attracting increasing attention in recent years. Isoliquiritigenin (ISL) is a flavonoid with a chalcone structure, and possesses many biological activities. However, its clinical application is significantly limited mainly due to its low oral bioavailability caused by poor hydrophilicity. To address this, ISL nanocrystals were developed in this study to improve its oral bioavailability. Three types of nanocrystals with differing particle size; R1, R2, and R3, were prepared by anti- solvent precipitation or anti-solvent precipitation combined with sonication, which was optimized by single-factor experiments. These nanocrystals were characterized based on their physical properties, in vitro release, and in vivo absorption performance. The mean particle size of R1, R2, and R3 was 555.7, 271.0, and 46.2, respectively. The dissolution ratio of ISL in the nanocrystals was significantly improved, with the quickest rate recorded in R2. Peak concentration and area under the concentration-time curve of R2 after oral administration in rats was 5.83- and 2.72-fold higher than that of the ISL solution, respectively. These findings indicate that the dissolution and absorption of ISL can be significantly enhanced by nanocrystals, and the dissolution behavior and pharmacokinetic properties of nanocrystals is significantly influenced by particle size.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.006 |
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".