Effect of Terpenes on the Skin Permeation of Lomerizine Dihydrochloride
Bibliographic record
Abstract
PURPOSE: Lomerizine dihydrochloride (LOM) is a Ca2+ channel blocker used as an antimigraine drug, which is currently administered orally in Japan. We therefore investigated the effect of terpenes in propylene glycol (PG) solvent on the percutaneous absorption of LOM by hairless mouse skin. METHODS: Attenuated total reflection-Fourier transform infrared spectroscopy (ATR-FTIR), confocal laser scanning microscopy (CLSM), and small angle X-ray scattering (SAXS) were carried out to analyze the effects of terpene enhancers on the biophysical properties of the stratum corneum (SC) of the skin. RESULTS: Of the terpenes tested, the highest permeation rate of LOM (28.8 mg/cm2/h) was observed with 1,8-cineole, while nerolidol conferred the lowest enhancement of LOM flux (14.2 mg/cm2/h). ATR-FTIR studies revealed that terpenes/PG induced higher CH2 stretching frequencies of SC lipids than PG alone. The extent of penetration of the lipophilic fluorescence probes Nile Red and DiI was measured by CLSM in in vitro skin permeation studies, using either PG or terpenes/PG as skin permeation enhancers. With PG alone, both fluorescence dyes were undetectable in the skin. In contrast, when co-administered with terpenes/PG, both probes were distributed into the intercellular space between corneocytes and detected in the deeper layers of the skin. SAXS measurements showed that in SC treated with a combination of 1,8-cineole and PG, the scattering peak of the SC was broad and very weak in intensity compared to untreated SC, whereas pretreatment with PG alone did not alter the peak profile. CONCLUSION: A combination of terpenes and PG enhance the skin permeation of LOM. Our findings suggest that the mechanism for this effect involves the ability of terpenes to increase the fluidity of SC lipids, thus enhancing the distribution of LOM into the intercellular region of the SC. This article is open to POST-PUBLICATION REVIEW. Registered readers (see "For Readers") may comment by clicking on ABSTRACT on the issue's contents page.
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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".