In Vitro Human Skin Penetration of Geraniol and Citronellol
Bibliographic record
Abstract
BACKGROUND: Geraniol and citronellol are commonly used fragrance components in consumer products. Both are listed as alleged fragrance allergens that should be declared in the European Union when used in cosmetics and consumer products. Such allergenic potential is determined largely by effects on the skin once these materials penetrate and elicit an immune response. Few data demonstrate their penetration abilities or their effects on percutaneous absorption. We wanted to determine the effects of these materials on skin absorption. Skin penetration characterization via flow-through diffusion study serves as a reasonable model for determining dermal dosing for fragrance materials. Such characterization can be used for more accurate safety exposure calculations and regulatory determinations. Extensive comparisons to in vivo data in humans or closely related animals will be required before accepting flow-through diffusion methods as in vivo alternatives by industry and regulatory bodies. OBJECTIVE: To evaluate the penetration abilities of geraniol and citronellol when they are used in a typical vehicle in consumer products. METHODS: In vitro skin penetration of radiolabeled geraniol and citronellol was studied under occlusion in human cadaver skin, using flow-through diffusion cells for scintillation counting to determine the percentage of dose absorbed. For comparison, two doses of each material were used: 2% and 5% in 3:1 diethyl phthalate/ethanol. RESULTS: After 24 hours, geraniol and citronellol had relatively low skin absorption rates; 3.8% +/- 2.1% of 2% citronellol, 4.7% +/- 1.9% of 5% citronellol, 3.5% +/- 1.9% of 2% geraniol, and 7.3% +/- 1.1% of 5% geraniol were recovered from skin and receptor fluid compartments. These materials showed good mass-balance recovery. The majority of the dose was recovered in the skin washes (a minimum of 64.7% +/- 4.6% recovered for 2% citronellol and a maximum of 79.3% +/- 3.9% recovered for 5% geraniol). Receptor fluid collection points over time showed a linear increase in the amounts of citronellol and geraniol that penetrated the skin, although overall absorption values were quite small. CONCLUSION: In vitro results indicate that geraniol and citronellol have low potentials for skin penetration, which has implications for their ability to induce allergenicity and for more predictive toxicologic profiling of these materials. In vivo studies should be done to correlate the in vitro results.
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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 | 0.000 | 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) | 0.003 | 0.001 |
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".