Hydroxyisohexyl 3-Cyclohexene Carboxaldehyde (Lyral) in Patch Test Preparations Under Varied Storage Conditions
Bibliographic record
Abstract
BACKGROUND: The common practice of preparing patch tests in advance has recently been called into question by researchers. It has been established that fragrance compounds are volatile and their testing efficacy may be affected by storage conditions and preparation. Allergens in fragrance mix I rapidly decrease in concentration after preapplication to test chambers. OBJECTIVES: This study aimed to investigate the volatility of hydroxyisohexyl 3-cyclohexene carboxaldehyde (HICC) in petrolatum when stored in test chambers and to explore the correlation between vapor pressure and allergen loss in petrolatum during preparation and storage. METHODS: Standardized HICC in petrolatum was prepared and stored in IQ Chambers and Finn Chambers with covers at 5°C, 25°C, and 35°C, and concentration was analyzed at intervals for up to 9 days using gel permeation chromatography. RESULTS: Changes in HICC concentrations were not statistically significant at 8 hours at 5°C, 25°C, and 35°C. After 9 days, HICC concentrations were found to fall approximately 30% when stored at 35°C, 10% at 25°C, and less than 5% at 5°C. There was no significant difference between IQ and Finn chambers. CONCLUSIONS: Hydroxyisohexyl 3-cyclohexene carboxaldehyde concentrations are more stable in petrolatum than many other studied fragrance allergens, but HICC is still at risk for decreasing concentration when exposed to ambient air or heat for prolonged periods.
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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 | 0.001 |
| 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".