The effect of ceramides on skin absorption by Raman spectroscopy
Bibliographic record
Abstract
INTRODUCTION: Ceramides are essential epidermal constituents that play a critical role in skin moisturization treatment as a raw material in cosmetics formulation. Recently, ceramides have been known to be frequently applied in various cosmetic formulations. Despite ceramide's beneficial characteristics, academic research regarding ceramides and their skin absorption remains insufficient. Therefore, our study conducted clinical research employing Raman spectroscopy to investigate the effects of ceramides on skin absorption to enhance the understanding of ceramides' dermatological functionality and their topical application in cosmetics science. MATERIALS AND METHODS: Twenty healthy individuals with dry skin have participated in this clinical trial. In this double-arm designed trial, the test group received an investigational product with ceramides (5000 ppm) and a control group received an investigational product without the ceramides while all other components remained identical. The subjects visited the clinical research center and acclimatized for 30 min in constant humidity and temperature for equilibrium, subsequently conducting a measurement. Before the trial, the research subject's target site (lower arm area) was kept clean, devoid of any cosmetic administering 24 h before the trial when investigational product was topically applied. RESULTS: Our findings with Raman spectroscopy statistically demonstrate that skin absorption amount, speed and depth for both groups improved overall (p < 0.05) after administration of the investigational product. Notably, the test group received an investigational product with ceramides (5000 ppm) indicating superior effectiveness across all parameters compared to a control group from comparison analysis of each parameter (p < 0.05). CONCLUSION: This study concludes that ceramide-containing cosmetics provide a beneficial effect on skin absorption via visual and statistical results of Raman spectroscopy analysis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".