Evaluating the Impact of a Cream Containing Horse Placental Extract on Eye Corner Wrinkles in Healthy Women: Single-Blind Comparative Study
Bibliographic record
Abstract
BACKGROUND: Placental extract has been mostly used in skin care for cosmetic purposes. However, the use of various placental extracts has been limited due to the lack of established and effective application methods. OBJECTIVE: In this study, we investigated the antiwrinkle effect of a cream formulation-LNC wrinkle eye cream (LNC-EC)-containing horse placental extract as the main ingredient. METHODS: A total of 24 healthy women, aged 37-54 years, with wrinkle grades 1-3, were treated with LNC-EC for 2 weeks. The cream was applied on one-half of the participants' faces, and the results were compared with the untreated half of the face. RESULTS: Visual inspection, using the wrinkle grade standard, showed that the area treated with LNC-EC had a significantly lower wrinkle grade than the untreated area when comparing before and after the application of LNC-EC. In addition, replica analysis showed a significant reduction in both the maximum wrinkle width and the number of wrinkles in the LNC-EC-treated area in comparison to the untreated area before and after the application. These results suggest that LNC-EC has an antiwrinkle effect on the corners of the eyes based on parameters like the maximum wrinkle width and the number of wrinkles. CONCLUSIONS: LNC-EC, with horse placental extract as its main ingredient, was shown to be effective in improving wrinkles at the eye corners, presumably due to a reduction in the maximum wrinkle width and the number of wrinkles. Interpretation of the results is limited because this study was conducted only in the intervention group. A randomized controlled trial with a placebo control group is necessary to verify the antiwrinkle effects of horse placental extract.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".