Randomised, split‐face study of a dermocosmetic cream containing <i>Sphingobioma xenophaga</i> extract and Neurosensine <sup>®</sup> in subjects with rosacea associated with erythema and sensitive skin
Bibliographic record
Abstract
INTRODUCTION: Rosacea is a chronic inflammatory skin condition associated with erythema, inflammation and skin sensitivity. OBJECTIVES: To assess the benefit of a dermocosmetic cream (DC cream) containing Sphingobioma xenophaga extract and soothing agent in adult females with rosacea-associated erythema and sensitive skin. MATERIALS AND METHODS: During phase 1, DC was applied twice daily on the randomized half-face and compared to usual-skincare (USC) for 28 days. During phase 2, DC was applied on the full face twice daily for 56 days. Clinical, instrumental and skin sensitivity assessments were performed at all visits; demodex density (standardized skin surface biopsy (SSSB) method) was performed at baseline and D28, quality of life (QoL) was assessed using the stigmatization questionnaire (SQ), Rosacea Quality of Life index (ROSAQoL) and Dermatology Life Quality Index (DLQI) at baseline and D84. RESULTS: At D28, a significant benefit of DC over USC was observed for erythema, tightness, burning and stinging (all p ≤ 0.05), erythema measured by chromameter (p < 0.01), corneometry and transepidermal water loss (p < 0.0001 and p < 0.05, respectively), skin sensitivity (p < 0.001) and significant reduction of mean demodex density (p < 0.05) on the DC side. At D84, DC significantly (all p < 0.05) improved clinical signs and symptoms on both sides of the face compared to baseline; SQ, ROSAQoL and DLQI scores improved by 40.4%, 25.0% and 55.7%, respectively compared to baseline. Tolerance was excellent. CONCLUSION: DC significantly improved erythema, skin sensitivity, demodex count, QoL and feeling of stigmatization of subjects with rosacea and is very well tolerated.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".