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- W4366184015 abstract "Introduction: Hyperpigmentation disorders (HPD) are a frequent reason for dermatology consultations as they can impair quality of life. The most frequent HPD are melasma, post-inflammatory hyperpigmentation and solar lentigos with increased melanin content on top of other pathophysiologic features. The development of an efficient and safe ingredient to manage facial skin tone heterogeneities is of great importance. Objectives: To evaluate the anti-pigmentation efficacy of 2-MNG in preventing UV-induced pigmentation in Chinese skin. Methods: Ten studies were conducted in Chinese women (20-50y). For each study, 30 volunteers of phototype III were recruited. Several products were applied (4mg/cm2) on mini zones of the back, in a randomized and blinded protocol, five days a week for seven weeks. During the second week, volunteers were exposed to 0.5MED of UV-daylight during 4 consecutive days. Assessments were performed using Chromameter and pigmentation and erythema scales. All studies were conducted under exactly the same conditions and validated using vitamin C 7% standard pivot. A Bayesian meta-analysis established a large comparison of 2-MNG anti-pigmentation performance versus 19 recognized actives (i.e. Kojic acid, Phenylethyl Resorcinol, Baicalin, Ellagic acid, Resveratrol, Ascorbyl glucoside, 4-butyl-resorcinol, Niacinamide). Results: 2-MNG 0.5% showed a significant anti-pigmentation efficacy versus vehicle. The meta-analysis showed that 2-MNG 0.5% provides statistically superior anti-pigmentation performance compared to all selected standards. Conclusions: This new ingredient is highly efficient compared to recognized marketed active ingredients. It is a promising approach allowing to develop dermocosmetic targeting hyperpigmentation concerns." @default.
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- W4366184015 date "2023-05-01" @default.
- W4366184015 modified "2023-09-28" @default.
- W4366184015 title "1258 Topical 2-mercaptonicotinoyl glycine (2-MNG): Anti-pigmentation performance versus recognized standards through bayesian meta-analysis in networks" @default.
- W4366184015 doi "https://doi.org/10.1016/j.jid.2023.03.1272" @default.
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