Product Images Leaders Coconut Lifting Recovery Mask

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The following image provide visual information about the product associated with Leaders Coconut Lifting Recovery Mask NDC 69424-390 by Sansung Life & Science Co., Ltd., such as packaging, labeling, and the appearance of the drug itself. This resource could be helpful for medical professionals, pharmacists, and patients seeking to verify medication information and ensure they have the correct product.

Image of cello pack - leaders coconut lifting recovery mask cello pack

Image of cello pack - leaders coconut lifting recovery mask cello pack

The Leaders Insolution Coconut Gel Lifting Recovery Mask is a dermatologist formulated mask for boosting elasticity and restoring skin density for firmer, younger-looking skin. The mask is made of 100% naturally fermented coconut gel, containing vitamins B and C, which provides 10 times more hydration than a cotton mask. The gel adheres perfectly to the skin giving natural soothing and hydrating properties that help in improving elasticity and appearance of wrinkles. The mask's active lifting ingredients help supply a firming effect by strengthening skin tissues and enhancing skin texture. The package contains a single-use mask with a 30 ml volume. Users should ensure to clean and dry their face before use, remove the mask from the package, contour it to fit the curves around the eyes, nose, and mouth, and leave on for 10-20 minutes, then remove the mask and gently pat the face with fingertips until the remaining serum is fully absorbed. The suggested use is 2-3 times a week. The mask is a skin protectant and is for external use only, and one should avoid contact with eyes. The mask is made by Sansung Life & Science Co., Ltd., and distributed by Leaders Cosmetics USA Inc., and it contains Witch Hazel Water and other active and inactive ingredients, and the expiry date is marked on the package. Users can contact [email protected] or call 1-213-788-3597 for questions or comments.*

* The product label images have been analyzed using a combination of traditional computing and machine learning techniques. It should be noted that the descriptions provided may not be entirely accurate as they are experimental in nature. Use the information in this page at your own discretion and risk.