Abstract: A method is disclosed. The method is generally useful for modifying a skin microbiome. The method comprises administering a topical composition to a subject's skin. A topical composition is also disclosed. The topical composition may be used for the method. The topical composition comprises a population of microorganisms, a component obtained from the population of microorganisms, or a combination thereof. The population of microorganisms is generally a Corynebacterium species. The Corynebacterium species comprises at least about 90%, optionally at least about 97%, sequence identity to a 16S rRNA sequence (SEQ ID NO: 1).

Abstract: A composition and a method for improving the gastrointestinal (GI) health of a human subject by promoting the activity of amylolytic and short-chain fatty acid (SCFA) producing (e.g. acetogenic and/or butyrogenic) microbes in the GI system of a human subject. The composition includes a mixture of microbiota accessible carbohydrates (MACs) that includes at least two different resistant starches and at least two different non-starch polysaccharides. A blend for inclusion in a dietary supplement includes, or is, the mixture.

Abstract: Methods and systems are disclosed to realistically simulate facial wrinkle aging of a person using a neutral state (natural look) image and one or more expression images (e.g., smile, frown, pout, wink) that induce wrinkles. The neutral and expression images are processed to simulate wrinkle aging by registering the wrinkles that are visible in the expression image onto the neutral image, thereby generating a wrinkle-aged simulated image. Advantageously, a person's own wrinkle histological data is utilized, hence providing an accurate and realistic wrinkle aging simulation. Similarly, the neutral image is processed to eliminate all visible wrinkles thereby generating a wrinkle de-aged simulation image. Additionally, blending of a neutral image with an aged or de-aged simulation image is disclosed, where the degree of blending is based on statistical modeling of skin condition with age and/or expected outcome of a particular type of treatment.