Aging Skin: Nourishing from the Inside Out, Effects of Good Versus Poor Nitrogen Intake on Skin Health and Healing

Skin is the outermost defense organ which protects us from the environment, constituting around 8 % of an adult’s body weight. Healthy skin contains one-eighth of the body’s total proteins. The balance of turnover and synthesis of skin proteins is primarily dependent on the availability of sufficient nitrogen-containing substrates, namely, amino acids, essential for protein metabolism in any other tissue and body organs. The turnover of skin proteins has been shown to be rapid, and the mobilization of amino acids at the expense of skin proteins is relevant in experimental models of protein malnutrition. As a result, alterations in nutritional status should be suspected, diagnosed, and eventually treated for any skin lesions. Protein malnutrition has a dramatic prevalence in patients aged >70 or more, independent of the reason for hospitalization. The quality of nutrition and content of essential amino acids are strictly connected to skin health and integrity of its protein components. Collagen fiber deposition is highly and rapidly influenced by alterations in the essential to nonessential amino acid ratios. The most relevant nutritional factor of skin health is the prevalence of essential amino acids

Assessment of skin photoaging with reflectance confocal microscopy

Background/Purpose: Increased interest in antiaging methods, mandates a development of reliable noninvasive technique to assess skin aging. In this study, we aimed to determine the effects of photoaging at histopathologic resolution by means of reflectance confocal microscopy

Computational characterization of reflectance confocal microscopy features reveals potential for automated photoageing assessment

Skin photoageing results from a combination of factors including ultraviolet (sun) exposure, leading to significant changes in skin morphology and composition. Conventional methods assessing the degree of photoageing, in particular histopathological assessment involve an invasive multistep process. Advances in microscopy have enabled a shift towards non-invasive in vivo microscopy techniques such as reflectance confocal microscopy (RCM) in this context. Computational image analysis of RCM images has the potential to be of use in the non-invasive assessment of photoageing. In this report, we computationally characterized a clinical RCM data set from younger and older Caucasians with varying levels of photoageing. We identified several mathematical relationships that related to the degree of photoageing as assessed by conventional scoring approaches (clinical photography, SCINEXA and RCM). Furthermore, by combining the mathematical features into a single computational assessment score, we observed significant correlations with conventional RCM (