Calculation of apparent age by linear combination of facial skin parameters: a predictive tool to evaluate the efficacy of cosmetic treatments and to assess the predisposition to accelerated aging

Comparison of facial skin ageing in healthy Asian and Caucasian females quantified by in vivo line-field confocal optical coherence tomography 3D imaging

BACKGROUND

Quantitative biomarkers of facial skin aging were investigated in 109 healthy Asian female volunteers, aged 20 to 70 years.

MATERIALS AND METHODS

In vivo 3D Line-field Confocal Optical Coherence Tomography (LC-OCT) imaging, enhanced by Artificial Intelligence (AI)-based quantification algorithms, was utilized to compute various metrics, including stratum corneum thickness (SC), viable epidermal (VE) thickness, and Dermal-Epidermal Junction (DEJ) undulation along with cellular metrics for the temple, cheekbone, and mandible.

RESULTS

Comparison with data from a cohort of healthy Caucasian volunteers revealed similarities in the variations of stratum corneum and viable epidermis layers, as well as cellular shape and size with age in both ethnic groups. However, specific findings emerged, such as larger, more heterogeneous nuclei in both layers, demonstrated by an increase in nuclei volume and their standard deviation, and increased network atypia, all showing significant age-related variations. Caucasian females exhibited a flatter and more homogeneous epidermis, evidenced by a decreased standard deviation of the number of layers, and a less dense cellular network with fewer cells per layer, indicated by a decrease in cell surface density.

CONCLUSION

Ethnicity-wise comparisons highlighted distinct biological features specific to each population. Asian individuals showed significantly higher DEJ undulation, higher compactness, and lower cell network atypia compared to their Caucasian counterparts across age groups. Differences in stratum corneum and viable epidermal thickness on the cheekbone were also significant. LC-OCT 3D imaging provides valuable insights into the aging process in different populations and underscores inherent biological differences between Caucasian and Asian female volunteers.

Modeling of global skin aging indices among Caucasian and Asian women

BACKGROUND

The skin aging process is defined as the gradual degradation of several skin properties such as firmness, color, or the appearance of wrinkles. These properties can be assessed by trained experts, who perform an overall evaluation of the entire face.

OBJECTIVE

The objective of this paper is the construction of two Global Skin Aging Indices specifically designed to model the overall skin aging process of Caucasian and Asian women.

METHODS

Two hundred forty Asian women and 129 Caucasian women aged between 20 and 60 years old are recruited. Parameters related to wrinkles, sagging, elasticity, and skin tone are measured (clinically or instrumentally). The global skin aging index is defined as the normalized projection on the first principal component of a principal component analysis of the skin measurements. Then, linear regressions are performed between the indices and age of both panels.

RESULTS

The first principal component carries around 50% of the initial variance for both indices. Both Global Skin Aging Indices statistically correlate with age (R2 ≥ 0.7, p-value < 0.05). An equation linking the indices with age is computed.

CONCLUSION

The proposed indices are good indicators of the overall aging process for Caucasian and Asian women. They offer new approaches to assess antiaging product efficacy.

Evaluation of facial skin age based on biophysical properties in vivo

OBJECTIVE

The evaluation of skin age, reflecting overall facial characteristics, has not been established. Previous studies focused on visual assessment or individual-specific feature such as wrinkles or skin color. We studied the evaluation model of skin age index (SAI) including the overall aging features including wrinkles, skin color, pigmentation, elasticity, and hydration.

METHODS

Total 300 healthy women aged between 20 and 69 years included in this study. Pearson correlation analysis performed to identify the key factors among the biophysical properties with aging and developed the prediction model of SAI. Statistical regression analysis and machine learning technique applied to build the prediction model using the coefficient of determination (R² ) and root mean square error (RMSE). Validation study of the SAI model performed on 24 women for 6 weeks application with anti-aging product.

RESULTS

Prediction model of SAI consisted of skin elasticity, wrinkles, skin color (brightness, Pigmented spot, and Uv spot), and hydration, which are major features for aging. The cforest model to assess a SAI using machine learning identified the highest R² and lowest RMSE compared to other models, such as svmRadial, gaussprRadial, blackboost, rpart, and statistical regression formula. The cforest prediction model confirmed a significant decrease of predicted SAI after 6 weeks of application of anti-aging product.

CONCLUSION

We developed a prediction model to evaluate a SAI using machine learning, and led to accurate predicted age for overall clinical aging. This model can a good standard index for evaluating facial skin aging and anti-aging products.

Promoting new concepts of skincare via skinomics and systems biology-From traditional skincare and efficacy-based skincare to precision skincare

Traditional skincare involves the subjective classification of skin into 4 categories (oily, dry, mixed, and neutral) prior to skin treatment. Following the development of noninvasive methods in skin and skin imaging technology, scientists have developed efficacy-based skincare products based on the physiological characteristics of skin under different conditions. Currently, the emergence of skinomics and systems biology has facilitated the development of precision skincare. In this article, the evolution of skincare based on the physiological states of the skin (from traditional skincare and efficacy-based skincare to precision skincare) is described. In doing so, we highlight skinomics and systems biology, with particular emphasis on the importance of skin lipidomics and microbiomes in precision skincare. The emerging trends of precision skincare are anticipated.

Surface rejuvenating effect of Achillea millefolium extract

Proopiomelanocortin is a precursor peptide that gives rise to several neuropeptides including adrenocorticotrophic hormone (ACTH) and β-endorphin. POMC-derived peptides have been shown to be synthesized in human epidermis where they modulate numerous skin functions. Because we previously observed that melanocortin receptor-2 and μ-opioid receptor 1, the respective receptors for ACTH and β-endorphin decreased with ageing in human epidermis, we have selected an active ingredient (INCI name: Achillea millefolium extract) able to upregulate receptor expressions. The aim of the present work was first to evaluate the effect of A. millefolium extract on the expression pattern of various epidermal differentiation markers ex vivo in normal human skin biopsies using quantitative image analysis and second to evaluate its capacity to rejuvenate the appearance of skin surface in vivo. Results show an improved expression profile of cytokeratin 10, transglutaminase-1 and filaggrin in cultured skin biopsies as well as an increased epidermal thickness. In vivo, a 2-month treatment with A. millefolium extract at 2% significantly improved the appearance of wrinkles and pores compared with placebo. Results were also directionally better than those of glycolic acid that was chosen as reference resurfacing molecule.

Visible changes of female facial skin surface topography in relation to age and attractiveness perception

OBJECTIVES

Evolutionary psychology suggests that a woman's age and physical appearance are important mate choice criteria. Given that changes in female facial skin surface topography are important, prominent visible signs of aging, male perceptual sensitivity for variation in this trait may also affect preference and attractiveness judgment.

METHODS

Two experiments were conducted to investigate perception (Experiment 1) and noticeability (Experiment 2) of skin surface topography manipulations in facial images of six British women, aged 45-65 years. In Experiment 1 skin surface topography cues were completely removed on the cheeks, the "crow's feet" area adjacent to the eye, under the eyes, above the upper lip, and on the forehead while, in Experiment 2, it was removed gradually (20% increments) on the forehead and around the eyes. In both experiments, stimuli were presented to American and German participants (total N = 300, aged 15-55 years) in omnibus pair-wise combinations (within-face). With each pair, respondents were asked to select that face which they considered as younger looking (Experiments 1 and 2) and more attractive (Experiment 1).

RESULTS

Faces with skin surface topography cues removed were judged significantly younger and more attractive than their original (unmodified) counterparts, with modifications on the forehead and around the eyes showing the highest differences. In these areas, participants were able to detect at least a 20% visual change in skin surface topography.

CONCLUSIONS

The results support the assertion that even small changes in skin surface topography affect the perceptions of a woman's facial age and attractiveness and may, thus, also influence men's mate preferences.