Development and application of artificial intelligence-based facial skin image diagnosis system: Changes in facial skin characteristics with ageing in Korean women.

OBJECTIVE: To develop and validate an artificial intelligence (AI)-based diagnostic system for analysing facial skin images using expert judgements and explore its feasibility for skin ageing research, specifically by evaluating facial skin changes in Korean women of various ages. METHODS: Our AI-based facial skin diagnosis system (Dr. AMORE®) uses facial images of Korean women to analyse wrinkles, pigmentation, skin pores, and other skin red spots. The system is trained using clinical expert evaluations and deep learning. We assessed the system's precision and sensitivity by analysing the correlation between the diagnoses by the AI system and those of the experts. We used 120 images of Korean women aged 10-60 years to evaluate the changes in various facial skin characteristics with ageing. RESULTS: The precision and sensitivity of the developed system were excellent (>0.9%), and the diagnosis scores using the detected area and intensity of each item were correlated significantly higher with the visual evaluation results of the clinical experts (>0.8, p < 0.001). We also analysed facial images of Korean women aged 10-60 years to quantify changes in the scores of wrinkles, pigmentation, and skin pores with age. We identified the age group with the most significant changes as 20s to 30s. Analysis of the detailed skin characteristics of each item showed that wrinkles and pigmentation changed significantly in the 20s-30s, and skin pores increased significantly in the 10s-20s. There was no significant correlation with age or change according to the age group for skin red spots. CONCLUSION: Developed AI-based facial skin diagnosis system can automatically diagnose skin conditions based on clinical expert judgement using only photographic images and analyse various items in detail, quantitatively, and visually. This AI system can provide new and useful approaches in research areas that require a lot of resources and different characterizations, such as the study of facial skin ageing.

OBJECTIF: Développer et valider un système de diagnostic basé sur l'intelligence artificielle (IA) pour analyser les images de la peau du visage à l'aide de jugements d'experts et explorer sa faisabilité pour la recherche sur le vieillissement de la peau, en particulier en évaluant les changements de la peau du visage chez les femmes Coréennes de différents âges. MÉTHODES: Notre système de diagnostic de la peau du visage basé sur l'intelligence artificielle (Dr. AMORE®) utilise des images du visage de femmes Coréennes pour analyser les rides, la pigmentation, les pores de la peau et d'autres taches rouges de la peau. Le système est entraîné à l'aide d'évaluations d'experts cliniques et de l'apprentissage profond. Nous avons évalué la précision et la sensibilité du système en analysant la corrélation entre les diagnostics du système d'IA et ceux des experts. Nous avons utilisé 120 images de femmes coréennes âgées de 10 à 60 ans pour évaluer les changements de diverses caractéristiques de la peau du visage avec le vieillissement. RÉSULTATS: la précision et la sensibilité du système développé étaient excellentes (>0.9%), et les scores de diagnostic utilisant la zone détectée et l'intensité de chaque élément étaient corrélés de manière significativement plus élevée avec les résultats de l'évaluation visuelle des experts cliniques (>.8, p < 0.001). Nous avons également analysé des images du visage de femmes coréennes âgées de 10 à 60 ans afin de quantifier les changements dans les scores des rides, de la pigmentation et des pores de la peau avec l'âge. Nous avons identifié le groupe d'âge présentant les changements les plus significatifs comme étant celui des 20­30 ans. L'analyse des caractéristiques détaillées de la peau pour chaque élément a montré que les rides et la pigmentation changeaient de manière significative chez les 20­30 ans, et que les pores de la peau augmentaient de manière significative chez les 10­20 ans. Il n'y avait pas de corrélation significative avec l'âge ou de changement en fonction du groupe d'âge pour les taches rouges de la peau. CONCLUSION: Le système de diagnostic de la peau du visage basé sur l'IA peut diagnostiquer automatiquement les affections cutanées sur la base d'un jugement d'expert clinique en utilisant uniquement des images photographiques et analyser divers éléments en détail, quantitativement et visuellement. Ce système d'IA peut fournir des approches nouvelles et utiles dans des domaines de recherché qui nécessitent beaucoup de ressources et de caractérisations différentes, comme l'étude du vieillissement de la peau du visage.

Initial empirical antibiotics of non-carbapenems for ESBL-producing E. coli and K. pneumoniae bacteremia in children: a retrospective medical record review.

BACKGROUND: The efficacy of non-carbapenems as an empirical antibiotic for extended-spectrum ß-lactamases (ESBL)-producing Escherichia coli and Klebsiella pneumoniae bacteremia in children remains controversial. We compared clinical and microbial outcomes according to the types of empirical antibiotics for treating pediatric patients with ESBL-producing E. coli and K. pneumoniae bacteremia. METHODS: Data from pediatric patients aged ≤ 18 years who were hospitalized with monomicrobial ESBL-producing E. coli or K. pneumoniae bacteremia at Asan Medical Center Children's Hospital, Seoul, Korea between January 2014 and May 2019 were analyzed retrospectively. The impact of empirical therapy was assessed as 30-day all-cause mortality and 2-day microbiological outcomes evaluated by the sterility of blood cultures collected on day 2 after empirical antibiotic administration. Logistic regression analysis was used to control for the effects of confounding variables. RESULTS: A total of 53 patients with bacteremia caused by ESBL-producing E. coli (n = 29) and K. pneumoniae (n = 24) were included in this study; the median age was 3.6 years, and all had underlying comorbidities. As empirical antibiotics, 27 patients were treated with meropenem, and non-carbapenem agents were administered to 26 patients; 84.6% (22/26) were converted to carbapenem antibiotics as the definitive antibiotic by day 2 after empirical antibiotic administration. Overall, the 30-day all-cause mortality of ESBL-producing E. coli and K. pneumoniae bacteremia was 17.0% (9/53). After adjustment, there was no statistically significant association of use of a non-carbapenem agent as an empirical antibiotic with microbiological failure on day 2 and 30-day all-cause mortality [adjusted odds ratio (OR) 1.0; 95% confidence interval (CI) 0.22-4.88, and adjusted OR 0.1; 95% CI 0.01-1.56]. CONCLUSIONS: The empirical use of non-carbapenems might not be a risk factor for mortality and early microbiological outcomes in pediatric patients with ESBL-producing E. coli and K. pneumoniae BSI if early transition to appropriate antimicrobial therapy was possible.

Effects of one year of daily face mask wearing on the skin during the coronavirus disease 2019 pandemic.

BACKGROUND: As coronavirus disease 2019 (COVID-19) continues, the long-term daily use of masks is increasing. A full year includes the four seasons of spring, summer, autumn, and winter. Skin may have been affected by the seasons and further affected by the use of masks. In a previous study, we confirmed the short-term and 6-month effects of wearing face masks. In this study, we investigated how certain characteristics of the skin change when wearing a mask for 1 year. Furthermore, we compared skin covered by the mask (mask-skin zone) to skin that was not covered. MATERIALS AND METHODS: The participants were 18 healthy adults (8 men; 10 women) who were asked to wear masks in their daily lives from June 2020 to June 2021. During this period, participants' skin characteristics, such as trans-epidermal water loss, skin hydration, skin elasticity, skin keratin amount, skin pore area, skin temperature, skin redness, and skin color, were measured five times. RESULTS: Trans-epidermal water loss, skin keratin amount, skin pore area, skin color, and skin elasticity changed significantly during the year. Furthermore, trans-epidermal water loss, skin hydration, skin keratin amount, skin pore area, and skin color were significantly different between the mask-wearing and non-mask-wearing areas of the face. CONCLUSION: The skin characteristics of the mask-skin zone can be affected by long-term wearing of a face mask under lifestyle and environmental conditions. During the COVID-19 pandemic, skin care for the mask-skin zone is also necessary for people who do not wear masks on a daily basis.

Long-term effects of face masks on skin characteristics during the COVID-19 pandemic.

BACKGROUND: Nowadays, face masks are a crucial part of our daily life. Previous studies on their impact on the skin usually focused on the adverse effects of face masks. Few studies have assessed their influence on skin characteristics. In a previous study, we identified the short-term effects of wearing face masks. Herein, we describe the long-term skin effects of face masks, for a period of 6 months. MATERIALS AND METHODS: Healthy volunteers (19 men and women), who wore face masks, participated in the study from June 2020 to December 2020. In all participants, skin characteristics such as trans-epidermal water loss (TEWL), skin hydration, skin elasticity, skin pore area, skin keratin amount, skin temperature, skin redness, skin temperature, skin redness, and skin color were measured three times. RESULTS: TEWL, skin hydration, skin elasticity, skin pore area, skin keratin amount, and skin color changed significantly after 6 months. TEWL, skin hydration, skin pore area, skin keratin amount, and skin color were significantly different between the mask-wearing and non-mask-wearing areas. CONCLUSION: Long-term daily use of face masks can alter skin characteristics. Special care should be focused on the mask-wearing regions.

Effect of face mask on skin characteristics changes during the COVID-19 pandemic.

BACKGROUND: Previous studies have demonstrated the possibility of adverse effects of prolonged wearing of personal protective equipment in healthcare workers. However, there are a few studies about the effects on skin characteristics after wearing a mask for non-healthcare workers. In this study, we evaluated the dermatologic effects of wearing a mask on the skin over time. MATERIALS AND METHOD: Twenty-one healthy men and women participated in the study. All participants wore masks for 6 hours consecutively. Three measurements were taken (a) before wearing the mask, (b) after wearing the mask for 1 hour, and (c) after wearing the mask for 6 hours. Skin temperature, skin redness, sebum secretion, skin hydration, trans-epidermal water loss, and skin elasticity were measured. RESULTS: The skin temperature, redness, hydration, and sebum secretion were changed significantly after 1 and 6 hours of wearing a mask. Skin temperature, redness, and hydration showed significant differences between the mask-wearing area and the non-mask-wearing area. CONCLUSION: Mask-wearing conditions and time can change several skin characteristics. In particular, it is revealed that the perioral area could be most affected.

Application of Spectro-DPRA, KeratinoSens™ and h-CLAT to estimation of the skin sensitization potential of cosmetics ingredients.

Ethical issues in animal toxicity testing have led to the search for alternative methods to determine the skin sensitization potential of cosmetic products. The emergence of ethical testing issues has led to the development of many alternative methods that can reliably estimate skin sensitization potentials. However, a single alternative method may not be able to achieve high predictivity due to the complexity of the skin sensitization mechanism. Therefore, several prediction assays, including both in chemico and in vitro test methods, were investigated and integrated based on the skin sensitization adverse outcome pathway. In this study, we evaluated three different integrated approaches to predict a human skin sensitization hazard using data from in vitro assays (KeratinoSens™ and human cell line activation test [h-CLAT]), and a newly developed in chemico assay (spectrophotometric direct peptide reactivity assay [Spectro-DPRA]). When the results of the in chemico and in vitro assays were combined, the predictivity of human data increased compared with that of a single assay. The highest predictivity was obtained for the approach in which sensitization potential was determined by Spectro-DPRA followed by final determination using the result of KeratinoSens™ and h-CLAT assays (96.3% sensitivity, 87.1% specificity, 86.7% positive predictive value, 96.4% negative predictive value and 91.4% accuracy compared with human data). While further optimization is needed, we believe this integrated approach may provide useful predictive data when determining the human skin sensitization potential of chemicals.

Exosomes derived from mesenchymal stem cells suppress angiogenesis by down-regulating VEGF expression in breast cancer cells.

Exosomes are small membrane vesicles released by a variety of cell types. Exosomes contain genetic materials, such as mRNAs and microRNAs (miRNAs), implying that they may play a pivotal role in cell-to-cell communication. Mesenchymal stem cells (MSCs), which potentially differentiate into multiple cell types, can migrate to the tumor sites and have been reported to exert complex effects on tumor progression. To elucidate the role of MSCs within the tumor microenvironment, previous studies have suggested various mechanisms such as immune modulation and secreted factors of MSCs. However, the paracrine effects of MSC-derived exosomes on the tumor microenvironment remain to be explored. The hypothesis of this study was that MSC-derived exosomes might reprogram tumor behavior by transferring their molecular contents. To test this hypothesis, exosomes from MSCs were isolated and characterized. MSC-derived exosomes exhibited different protein and RNA profiles compared with their donor cells and these vesicles could be internalized by breast cancer cells. The results demonstrated that MSC-derived exosomes significantly down-regulated the expression of vascular endothelial growth factor (VEGF) in tumor cells, which lead to inhibition of angiogenesis in vitro and in vivo. Additionally, miR-16, a miRNA known to target VEGF, was enriched in MSC-derived exosomes and it was partially responsible for the anti-angiogenic effect of MSC-derived exosomes. The collective results suggest that MSC-derived exosomes may serve as a significant mediator of cell-to-cell communication within the tumor microenvironment and suppress angiogenesis by transferring anti-angiogenic molecules.