Tumor necrosis factor (TNF)-like weak inducer of apoptosis (TWEAK) is a multifunctional cytokine that acts through its receptor fibroblast growth factor-inducible 14 (Fn14). Recent studies demonstrated that the TWEAK/Fn14 signals participate in the development of psoriasis. The purpose of this study was to further explore the effect of Fn14 inhibition on experimental psoriasis. Psoriasis-like skin disease was induced in the wild-type and Fn14-knockout BALB/c mice. We found that Fn14 deficiency ameliorates psoriasis-like lesion in this model, accompanied by less inflammatory cell infiltration and proinflammatory cytokine production in lesional skin. The cutaneous expression of TNF receptor type 2 also decreased in the Fn14-deficient mice. Moreover, the topical application of TWEAK exacerbated psoriatic lesion in the wild-type but not in the Fn14-deficient mice. Furthermore, TWEAK promoted the expression of interleukin 8, keratin 17, and epidermal growth factor receptor (EGFR) but inhibited the expression of involucrin in psoriatic keratinocytes in vitro. Interestingly, such effect of TWEAK was abrogated by an EGFR inhibitor (erlotinib). TWEAK also enhances the proliferation and interleukin-6 production of dermal microvascular endothelial cells under psoriatic condition. In conclusion, TWEAK/Fn14 signals contribute to the development of psoriasis, and involves the modulation of resident cells and the transduction of the EGFR pathway. Fn14 inhibition might be a novel therapeutic strategy for patients with psoriasis.

Cutaneous squamous cell carcinoma (cSCC) is the second most common form of non-melanoma skin cancer, causing as many deaths yearly as melanoma in the United States. However, there are limited reliable biomarkers to predict its biological behavior and clinical outcome. The cell division cycle 20 (CDC20) has recently been reported to play a role in cancer progression. But its clinical significance in cSCC has not been studied. The aim of this study was to investigate whether CDC20 was involved in the tumorigenesis of cSCC. We firstly analyzed relative CDC20 mRNA level in two GEO microarray data using GEO2R. In GSE32628, CDC20 mRNA level is significantly higher in precancerous actinic keratoses (AK) (n¼13, p¼0.016) and cSCC (n¼13, p¼0.0007) than the paired normal skin (n¼13). In GSE45216, CDC20 expression was significantly higher in well-differentiated cSCC (n¼15, p¼0.0205), and moderately/poorly differentiated cSCC (n¼15, p¼0.0003) than in AK (n¼10). We then tested the CDC20 expression in 21 paired cSCC and corresponding normal tissues using immunohistochemical staining, and subsequent semiquantitative analysis of the IHC results confirmed increased CDC20 expression in cSCC tissues (n¼21, p < 0.0001). Furthermore, we detected CDC20 expression in 144 samples with different pathological stage. The result showed higher CDC20 in cSCC in situ (n¼27, p < 0.0001), well-differentiated cSCC (n¼29, p < 0.0001), and moderately/poorly differentiated cSCC (n¼25, p < 0.0001) than in normal skin (n¼32) and correlated well with disease progression. CDC20 expression is very low in normal intact skin and is significantly increased in cSCC tumor cells, suggesting it can work as a biomarker for cSCC. Furthermore, elevated expression of CDC20 in both AK and cSCC in situ indicate the induction of CDC20 expression is an early event in cSCC development. However, we didn't have any follow-up data from our patients, so we can't draw any conclusion about the prognosis value of CDC20.

Gyeonggi-do, Korea (the Republic of) Introduction : Recently, many researches have been actively conducted to evaluate age by artificial intelligence using various parameters. Prediction of skin age is important because biological age and skin age differ due to various environmental factors, beauty habits, and genetic factors. This study predicted skin age by using multiple regression analysis by five skin parameters that affect aging, and analyzed the predicted age of the group using the First Care Activation Serum and the group without it. Method : 290 women between the ages of 22 and 80 have been recruited in the study. Ninety-five people used First Care Activation Serum for at least three years (Test group), while 195 others did not use (Control group). Subjects were measured by ten parameters (The skin hydration, skin color, gloss, wrinkles, Trans-epidermal water loss, Transparency, Sebum, pH, Melanin and Erythema). Result : Five parameters (The skin hydration, wrinkles, skin color, transparency, and gloss) were changed according to age among ten parameters. Thus, these five parameters were used to perform multiple regression analysis to derive a regression formula for predicting skin age. The regression formula for predicting age using the five skin parameters was suitable for predicting age by having adjusted R-square of 0.685 and showing significant results. Test group was used First Care Activation Serum for an average of 12.05 years, and the predicted skin age was 17.91 years younger than those that did not use product. Discussion : In this study, we developed a formula for predicting skin age using five simple skin measurements. Furthermore, this regression formula is suitable for predicting age because it has 68.5% of the expression's explanatory power. The study also confirmed that skin age may vary depending on beauty habits.