Particle Simulation on Epidermal Skin Formation - Mechanism of Basal Layer Formation -

Skin is the largest organ of the human body. The bottom of the epidermis is called the basal layer and is very uneven. However, the mechanism of uneven formation of the basal layer has not yet been elucidated. Computational simulation can be useful in further understanding the mechanisms of skin formation. We propose a particle model that can handle complex biological phenomena, including cell interactions and is a suitable method for the simulation of skin formation. In this study, we created a model similar to the actual skin using three-dimensional analysis and elucidated the formation mechanism of the basal layer. Particularly, each basal cell of this model is subjected to three patterns of cell division, which can simulate skin formation with an increase and decrease of basal cells and the consequent generation of upper cell layers. Therefore, we analyzed the association between these cell division patterns and the uneven formation of the cell layer.The 6th TSME International Conference on Mechanical Engineering, 16-18 December 2015, the Regent Cha-am beach Resort, Hua-Hin, Thailand

Particle Simulation of Skin Basal Layer Formation

There has been increasing concern regarding the cosmetic aspects of skin in recent years. Computational simulation can be useful in understanding the mechanism underlying skin formation. The bottom of the epidermis is called the basal layer and is very undulation. In this study, we focus on the basal layer formation. We created a particle model, which forms an undulation basal layer and regenerates the basal layer formation by numerical simulation. At first, two-dimensional basal layer formation without epidermal turnover was simulated. The results showed film shape changes and the stability, as a layer in the process of long-time with an increase and decrease of basal cells. Next, the model was applied to three-dimensional basal layer formation with epidermal turnover. As the structure of the basal layer was deformed, the upper structure of the epidermis comprising the cells divided from the basal layer also became irregular. The simulation results accurately represented and reproduced the three-dimensional basal layer formation and epidermis turnover process.2nd Conference on Advances in Prevention and Treatment of Cancer (CAPTC 2016), March 18-20, 2016, Los Angeles, US

Particle Simulation on Human Epidermal Aging- Effect of Basal Layer and Cell Division Rate -

Wrinkles and freckles appear on people due to aging and, as such, affect their appearance. The epidermis is the outermost layer of a human’s skin, and epidermal conditions can be diagnosed from it in order to provide appropriate care. Recently, those interested in anti-aging treatments have paid greater attention to the aging of the epidermal layer. The epidermis consists of four different layers. In particular, the basal layer, which is at the bottom of epidermis, has an undulating structure. This undulation is associated with aging: undulations in the basal layer become flat when the epidermis ages. However, the mechanisms between the aging process and the basal layer have not yet been made clear because it is difficult to directly observe the skin’s basal layer. In order to investigate long-term skin formation, we created a model that simulates actual skin. Our model can analyze the epidermis while including undulations in the structure of the basal layer. In order to test this, we set conditions for the number of basal cells and the basal cell division rate so as to simulate aging and young epidermises. In the case of aging epidermises, the number of basal cells was fewer and the basal cell division rate was lower than for young skin. As a result of this analysis, the characteristics of aging skin were found.The 7th International Conference on Mechanical Engineering (TSME-ICoME 2016), 13-16 December 2016, Chiang Mai, Thailand

Generating reliable tourist accommodation statistics: Bootstrapping regression model for overdispersed long-tailed data

Purpose: Few studies have applied count data analysis to tourist accommodation data. This study was undertaken to investigate the characteristics and to seek for the most fitting models for population total estimation in relation to tourist accommodation data. Methods: Based on the data of 10,503 hotels, obtained from by a nationwide Japanese survey, the bootstrap resampling method was applied for re-randomisation of the data. Training and test sets were derived by randomly splitting each of the bootstrap samples. Six count models were fitted to the training set and validated with the test set. Bootstrap distributions for parameters of significance were used for model evaluation. Results: The outcome variable (number of guests), was found to be heterogenous, over dispersed and long-tailed, with excessive zero counts. The hurdle negative binomial and zero-inflated negative binomial models outperformed the other models. The accuracy (se) of the estimation of total guests with training sets that ranged from 5% to 85%, was from 3.7 to 0.4 respectively. Results appear little overestimated. Implications: Findings indicated that the integration of the bootstrap resampling method and count regression provide a statistical tool for generating reliable tourist accommodation statistics. The use of bootstrap would help to detect and correct the bias of the estimation

The Long-Term Impact of COVID-19 on Inbound Tourism from China: Using 2020/2022 Web-Based Survey Data

This study discusses the long-term impact of the COVID-19 pandemic on inbound tourism from China, aiming to investigate its prospects during the post-pandemic period. After briefly reviewing trends concerning COVID-19 impact studies at home and abroad, basic results from two cross-sections of web-based data in 2020 and 2022 are introduced to identify how the pandemic impacted not only daily activity and travel patterns but also the intentions of visiting Japan in the post-pandemic period. Finally, we summarize the challenges that we should verify to support inbound tourism restoration policies

Heparin inhibits endothelin-1 production in cultured rat mesangial cells

Heparin inhibits endothelin-1 production in cultured rat mesangial cells. The present study was designed to examine whether heparin inhibits basal or stimulated endothelin-1 production by arginine vasopressin (AVP) and platelet-derived growth factor (PDGF) in cultured rat mesangial cells. In addition, the reversibility of the heparin effect on mesangial cell endothelin-1 production was examined. AVP and PDGF stimulated endothelin-1 secretion in a concentration-dependent manner in these cells. Heparin (10 to 100 U/ml) exhibited concentration-related inhibition of AVP- and PDGF-stimulated endothelin-1 secretion. Heparin also had weak but significant inhibitory effects on basal endothelin-1 secretion in these cells. The protein kinase (PKC)-activating phorbor ester, phorbor myristate acetate (PMA), stimulated endothelin-1 secretion and heparin inhibited PMA-stimulated endothelin-1 secretion. In addition, the inhibitory effect of heparin was completely abolished in PKC-depleted mesangial cells. Mesangial cells which were exposed to a high concentration (100 U/ml) of heparin for 24 hours were capable of producing endothelin-1 after a short lag period of removal of heparin from the culture medium. These mesangial cells also showed recovery of responses to AVP and PDGF by secreting a significantly greater amount of endothelin-1 than the non-stimulated level. These results indicate that heparin potently inhibits mesangial cell endothelin-1 production, especially when stimulated by AVP or PDGF. This inhibitory effect of heparin is probably PKC dependent, and reversible