S100A7 Co-localization and Up-regulation of Filaggrin in Human Sinonasal Epithelial Cells

Objective:Filaggrin(FLG)is a protein expressed in the epidermis and involved in the maintenance of the epidermal barrier.However,the expression and localization of FLG in the upper airway remain controversial.The present study aimed to determine the significance of FLG and the effect of S100A7 on FLG expression in the upper respiratory mucosa.Methods:Human nasal epithelial cells(HNECs)were cultured and examined for FLG expression and S100A7 effects by real-time polymerase chain reaction and Western blotting.The localization and distribution of FLG were assessed using sinonasal mucosa.Results:A significant expression of FLG was detected at the mRNA and protein levels in HNECs.A moderate FLG immunoreactivity was observed in the epithelial cells,but no staining was seen in epithelial goblet cells.S100A7 increased the FLG mRNA level in HNECs in a dose-dependent manner and also up-regulated the FLG protein in a dose-dependent manner.Conclusion:This study significantly contributes to a better understanding of the role of FLG in the pathogenesis of airway inflammation from the viewpoint of the epithelial barrier function.FLG-related events in response to S100A7 protein may represent novel therapeutic targets for the treatment of upper airway inflammation.

Evaluation Method of the Gait Motion Based on Self-organizing Map Using the Gravity Center Fluctuation on the Sole

This paper describes the evaluation method of the gait motion in walk rehabilitation. We assume that the evaluation consists of the classification of the measured data and the prediction of the feature of the gait motion. The method may enable a doctor and a physical therapist to recognize the condition of the patients more easily, and increase the motivation of patient further for rehabilitation. However, it is difficult to divide the gait motion into discrete categories, since the gait motion continuously changes and does not have the clear boundaries. Therefore, the self-organizing map （SOM） that is able to arrange the continuous data on the almost continuous map is employed in order to classify them. And, the feature of the gait motion is predicted by the classification. In this study, we adopt the gravity-center fluctuation （GCF） on the sole as the measured data. First, it is shown that the pattern of the CCF that is obtained by our developed measurement system includes the feature of the gait motion. Secondly, the relation between the pattern of the GCF and the feature of the gait motion that the doctor and the physical therapist evaluate by visual inspection is considered using the SOM. Next, we describe the prediction of following features measured by numerical values： the length of stride, the velocity of walk and the difference of steps that are important for the doctor and the physical therapist to make a diagnosis of the condition of the gait motion in walk rehabilitation. Finally, it is investigated that the position of a new test data that is arranged on the map accords with the prediction. As a consequence, we confirm that the method using the SOM is often useful to classify and predict the condition of the patient.