Cyclosporin A (CsA) has been used as a potent immunosuppressive agent for inhibiting the graft rejection after organ transplantation. However, CsA provokes lots of side effects including hirsutism, the phenomenon of abnormal hair growth in the body. In the present study, we investigated the hair growth stimulating effect of CsA using in vivo and in vitro test models. When topically applied on the back skin of mice, CsA induced fast telogen to anagen transition. In contrast, CsA had no effect on the growth of human hair follicle tissues cultured in vitro, indicating that it might not have the mitogenic effect on hair follicles. To identify the genes related with CsA-induced hair growth, we performed differential display RT-PCR. Among the genes obtained, the expression of synapse associated protein 102 (SAP102) was verified using competitive RT-PCR. The result showed that the expression of SAP102 was significantly induced by CsA treatment in the back skin of C57BL/6 mice. However, the increase of SAP102 mRNA was also seen in spontaneous anagen mice, suggesting that induction of SAP102 is one event of the anagen hair growth response regardless of how the growth state was induced. SAP102 was not expressed in cultured human hair outer root sheath and dermal papilla cells. Immunohistochemistry analysis showed that CsA induced the expression of SAP102 in perifollicular region of mouse anagen hair. Together, these results suggest that SAP102 is one of hair-cycle-dependent genes, whose expression is related with the anagen progression.

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Objectives To evaluate the pattern identification tool for knee osteoarthritis and to investigate the relationship between pattern identification tool and knee ROM (range of motion), VAS (visual analog scale) and WOMAC (Western Ontario & McMaster Universities osteoarthritis index). Methods We studied 50 patients who are diagnosed as degenerative osteoarthritis . With one patient dropping out, total of 49 patient went through pattern identification tool. Re-test of the pattern identification tool was implemented after about a week. The reliability was analyzed by calculating ICC (intraclass correlation coefficient). Also, reliability of each pattern identification score was calculated along with influence factor and correlation between knee ROM, VAS and WOMAC. Results Reliability of the pattern identification tool was evaluated as 'poor agreement beyond chance' with ICC value of 0.396. Reliablility of each pattern identification score was calculated and four out of five were measured 'good' with one 'moderate' reliability. Two of inter-item consistency were 'good', two were 'acceptable' and one was 'questionable'. Correlation between each pattern identification and knee ROM showed 'clear negative linear relationship' with two patterns. VAS showed 'clear positivie linear relationship' with all five patterns. WOMAC showed 'positivie linear relationship' with all five patterns. Conclusions According to the results, pattern identification tool for knee osteoarthritis seems to have meaningful relationship with other agnedas. Also, further research is needed to develop the tool. (J Korean Med Rehabil 2019;29(3):113-128)