Objective To investigate the protective effect and mechanism of recombinant hirudin on avulsed flap and to explore the application of recombinant hirudin in clinical treating avulsed flap.Methods 108 Sprague-Dawley rats were randomly divided into three groups:local injecting recombinant hirudin (group A),local injecting low molecular heparin (group B),and local injecting physiological saline (group C).The far ends were sutured after forming dorsal avulsed flap with local freeing.The levels of P-selectin and VEGF were detected,and the inflammatory cell aggregation and formation of microthrombus were observed in pathological section.On 14th postsurgery day the survival rate of flap was calculated.Results The content of P-selectin in group A was lower than that of groups B and C,with a statistical difference (P＜0.05).The content of VEFG in group A was higher than that of groups B and C,with a statistical difference (P＜0.05).On 14th postsurgery day,group A was higher than that in groups B (P＜0.05)and C (P＜0.01) in the survival rate of flap.Conclusions Locally injected recombinant hirudin can actively suppress the production of P-selectin,reduce accumulation of inflammatory cells,prevent information of microthrombus,improve ischemia and anoxia of avulsed flaps,decrease injuries of endotheliocyte,enhance the expression of VEGF,and stimulate hyperplasia of neogenesis capillaries that elevate survival rate of avulsed flaps.

The elastic parameters of soft tissues are important for medical diagnosis and virtual sur-gery simulation.In this study;we propose a novel nonlinear parameter estimation method for soft tissues.Firstly;an in-house data acquisition platform was used to obtain external forces and their corresponding deformation values.To provide highly precise data for estimating nonlinear param-eters;the measured forces were corrected using the constructed weighted combination forecasting model based on a support vector machine (WCFM_SVM). Secondly;a tetrahedral finite element parameter estimation model was established to describe the physical characteristics of soft tissues;using the substitution parameters of Young's modulus and Poisson's ratio to avoid solving compli-cated nonlinear problems.To improve the robustness of our model and avoid poor local minima;the initial parameters solved by a linear finite element model were introduced into the parameter estimation model. Finally;a self-adapting Levenberg–Marquardt (LM) algorithm was presented;which is capable of adaptively adjusting iterative parameters to solve the established parameter estimation model. The maximum absolute error of our WCFM_SVM model was less than 0.03 Newton;resulting in more accurate forces in comparison with other correction models tested. The maximum absolute error between the calculated and measured nodal displacements was less than 1.5 mm;demonstrating that our nonlinear parameters are precise.