Objective. Increased signaling by transforming growth factor ␤ (TGF␤) has been implicated in systemic sclerosis (SSc; scleroderma), a complex disorder of connective tissues characterized by excessive accumulation of collagen and other extracellular matrix components in systemic organs. To directly assess the effect of sustained TGF␤ signaling in SSc, we established a novel mouse model in which the TGF␤ signaling pathway is activated in fibroblasts postnatally.Methods. The mice we used (termed TBR1 CA ; Cre-ER mice) harbor both the DNA for an inducible constitutively active TGF␤ receptor I (TGF␤RI) mutation, which has been targeted to the ROSA locus, and a Cre-ER transgene that is driven by a fibroblast-specific promoter. Administration of 4-hydroxytamoxifen 2 weeks after birth activates the expression of constitutively active TGF␤RI.Results. These mice recapitulated clinical, histologic, and biochemical features of human SSc, showing pronounced and generalized fibrosis of the dermis, thinner epidermis, loss of hair follicles, and fibrotic thickening of small blood vessel walls in the lung and kidney. Primary skin fibroblasts from these mice showed elevated expression of downstream TGF␤ targets, reproducing the hallmark biochemical phenotype of explanted SSc dermal fibroblasts. The mouse fibroblasts also showed elevated basal expression of the TGF␤-regulated promoters plasminogen activator inhibitor 1 and 3TP, increased Smad2/3 phosphorylation, and enhanced myofibroblast differentiation.Conclusion. Constitutive activation of TGF␤ signaling in fibroblastic cells of mice after birth caused a marked fibrotic phenotype characteristic of SSc. These mice should be excellent models with which to test therapies aimed at correcting excessive TGF␤ signaling in human scleroderma.

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In the automated fiber placement process, the continuous placement paths need to be discretized into a finite number of path points because the laying head cannot continuously trace the predetermined curved path. However, the discretization of the placement path, which is a spatial curve, will inevitably introduce error. In this paper, an improved path discretization algorithm is proposed for the fiber placement of complex double-curved structures. Firstly, the discrete error was decomposed into normal direction and binormal direction, and they are correlated with the laying process and their influences on the laying quality are discussed, respectively. Secondly, the relationship between the binormal error and the overlap of the tow is analyzed with differential geometry, and the influence of the normal error on laying force is discussed by the pressure experiment and the finite element method. Finally, the improved path discretization algorithm has been verified on double-curved surface and compared with the traditional path discrete algorithms. The results showed that the number of discrete path points decreases by 45.8% on average compared with the chordal deviation discretization algorithm and by 63.1% compared with the equal-arc discretization algorithm.