Cardiac fibrosis is associated with activation of cardiac fibroblasts (CFs), a pathological, phenotypic transition that is widely believed to be irreversible in the late stages of disease development. Sensing of a stiffened mechanical environment through regulation of integrin-based adhesion plaques and activation of the Piezo1 mechanosensitive ion channel is known to factor into this transition. Here, using integrated in vitro and in silico models, we discovered a mutually reinforcing, mechanical positive feedback loop between integrin β1 and Piezo1 activation that forms a bistable switch. The bistable switch is initiated by perturbations in matrix elastic modulus that amplify to trigger downstream signaling involving Ca2+ and YAP that, recursively, leads fibroblasts to further stiffen their environment. By simultaneously interfering with the newly identified mechanical positive feedback loop and modulating matrix elastic modulus, we reversed markers of phenotypical transition of CF, suggesting new therapeutic targets for fibrotic disease.

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Abstract. Micro-blogging, which has greatly influenced people's life, is experiencing fantastic success in the worldwide. However, during its rapid development, it has encountered the problem of content pollution. Various pollution in the micro-blogging platforms has hurt the credibility of micro-blogging and caused significantly negative effect. In this paper, we mainly focus on detecting fake followers which may lead to a problematic situation on social media networks. By extracting major features of fake followers in Sina Weibo, we propose a binary classifier to distinguish fake followers from the legitimate users. The experiments show that all the proposed features are important and our method greatly outperforms to detect fake followers. We also present an elaborate analysis on the phenomenon of fake followers, infer the supported algorithms and principles behind them, and finally provide several suggestions for micro-blogging systems and ordinary users to deal with the fake followers.