Urokinase-type plasminogen activator activity may be the most sensitive factor affecting HCC invasion in the plasminogen activation system and a strong predictor for the recurrence of HCC. We suggest that cases with uPA activity of more than 0.70 ng/mL should be carefully followed up for possible HCC recurrence.
Cardiac hypertrophy in response to multiple stimuli has important physiological and pathological significances. GATA4 serves as a nuclear integrator of several signalling pathways during cardiac hypertrophy. Sp1 and Sp3 are also reported to be involved in this process. However, the mechanism by which GATA4 acts as a mediator, integrating these ubiquitously expressed transcriptional factors, is poorly understood. We found that the expression of GATA4 and Sp1 was up-regulated in the myocardium of a pressure overload hypertrophy rat model, as well in phenylephrine-induced (PE-induced) hypertrophic growth of neonatal cardiomyocytes. GST pull-down assays demonstrated that GATA4 could interact with Sp1 in vitro. Therefore, we proposed that GATA4 cooperates with Sp1 in regulating ANF expression, as its reactivation is closely linked with hypertrophy. Further studies demonstrated that GATA4 could activate the ANF promoter synergistically with Sp1 through direct interaction. In contrast, Sp3 exhibited antagonistic function, and overexpression of Sp3 repressed the transcriptional synergy between Sp1 and GATA4. We also found that Sp1 alone could activate the ANF promoter in cardiomyocytes, whereas Sp3 exerted negative effects on ANF expression. Bioinformatics analysis revealed novel Sp-binding sites on the ANF promoter. The recruitment of GATA4 and Sp1 on the ANF promoter was enhanced during phenylephrine-mediated hypertrophy, whereas the recruitment of Sp3 was reduced. The phosphorylation of GATA4 by ERK1/2 kinase could enhance the affinity between GATA4 and Sp1. Thus, our findings revealed the critical interaction of GATA4 and Sp1 in modulating ANF expression, indicating their involvement in cardiac hypertrophy.
Simulating the evolution of the Human Immunodeficiency Virus (HIV) epidemic requires a detailed description of the population network, especially for small populations in which individuals can be represented in detail and accuracy. In this paper, we introduce the concept of a Complex Agent Network(CAN) to model the HIV epidemics by combining agent-based modelling and complex networks, in which agents represent individuals that have sexual interactions. The applicability of CANs is demonstrated by constructing and executing a detailed HIV epidemic model for men who have sex with men (MSM) in Amsterdam, including a distinction between steady and casual relationships. We focus on MSM contacts because they play an important role in HIV epidemics and have been tracked in Amsterdam for a long time. Our experiments show good correspondence between the historical data of the Amsterdam cohort and the simulation results.
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