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Circadian function and p53 network are interconnected on the molecular level, but the dynamics induced by the interaction between the circadian factor Per2 and the tumor suppressor p53 remains poorly understood. Here, we constructed an integrative model composed of a circadian clock module and a p53-Mdm2 feedback module to study the dynamics of p53-Per2 network in unstressed cells. As expected, the model can accurately predict the circadian rhythm, which is consistent with diverse experimental observations. In addition, using a combination of theoretical analysis and numerical simulation, the results demonstrated that p53 expression enhances the phase advance of circadian rhythm and reduces the robustness of circadian rhythm. Furthermore, the time delay required for the transcription and translation of Per2 protein induces oscillations by undergoing a supercritical Hopf bifurcation, and improves the robustness of circadian rhythm. In summary, this work shows that the p53-Per2 interaction and the time delay are two essential factors for circadian functions.

In this paper, a novel dynamical model of p53 network is formulated to study the contribution of both negative feedback loops and time delays to the generation of p53 oscillation when cells respond to ionizing radiation. The results showed that the ATM-p53-Wip1 negative feedback loop plays a major role in inducing p53 oscillation, while the p53-Mdm2 loop cannot induce oscillation under the premise of ATM-p53-Wip11oop presence. In addition, sufficient Wip1 inhibition is also necessary for p53 oscillation, while excessive Mdm2 inhibition stops p53 oscillation. Furthermore, by analyzing the effect of time delay on p53 oscillation network, it is observed that time delay induces a supercritical Hopf bifurcation to drive p53 oscillation, and both the amplitude and period will increase with time delay. As expected, the results are in consistence with some biological experiments and observations.

To explore the mechanism of Etanercept in the treatment of rheumatoid arthritis (RA), we investigated whether the Th1/Th2 and Th17/regulatory T cells (Treg) imbalance could be reversed by Etanercept and whether the reversal was related to the improvement of clinical indications.We conducted a 12-week study in 40 active RA patients, of whom 20 were given a stable weekly dose of methotrexate (MTX) alone and the other ten received a combined therapy of Etanercept and MTX. Ten healthy donors were chosen as controls. Frequencies of Th1, Th2, Th17, and Treg were quantified using flow cytometry, and related serum cytokines were detected by enzyme-linked immunosorbent assay. The composite 28-joint count Disease Activity Score, erythrocyte sedimentation rate, and C-reactive protein were assessed at each visit.Percentages of IFN-γ(+)Th1 and IL-17(+)Th17 among CD4(+) T cells were significantly higher, while CD4(+)CD25(high)Foxp3(+) Treg were significantly lower in RA patients compared with those in healthy control. After 12 weeks of therapy of MTX single or combination of MTX and Etanercept, the circulating Th17/Treg ratio significantly decreased, while no significant difference was observed in Th1/Th2 ratio. In combined therapy group, the Th17/Treg ratio was positively correlated with the remittance of disease activity. IL-1β, TNF-α, IL-6, IL-17, and IL-23 were significantly decreased, while TGF-β was significantly elevated. The Th17/Treg ratio was positively related to TGF-β, but negatively correlated with IL-6.Etanercept in combination with MTX ameliorates RA activity by normalizing the distribution of Th17 and Treg, and their related cytokines, which may partly explain the mechanism of combined therapy of Etanercept plus MTX in RA treatment.

Detecting lines in a digital image is a crucial step in many applications, such as visual navigation, feature recognition. In this paper, an algorithm which is based on part Hough transform is proposed for extracting straight lines from building image. Firstly, edges are detected based on Canny detector. Secondly, An algorithm that follows image boundary categorizes edges. Thirdly, Hough transformation extracts straight lines to each classification of image. Experiment results shows that the proposed algorithm is better than Hough transform. It can detect lines correctly in building images with high accuracy, low false detection and low missing detection.