In-stent restenosis is still a clinic trouble for percutaneous coronary intervention in drug-stent era. The molecular basis of restenosis is intensively associated with inflammation. TLR3 and TLR4 as innate immune factors have been proven to play a key role in atherosclerosis disease. The aim of this study is to study the TLR3 and TLR4 expressions and their downstream signaling proteins in the inflammatory process of restenosis after drug-stent therapy. mRNA and protein expression of TLR3 and TLR4 were detected in peripheral blood monocytes of primary group (n = 38), N-ISR group (n = 36) and ISR group (n = 33). Some inflammatory factors (including TLR3 and TLR4) were evaluated in serum of three groups. mRNA and protein expression of TLR3 and TLR4 and their downstream signaling proteins have shown a higher level in restenosis patients than non-restenosis patients and even primary patients who accepted first stent therapy. In serum, different from some nonspecific and downstream inflammatory factors, TLR3 and TLR4 also show a significantly higher level in ISR group compared with N-ISR group and primary group. This study provides a potential clinical biomarker for in-stent restenosis in drug-stent patients and some interesting data about the role of TLRs and their downstream signaling factors in the inflammatory process of in-stent restenosis. Compared with first stent therapy and non-restenosis patients, it is hopeful that TLR3 and TLR4 are potential noninvasive biomarkers in prognosis restenosis.
This paper proposes a novel optimization layout method for supporting clamps in a pipeline system. In this method, the global sensitivity analysis based on the Sobol method is presented to determine the influence of clamp position on the first-order frequency difference, the maximum vibration response displacement, and the maximum vibration stress. The modeling density of the finite element calculation is determined, and then a surrogate model of the relationship between the optimized input and the output is established through the neural network. The optimized position and orientation of the clamp are obtained by the genetic algorithm. Finally, a typical pipeline with clamps are conducted as an example to verify the effectiveness of the proposed optimization method. The simulations were compared with the experiment, and the result shows that the proposed optimization method can reduce the vibration of the pipeline system significantly, thus providing a new method for the arrangement of clamps in pipeline system.
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