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SUMMARYThis work presents a novel procedure for identifying the dynamic characteristics of a building and diagnosing whether the building has been damaged by earthquakes, using a back-propagation neural network approach. The dynamic characteristics are directly evaluated from the weighting matrices of the neural network trained by observed acceleration responses and input base excitations. Whether the building is damaged under a large earthquake is assessed by comparing the modal parameters and responses for this large earthquake with those for a small earthquake that has not caused this building any damage. The feasibility of the approach is demonstrated through processing the dynamic responses of a ÿve-storey steel frame, subjected to di erent strengths of the Kobe earthquake, in shaking table tests.

Lysophosphatidic acid (LPA), an extracellular lipid mediator, exerts multiple bioactivities through activating G protein-coupled receptors. LPA receptor 3 (LPA 3 ) is a member of the endothelial differentiation gene family, which regulates differentiation and development of the circulation system. However, the relationship among the LPA receptors (LPARs) and erythropoiesis is still not clear. In this study, we found that erythroblasts expressed both LPA 1 and LPA 3 , and erythropoietic defects were observed in zLPA 3 antisense morpholino oligonucleotide-injected zebrafish embryos. In human model, our results showed that LPA enhanced the erythropoiesis in the cord blood-derived human hematopoietic stem cells (hHSCs) with erythropoietin (EPO) addition in the plasma-free culture. When hHSCs were treated with Ki16425, an antagonist of LPA 1 and LPA 3 , erythropoietic process of hHSCs was also blocked, as detected by mRNA and protein expressions of CD71 and GlyA. In the knockdown study, we further demonstrated that specific knockdown of LPA 3 , not LPA 1 , blocked the erythropoiesis. The translocation of b-catenin into the nucleus, a downstream response of LPAR activation, was blocked by Ki16425 treatment. In addition, upregulation of erythropoiesis by LPA was also blocked by quercetin, an inhibitor of the b-catenin/ T-cell factor pathway. Furthermore, the enhancement of LPA on erythropoiesis was diminished by blocking c-Junactivated kinase/signal transducer and activator of transcription and phosphatidylinositol 3-kinase/AKT activation, the downstream signaling pathways of EPO receptor, suggested that LPA might play a synergistic role with EPO to regulate erythropoietic process. In conclusion, we first reported that LPA participates in EPO-dependent erythropoiesis through activating LPA 3 .

Many single nucleotide polymorphisms (SNPs) have been found to be associated with breast cancer, but their SNP interactions are seldom addressed. In this study, we focused on the joint effect for SNP combinations of seven CXCL12-related genes involved in major cancer-related pathways. SNP genotyping was determined by PCR-restriction fragment length polymorphism (RFLP) in this study (case = 220, control = 334). Different numbers of combinational SNPs with genotypes called the SNP barcodes from different chromosomes were used to evaluate their joint effect on breast cancer risk. Except for vascular endothelial growth factor (VEGF) rs3025039-CT, none of these SNPs were found to individually contribute to breast cancer risk. However, for two combined SNPs, the proportion of subjects with breast cancer was significantly low in the SNP barcode with CC-GG genotypes in rs2228014-1801157 (CXCR4-CXCL12) compared to those with non-CC-GG genotypes. Similarly, the SNP barcode of rs12812942-rs2228014-rs3025039 (CD4-CXCR4-VEGF) and rs12812942-rs3136685-rs2228014-rs1801157 (CD4- CCR7-CXCR4-CXCL12) with specific genotype patterns (AT-CC-CC and AT-AG-CC-GG) among three and four combinational SNPs were significantly low in breast cancer occurrence. More SNP combinations larger than five SNPs were also addressed, and these showed similar effects. After controlling for age, and comparing their corresponding non-SNP barcodes, the estimated odds ratios for breast cancer ranged between 0.20 and 0.71 for specific SNP barcodes with two to seven SNPs. In conclusion, we have associated the potential combined CXCL12-related SNPs with genotypes that were protective against breast cancer, and that may contribute to identification of a low-risk population for the development of breast cancer.

This study presents a wavelet neural networkbased approach to dynamically identifying and modeling a building structure. By combining wavelet decomposition and artificial neural networks (ANN), wavelet neural networks (WNN) are used for solving chaotic signal processing. The basic operations and training method of wavelet neural networks are briefly introduced, since these networks can approximate universal functions. The feasibility of structural behavior modeling and the possibility of structural health monitoring using wavelet neural networks are investigated. The practical application of a wavelet neural network to the structural dynamic modeling of a building frame in shaking tests is considered in an example. Structural acceleration responses under various levels of the strength of the Kobe earthquake were used to train and then test the WNNs. The results reveal that the WNNs not only identify the structural dynamic model, but also can be applied to monitor the health condition of a building structure under strong external excitation.