Uncertain Dynamic Characteristic Analysis for Structures with Spatially Dependent Random System Parameters.

This work presents a robust non-deterministic free vibration analysis for engineering structures with random field parameters in the frame of stochastic finite element method. For this, considering the randomness and spatial correlation of structural physical parameters, a parameter setting model based on random field theory is proposed to represent the random uncertainty of parameters, and the stochastic dynamic characteristics of different structural systems are then analyzed by incorporating the presented parameter setting model with finite element method. First, Gauss random field theory is used to describe the uncertainty of structural material parameters, the random parameters are then characterized as the standard deviation and correlation length of the random field, and the random field parameters are then discretized with the Karhunen-Loeve expansion method. Moreover, based on the discretized random parameters and finite element method, structural dynamic characteristics analysis is addressed, and the probability distribution density function of the random natural frequency is estimated based on multi-dimensional kernel density estimation method. Finally, the random field parameters of the structures are quantified by using the maximum likelihood estimation method to verify the effectiveness of the proposed method and the applicability of the constructed model. The results indicate that (1) for the perspective of maximum likelihood estimation, the parameter setting at the maximum value point is highly similar to the input parameters; (2) the random field considering more parameters reflects a more realistic structure.

Association between single nucleotide polymorphisms on chromosome 17q and the risk of prostate cancer in a Chinese population.

In European populations, 7 single nucleotide polymorphisms (SNPs) on chromosome 17q, 3 SNPs on 17q12, and 4 SNPs on 17q24.3 were recently identified to be closely related to the risk of prostate cancer by a genome-wide association study. In Japanese populations, the correlation between 2 SNPs on 17q and the risk of prostate cancer and tumor aggressiveness was also confirmed by a large-scale experiment. However, whether 17q is associated with prostate cancer and its clinical manifestations in Chinese populations is still unknown. Therefore, we conducted a case-control study in a northern Chinese population and tested 2 SNPs, rs4430796 and rs1859962, on 17q in 124 prostate cancer patients and 111 controls using polymerase chain reaction-high resolution melting curve (PCR-HRM) combined with sequencing. We analyzed the association of the 2 SNPs with the risk of prostate cancer as well as patients' lifestyles, onset ages, Gleason scores, PSA levels, and pathologic stages. We found a significant difference in the G allele of SNP rs1859962 (P = 0.035, OR = 1.51, 95% CI = 1.03-2.21) but not in the rs4430796 genotype frequency or allele frequency distribution between prostate cancer patients and the controls (P > 0.05). Neither of the SNPs was significantly associated with the onset age, Gleason score, PSA level, pathologic stage, or other clinical indicators of patients with prostate cancer (P > 0.05). Our results show that polymorphism of the G allele of SNP rs1859962 is associated with the risk of prostate cancer in a Chinese population.

[Two single nucleotide polymorphisms on chromosome 3 and the risk of prostate cancer in Chinese men].

OBJECTIVE: To investigate the correlation of the common variant single nucleotide polymorphisms (SNP) on chromosome 3 with the incidence and related risk factors of prostate cancer (PCa) in Chinese men. METHODS: Using the case-control meth- od, we included 124 PCa patients in the PCa group and 111 age- and gender-matched cancer-free healthy subjects as normal controls. We detected the distribution of allele and genotype frequencies of the SNP rs10934853 and rs2660753 with the polymerase chain reaction-high resolution melting curve (PCR-HRM) combined with gene sequencing, analyzed the cumulative effect of the risk genotypes of these two independent variants, and determined the correlation between different genotypes of these two SNPs and clinically related risk factors in the PCa patients. RESULTS: As for the genotypes of rs10934853, there were 28 cases of AA (22.8%), 46 cases of CC (37.4%), and 49 cases of AC (39.8%) in the PCa patients, as compared with 24 (22.0%), 34 (31.2%) and 51 (46.8%) in the healthy controls. As regards the genotypes of rs2660753, there were 13 cases of AA (11.0%), 59 cases of GG (50.0%) and 46 cases of AG (39.0%) in the PCa patients, in comparison with 9 (8.8%), 47 (45.6%) and 47 (45.6%) in the controls. No significant differences were found in the distribution of the genotype and allele frequencies of rs10934853 and rs2660753 between the two groups (P = 0.520 & 0.582). Analysis on the cumulative effect of the risk genotypes of rs10934853 and rs2660753 showed a slightly higher risk of PCa (OR = 1.831 & 1.968) in the two groups with risk genotypes than in the one with wild types (P > 0.05). Different genotypes of rs10934853 and rs2660753 were not correlated with clinically related risk factors of the PCa patients (P > 0.05). CONCLUSION: SNP rs10934853 and rs2660753 on chromosome 3 are not obviously correlated with PCa in Chinese patients, and may not be a genetic risk factor of PCa.