No abstract

Retinoic acid‐inducible gene I‐like receptors (RLRs) play an essential role in human innate immune, which may influence the spontaneous clearance of hepatitis B virus (HBV) infection. We aimed to investigate whether the SNPs in RLR family were associated with HBV spontaneous clearance. The current study included 82 participants with spontaneous clearance, 601 asymptomatic hepatitis B surface antigen (HBsAg) carriers, and 168 participants with chronic hepatitis B (CHB). Six SNPs (DDX58 rs3824456, rs3205166, DHX58 rs2074160, rs2074158, IFIH1 rs2111485, rs3747517) were genotyped to explore their association with HBV spontaneous clearance. Patients carrying the mutant allele C at rs3824456 or A at rs2074160 were more likely to achieve spontaneous clearance compared with asymptomatic HBsAg carriers (additive model: odds ratio [OR] = 0.69, 95% confidence interval [CI] =  0.49–0.97; dominant model: OR = 0.54, 95% CI = 0.31–0.95, respectively). In addition, patients carrying the mutant allele G at rs2111485 were more likely to achieve spontaneous clearance compared with CHB (dominant model: OR = 0.47, 95% CI = 0.25–0.87). The mutations were protective factors for HBV spontaneous clearance. These results suggest the DDX58 rs3824456, DHX58 s2074160, IFIH1 rs2111485 were associated with spontaneous clearance of HBV, which may be predictive markers in the Chinese Han population of HBV.

Complex nonlinear optimization problems are involved in optimal spatial search, such as location allocation problems that occur in multidimensional geographic space. Such search problems are generally difficult to solve by using traditional methods. The bat algorithm (BA) is an effective method for solving optimization problems. However, the solution of the standard BA is easily trapped at one of its local optimum values. The main cause of premature convergence is the loss of diversity in the population. The niche technique is an effective method to maintain the population diversity, to enhance the exploration of the new search domains, and to avoid premature convergence. In this paper, a geographic information system- (GIS-) based niche hybrid bat algorithm (NHBA) is proposed for solving the optimal spatial search. The NHBA is able to avoid the premature convergence and obtain the global optimal values. The GIS technique provides robust support for processing a substantial amount of geographical data. A case in Fangcun District, Guangzhou City, China, is used to test the NHBA. The comparative experiments illustrate that the BA, GA, FA, PSO, and NHBA algorithms outperform the brute-force algorithm in terms of computational efficiency, and the optimal solutions are more easily obtained with NHBA than with BA, GA, FA, and PSO. Moreover, the precision of NHBA is higher and the convergence of NHBA is faster than those of the other algorithms under the same conditions.