Association Between MTHFR C677T Polymorphism and Susceptibility to Autism Spectrum Disorders: A Meta-Analysis in Chinese Han Population.

Prior studies have examined the influence of MTHFR C677T on autism susceptibility, however, there are no consensus conclusions and specific analyses of a Chinese population. This meta-analysis included a false-positive report probability (FPRP) test to comprehensively evaluate the association of MTHFR C677T polymorphism with autism susceptibility among a Chinese Han population. A large-scale literature retrieval was conducted using various databases including PubMed, Embase, Wan Fang, and the Chinese National Knowledge Infrastructure (CNKI) up to July 31, 2020, with a total of 2,258 cases and 2,073 controls included. The strength of correlation was assessed by odds ratios (ORs) and 95% confidence intervals (95% CIs). MTHFR C677T showed a significant correlation with increased ASD susceptibility under all genetic models (T vs. C, OR = 1.89, 95% CI 1.28 to 2.79; TT vs. CC: OR = 2.44, 95% CI 1.43 to 4.15; CT vs. CC, OR = 1.73; 95% CI 1.19 to 2.51; CT + TT vs. CC: OR = 2.03, 95% CI 1.31 to 3.15; TT vs. CT + CC, OR = 1.95, 95% CI 1.21 to 3.13). Stratification analysis by region also revealed a consistent association in the Northern Han subgroup, but not in the Southern Han subgroup. Pooled minor allele frequency (MAF) of 30 studies were 45% in Northern Han and 39% in Southern Han. To avoid a possible "false positive report," we further investigated the significant associations observed in the present meta-analysis using the FPRP test, which consolidated the results. In conclusion, MTHFR C677T polymorphism is associated with the increased risk of autism in China, especially in Northern Han. For those mothers and children who are generally susceptible to autism, prenatal folate and vitamin B12 may reduce the risk that children suffer from autism, especially in Northern Han populations. In the future, more well-designed studies with a larger sample size are expected.

An improved SOM algorithm and its application to color feature extraction.

Reducing the redundancy of dominant color features in an image and meanwhile preserving the diversity and quality of extracted colors is of importance in many applications such as image analysis and compression. This paper presents an improved self-organization map (SOM) algorithm namely MFD-SOM and its application to color feature extraction from images. Different from the winner-take-all competitive principle held by conventional SOM algorithms, MFD-SOM prevents, to a certain degree, features of non-principal components in the training data from being weakened or lost in the learning process, which is conductive to preserving the diversity of extracted features. Besides, MFD-SOM adopts a new way to update weight vectors of neurons, which helps to reduce the redundancy in features extracted from the principal components. In addition, we apply a linear neighborhood function in the proposed algorithm aiming to improve its performance on color feature extraction. Experimental results of feature extraction on artificial datasets and benchmark image datasets demonstrate the characteristics of the MFD-SOM algorithm.

Statistical virtual eye model based on wavefront aberration.

Wavefront aberration affects the quality of retinal image directly. This paper reviews the representation and reconstruction of wavefront aberration, as well as the construction of virtual eye model based on Zernike polynomial coefficients. In addition, the promising prospect of virtual eye model is emphasized.