Since hyperspectral images contain fine spectral information of the target objects, there is continuous demand for the detailed analysis about such images. A somewhat neglected but critically important challenge regarding hyperspectral image is the presence of "spatial stray light" - a phenomenon caused by scattering of photons from target objects. In this study, neighborhood unhomogeneity method is used to detect the edge of spatial stray light region in hyperspectral images. Analyses were conducted on reflectance datasets of standard card, potato leaf, and corn kernels from three inbred lines. By using neighborhood unhomogeneity method, the edge of spatial stray light region could be detected obviously and experimental results show the effectiveness of the proposed method. © 2014 Elsevier GmbH.

Background

Marie Unna hereditary hypotrichosis (MUHH) is an autosomal dominant disorder characterised by coarse, wiry, twisted hair developed in early childhood and subsequent progressive hair loss. MUHH is a genetically heterogeneous disorder. No gene in 1p21.1-1q21.3 region responsible for MUHH has been identified.

Methods

Exome sequencing was performed on two affected subjects, who had normal vertex hair and modest alopecia, and one unaffected individual from a four-generation MUHH family of which our previous linkage study mapped the MUHH locus on chromosome 1p21.1-1q21.3.

Results

We identified a missense mutation in EPS8L3 (NM_024526.3: exon2: c.22G->A:p.Ala8Thr) within 1p21.1-1q21.3. Sanger sequencing confirmed the cosegregation of this mutation with the disease phenotype in the family by demonstrating the presence of the heterozygous mutation in all the eight affected and absence in all the seven unaffected individuals. This mutation was found to be absent in 676 unrelated healthy controls and 781 patients of other disease from another unpublished project of our group.

Conclusions

Taken together, our results suggest that EPS8L3 is a causative gene for MUHH, which was helpful for advancing us on understanding of the pathogenesis of MUHH. Our study also has further demonstrated the effectiveness of combining exome sequencing with linkage information for identifying Mendelian disease genes.