38 research outputs found

    A review of applying second-generation wavelets for noise removal from remote sensing data.

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    The processing of remotely sensed data includes compression, noise reduction, classification, feature extraction, change detection and any improvement associated with the problems at hand. In the literature, wavelet methods have been widely used for analysing remote sensing images and signals. The second-generation of wavelets, which is designed based on a method called the lifting scheme, is almost a new version of wavelets, and its application in the remote sensing field is fresh. Although first-generation wavelets have been proven to offer effective techniques for processing remotely sensed data, second-generation wavelets are more efficient in some respects, as will be discussed later. The aim of this review paper is to examine all existing studies in the literature related to applying second-generation wavelets for denoising remote sensing data. However, to make a better understanding of the application of wavelet-based denoising methods for remote sensing data, some studies that apply first-generation wavelets are also presented. In the part of hyperspectral data, there is a focus on noise removal from vegetation spectrum

    Common Molecular Etiologies Are Rare in Nonsyndromic Tibetan Chinese Patients with Hearing Impairment

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    Background: Thirty thousand infants are born every year with congenital hearing impairment in mainland China. Racial and regional factors are important in clinical diagnosis of genetic deafness. However, molecular etiology of hearing impairment in the Tibetan Chinese population living in the Tibetan Plateau has not been investigated. To provide appropriate genetic testing and counseling to Tibetan families, we investigated molecular etiology of nonsyndromic deafness in this population. Methods: A total of 114 unrelated deaf Tibetan children from the Tibet Autonomous Region were enrolled. Five prominent deafness-related genes, GJB2, SLC26A4, GJB6, POU3F4, and mtDNA 12S rRNA, were analyzed. Inner ear development was evaluated by temporal CT. A total of 106 Tibetan hearing normal individuals were included as genetic controls. For radiological comparison, 120 patients, mainly of Han ethnicity, with sensorineural hearing loss were analyzed by temporal CT. Results: None of the Tibetan patients carried diallelic GJB2 or SLC26A4 mutations. Two patients with a history of aminoglycoside usage carried homogeneous mtDNA 12S rRNA A1555G mutation. Two controls were homozygous for 12S rRNA A1555G. There were no mutations in GJB6 or POU3F4. A diagnosis of inner ear malformation was made in 20.18 % of the Tibetan patients and 21.67 % of the Han deaf group. Enlarged vestibular aqueduct, the most common inner ear deformity, was not found in theTibetan patients, but was seen in 18.33 % of the Han patients. Common molecular etiologies

    GJB2 mutation spectrum in 2063 Chinese patients with nonsyndromic hearing impairment

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    Background: Mutations in GJB2 are the most common molecular defects responsible for autosomal recessive nonsyndromic hearing impairment (NSHI). The mutation spectra of this gene vary among different ethnic groups. Methods: In order to understand the spectrum and frequency of GJB2 mutations in the Chinese population, the coding region of the GJB2 gene from 2063 unrelated patients with NSHI was PCR amplified and sequenced. Results: A total of 23 pathogenic mutations were identified. Among them, five (p.W3X, c.99delT, c.155_c.158delTCTG, c.512_c.513insAACG, and p.Y152X) are novel. Three hundred and seven patients carry two confirmed pathogenic mutations, including 178 homozygotes and 129 compound heterozygotes. One hundred twenty five patients carry only one mutant allele. Thus, GJB2 mutations account for 17.9% of the mutant alleles in 2063 NSHI patients. Overall, 92.6% (684/739) of the pathogenic mutations are frame-shift truncation or nonsense mutations. The four prevalent mutations; c.235delC, c.299_c.300delAT, c.176_c.191del16, and c.35delG, account for 88.0% of all mutantalleles identified. The frequency of GJB2 mutations (alleles) varies from 4% to 30.4% among different regions of China. It also varies among different sub-ethnic groups. Conclusion: In some regions of China, testing of the three most common mutations can identify at least one GJB2 mutant allele in all patients. In other regions such as Tibet, the three most common mutations account for only 16% the GJB2 mutant alleles. Thus, in this region, sequencing of GJB2 would be recommended. In addition, the etiology of more than 80% of the mutant alleles for NSHI in China remains to be identified. Analysis of other NSHI related genes will be necessary

    Pan-cancer analysis of whole genomes

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    Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe
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