Paracentric inversion involving NOR of chromosome 8 in a boar: studies of synaptonemal complexes under a light microscope

International audienc

C-band variants of telocentric chromosomes in swine: evidence and inheritance studies

International audienc

Polymorphisms in DMRT1 coding and promoter regions are probably not causative for swine sex reversal (XX, SRY-negative) syndrome

SRY-negative XX sex reversal is an inherited or sporadically occurring disorder, where testis development appears in the absence of the SRY gene. Although the molecular background of this intersexuality syndrome in pigs is unknown, it was proposed that familial cases might be inherited as a single autosomal recessive trait. Because DMRT1 (Doublesex and Mab-3 related transcription factor 1) is an autosomal locus in pig (SSC1q21), shows sexually dimorphic expression in swine gonads and has strong significance in vertebrate testis development, the molecular analysis of this gene was performed in previously reported three intersexes (38,XX, SRY-negative), the progeny of a single boar from a Polish farm. The first two exons encoding functional DM (double sex and mab-3) domain and the promoter region (the 5'flanking sequence) (altogether 3894 bp) were sequenced and compared with male and female control pigs (n = 16) and with publicly available sequences. Three different polymorphisms were found in the coding region, one Indel type polymorphism (DNA 142_144indelAGC) causing a deletion of an amino acid (protein S47_G48indelS) and two silent SNPs (DNA G432A and G492A). The promoter region seems to be highly polymorphic, since 17 SNPs and 5 indels were detected. However, the sequences of control males and females were concordant with those of the intersexes. These results indicate that DMRT1 is an unlikely candidate gene for SRY-negative XX sex reversal in pig

Local embedding and dimensionality reduction in detection of skin tumor tissue

This article shows the limitation of the usage of dimensionality reduction methods. For this purpose three algorithms were analyzed on the real medical data. This data are multispectral images of human skin labeled as tumor or non-tumor regions. The classification of new data required the special algorithm of new data mapping that is also described in the paper. Unfortunately, the final conclusion is that this kind of local embedding algorithms should not be recommended for this kind of analysis and prediction

Selection of the most important components from multispectral images for detection of tumor tissue

The problem raised in this article is the selection of the most important components from multispectral images for the purpose of skin tumor tissue detection. It occured that 21 channel spectrum makes it possible to separate healthy and tumor regions almost perfectly. The disadvantage of this method is the duration of single picture acquisition because this process requires to keep the device very stable. In the paper two approaches to the problem are presented: hill climbing strategy and some ranking methods