ABSTRACT
DMRT, a gene family related to sexual determination, encodes a large group of transcription factors (DMRTs) with the double-sex and mab-3 (DM) domain (except for DMRT8), which is able to bind to and regulate DNAs. Current studies have shown that the DMRT gene family plays a critical role in the development of sexual organs (such as gender differentiation, gonadal development, germ cell development, etc.) as well as extrasexual organs (such as musculocartilage development, nervous system development, etc.). Additionally, it has been suggested that DMRTs may be involved in the cancer development and progression (such as prostate cancer, breast cancer, lung cancer, etc.). This review summarizes the research progress about the mammalian DMRTs' structure, function and its critical role in cancer development, progression and therapy (mainly in human and mice), which suggests that DMRT gene could be a candidate gene in the study of tumor formation and therapeutic strategy.
Subject(s)
Male , Animals , Humans , Mice , Transcription Factors/genetics , Mammals/metabolism , Cell Differentiation , Neoplasms/geneticsABSTRACT
Objective To evaluate the immunity efficacy of human amniotic membranes on rats. Methods One hundred and fifty Wistar rats were randomly divided into five groups:biological amnion group,immunosuppression group,immunostimulation group, sham-operated group and blank control group. According to the study period,each group of thirty rats would be randomly divided into five experimental operation subgroups:the 1st week,the 2nd week,the 4th week,the 8th week group and the 12th week groups. The rats were implanted subcutaneously,then intramuscular injection of gentamicin sulfate for 3 days to resist the infection ,and the immune organ coefficient,and the killing abilities of NK cell ,IL-1β,IL-6 and TNF-αserum levels were detected according to the study period.Results At 1st ,2nd ,4th ,8th and 12th week after amniotic membrane implantation in rats,compared with the sham-operated and blank control groups,the biological amnion group had nonsignificant differences (P>0.05). At 1st week after amniotic membrane implantation in rats, immunosuppression group showed different levels of the immunosuppressive effect,such as the analysis of immune organ coefficient , which had significant differences compared with other groups (P<0.01). At 1st week after amniotic membrane implantation in rats,the imunostimulation group showed a certain degree of the immunostimulant effect,such as the killing abilities of NK cell,which had marked differences compared with other groups (P<0.05). Conclusion The amniotic membranes have satisfactory immune safety with implantation in rats and do not cause significant adverse immune reactions.
ABSTRACT
The abundance of an mRNA species depends not only on the transcription rate at which it is produced, but also on its decay rate,which determines how quickly it is degraded. Both transcription rate and decay rate are important factors in regulating gene expression. With the advance of the age of genomics, there are a considerable number of gene expression datasets, in which the expression profiles of tens of thousands of genes are often non-uniformly sampled. Recently,numerous studies have proposed to infer the regulatory networks from expression profiles. Nevertheless, how mRNA decay rates affect the computational prediction of transcription rate profiles from expression profiles has not been well studied. To understand the influences, we present a systematic method based on a gene dynamic regulation model by taking mRNA decay rates, expression profiles and transcription profiles into account. Generally speaking,an expression profile can be regarded as a representation of a biological condition. The rationale behind the concept is that the biological condition is reflected in the changing of gene expression profile. Basically,the biological condition is either associated to the cell cycle or associated to the environmental stresses. The expression profiles of genes that belong to the former, so-called cell cycle data, are characterized by periodicity, whereas the expression profiles of genes that belong to the latter, so-called condition-specific data, are characterized by a steep change after a specific time without periodicity. In this paper, we examine the systematic method on the simulated expression data as well as the real expression data including yeast cell cycle data and condition-specific data (glucose-limitation data). The results indicate that mRNA decay rates do not significantly influence the computational prediction of transcription-rate profiles for cell cycle data. On the contrary,the magnitudes and shapes of transcription-rate profiles for condition specific data are significantly affected by mRNA decay rates. This analysis provides an opportunity for researchers to conduct future research on inferring regulatory networks computationally with available expression profiles under different biological conditions.