期刊
YAKUGAKU ZASSHI-JOURNAL OF THE PHARMACEUTICAL SOCIETY OF JAPAN
卷 127, 期 3, 页码 491-500出版社
PHARMACEUTICAL SOC JAPAN
DOI: 10.1248/yakushi.127.491
关键词
reproductive toxicology; species differences; placenta; endocrine; organotin; transgenic mouse
Rodent models have great utility for evaluating the potential of environmental chemicals to alter human reproductive development. However, animal studies have some problems of species differences in extrapolating to human developmental toxicity induced by xenobiotics, because the placental endocrine functions in particular vary considerably among different species. For example, estrogen biosynthesis during pregnancy in humans is much different from that in rodents. In humans, ovarian function gradually declines after fertilization, as the placenta becomes the primary site of estrogen biosynthesis during pregnancy. In contrast to the process in humans, the ovary (not the placenta) is the main source of estrogen during pregnancy in rodents, because the placenta of rodents does not express the catalytic enzymes for estrogen biosynthesis, such as aromatase. The regulation of estrogen biosynthesis in the placenta is very important for human embryos because altering placental function can cause permanent effects on embryos. It has been suggested that rodents are therefore unsuitable for evaluating the potential effects of xenobiotics on the human reproductive system and developmental toxicity induced by the alteration of placental endocrine functions. Consequently, there is an urgent need to establish effective tools to evaluate the in vivo reproductive and developmental toxicity of environmental contaminants that disrupt the placental endocrine functions, including maintenance of local estrogen concentrations in the placenta. To resolve the problems, in this review we propose using transgenic mice, in which the transgene is controlled by placental-specific promoters, and local transgene systems into the placenta using viral vectors.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据