专利快速检索-快速检索全球专利，免费商用专利数据库-IPRDB

1. 发明授权

US5569581A Alteration and prediction of male fertility using seminal plasma and its components 失效
标题翻译：使用精液等离子体及其组分改变和预测男性生殖力
公开(公告)号：US5569581A
公开(公告)日：1996-10-29
申请号：US154226
申请日：1993-11-17
申请人： Gary Killian , David Chapman , Aida Cancel , Margaret A. Henault
发明人： Gary Killian , David Chapman , Aida Cancel , Margaret A. Henault
IPC分类号： G01N33/68 , C12Q1/00
CPC分类号： G01N33/689 , G01N2800/367 , Y10S435/806
摘要： Two-dimensional polyacrylamide gel electrophoresis of seminal plasma samples indicate that two proteins (26 kDa, pI 6.2; 55 kDa, pI 4.5) predominated in higher fertility bulls and two proteins (16 kDa, pI 4.1; 16 kDa, pI 6.7) predominated in lower fertility bulls. A regression model was developed to predict bull fertility using the four fertility-associated protein densities. A plot of actual bull fertility versus that calculated by this model was linear and positively correlated (r=0.89). These findings indicate that bull seminal plasma contains fertility-associated proteins which are predictive of bull fertility. Additionally, the ability of seminal plasma to alter the in vitro fertility of ejaculated bull sperm was examined using a sperm penetration assay for zona-free bovine oocytes. Washed, ejaculated sperm from bulls of below (low) or above average (high) fertility were mixed with seminal plasma from the same bull, or with seminal plasma from a bull of contrasting fertility. Washed sperm exposed to seminal plasma from high fertility bulls penetrated more oocytes than when those sperm were mixed with seminal plasma from low fertility bulls (p
摘要翻译：精浆血浆样品的二维聚丙烯酰胺凝胶电泳表明，两种蛋白质（26 kDa，pI 6.2; 55 kDa，pI 4.5）在较高生育力公牛和两种蛋白质（16 kDa，pI 4.1; 16 kDa，pI 6.7）中占主导地位较低的生育力公牛。开发了一种回归模型，用四种生育相关蛋白质密度来预测公牛的生育能力。实际公牛生产力与该模型计算的情节呈线性相关（r = 0.89）。这些研究结果表明，牛精液血浆含有生育相关蛋白，可预测公牛的生育能力。另外，使用无精子牛卵母细胞的精子渗透测定法检查了精浆等离子体改变射精公牛精子体外生育能力的能力。从低于（低）或高于平均（高）生育率的公牛洗精，射精精子与来自同一头公牛的精液血浆或与生殖力相反的公牛的精浆混合。冲洗精子暴露于高生育力公牛的精液血浆，渗透更多的卵母细胞比那些精子与低生育力公牛的精浆混合（p <0.01）。混合低生殖力精子与高生育精液血浆相比，低生殖力精子与低生育精液等离子体相比，通常能提高穿透能力。

IPRDB

热门服务

关于我们

友情链接

联系方式