Abstract: Unexplained recurrent spontaneous abortion (URSA) is a complex and challenging pregnancy disorder with unclear pathogenesis. The CBA/J × DBA/2 (Clark) mouse model is a well-recognized classic model for URSA, characterized by recessive, recurrent, and peri-implantation embryo resorption with a stable abortion rate of 20%-30%. This inbred model features a uniform genetic background, and the abortion rate attributed to chromosomal abnormalities is approximately 4%, consistent with human etiological data. However, challenges remain in model establishment, including variable pregnancy rates, inaccurate pregnancy timing determination, and high modeling costs. This study systematically summarizes the key technical points and practical experience for constructing the Clark model. To improve pregnancy rate, we optimized animal selection, age matching, housing environment, estrous cycle identification, and male-female pre-exposure, and clarified that superovulation is unsuitable for this model, while male sexual refractory period and Bruce effect should be avoided. We also established a multi-dimensional pregnancy judgment system combining vaginal plug inspection, dynamic body weight monitoring, fecal observation, abdominal palpation, visual inspection, and laparotomy. Novel findings include: a slight body weight decrease of 1%-5% on the day after plug detection; a body weight gain of approximately 1.0 g at GD4-6 (peri-implantation) indicating early pregnancy; a body weight gain ≥2.0 g at GD8 allowing earlier pregnancy confirmation; and drier feces in pregnant mice at GD4-6. This paper systematically organizes the key techniques in the whole process of model construction, which can significantly improve pregnancy rate and gestational age accuracy, reduce modeling costs, and provide a stable and reproducible model basis for URSA pathogenesis research and drug efficacy evaluation.

Key words: unexplained recurrent spontaneous abortion, abortion mouse model, CBA/J, DBA/2, estrous cycle, caged together, vaginal plug

摘要： 不明原因复发性流产(URSA)病因复杂、机制不明,CBA/J×DBA/2(Clark)小鼠模型是公认的URSA经典动物 模型,具有隐性、反复性、围着床期流产特征,流产率稳定在20%~30%,遗传背景单一、染色体异常所致流产率约 4%,与人类病因学高度契合。但该模型培育中存在受孕率波动、受孕时间判定不准、建模成本高等问题。本文系 统总结Clark模型建立的技术要点与实操经验,围绕动物选择、周龄把控、饲养环境、动情周期鉴定、雌雄预接触等 环节优化以提升受孕率,明确超数排卵不适用、需规避雄鼠性不应期与Bruce效应;建立检栓法、体质量动态监测、 粪便观察、摸胎/视腹、剖宫探查等多维度受孕判定体系,提出见栓次日体质量微降1%~5%、GD4~6体质量涨幅约 1.0 g、GD8体质量增加≥2.0 g可提前判定受孕,GD4~6孕鼠粪便变干等创新经验。本文系统梳理模型构建全流 程关键技术,可显著提升受孕率与孕龄判定准确性,降低建模成本,为URSA机制研究、药效评价提供稳定、可重复 的模型基础。

关键词: 不明原因复发性流产, 流产小鼠模型, CBA/J, DBA/2, 动情周期, 合笼, 阴栓