Uslu Bahar, Dioguardi Carola Conca, Haynes Monique, Miao De-Qiang, Kurus Meltem, Hoffman Gloria, Johnson Joshua
Department of Obstetrics, Gynecology, and Reproductive Sciences, Yale School of Medicine, 333 Cedar Street, New Haven, Connecticut, USA.
Current Address: Center for Reproductive Biology, Washington State University, PO Box 647521, Pullman, 99164, Washington, USA.
J Ovarian Res. 2017 Jan 13;10(1):3. doi: 10.1186/s13048-016-0296-x.
A standard histomorphometric approach has been used for nearly 40 years that identifies atretic (e.g., dying) follicles by counting the number of pyknotic granulosa cells (GC) in the largest follicle cross-section. This method holds that if one pyknotic granulosa nucleus is seen in the largest cross section of a primary follicle, or three pyknotic cells are found in a larger follicle, it should be categorized as atretic. Many studies have used these criteria to estimate the fraction of atretic follicles that result from genetic manipulation or environmental insult. During an analysis of follicle development in a mouse model of Fragile X premutation, we asked whether these 'historical' criteria could correctly identify follicles that were not growing (and could thus confirmed to be dying).
Reasoning that the fraction of mitotic GC reveals whether the GC population was increasing at the time of sample fixation, we compared the number of pyknotic nuclei to the number of mitotic figures in follicles within a set of age-matched ovaries.
We found that, by itself, pyknotic nuclei quantification resulted in high numbers of false positives (improperly categorized as atretic) and false negatives (improperly categorized intact). For preantral follicles, scoring mitotic and pyknotic GC nuclei allowed rapid, accurate identification of non-growing follicles with 98% accuracy. This method most often required the evaluation of one follicle section, and at most two serial follicle sections to correctly categorize follicle status. For antral follicles, we show that a rapid evaluation of follicle shape reveals which are intact and likely to survive to ovulation.
Combined, these improved, non-arbitrary methods will greatly improve our ability to estimate the fractions of growing/intact and non-growing/atretic follicles in mouse ovaries.
一种标准的组织形态计量学方法已被使用了近40年，该方法通过计数最大卵泡横切面中固缩颗粒细胞（GC）的数量来识别闭锁（如即将死亡）卵泡。该方法认为，如果在初级卵泡的最大横切面中看到一个固缩的颗粒细胞核，或者在较大卵泡中发现三个固缩细胞，则应将其归类为闭锁卵泡。许多研究都使用这些标准来估计由基因操作或环境损伤导致的闭锁卵泡比例。在对脆性X前突变小鼠模型的卵泡发育进行分析时，我们询问这些“历史”标准是否能够正确识别未生长（因此可确定为即将死亡）的卵泡。
考虑到有丝分裂GC的比例可揭示样本固定时GC群体是否在增加，我们比较了一组年龄匹配的卵巢中卵泡内固缩细胞核的数量与有丝分裂图像的数量。
我们发现，仅进行固缩细胞核定量会导致大量假阳性（错误分类为闭锁卵泡）和假阴性（错误分类为完整卵泡）。对于窦前卵泡，对有丝分裂和固缩GC细胞核进行评分可快速、准确地识别未生长卵泡，准确率达98%。该方法通常只需评估一个卵泡切片，最多评估两个连续卵泡切片就能正确分类卵泡状态。对于窦卵泡，我们表明快速评估卵泡形状可揭示哪些卵泡是完整的且可能存活至排卵。
综合起来，这些改进的、非随意性的方法将大大提高我们估计小鼠卵巢中生长/完整卵泡和未生长/闭锁卵泡比例的能力。
