Literature DB >> 32862048

The frequency of collapse as a predictor of feline blastocyst quality.

Barbara Kij1, Joanna Kochan1, Karolina Fryc2, Wojciech Niżański3, Sylwia Prochowska3, Julia Gabryś1, Agnieszka Nowak1, Monika Bugno-Poniewierska4.   

Abstract

Domestic cats are frequently used as a research model for felid species that are threatened with extinction. Until now, the development of feline embryos has been evaluated using both classical observation methods and time-lapse monitoring (TLM). Blastocyst collapse observed using time-lapse cinematography is used as a predictor of blastocyst quality and is closely related to implantation potential. The aim of this study was to determine the relationship between the quality of domestic cat blastocysts obtained after in vitro fertilization and the frequency and duration of collapse, and of hatching. There was a significant difference in the average number of collapses and weak contractions between good and poor quality blastocysts. There was no significant difference between hatching and non-hatching blastocysts in terms of blastocyst cavity formation time or average number and duration of collapse. These results showed that the time of cavity formation was not related to blastocyst quality. The number of collapses and the occurrence of hatching were positively related to blastocyst quality, and poor quality blastocysts have, as a consequence, a reduced potential for implantation. TLM plays a significant role in cat embryo evaluation.
Copyright © 2020 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Blastocyst; Blastocyst quality; Collapses; Domestic cat

Mesh:

Year:  2020        PMID: 32862048     DOI: 10.1016/j.theriogenology.2020.08.008

Source DB:  PubMed          Journal:  Theriogenology        ISSN: 0093-691X            Impact factor:   2.740


  1 in total

1.  Relationships of morphological and phototextural attributes of presumptive ovine zygotes and early embryos to their developmental competence in vitro: a preliminary assessment using time-lapse imaging.

Authors:  Karolina Fryc; Agnieszka Nowak; Barbara Kij-Mitka; Joanna Kochan; Maciej Murawski; Samantha Pena; Pawel Mieczyslaw Bartlewski
Journal:  Anim Reprod       Date:  2022-04-08       Impact factor: 1.807

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.