2 resultados para Pre-implantation tissue-typing

em Universidad Politécnica de Madrid


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Rabbit does in modern rabbitries are under intensive reproductive rhythms. Females are high milk producers with high energetic expenses due to the extensive overlap between lactation and gestation. This situation leads to a negative energy balance with a mobilization of body fat especially in primiparous rabbit does. Poor body condition and poor health status severely affect the reproductive features (fertility rate and lifespan of the doe as well as ovarian physiology). This paper reviews some reproductive and nutritional approaches used in the last years to improve the reproductive performance of rabbit females, mainly focusing on the influence on ovarian response and embryo quality and with emphasis on epigenetic modifications in pre-implantation embryos and offspring consequences.

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Many studies investigating the aging brain or disease-induced brain alterations rely on accurate and reproducible brain tissue segmentation. Being a preliminary processing step prior to the segmentation, reliableskull-stripping the removal ofnon-brain tissue is also crucial for all later image assessment. Typically, segmentation algorithms rely on an atlas i.e. pre-segmented template data. Brain morphology, however, differs considerably depending on age, sex and race. In addition, diseased brains may deviate significantly from the atlas information typically gained from healthy volunteers. The imposed prior atlas information can thus lead to degradation of segmentation results. The recently introduced MP2RAGE sequence provides a bias-free T1 contrast with heavily reduced T2*- and PD-weighting compared to the standard MP-RAGE [1]. To this end, it acquires two image volumes at different inversion times in one acquisition, combining them to a uniform, i.e. homogenous image. In this work, we exploit the advantageous contrast properties of the MP2RAGE and combine it with a Dixon (i.e. fat-water separation) approach. The information gained by the additional fat image of the head considerably improves the skull-stripping outcome [2]. In conjunction with the pure T1 contrast of the MP2RAGE uniform image, we achieve robust skull-stripping and brain tissue segmentation without the use of an atlas