0000000000359629

AUTHOR

Lucia Sacchi

0000-0002-1390-9825

Gatekeeper of pluripotency: A common Oct4 transcriptional network operates in mouse eggs and embryonic stem cells

Abstract Background Oct4 is a key factor of an expanded transcriptional network (Oct4-TN) that governs pluripotency and self-renewal in embryonic stem cells (ESCs) and in the inner cell mass from which ESCs are derived. A pending question is whether the establishment of the Oct4-TN initiates during oogenesis or after fertilisation. To this regard, recent evidence has shown that Oct4 controls a poorly known Oct4-TN central to the acquisition of the mouse egg developmental competence. The aim of this study was to investigate the identity and extension of this maternal Oct4-TN, as much as whether its presence is circumscribed to the egg or maintained beyond fertilisation. Results By comparing …

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Maternal Oct-4 is a potential key regulator of the developmental competence of mouse oocytes

Abstract Background The maternal contribution of transcripts and proteins supplied to the zygote is crucial for the progression from a gametic to an embryonic control of preimplantation development. Here we compared the transcriptional profiles of two types of mouse MII oocytes, one which is developmentally competent (MIISN oocyte), the other that ceases development at the 2-cell stage (MIINSN oocyte), with the aim of identifying genes and gene expression networks whose misregulated expression would contribute to a reduced developmental competence. Results We report that: 1) the transcription factor Oct-4 is absent in MIINSN oocytes, accounting for 2) the down-regulation of Stella, a matern…

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Big Data as a Driver for Clinical Decision Support Systems: A Learning Health Systems Perspective

Big data technologies are nowadays providing health care with powerful instruments to gather and analyze large volumes of heterogeneous data collected for different purposes, including clinical care, administration, and research. This makes possible to design IT infrastructures that favor the implementation of the so-called “Learning Healthcare System Cycle,” where healthcare practice and research are part of a unique and synergic process. In this paper we highlight how “Big Data enabled” integrated data collections may support clinical decision-making together with biomedical research. Two effective implementations are reported, concerning decision support in Diabetes and in Inherited Arrh…

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