Modeling to Optimize Terminal Stem Cell Differentiation

Abstract

Embryonic stem cell (ESC), iPCs, and adult stem cells (ASCs) all are among the most promising potential treatments for heart failure, spinal cord injury, neurodegenerative diseases, and diabetes. However, considerable uncertainty in the production of ESC-derived terminally differentiated cell types has limited the efficiency of their development. To address this uncertainty, we and other investigators have begun to employ a comprehensive statistical model of ESC differentiation for determining the role of intracellular pathways (e.g., STAT3) in ESC differentiation and determination of germ layer fate. The approach discussed here applies the Baysian statistical model to cell/developmental biology combining traditional flow cytometry methodology and specific morphological observations with advanced statistical and probabilistic modeling and experimental design. The final result of this study is a unique tool and model that enhances the understanding of how and when specific cell fates are determined during differentiation. This model provides a guideline for increasing the production efficiency of therapeutically viable ESCs/iPSCs/ASC derived neurons or any other cell type and will eventually lead to advances in stem cell therapy.

Assessment of the Field of Assisted Reproductive Technology: Improvements and the Future of Human In Vitro Fertilization

“…In order to most accurately ascertain probabilities of success with embryo transfer (ET), it is of utmost importance that an embryo with the highest likelihood of implantation is chosen. While currently there is no universally accepted method for picking such an embryo, some new models show promise, albeit lacking verification and publication of results [18,19]. Certain characteristics, such as duration of infertility, maternal age, number of ART treatment cycles, and patient pathology, are most inversely correlated with embryo quality and, thus, pregnancy success [17,18,20,21].…”

“…While currently there is no universally accepted method for picking such an embryo, some new models show promise, albeit lacking verification and publication of results [18,19]. Certain characteristics, such as duration of infertility, maternal age, number of ART treatment cycles, and patient pathology, are most inversely correlated with embryo quality and, thus, pregnancy success [17,18,20,21]. The hope of these models is that multiple pregnancy rates can be greatly diminished by screening patients to determine good candidates (and embryos) for SET and thereby decreasing use of DET.…”

“…However, this is itself a problem, as the waiting period preceding treatment not only causes the average age of the women undergoing IVF to increase, but this older patient population brings with it higher costs and a larger number of complications. As many studies have shown, maternal age is the most important, and best, indicator of pregnancy success; it generally informs both embryo quality and frequency, which decrease with increasing age, while abnormalities rise [18,31,44]. Advanced maternal age (AMA), patients 40 years old or more, require larger doses of follicle-stimulating hormone (FSH) to stimulate the follicle to produce collectible eggs as well as more monitoring and tests throughout the treatment cycle [5,30,45].…”