Personalized medicine for in vitro fertilization procedure using modeling and optimal control

Germline Gene Editing: The Gender Issues

Human germline gene editing constitutes an extremely promising technology; at the same time, however, it raises remarkable ethical, legal, and social issues. Although many of these issues have been largely explored by the academic literature, there are gender issues embedded in the process that have not received the attention they deserve. This paper examines ways in which this new tool necessarily affects males and females differently-both in rewards and perils. The authors conclude that there is an urgent need to include these gender issues in the current debate, before giving a green light to this new technology.

Prediction of ovarian response in IVF/ICSI cycles

Objective:

Our study aims to evaluate the various correlations between demographic, biochemical, ultrasound, and ovarian stimulation parameters with the percentage of mature oocytes in conventional stimulation for IVF/ICSI cycles in order to develop a predictive model to improve our understanding of the oocyte maturation process.

Methods:

This is a retrospective cohort study; patients underwent conventional antagonist ovarian stimulation protocols for fresh IVF/ICSI cycles. A total of 256 IVF/ICSI cycles were included. Age, antral follicle count (AFC), baseline serum follicle-stimulating hormone (FSH) levels, baseline serum luteinizing hormone (LH) levels, baseline serum estradiol (E2) levels, peak estradiol, P4 on hCG day, the body mass index (BMI), and stimulation length were measured. The variables were tested for correlations with the number of retrieved oocytes (#RO) and the number of mature oocytes (#MO). A backward stepwise regression was performed to identify the variables that correlated more strongly with percentage of mature oocytes (%MO).

Results:

A predictive equation was obtained with the variables that were not excluded in the model. % MO = 72.700 - 0.910 (Age) + 0.979 (BMI) + 1.209 (Baseline serum LH) - 0.647 (Progesterone on human Chorionic Gonadotropin day).

Conclusions:

We concluded that age, the BMI, baseline serum LH, and progesterone level on hCG day may predict %MO. Prospective studies are required to validate this predictive equation.