Over the past four decades, due to cultural and social changes, women in the developed world have significantly delayed childbirth. This trend is even worse for patients who attend infertility clinics. It is well-known that live birth rates in women older than 35 are significantly lower than in those younger, both naturally and with assisted reproduction. Fertility decline is, in part, due to an increase in oocyte aneuploidy that leads to a reduced embryo quality, as well as an increased incidence of miscarriages and birth defects. Here we show that aging-associated malfunction is not restricted to the oocyte, as cumulus granulosa cells also display a series of defects linked to mitochondrial activity. In, both, human and mouse model, a decline in cumulus cell function due to increased maternal age is accompanied by a decreased expression of enzymes responsible for Coenzyme Q (CoQ) production, particularly Pdss2 and CoQ6. In an aged mouse model supplementation with Coenzyme Q10—a potent stimulator of mitochondrial function—restored cumulus cell number, stimulated glucose uptake, and increased progesterone production. CoQ10 supplementation might, thus, improve oocyte and cumulus cells quantity and quality, by improving the mitochondrial metabolism in females of advanced maternal age.

In in vitro fertilization (IVF) treatments, early identification of embryos with high implantation potential is required for shortening time to pregnancy while avoiding clinical complications to the newborn and the mother caused by multiple pregnancies. Current classification tools are based on morphological and morphokinetic parameters that are manually annotated using time‐lapse video files. However, manual annotation introduces interobserver and intraobserver variability and provides a discrete representation of preimplantation development while ignoring dynamic features that are associated with embryo quality. A fully automated and standardized classifiers are developed by training deep neural networks directly on the raw video files of >6200 blastulation‐labeled and >5500 implantation‐labeled embryos. Prediction of embryo implantation is more accurate than the current state‐of‐the‐art morphokientic classifier. Embryo classification improves with video length where the most predictive images show only partial association with morphological features. Deep learning substitute to human evaluation of embryo developmental competence thus contributes to implementing single embryo transfer methodology.

Follicular fluid (FF) constitutes the microenvironment of the developing oocyte. We recently characterized its lipid composition and found lipid signatures of positive pregnancy outcome after in vitro fertilization (IVF). In the current study, we aimed to test the hypothesis that unexplained female infertility is related to lipid metabolism, given the lipid signature of positive-outcome IVF patients we previously found. Assuming that FF samples from IVF patients with male factor infertility can represent a non-hindered metabolic microenvironment, we compared them to FF taken from women with unexplained infertility. FF from patients undergoing IVF was examined for its lipid composition. We found highly increased triacylglycerol levels, with a lower abundance of monoacylglycerols, phospholipids and sphingolipids in the FF of patients with unexplained infertility. The alterations in the lipid class accumulation were independent of the body mass index (BMI) and were altogether kept across the age groups. Potential lipid biomarkers for pregnancy outcomes showed a highly discriminative abundance in the FF of unexplained infertility patients. Lipid abundance distinguished IVF patients with unrecognized infertility and provided a potential means for the evaluation of female fertility.

To assess the predictive value of human Chorionic Gonadotropin (hCG) theca-stimulation test for ovarian reserve in women undergoing in-vitro fertilization (IVF) treatments. 39 women were included in the study. All participants received a single hCG 10000 IU injection on cycle day 2–3. Serum levels of estradiol, testosterone, androstenedione and 17-OH progesterone were measured prior to the injection and on days 1, 3 and 7 following the injection. hCG-induced hormone levels were compared with ovarian response during the subsequent IVF cycle. There were 11 good responders (>10 oocytes) and 22 low responders (<3 oocytes). Before hCG stimulation serum E2 levels were higher in low responders compared to good responders (370.3 ± 443 vs. 138.3 ± 54 pmol/ml). Following hCG stimulation, day 3 androstendione levels showed an increase in good responders compared to low responders. The ratio between day 3 androstendione and day 0 estradiol was significantly different between the two groups (p = 0.03). ROC analysis of this test revealed area = 0.837 (good prediction), which was much better than day 3 FSH (area = 0.635, poor prediction). These preliminary results demonstrate the potential use of the hCG theca stimulation test in differentiating between good and poor responders. Larger series are needed for further verification of the test in routine clinical application.