Yagmur Ergun

Incorporating artificial intelligence (AI) into in vitro fertilization (IVF) laboratories signifies a significant advancement in reproductive medicine. AI technologies, such as neural networks, deep learning, and machine learning, promise to enhance quality control (QC) and quality assurance (QA) through increased accuracy, consistency, and operational efficiency. This comprehensive review examines the effects of AI on IVF laboratories, focusing on its role in automating processes such as embryo and sperm selection, optimizing clinical outcomes, and reducing human error. AI’s data analysis and pattern recognition capabilities offer valuable predictive insights, enhancing personalized treatment plans and increasing success rates in fertility treatments. However, integrating AI also brings ethical, regulatory, and societal challenges, including concerns about data security, algorithmic bias, and the human–machine interface in clinical decision-making. Through an in-depth examination of current case studies, advancements, and future directions, this manuscript highlights how AI can revolutionize IVF by standardizing processes, improving patient outcomes, and advancing the precision of reproductive medicine. It underscores the necessity of ongoing research and ethical oversight to ensure fair and transparent applications in this sensitive field, assuring the responsible use of AI in reproductive medicine.

Salt is frequently introduced in ecosystems, where it acts as a pollutant. This study examined how changes in salinity affect the survival and development of zebrafish from the two-cell to the blastocyst stage and from the blastocyst to the larval stage. Control zebrafish embryos were cultured in E3 medium containing 5 mM Sodium Chloride (NaCl), 0.17 mM Potassium Chloride (KCL), 0.33 mM Calcium Chloride (CaCl₂), and 0.33 mM Magnesium Sulfade (MgSO₄). Experiments were conducted using increasing concentrations of each individual salt at 5×, 10×, 50×, and 100× the concentration found in E3 medium. KCL, CaCl₂, and MgSO₄ did not result in lethal abnormalities and did not affect early embryo growth at any of the concentrations tested. Concentrations of 50× and 100× NaCl caused embryonic death in both stages of development. Concentrations of 5× and 10× NaCl resulted in uninflated swim bladders in 12% and 65% of larvae, compared to 4.2% of controls, and caused 1654 and 2628 genes to be differentially expressed in blastocysts, respectively. The ATM signaling pathway was affected, and the Sonic Hedgehog pathway genes Shh and Ptc1 implicated in swim bladder development were downregulated. Our findings suggest that increased NaCl concentrations may alter gene expression and cause developmental abnormalities in animals found in affected ecosystems.

Mitochondrial unfolded protein stress response (mtUPR) plays a critical role in regulating cellular and metabolic stress response and helps maintain protein homeostasis. Caseinolytic peptidase P (CLPP) is one of the key regulators of mtUPR and promotes unfolded protein degradation. Previous studies demonstrated that global deletion of Clpp resulted in female infertility, whereas no impairment was found in the mouse model with targeted deletion of Clpp in cumulus/granulosa cells. These results suggest the need to delineate the function of Clpp in oocytes. In this study, we aimed to further explore the role of mtUPR in female reproductive competence and senescence using a mouse model. Oocyte-specific targeted deletion of Clpp in mice resulted in female subfertility associated with metabolic and functional abnormalities in oocytes, thus highlighting the importance of CLPP-mediated protein homeostasis in oocyte competence and reproductive function.