Sperm selection in IVF: the long and winding road from bench to bedside

'Intracytoplasmic sperm injection (ICSI) paradox' and 'andrological ignorance': AI in the era of fourth industrial revolution to navigate the blind spots

The quandary known as the Intracytoplasmic Sperm Injection (ICSI) paradox is found at the juncture of Assisted Reproductive Technology (ART) and 'andrological ignorance' - a term coined to denote the undervalued treatment and comprehension of male infertility. The prevalent use of ICSI as a solution for severe male infertility, despite its potential to propagate genetically defective sperm, consequently posing a threat to progeny health, illuminates this paradox. We posit that the meteoric rise in Industrial Revolution 4.0 (IR 4.0) and Artificial Intelligence (AI) technologies holds the potential for a transformative shift in addressing male infertility, specifically by mitigating the limitations engendered by 'andrological ignorance.' We advocate for the urgent need to transcend andrological ignorance, envisaging AI as a cornerstone in the precise diagnosis and treatment of the root causes of male infertility. This approach also incorporates the identification of potential genetic defects in descendants, the establishment of knowledge platforms dedicated to male reproductive health, and the optimization of therapeutic outcomes. Our hypothesis suggests that the assimilation of AI could streamline ICSI implementation, leading to an overall enhancement in the realm of male fertility treatments. However, it is essential to conduct further investigations to substantiate the efficacy of AI applications in a clinical setting. This article emphasizes the significance of harnessing AI technologies to optimize patient outcomes in the fast-paced domain of reproductive medicine, thereby fostering the well-being of upcoming generations.

In Contemporary Reproductive Medicine Human Beings are Not Yet Dispensable

In the past few years almost every aspect of an IVF cycle has been investigated, including research on sperm, color doppler in follicular studies, prediction of embryo cleavage, prediction of blastocyst formation, scoring blastocyst quality, prediction of euploid blastocysts and live birth from blastocysts, improving the embryo selection process, and for developing deep machine learning (ML) algorithms for optimal IVF stimulation protocols. Also, artificial intelligence (AI)-based methods have been implemented for some clinical aspects of IVF, such as assessing patient reproductive potential and individualizing gonadotropin stimulation protocols. As AI has the inherent capacity to analyze "Big" data, the goal will be to apply AI tools to the analysis of all embryological, clinical, and genetic data to provide patient-tailored individualized treatments. Human skillsets including hand eye coordination to perform an embryo transfer is probably the only step of IVF that is outside the realm of AI & ML today. Embryo transfer success is presently human skill dependent and deep machine learning may one day intrude into this sacred space with the advent of programed humanoid robots. Embryo transfer is arguably the rate limiting step in the sequential events that complete an IVF cycle. Many variables play a role in the success of embryo transfer, including catheter type, atraumatic technique, and the use of sonography guidance before and during the procedure of embryo transfer. In contemporary Reproductive Medicine human beings are not yet dispensable.

New horizons in human sperm selection for assisted reproduction

Male infertility is a commonly encountered pathology that is estimated to be a contributory factor in approximately 50% of couples seeking recourse to assisted reproductive technologies. Upon clinical presentation, such males are commonly subjected to conventional diagnostic andrological practices that rely on descriptive criteria to define their fertility based on the number of morphologically normal, motile spermatozoa encountered within their ejaculate. Despite the virtual ubiquitous adoption of such diagnostic practices, they are not without their limitations and accordingly, there is now increasing awareness of the importance of assessing sperm quality in order to more accurately predict a male's fertility status. This realization raises the important question of which characteristics signify a high-quality, fertilization competent sperm cell. In this review, we reflect on recent advances in our mechanistic understanding of sperm biology and function, which are contributing to a growing armory of innovative approaches to diagnose and treat male infertility. In particular we review progress toward the implementation of precision medicine; the robust clinical adoption of which in the setting of fertility, currently lags well behind that of other fields of medicine. Despite this, research shows that the application of advanced technology platforms such as whole exome sequencing and proteomic analyses hold considerable promise in optimizing outcomes for the management of male infertility by uncovering and expanding our inventory of candidate infertility biomarkers, as well as those associated with recurrent pregnancy loss. Similarly, the development of advanced imaging technologies in tandem with machine learning artificial intelligence are poised to disrupt the fertility care paradigm by advancing our understanding of the molecular and biological causes of infertility to provide novel avenues for future diagnostics and treatments.

The Conceivable Functions of Protein Ubiquitination and Deubiquitination in Reproduction

Protein ubiquitination with general existence in virtually all eukaryotic cells serves as a significant post-translational modification of cellular proteins, which leads to the degradation of proteins via the ubiquitin–proteasome system. Deubiquitinating enzymes (DUBs) can reverse the ubiquitination effect by removing the ubiquitin chain from the target protein. Together, these two processes participate in regulating protein stability, function, and localization, thus modulating cell cycle, DNA repair, autophagy, and transcription regulation. Accumulating evidence indicates that the ubiquitination/deubiquitination system regulates reproductive processes, including the cell cycle, oocyte maturation, oocyte-sperm binding, and early embryonic development, primarily by regulating protein stability. This review summarizes the extensive research concerning the role of ubiquitin and DUBs in gametogenesis and early embryonic development, which helps us to understand human pregnancy further.

Microfluidic sperm selection yields higher sperm quality compared to conventional method in ICSI program: A pilot study

An appropriate preparation technique, should be capable of isolating highquality spermatozoa for intracytoplasmic sperm injection (ICSI). The aim was to assess sperm quality parameters, DNA integrity, embryo development, and clinical outcomes using a practical and accessible Microfluidic Sperm Sorting (MSS) technique. A total of 95 ICSI cases performed using sperm samples were prepared with our MSS (group 1) or by Direct Swim Up (DSU; control) method (group 2). Both sperm quality parameters and sperm DNA fragmentation (SDF) were compared between the groups. DNA fragmentation was assessed using Sperm Chromatin Dispersion (SCD) test and fine morphology was assessed using Motile Sperm Organelle Morphology Examination (MSOME). Embryo development and clinical outcomes were compared between the groups. In the MSS group, progressive motility and the fraction of Class I sperm morphology sperm were significantly higher compared to DSU group (P < 0.01 and P < 0.001, respectively). Moreover, the rates of DNA fragmentation and immotile spermatozoa were significantly lower in MSS when compared to DSU group (P < 0.001). Also, higher rates of high-quality embryo formation (P < 0.001), implantation (P = 0.04) and pregnancy (P = 0.05) were achieved in the MSS compared to DSU groups. The MSS technique proved to be a noninvasive, disposable, easy to use, and inexpensive method for separation of high-quality spermatozoa. Both laboratory parameters and clinical outcomes were improved with application of MSS for neat sperm collection in ICSI.AbbreviationsICSI: Intracytoplasmic Sperm Injection; MSS: Microfluidic Sperm Sorting; Sperm DNA Fragmentation (SDF); SCD: Sperm Chromatin Dispersion; MSOME: Motile Sperm Organelle Morphology Examination; DGC: Density Gradient Centrifugation; DSU: Direct Swim Up; ROS: Reactive Oxygen Species; ART: Assisted Reproducetive Technology.