Introducing our revolutionary microfluidic sperm selection device (MSSP) for assisted reproductive treatments. MSSP outperforms conventional methods, yielding a remarkable 68% more motile sperm with reduced DNA fragmentation and apoptosis. It also excels in post-cryopreservation recovery compared to existing techniques. Side-by-side comparisons with human semen (n=33) reveal an 85% improvement in DNA integrity and a 90% reduction in sperm apoptosis, highlighting MSSP's superior efficacy and ease of use in mimicking natural conception processes.

This study compares a novel microfluidic chamber to traditional Density Gradient Centrifugation (DGC) for selecting motile sperm with minimal DNA damage. Results showed the microfluidic chamber to be a superior alternative, enhancing DNA integrity and sperm motility. While high sperm DNA fragmentation negatively affects reproductive outcomes, existing methods lack clinical relevance. In a cohort study with 21 semen samples, the microfluidic device consistently outperformed DGC in DNA integrity and motility. The device, promising for clinical use, offers a simple, user-friendly approach compared to DGC. However, limitations include the absence of infertile patient samples and the need for a larger study. In conclusion, the microfluidic chamber shows potential as a new, effective tool for improved sperm selection in assisted reproductive technologies.

This study explored the use of artificial intelligence (AI) to enhance the speed and accuracy of identifying sperm in complex testicular tissue samples. The results demonstrated that trained AI significantly outperformed a trained embryologist, providing real-time, precise sperm identification with higher accuracy. The proof-of-concept study showcased the potential for seamless integration of AI into laboratory workflows, reducing processing times from hours to minutes. While promising, further clinical trials on diverse samples are needed to validate the effectiveness of AI in different scenarios. In summary, AI-powered image analysis has the potential to revolutionize sperm identification in surgical samples, potentially improving success rates in assisted reproductive treatments.

This proof-of-concept study investigated the effectiveness of artificial intelligence (AI) in improving the efficiency and efficacy of sperm searches in azoospermic samples. Using two cohorts, the AI significantly outperformed an embryologist in terms of time taken and accuracy. The results suggest that AI has the potential to seamlessly integrate into laboratory workflows, reducing sperm identification times from hours to minutes and potentially enhancing success rates in assisted reproductive treatments.

In 1979, the convergence of microfabrication and analytical methods gave rise to the field of microfluidics. Over the ensuing decades, microfluidics and microfabrication have garnered significant attention due to their diverse applications in the modern in vitro fertilization (IVF) laboratory or clinic, particularly in handling microlitre or nanolitre volumes of fluid. Unlike 2D models, which lack physiological relevance and three-dimensional (3D) tissue architecture, microfabrication and microfluidics have emerged as pivotal tools for advancing cell culture platforms. These technologies facilitate the development of sophisticated 3D culture systems, offering numerous advantages over conventional 2D models. The potential for evaluating such perfusion systems in a clinical setting lies in the exploration of novel microfabrication approaches.