ABSTRACT
Assisted reproductive technology (ART) is an important invention for the treatment of human infertility, and the isolation of high-quality sperm with progressive motility is one of the most critical steps that eventually affect the fertilization rate. Conventional sperm separation approaches include the swim-up method and density gradient centrifugation. However, the quality of isolated sperm obtained from both approaches can still be improved by improving sorted sperm motility, minimizing the DNA fragmentation rate, and removing abnormal phenotypes. Here, we report a Progressive Sperm Sorting Chip (PSSC) for high-quality sperm isolation. Based on the rheotaxis behavior of sperm, a gradient flow field is created in the chip for progressive sperm sorting. Clinical experiment results for 10 volunteers showed that greater than 90% of isolated sperm exhibit high motility (> 25 µm/s), high linearity (0.8), and a very low DNA fragmentation rate (< 5%). In addition, the whole process is label and chemical free. These features aid in gentle sperm sorting to obtain healthy sperm. This device uniquely enables the selection of high-quality sperm with progressive motility and might be clinically applied for infertility treatment in the near future.
ABSTRACT
OBJECTIVE: To identify predictor microRNAs (miRNAs) from patients with repeated implantation failure (RIF). DESIGN: Systemic analysis of miRNA profiles from the endometrium of patients undergoing in vitro fertilization (IVF). SETTING: University research institute, private IVF center, and molecular testing laboratory. PATIENT(S): Twenty five infertile patients in the discovery cohort and 11 patients in the validation cohort. INTERVENTIONS(S): None. MAIN OUTCOME MEASURE(S): A signature set of miRNA associated with the risk of RIF. RESULT(S): We designed a reproductive disease-related PanelChip to access endometrium miRNA profiles in patients undergoing IVF. Three major miRNA signatures, including hsa-miR-20b-5p, hsa-miR-155-5p, and hsa-miR-718, were identified using infinite combination signature search algorithm analysis from 25 patients in the discovery cohort undergoing IVF. These miRNAs were used as biomarkers in the validation cohort of 11 patients. Finally, the 3-miRNA signature was capable of predicting patients with RIF with an accuracy >90%. CONCLUSION(S): Our findings indicated that specific endometrial miRNAs can be applied as diagnostic biomarkers to predict RIF. Such information will definitely help to increase the success rate of implantation practice.