Semen analysis articles from across Nature Portfolio

In this Review, the authors discuss how machine learning can improve sperm selection, focusing on the near-term, achievable machine learning methods based on available assessments of selected sperm and the areas in which the most considerable gains are possible.

Semen quality in young men has been declining, and shows geographical, as well as temporal, variation. Several aspects of modern life, including lifestyle and environmental factors, stress, and exposure to endocrine disruptors and radiation, could be contributing to these trends. In this Review, the authors describe how semen quality is changing in the 21^stcentury, and consider how we can best identify and avoid the underlying causes.

Seminal plasma is a potential source of biomarkers of male reproductive system disorders. Drabovich et al. describe the development of seminal plasma proteomics and the progress towards the clinical use of biomarkers of male infertility and prostate cancer.

Evidence for the existence of racial disparities in semen parameters is increasing, exemplified by a recent study in men from white, Black and Asian populations. However, reference standards for semen parameters might not account for these disparities.

The past year has seen several new developments in the field of male reproductive health, including a major revision of how urologists should assess semen quality following the release of new WHO guidelines, novel approaches to sperm selection for intracytoplasmic sperm injection, and changes in how clinicians might evaluate and treat patients with hematospermia.

The fact that semen analysis cannot predict fertility has long been a source of frustration for both patients and physicians. Studies have demonstrated that semen analyses have poor predictive value for fertility status. Thus, the WHO reference values for human semen characteristics are of particular interest to anyone attempting to conceive and to the professionals who must counsel these individuals.