Accurate prognosis of male fertility based on semen measurements is still not straightforward. This study was designed to identify the best predictors of fertility and to develop a multiple regression model predicting fertility using selected parameters of semen analysis. The predictive value of standard semen parameters and selected functional tests were studied in 113 fertile men and in 109 subfertile men whose spouses had a normal infertility workup. Individual semen parameters were evaluated using the receiver operating characteristic curve. Logistic regression based on linear functions of analysed sperm parameters was used to predict the chance of spontaneous conception. Logistic regression modelling revealed that the best prediction of spontaneous conception was obtained using 12 semen parameters: sperm concentration, total progressive motility (A + B), motility grade C or D, normal sperm morphology, defects of: head, acrosome, midpiece and tail, spontaneous acrosome reaction, hypo-osmotic swelling (HOS) test and acid aniline blue test. This mathematical model reached 90.3% accuracy in predicting in vivo conception and 90.8% for its lack. A satisfactory prediction of male fertility was also obtained using only four semen measurements: sperm concentration, total progressive motility (grade A + B), normal morphology, and HOS test; this model correctly identified as fertile 84.1% of those who conceived and identified as subfertile 88.1% of those who did not achieve pregnancy. In conclusion, basic semen analysis and selected functional tests of sperm provide important information regarding male fertility status.

A body of data exists on reactive oxygen species (ROS) release, however, no direct correlation was found between the oxidative stress and infertility. The aim of the study was to measure semen oxidative stress and its correlation with classical in vitro fertilization (IVF) rate. A prospective study in academic non-profit institution where 79 infertile couples were subjected to IVF programme was conducted. Two infertile groups were discriminated according to the pronuclei presence in IVF. The main outcome measure (pronuclei presence) was then correlated with lipid peroxidation product in semen (ROS effect). Although the average IL-8 levels and malondialdehyde (MDA) content in semen did not differ between the studied subgroups (successful vs. non-successful fertilization), a statistically significant negative correlation was found between MDA level and fertilization rate in performed regression analysis. Thus we may suggest that MDA levels in seminal plasma may have prognostic value for IVF success.

Objectives: The aim of the study was to check the quality of computer-assisted sperm analysis (CASA) system in comparison to the reference manual method as well as standardization of the computer-assisted semen assessment. Material and methods:The study was conducted between January and June 2015 at the Andrology Laboratory of the Division of Infertility and Reproductive Endocrinology, Poznań University of Medical Sciences, Poland. The study group consisted of 230 men who gave sperm samples for the first time in our center as part of an infertility investigation. The samples underwent manual and computer-assisted assessment of concentration, motility and morphology. A total of 184 samples were examined twice: manually, according to the 2010 WHO recommendations, and with CASA, using the program settings provided by the manufacturer. Additionally, 46 samples underwent two manual analyses and two computer-assisted analyses. The p-value of p < 0.05 was considered as statistically significant.Results: Statistically significant differences were found between all of the investigated sperm parameters, except for non-progressive motility, measured with CASA and manually. In the group of patients where all analyses with each method were performed twice on the same sample we found no significant differences between both assessments of the same probe, neither in the samples analyzed manually nor with CASA, although standard deviation was higher in the CASA group. Conclusions:Our results suggest that computer-assisted sperm analysis requires further improvement for a wider application in clinical practice.

A proportion of fertilized oocytes during classical in vitro fertilization (IVF) procedure was analysed depending on the following factors: number of mature oocytes, seminological criteria such as sperm morphology in raw semen and after its selection in a density gradient (six structural defects of a male gamete were taken into consideration), sperm concentration, motility parameters according to World Health Organization criteria and the functional tests: hypo-osmotic swelling assay and acrosomal reaction induced by calcium ionophore. Evaluation of DNA content in sperm by image cytometry and determination of malonyldialdehydes in seminal plasma were also performed. Seventy-nine semen samples from patients undergoing IVF were assessed. Apart from significant correlations obtained for selected semen parameters and proportion of fertilized eggs, logistic regression analysis showed that the best predictive factors for oocyte fertilization were normal morphology of sperm before and after gradient selection, grade B and C of sperm movement in raw semen, and DNA content after density gradient centrifugation, which all accounted for 76.7% of fertilization predictive value.

We determined the CCR5 chemokine receptor and cytochrome P450 aromatase (P450arom) transcript copies number in swim-up sperm isolated from fertile and infertile men. The ejaculates were purified by centrifugation through discontinuous Percoll density gradient and swim-up techniques. RNA was isolated from sperm, treated with DNase I and reverse-transcribed into cDNA. Quantitative analysis of CCR5 and P450arom cDNA were performed by real-time quantitative (RQ-PCR) SYBR Green I analysis. There was a higher content of CCR5 and P450arom transcripts copy number in swim-up sperm of fertile than from infertile donors. The decrease in CCR5 and P450arom transcripts in swim-up sperm may be associated with male infertility.