Comparison of the penetration ability of human spermatozoa into bovine cervical mucus and zona-free hamster eggs

Ram spermatozoa migrating through artificial mucus in vitro have reduced mitochondrial membrane potential but retain their viability

Sperm motility in vitro is one of the most common predictors of fertility in male screening. We propose that a mucus-penetration assay can isolate a cellular subpopulation critical to reproductive success. To this end, a device was designed with three modules (sample, test and collection) and its conditions of use evaluated (length of mucus, incubation time, mucus medium, sperm concentration and position in relation to the horizontal). The number of spermatozoa migrating and the viability and acrosomal status of the spermatozoa not migrating were calculated. The second objective was to evaluate the qualitative parameters of the spermatozoa migrating in 1.6% polyacrylamide for 30 min. The number of spermatozoa migrating and the sperm motility, viability and the acrosomal and mitochondrial status of three sperm populations (fresh, not migrating and migrating) were determined. A higher number of migrating spermatozoa were observed after 60 min of incubation, but this situation adversely affected sperm quality. The methylcellulose-based test showed a significantly lower number of migrating spermatozoa than the polyacrylamide test. The position at an angle of 45° resulted in a higher number of migrating spermatozoa in the polyacrylamide-based test. The sperm counts for three consecutive assays indicated an acceptable repeatability of the method. The viability and acrosomal status of the migrating spermatozoa showed no significant changes with regard to the control when the device was placed at 45°, whereas these parameters showed lower values at 0°. The percentage of high mitochondrial membrane potential spermatozoa was significantly reduced in the population of migrating spermatozoa.

A neural network to analyze fertility data

OBJECTIVE

To program an artificial intelligence system, a neural network, and use it to predict results of sperm penetration in bovine cervical mucus (Penetrak assay; Serono Laboratories, Norwell, MA) and zona-free hamster egg penetration from the semen analysis.

DESIGN

Results of 139 Penetrak assays, 1,416 zona-free hamster egg penetration assays, and the corresponding semen analyses were retrospectively analyzed by an artificial neural network.

MAIN OUTCOME MEASURES

Classification errors of the neural network were compared with those of linear and quadratic discriminant function analyses.

RESULTS

Data were separated into training and test sets. For the Penetrak result, linear and quadratic discriminant function analysis correctly predicted 58% and 74% of the training set results and only 64.1% and 69.2% of the test data, respectively. The neural network correctly predicted 92% of training set results and 80% of test set results. For the zona-free hamster egg penetration assay outcome, linear and quadratic discriminant function analysis correctly classified 66.3% and 46.0% of the training set and 64.9% and 44.7% of the test set, respectively. The neural network correctly classified 75.7% of the training data and 67.8% of the test data.

CONCLUSIONS

Using the semen analysis, the neural network correctly classified 67.8% of zona-free hamster egg penetration assay results and 80% of Penetrak results it had not encountered previously, suggesting that this method of data analysis may be successfully employed to predict fertility potential.

Artificial intelligence in medicine and male infertility

MAIN PROBLEM

fertility data is inadequately assessed by traditional statistical methods for a variety of reasons. First, the principal test of male fertility potential, the Semen Analysis (SA) is a composite of several dissimilar parameters, and the SA and other laboratory tests of fertility potential reflect physiological mechanisms that interact in complex ways. Second, patient data is often fragmented, obtained from multiple sources. Importantly, 2 patients are required for the final result.

METHODS

Novel and powerful computational method, the neural network, was explored to analyze fertility data. An integrated series of programs was written in the C computer language to implement a back propagation algorithm. A model data analysis system was chosen, predicting the penetration of zona-free hamster ova by sperm (Sperm Penetration Assay (SPA)) and the distance travelled by the farthest swimming sperm (Penetrak Assay) from the SA, for these 2 assays are generally believed by the reproductive medical community to be independent of the SA. The classification accuracy of the neural network was compared to 2 standard statistical methods, linear discriminant function analysis (LDFA) and quadratic discriminant function analysis (QDFA).

RESULTS

A neural network could be trained to correctly predict the Penetrak result in over 80% of assays it had not previously encountered, and another network could predict the SPA outcome in nearly 70%. The neural network was superior to LDFA and QDFA in predicting both assay outcomes (for Penetrak: LDFA = 64%, QDFA = 69%; for SPA: LDFA = 65%, QDFA = 45%).(ABSTRACT TRUNCATED AT 250 WORDS)

Assessment of bull fertility using a mucus penetration test and a human chorionic gonadotrophin stimulation test

The relative predictive abilities of an in vitro mucus penetration test and a human chorionic gonadotrophin (hCG) stimulation test were compared for assessing bull fertility. Cervical mucus was collected from 22 Holstein cows and then stored in liquid nitrogen. Semen was collected from 13 Holstein bulls and evaluated for standard semen parameters. The mucus penetration test was performed with fresh ejaculates, and the results were expressed as the distance traveled by the vanguard spermatozoa during incubation at 38 degrees C for 10 min. Increases in plasma testosterone levels were determined by a ratio of testosterone concentration before and after hCG injection. Sperm motility and mucus penetration were significantly correlated with the conception rate. However, no significant correlation was confirmed between the increased plasma testosterone levels and conception rate. The results indicate that the mucus penetration test is an effective method for predicting the fertility of bulls.

Impact of methodological factors on sperm penetration into cervical mucus in cattle

The aim of this study was to investigate the influence of methodological factors on the interaction of bovine spermatozoa and homologous cervical mucus. Cervical mucus was obtained from three cows during estrus. To evaluate the penetration ability of frozen-thawed semen samples of five different bulls, fresh mucus as well as frozen-thawed mucus, stored for 1, 10 or 30 d in liquid nitrogen, were used. Penetration assays were performed at 38 degrees C for 10 min, and the most advanced spermatozoon was located and the distance determined. Semen parameters were examined by a computer-assisted videomicrographic system. Conservation of mucus in liquid nitrogen for up to 30 d did not influence the results of the penetration assay. In contrast, the mucus of individual cows showed significant differences in the migration distance of spermatozoa. Sperm concentration, mean velocity and number of forward moving spermatozoa were significantly correlated with mucus penetration. These results demonstrated that the mucus penetration assay in cattle can be performed by dividing a mucus sample from a cow into many portions and storing the sample in liquid nitrogen.

A comparison of the bovine cervical mucus penetration test and the postcoital test

In 68 ejaculates an in vitro bovine cervical mucus penetration-test (Penetrak) was compared to the postcoital-test and the spermiogram. There was a positive correlation between the Penetrak-Test and concentration, motility, and morphology of the spermatozoa, however there was no correlation to the postcoital test. In connection with the PCT, the bovine mucus penetration-test seems to be a useful tool in the exploration of male infertility.

Penetration ability of human spermatozoa into standardized bovine cervical mucus (Penetrak) in patients with normal and pathological semen samples

Semen samples from 89 men were analyzed and evaluated with a standardized bovine cervical mucus penetration test (Penetrak). 29 patients had a normozoospermia, 22 patients a teratozoospermia and 38 patients an oligozoospermia of various degree. The most important parameters of semen analysis were compared with sperm mucus penetration. The sperm mucus penetration test correlated best with progressive motility (r = 0.6758), followed by total motility (r = 0.6302), sperm count (r = 0.6190), and % normal spermatozoa (r = 0.5493) (p less than 0.01 for each correlation coefficient). In the group of patients with normozoospermia 6 cases had been detected with insufficient sperm mucus penetration and in both groups with subfertility 15 cases with adequate sperm mucus penetration. 8 semen samples with normal sperm count and normal sperm motility were used for IVF. Only 6 patients with normal sperm penetration (greater than 30 mm/90') the spermatozoa fertilized the ova, but not from two patients, who had a sperm mucus penetration of less than 30 mm/90'. The study demonstrated that standardized bovine mucus penetration test detects disturbances of sperm motility which may not be discovered by conventional semen analysis.

Relationship between the sperm penetration assay and other tests of sperm function

Semen from 88 men of infertile couples and 33 fertile donors differed in seminal fluid analysis (sperm density and motility) (SFA) as well as in the penetration of hamster ova (SPA) and bovine cervical mucus (MPT). In the fertile group, significantly more subjects had adequate SFA, SPA, or MPT results than in the infertile group. When the two groups were subdivided into those with normal or those with abnormal SFA, no differences were noted in SPA, MPT, or postcoital test (PCT) scores. The SFA parameter most consistently reflected in the results of the SPA, MPT, and PCT was sperm density. This was most evident when the SFA was poor. The worst prognosticator of fertility was the SFA, with 30% of the fertile donors having an abnormal SFA. The worst prognosticator of infertility was the MPT, with 79% of the patients penetrating in the fertile range. The SPA was a significantly better predictor than either the SFA or MPT. SPA and MPT results were positively correlated only in the overall infertile group. The SPA, MPT, and PCT measure sperm qualities distinct from those revealed by the SFA, and from each other, and in combination provide the best assessment of fertility.