Evaluation of shape variability of stallion sperm heads by means of image analysis and Fourier descriptors

Morphometry of Boar Spermatozoa in Semen Stored at 17 °C—The Influence of the Staining Technique

Simple Summary

To obtain satisfactory results in artificial insemination, it is necessary to use high-quality ejaculates for the production of insemination doses and then maintain the biological value of the sperm during storage. Boar spermatozoa, owing to the specific structure of the cell membrane, are particularly sensitive to temperature changes. For this reason, cryopreservation cannot be used in artificial insemination practice, and there may be limitations to successful storage of semen in a liquid state. The practice of using boar semen for artificial insemination does not include analyses of the effect of storage time of boar semen on sperm dimensions. Therefore, the aim of the study was to analyse the morphometry of sperm during storage of liquid boar semen. An attempt was also made to evaluate the suitability of three staining methods for assessment of boar sperm morphometry. The morphometric dimensions of boar sperm were shown to change during storage of liquid semen. These changes affected the sperm head more than the tail and were due to the staining method used. The analyses are very important as they provide more information about the morphometric dimensions of the sperm during preservation of boar semen. The applied sperm staining techniques allows for a more accurate assessment of male reproductive cells.

Abstract

The aim of the study was to assess the morphometry of sperm during storage of liquid boar semen at 17 °C. An attempt was also made to evaluate the suitability of three staining methods for assessment of boar sperm morphometry. The study was carried out on 20 Landrace boars. Semen was collected from the boars every 5 days by the manual method. Four ejaculates from each boar were analysed (80 ejaculates in total). Analyses were performed five times: at 1 h, 24 h, 48 h, 96 h, and 168 h after semen collection. Blisters with insemination doses were opened immediately before the analyses. From each insemination dose, smears were prepared for morphometric evaluation of sperm, which were stained by three methods (eosin-nigrosin—EN, eosin-gentian—EG, and SpermBlue—SB). Morphometric measurements of 15 randomly selected sperm with normal morphology were performed on each slide. The morphometric measurements included the following parameters: sperm head length, width, area, and perimeter; tail length; and total sperm length. The results of the morphometric measurements were used to calculate the head shape index. The morphometric dimensions of the sperm were shown to change during storage of semen at 17 °C. The extent of these changes, however, depended on the staining method used, as the three methods result in different morphometric dimensions of sperm, in the case of both the head and the tail. In the slides stained by the eosin-nigrosin method, the dimensions of the head and tail were smaller at every time of storage than in the slides stained by the SpermBlue and eosin-gentian methods.

Deep Learning-Based Morphological Classification of Human Sperm Heads

Human infertility is considered as a serious disease of the reproductive system that affects more than 10% of couples across the globe and over 30% of the reported cases are related to men. The crucial step in the assessment of male infertility and subfertility is semen analysis that strongly depends on the sperm head morphology, i.e., the shape and size of the head of a spermatozoon. However, in medical diagnosis, the morphology of the sperm head is determined manually, and heavily depends on the expertise of the clinician. Moreover, this assessment as well as the morphological classification of human sperm heads are laborious and non-repeatable, and there is also a high degree of inter and intra-laboratory variability in the results. In order to overcome these problems, we propose a specialized convolutional neural network (CNN) architecture to accurately classify human sperm heads based on sperm images. It is carefully designed with several layers, and multiple filter sizes, but fewer filters and parameters to improve efficiency and effectiveness. It is demonstrated that our proposed architecture outperforms state-of-the-art methods, exhibiting 88% recall on the SCIAN dataset in the total agreement setting and 95% recall on the HuSHeM dataset for the classification of human sperm heads. Our proposed method shows the potential of deep learning to surpass embryologists in terms of reliability, throughput, and accuracy.

Dependence of the frequency of sperm defects and dimensions on sperm motility in ejaculates of Polish Landrace boars

An attempt was made to determine the dependence of the frequency of sperm defects and dimensions on sperm motility in ejaculates of Polish Landrace boars. The study was conducted on 393 ejaculates collected from 33 Polish Landrace boars. Ejaculates were grouped according to the percentage of sperm with progressive motility, distinguishing ejaculates in which the percentage of motile sperm was 70% and 80%. In each ejaculate, the frequency of morphological changes in the sperm was determined and morphometric measurements of the sperm were made. Ejaculates with a higher proportion of sperm with progressive motility were found to contain more sperm. The ejaculate volume and sperm concentration in the ejaculate were not found to be directly associated with sperm motility. The frequency of primary defects was linked to sperm motility. Ejaculates with higher sperm motility contained fewer sperm with primary defects. The frequency of minor morphological changes, however, shows no significant dependence on sperm motility in the ejaculate. The primary morphological sperm defects most often found in ejaculates are a proximal droplet and the Dag defect. Both of these morphological forms are more common in ejaculates with lower sperm motility. The most common secondary sperm defects include sperm with a simple bent tail, sperm with a free normal head, and sperm with a distal droplet. These defects were not found to depend on sperm motility in the ejaculate. Sperm cells in ejaculates with greater sperm motility had slightly larger dimensions than sperm in ejaculates with lower sperm motility. Ejaculates with higher sperm motility are preferable for use in practice, not only because more insemination portions can be prepared from them, but also due to the lower frequency of primary defects.

Mouse spermatozoa with higher fertilization rates have thinner nuclei

Background

Although spermatozoa with normal morphology are assumed to have uniform fertilization ability, recent data show that even normal spermatozoa have considerable variation in their head shape which is associated with differences in fertilization ability. Appropriate quantitative indicators for good sperm morphology, however, remain unidentified.

Methods

Therefore, in an effort to identify such an indicator, we compared the nuclear contour of normal mouse spermatozoa by quantitative multivariate analysis using elliptic Fourier descriptors combined with principal component analysis. The spermatozoa were obtained from different strains and collection sites which have been shown to be associated with different fertilization abilities.

Results

We found that the head was 5.7% thinner in spermatozoa from the B6D2F1 (BDF1) strain, known to have a higher fertilization rate, than in those from the C57BL/6N (B6N) strain, which has a lower fertilization rate. Moreover, zona-penetrated spermatozoa in the perivitelline space consistently had 5.4% thinner heads than those isolated from the epididymis before ejaculation. The aspect ratio, which represents the sperm head thinness, uniquely distinguished these sperm populations, confirming its validity as a morphological indicator.

Discussion

Because aspect ratio has also been shown to characterize human spermatozoa, this unique morphometric indicator might be applicable to compare normal spermatozoa among multiple patients, which will greatly facilitate and enhance current reproductive technologies.

Ejaculate Traits and Sperm Morphology Depending on Ejaculate Volume in Duroc Boars

Introduction

The aim of this study was to evaluate the dependence between ejaculate traits, sperm morphology, and ejaculate volume in Duroc boars.

Material and Methods

The analysis involved 121 ejaculates collected from 12 Duroc boars kept in three artificial insemination centres located in central Poland. Ejaculates were collected manually at one-month intervals, over a period of 10 months. At least 10 ejaculates were collected from each boar. The material was divided by ejaculate volume and each ejaculate was assigned to one of three volume groups: 160 mL and lower, 161–200 mL, and 201 mL and higher. The ejaculates were assessed to identify the basic physical traits and determine the incidence of morphological abnormalities in the spermatozoa, specifying major and minor abnormalities. Furthermore, the morphological structure indices for the spermatozoa were also calculated.

Results

In large-volume ejaculates, spermatozoa were more elongated in shape, their heads were more elongated and had the largest flagella. With an increase in the ejaculate volume, sperm concentration in the ejaculate decreased. Moreover, while the total number of sperm in the ejaculate increased, the number of insemination doses obtained from a single ejaculate were higher.

Conclusion

The volume of ejaculate has little impact on the occurrence of morphological abnormalities and the size of sperm cells. Ejaculate volume is important for the shape of the sperm cells.

Automatic classification of human sperm head morphology

BACKGROUND AND OBJECTIVE

Infertility is a problem that affects up to 15% of couples worldwide with emotional and physiological implications and semen analysis is the first step in the evaluation of an infertile couple. Indeed the morphology of human sperm cells is considered to be a clinical tool dedicated to the fertility prognosis and serves, mainly, for making decisions regarding the options of assisted reproduction technologies. Therefore, a complete analysis of not only normal sperm but also abnormal sperm turns out to be critical in this context. This paper sets out to develop, implement and calibrate a novel methodology to characterize and classify sperm heads towards morphological sperm analysis. Our work is aimed at focusing on a depth analysis of abnormal sperm heads for fertility diagnosis, prognosis, reproductive toxicology, basic research or public health studies.

METHODS

We introduce a morphological characterization for human sperm heads based on shape measures. We also present a pipeline for sperm head classification, according to the last Laboratory Manual for the Examination and Processing of Human Semen of the World Health Organization (WHO). In this sense, we propose a two-stage classification scheme that permits to classify sperm heads among five different classes (one class for normal sperm heads and four classes for abnormal sperm heads) combining an ensemble strategy for feature selection and a cascade approach with several support vector machines dedicated to the verification of each class. We use Fisher's exact test to demonstrate that there is no statistically significant differences between our results and those achieved by domain experts.

RESULTS

Experimental evaluation shows that our two-stage classification scheme outperforms some state-of-the-art monolithic classifiers, exhibiting 58% of average accuracy. More interestingly, on the subset of data for which there is a total agreement between experts for the label of the samples, our system is able to provide 73% of average classification accuracy.

CONCLUSIONS

We show that our system behaves like a human expert; therefore it can be used as a supplementary source for labeling new unknown data. However, as sperm head classification is still a challenging issue due to the uncertainty on the class label of each sperm head, with the consequent high degree of variability among domain experts, we conclude that there are still opportunities for further improvement in designing a more accurate system by investigating other feature extraction methods and classification schemes.

Current status and potential of morphometric sperm analysis

The spermatozoon is the most diverse cell type known and this diversity is considered to reflect differences in sperm function. How the diversity in sperm morphology arose during speciation and what role the different specializations play in sperm function, however, remain incompletely characterized. This work reviews the hypotheses proposed to explain sperm morphological evolution, with a focus on some aspects of sperm morphometric evaluation; the ability of morphometrics to predict sperm cryoresistance and male fertility is also discussed. For this, the evaluation of patterns of change of sperm head morphometry throughout a process, instead of the study of the morphometric characteristics of the sperm head at different stages, allows a better identification of the males with different sperm cryoconservation ability. These new approaches, together with more studies employing a greater number of individuals, are needed to obtain novel results concerning the role of sperm morphometry on sperm function. Future studies should aim at understanding the causes of sperm design diversity and the mechanisms that generate them, giving increased attention to other sperm structures besides the sperm head. The implementation of scientific and technological advances could benefit the simultaneous examination of sperm phenotype and sperm function, demonstrating that sperm morphometry could be a useful tool for sperm assessment.

Geometric morphometrics of rodent sperm head shape

Mammalian spermatozoa, particularly those of rodent species, are extremely complex cells and differ greatly in form and dimensions. Thus, characterization of sperm size and, particularly, sperm shape represents a major challenge. No consensus exists on a method to objectively assess size and shape of spermatozoa. In this study we apply the principles of geometric morphometrics to analyze rodent sperm head morphology and compare them with two traditional morphometry methods, that is, measurements of linear dimensions and dimensions-derived parameters calculated using formulae employed in sperm morphometry assessments. Our results show that geometric morphometrics clearly identifies shape differences among rodent spermatozoa. It is also capable of discriminating between size and shape and to analyze these two variables separately. Thus, it provides an accurate method to assess sperm head shape. Furthermore, it can identify which sperm morphology traits differ between species, such as the protrusion or retraction of the base of the head, the orientation and relative position of the site of flagellum insertion, the degree of curvature of the hook, and other distinct anatomical features and appendices. We envisage that the use of geometric morphometrics may have a major impact on future studies focused on the characterization of sperm head formation, diversity of sperm head shape among species (and underlying evolutionary forces), the effects of reprotoxicants on changes in cell shape, and phenotyping of genetically-modified individuals.

Evaluation of sperm head shape at high magnification revealed correlation of sperm DNA fragmentation with aberrant head ellipticity and angularity

OBJECTIVE

To test for an association between DNA fragmentation and head shape at high magnification in fresh motile spermatozoa.

DESIGN

Observational study.

SETTING

Academic tertiary care center.

PATIENT(S)

A total of 60 men in our assisted reproductive program.

INTERVENTION(S)

Quantifying sperm head shape using elliptic Fourier analysis, and detecting DNA fragmentation by use of a terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) assay.

MAIN OUTCOME MEASURE(S)

Correlation between percentage of spermatozoa with abnormal head shape and percentage of DNA fragmentation.

RESULT(S)

Elliptic Fourier analysis decomposed sperm head shapes into four quantitative parameters: ellipticity, anteroposterior (AP) symmetry, lateral symmetry, and angularity. The DNA fragmentation was statistically significantly correlated with abnormal angularity, and moderately with abnormal ellipticity but not with abnormal AP symmetry or lateral symmetry. Forward stepwise multiple logistic regression analysis revealed a statistically significantly higher percentage of DNA fragmentation in spermatozoa with abnormal ellipticity and abnormal angularity than in spermatozoa with normal-shaped head (6.1% and 5.4% vs. 2.8%). Spermatozoa with large nuclear vacuoles also correlated with sperm DNA fragmentation, and had a statistically significantly higher percentage of DNA fragmentation (4.7%).

CONCLUSION(S)

Among the morphologic features of the sperm head, abnormal ellipticity, angularity, and large nuclear vacuoles are associated with DNA fragmentation.

The effect of radio electric asymmetric conveyer treatment on sperm parameters of subfertile stallions: a pilot study

The Radio Electric Asymmetric Conveyer (REAC) has been mostly applied to treat symptoms related to psychological stress. In the study, we demonstrated the effect of REAC-Veterinary Neuro Psycho Physical Optimization (VNPPO) treatment protocol on sperm parameters of subfertile (n=11) and fertile (n=4) stallions. Subfertile stallions showed a reduced sperm concentration, progressive motility and normal morphology compared to fertile stallions. An increase in progressive sperm motility and quality of sperm morphology was found in subfertile stallions after the REAC-VNPPO treatment. The positive effect of the REAC-VNPPO treatment was visible in a reduced number of reacted or absent acrosomes, nuclei with marginated chromatin and presence of cytoplasmic residues. Thus, we suggest that the REAC-VNPPO treatment for stallions with idiopathic subfertility may enhance the reproductive performance of stallions.