Implementation of novel statistical procedures and other advanced approaches to improve analysis of CASA data

Artificial intelligence and porcine breeding

Livestock management is evolving into a new era, characterized by the analysis of vast quantities of data (Big Data) collected from both traditional breeding methods and new technologies such as sensors, automated monitoring system, and advanced analytics. Artificial intelligence (A-In), which refers to the capability of machines to mimic human intelligence, including subfields like machine learning and deep learning, is playing a pivotal role in this transformation. A wide array of A-In techniques, successfully employed in various industrial and scientific contexts, are now being integrated into mainstream livestock management practices. In the case of swine breeding, while traditional methods have yielded considerable success, the increasing amount of information requires the adoption of new technologies such as A-In to drive productivity, enhance animal welfare, and reduce environmental impact. Current findings suggest that these techniques have the potential to match or exceed the performance of traditional methods, often being more scalable in terms of efficiency and sustainability within the breeding industry. This review provides insights into the application of A-In in porcine breeding, from the perspectives of both sows (including welfare and reproductive management) and boars (including semen quality and health), and explores new approaches which are already being applied in other species.

Post-testicular sperm maturation in ancient holostean species

Fish speciation was accompanied by changes in the urogenital system anatomy. In evolutionarily modern Teleostei, male reproductive tracts are fully separated from the excretory system, while in evolutionarily ancient Chondrostei and Holostei, the excretory and reproductive tracts are not separated. Sturgeon post-testicular sperm maturation (PTSM) occurring as a result of sperm/urine mixing is phenomenologically well described, while, in holosteans, functional intimacy of seminal ducts with kidney ducts and the existence of PTSM still need to be addressed. In Lepisosteus platostomus (Holostei), sperm samples were collected from testes (TS), efferent ducts (EDS), and Wolffian ducts (WDS). While WDS was motile, no motility was found in TS and EDS. The existence of PTSM was checked by in vitro PTSM procedure. After TS and EDS incubation in seminal fluid from WDS, no more than 5% motile spermatozoa were observed in TS, whereas in EDS the motility percentage was up to 75%. Experimental dyeing of urogenital ducts in gars and sturgeons revealed some differences in the interconnection between sperm ducts and kidneys. It is concluded that post-testicular sperm maturation occurs in gars and suggests that infraclass Holostei occupies an intermediate evolutionary position between Teleostei and Chondrostei in the anatomical arrangement of the urogenital system.

A new computational approach, based on images trajectories, to identify the subjacent heterogeneity of sperm to the effects of ketanserin

The identification of kinematic subpopulations is of paramount importance to understanding the biological nature of the sperm heterogeneity. Nowadays, the data of motility parameters obtained by a computer-assisted sperm analysis (CASA) system has been used as input to distinct algorithms to identify kinematic subpopulations. In contrast, the images of the trajectories were depicted only as examples of the patterns of motility in each subpopulation. Here, python code was written to reconstruct the images of trajectories, from their coordinates, then the images of trajectories were used as input to a machine learning clustering algorithm of classification, and the subpopulations were described statistically by the motility parameters. Finally, the images of trajectories in each subpopulation were displayed in a way we called Pollock plots. Semen samples of boar sperm were treated with distinct concentrations of ketanserin (an antagonist of the 5-HT2 receptor of serotonin) and untreated samples were used as a control. The motility of sperm in each sample was analyzed at 0 and 30 min of incubation. Six subpopulations were found. The subpopulation 2 presented the highest values of velocities at 0 or 30 min. After 30 min of incubation, the ketanserin increased the values of the curvilinear velocity at high concentrations, whereas the linearity and the straight velocity decreased. Our computational model permits better identification of the kinematic subpopulations than the traditional approach and provides insights onto the heterogeneity of the response to ketanserin; thus, it could significantly impact the research on the relationship between sperm heterogeneity-fertility.

Characterization of the Germplasm Bank for the Spanish Autochthonous Bull Breed "Asturiana de la Montaña"

Semen cryobanks are critical for preserving autochthonous and rare breeds. Since sperm cryopreservation has been optimized for commercial breeds, non-commercial ones (often endangered) must be characterized to ensure the germplasm's viability. This study reports an investigation of the "Asturiana de la Montaña" breed (AM), a valuable Spanish autochthonous cattle breed adapted to the mountainous Atlantic environment. The survey included cryopreserved semen doses from 40 bulls stored at the Principado de Asturias Germplasm Bank. Data were obtained from the routine fresh semen analysis, CASA (motility), and flow cytometry analyses of fresh and post-thawing semen, and the 56-day non-return-rate (NRR) in heifers and cows (all results as 1st and 3rd quartiles). Fresh samples (artificial vagina) were within the normal range for cattle (4-6 mL, 5-10 × 10⁹/mL; mass motility 5). Post-thawing results showed motility below typical for commercial breeds (total motility 26-43%, progressive 14-28%), with higher values for viability (47-62%). Insemination results showed a good performance for this breed (NRR: 47-56%; higher for heifers). Sperm volume increased with age, with little or no effects on sperm quality. Few associations were found between post-thawing quality or freezability and NRR, LIN being the variable more strongly associated (positively). The AM semen bank shows a good prospect for preserving and disseminating the genetics of this breed. This survey indicates that dedicated research is needed to adapt freezing protocols to this breed, optimizing post-thawing results.

Optimizing Bull Semen Cryopreservation Media Using Multivariate Statistics Approaches

Cryo-injury reduces post-thaw semen quality. Extender components play a protective role, but existing experimental approaches do not elucidate interactions among extender components, semen samples, and post-thaw quality. To identify optimal concentrations for 12 extender ingredients, we ran 122 experiments with an I-optimal completely random design using a large dataset from our previous study. We obtained a maximum predicted total motility of 70.56% from an I-optimal design and 73.75% from a Monte Carlo simulation. Individual bull variations were significant and interacted with extenders independently. 67% of bulls reliably preferred extender formulations to reach maximum motility. Multifactor analysis suggests that some antioxidants may offer superior protection over others. Partial least squares path modeling (PLS-PM) found the highest positive loadings for glutathione in the antioxidant class, glycerol in the CPA class, and fructose in the basic compounds class. The optimal ranges for milk, water, and ethylene glycol were extremely narrow. Egg yolk, cholesterol-loaded cyclodextrin, and nerve growth factor had medium-loading impacts. PLS-PM showed that CPA, osmoregulators, and basic components were the most efficient contributors to motility, while the antioxidant and extracellular protectant classes had less efficiency. Thus, ingredients, concentrations, and interactions of extender compounds are critical to extender formulation, especially when using multiple compounds with the same function.

Assessment of sperm motility in livestock: Perspectives based on sperm swimming conditions in vivo

Evaluation of sperm motility is well-established in farm animals for quickly selecting ejaculates for semen processing into insemination doses and for evaluating the quality of preserved semen. Likewise, sperm motility is a fundamental parameter used by spermatologists in basic and applied science. Motility is commonly assessed using computer-assisted semen analysis (CASA). Recent increases in computational power, as well as utilization of mobile CASA systems and open-source CASA programs, broaden the possibilities for motility evaluation. Despite this technological progress, the potential of computer-generated motility data to assess male fertility remains challenging and may be limited. Relevance for fertility assessment could be improved if measurement conditions would more closely mimic the in vivo situation. Hence, this review is focused on the current trends of automated semen assessment in livestock and explores perspectives for future use with respect to the physiological and physical conditions encountered by sperm in the female reproductive tract. Validation of current CASA systems with more complex, microfluidic-based devices mimicking the female reproductive tract environment could improve the value of sperm kinematic data for assessing the fertilizing capacity of semen samples, not only for application in livestock but also for use in conducting assisted reproduction techniques in other species.

What is the importance of sperm subpopulations?

The study of sperm subpopulations spans three decades. The origin, meaning, and practical significance, however, are less clear. Current technology for assessing sperm morphology (CASA-Morph) and motility (CASA-Mot) has enabled the accurate evaluation of these features, and there are many options for data classification. Subpopulations could occur as a result of the stage of development of each spermatozoon in the subpopulation. Spermatogenesis might contribute to the production of these subpopulations. Insights from evolutionary biology and recent molecular research are indicative of the diversity among male gametes that could occur from unequal sharing of transcripts and other elements through cytoplasmic bridges between spermatids. Sperm cohorts exiting the gonads would contain different RNA and protein contents, affecting the spermatozoon physiology and associations with the surrounding environmental milieu. Subsequently, these differences could affect how spermatozoa interact with the environmental milieu (maturation, mixing with seminal plasma, and interacting with the environmental milieu, or female genital tract and female gamete). The emergence of sperm subpopulations as an outcome of evolution, related to the reproductive strategies of the species, genital tract structures, and copulatory and fertilization processes. This kind of approach in determining the importance of sperm subpopulations in fertilization capacity should have a practical impact for conducting reproductive technologies, inspiring and enabling new ways for the more efficient use of spermatozoa in the medical, animal breeding, and conservation fields. This manuscript is a contribution to the Special Issue in memory of Dr. Duane Garner.

Evaluation of microenvironment cleanliness for computer assisted sperm analysis system based on fusion of neutrosophic feasures

BACKGROUND AND OBJECTIVE

Computer assisted sperm analysis (CASA) provides a quantitative assessment of the quality of male fertility. But sometimes there are difficulties in comparing among diagnoses of different laboratories due to the deficiency of quality control indicators, especially for microenvironment cleanliness. An unclean microenvironment may seriously degrade the quality of microscopic images, resulting in diagnosis inaccuracy. The primary reason for the scarcity of microenvironment cleanliness indicators is non-sperm objects can't be recognized from microscopic images accurately. In this paper, to overcome the issues mentioned above and lay a foundation for CASA's quality control from the perspective of digital image processing, an algorithm for non-sperm objects extraction was designed and then an approach for evaluating of microenvironment cleanliness proposed.

METHOD

First, two features neutrosophic grayscale and neutrosophic gradient were designed. Then based on them, a neutrosophic similarity measurement was developed. Combined with Otsu method, the measurement was applied to extract non-sperm objects by adjusting the value of noise factor. Finally, the indicator ratio of non-sperm objects (RNSO) was formed for evaluating the degree of microenvironment cleanliness.

CONCLUSION

The experiments demonstrated non-sperm targets can be extracted efficiently and effectively by adjusting the noise factor of the proposed algorithm. The RNSO indicator can reflect microenvironment cleanliness degree properly and indicate whether the operations of sample production or video acquiring meet standards. So, it can provide convictive and quantitative information for CASA's quality control.

Assessment of Chilling Injury in Boar Spermatozoa by Kinematic Patterns and Competitive Sperm-Oviduct Binding In Vitro

Sensitive detection of chilling injury in boar spermatozoa is required to evaluate novel hypothermic preservation concepts. The study’s aim was to examine whether analyses of motility patterns and sperm binding in a competitive oviduct explant assay (cOEA) sensitively detect chilling-induced alterations in sperm function. Semen samples (n = seven boars) were split into four subsamples by dilution either in Beltsville Thawing Solution (BTS) or Androstar® Plus and stored at 5 °C or 17 °C. Storage temperature had a significant effect on the distribution of spermatozoa in seven major kinematic clusters. The effect size of chilling at 5 °C as estimated by Cramer’s V was higher (p < 0.05) in the BTS medium (0.21) compared to AndroStar® Plus (0.11). Spermatozoa extended in Androstar® Plus had higher relative binding capacity compared to sperm in BTS (p < 0.05). Binding indices correlated with the percentage of viable, acrosome-intact (r = 0.62) and motile spermatozoa (r = 0.72, both p < 0.001). The cluster size of sperm with slow, vigorous movement was negatively correlated with sperm-oviduct binding (r = −0.43, p < 0.05). In conclusion, the cluster analysis of sperm kinematics and competitive sperm oviduct binding in vitro present meaningful biological tests to assess novel concepts for hypothermic semen preservation.

A New Approach of Sperm Motility Subpopulation Structure in Donkey and Horse

This study aimed to characterize the sperm kinematic values with high frames per second, to define the subpopulation structure of a horse and a donkey and compare them. A total of 57 fresh semen ejaculates (26 Spanish and 16 Arabian horse breeds and 10 donkeys) were collected and subsequently analyzed for kinematic parameters using the Computer-aided sperm motility analysis ISAS®v1.2 system and using a Spermtrack® 10-μm depth counting chamber. Sequences were recorded at 250 frames per second, and eight kinematic parameters were automatically evaluated. All kinematic parameters showed significant differences between a donkey and a horse and between horse breeds. All ejaculates evaluated showed excellent semen motility characteristics, with significantly higher values for all kinematic parameters for donkeys compared with horses except for beat-cross frequency. Donkey sperm was faster and linear than the horse. Regarding horse breeds differences, the Spanish horse had higher average path velocity, curvilinear velocity, and beat-cross frequency compared with the Arabian horse. Spanish horse sperm was rapid, but Arab horse was more linear. The principal component analysis showed three sperm subpopulations in the ejaculate of donkeys and horses with a significantly different motility characteristic between them. The dominant subpopulation for both donkey and horse was for rapid, straight, and linear with a high beat sperm (38.2 and 41.7%, respectively), whereas the lowest subpopulation was for the slowest and non-linear sperms. This, plus slight differences in the distribution of these subpopulations between Arabian and Spanish horses, were found. In conclusion, higher frames permitted to have a new interpretation of motile subpopulations with species and breed differences. More so, future works on donkey and horse breed spermatozoa should take into account differences between breeds that may interfere and alter the real analysis performed.

Expanding the Limits of Computer-Assisted Sperm Analysis through the Development of Open Software

Computer assisted sperm analysis (CASA) systems can reduce errors occurring in manual analysis. However, commercial CASA systems are frequently not applicable at the forefront of challenging research endeavors. The development of open source software may offer important solutions for researchers working in related areas. Here, we present an example of this, with the development of three new modules for the OpenCASA software (hosted at Github). The first is the Chemotactic Sperm Accumulation Module, a powerful tool for studying sperm chemotactic behavior, analyzing the sperm accumulation in the direct vicinity of the stimuli. This module was validated by comparing fish sperm accumulation, with or without the influence of an attractant. The analysis clearly indicated cell accumulation in the treatment group, while the distribution of sperm was random in the control group. The second is the Sperm Functionality Module, based on the ability to recognize five sperm subpopulations according to their fluorescence patterns associated with the plasma membrane and acrosomal status. The last module is the Sperm Concentration Module, which expands the utilities of OpenCASA. These last two modules were validated, using bull sperm, by comparing them with visual counting by an observer. A high level of correlation was achieved in almost all the data, and a good agreement between both methods was obtained. With these newly developed modules, OpenCASA is consolidated as a powerful free and open-source tool that allows different aspects of sperm quality to be evaluated, with many potential applications for researchers.

Methodological considerations for examining the relationship between sperm morphology and motility

Sperm cells of all taxa share a common goal to reach and fertilize an ovum, yet sperm are one of the most diverse cell types in nature. While the structural diversity of these cells is well recognized, the functional significance of variation in sperm design remains elusive. An important function of spermatozoa is a need to migrate toward the ova, often over long distances in a foreign environment, which may include a complex and hostile female reproductive tract. Several comparative and experimental studies have attempted to address the link between sperm morphology and motility, yet the conclusions drawn from these studies are often inconsistent, even within the same taxa. Much of what we know about the functional significance of sperm design in internally fertilizing species has been gleaned from in vitro studies, for which experimental parameters often vary among studies. We propose that discordant results from these studies are in part due to a lack of consistency of methods, conditions that do not replicate those of the female reproductive tract, and the overuse of simple linear measures of sperm shape. Within this review, we provide a toolkit for imaging, quantifying, and analyzing sperm morphology and movement patterns for in vitro studies and discuss emerging approaches. Results from studies linking morphology to motility enhance our understanding of the evolution of adaptive sperm traits and the mechanisms that regulate fertility, thus offering new insights into methods used in assisted reproductive technologies in animal science, conservation and public health.

Male Infertility is a Women's Health Issue-Research and Clinical Evaluation of Male Infertility Is Needed

Infertility is a devastating experience for both partners as they try to conceive. Historically, when a couple could not conceive, the woman has carried the stigma of infertility; however, men and women are just as likely to contribute to the couple’s infertility. With the development of assisted reproductive technology (ART), the treatment burden for male and unexplained infertility has fallen mainly on women. Equalizing this burden requires reviving research on male infertility to both improve treatment options and enable natural conception. Despite many scientific efforts, infertility in men due to sperm dysfunction is mainly diagnosed by a semen analysis. The semen analysis is limited as it only examines general sperm properties such as concentration, motility, and morphology. A diagnosis of male infertility rarely includes an assessment of internal sperm components such as DNA, which is well documented to have an impact on infertility, or other components such as RNA and centrioles, which are beginning to be adopted. Assessment of these components is not typically included in current diagnostic testing because available treatments are limited. Recent research has expanded our understanding of sperm biology and suggests that these components may also contribute to the failure to achieve pregnancy. Understanding the sperm’s internal components, and how they contribute to male infertility, would provide avenues for new therapies that are based on treating men directly for male infertility, which may enable less invasive treatments and even natural conception.

Melatonin Non-Linearly Modulates Bull Spermatozoa Motility and Physiology in Capacitating and Non-Capacitating Conditions

Bull spermatozoa physiology may be modulated by melatonin. We washed ejaculated spermatozoa free of melatonin and incubated them (4 h, 38 °C) with 0-pM, 1-pM, 100-pM, 10-nM and 1-µM melatonin in TALP-HEPES (non-capacitating) and TALP-HEPES-heparin (capacitating). This range of concentrations encompassed the effects mediated by melatonin receptors (pM), intracellular targets (nM–µM) or antioxidant activity (µM). Treatment effects were assessed as motility changes by computer-assisted sperm analysis (CASA) of motility and physiological changes by flow cytometry. Melatonin effects were more evident in capacitating conditions, with 100 pM reducing motility and velocity (VCL) while increasing a “slow” subpopulation. All concentrations decreased apoptotic spermatozoa and stimulated mitochondrial activity in viable spermatozoa, with 100 pM–1 µM increasing acrosomal damage, 10 nM–1 µM increasing intracellular calcium and 1 pM reducing the response to a calcium-ionophore challenge. In non-capacitating media, 1 µM increased hyperactivation-related variables and decreased apoptotic spermatozoa; 100 pM–1 µM increased membrane disorders (related to capacitation); all concentrations decreased mitochondrial ROS production. Melatonin concentrations had a modal effect on bull spermatozoa, suggesting a capacitation-modulating role and protective effect at physiological concentrations (pM). Some effects may be of practical use, considering artificial reproductive techniques.

Motile sperm subpopulations in bull semen using different clustering approaches - Associations with flow cytometric sperm characteristics and fertility

There are sperm subpopulations (SPs) with different kinematic characteristics in various species, however, biological relevance of these SPs is still uncertain. The objective of the present study was to investigate associations of motile sperm SPs with sperm characteristics determined by evaluations with flow cytometry and assessment of bull fertility, using multiple approaches for sperm clustering. Semen from 24 bulls was evaluated concomitantly using computer-assisted sperm analysis (CASA) and flow cytometry before freezing and after thawing. Motile SPs were determined utilizing two acknowledged clustering methods (TwoStep and K-Means) and one customized method. With the customized method, there was utilization of mean values of sperm velocity and linearity as thresholds for direct assignment of motile spermatozoa into four SPs. Regardless of approach for identifying SPs, sperm quality, as determined using flow cytometry, was correlated particularly with the subpopulation (SP) of fast and linear spermatozoa immediately after thawing and with the SP of fast and nonlinear spermatozoa before freezing and 3 h after thawing. Furthermore, there was a positive correlation between proportion of spermatozoa with fast and nonlinear movements before freezing and bull non-return to estrous rates. These results indicate that with different sperm SPs, there are different biological implications which can be evaluated to gain useful information concerning semen quality as determined using flow cytometry and fertility. Furthermore, determining SPs by assigning motile spermatozoa into clusters based on a combination of "below and "above" threshold values for sperm velocity and linearity might be considered a practical alternative to otherwise intricate clustering procedures.

Assessments of sperm quality integrating morphology, swimming patterns, bioenergetics and cell signalling

Spermatozoa are diverse in form and function and these differences impact on their fertilizing capacity. Because of considerable inter-male and inter-species differences in sperm traits, assessments of sperm quality demand that we consider variations at different levels. We should thus pay attention not only to average values but also intra- and inter-sperm population variations and subpopulation structure. Sperm shape and size evolve in reponse to postcopulatory sexual selection. Assessments of morphological variation, with conventional microscopy or with computer-assisted systems, should bear this in mind. In rodents sperm head shape is asymmetric so it requires more complex tools, such as geometric morphometrics. Sperm function also evolves under postcopulatory sexual selection and this could be used as a basis to assess sperm performance. Sperm cells swim actively to overcome barriers in the female tract and develop a peculiar motility pattern in the final stages prior to and during fertilization. Both types of movement can be analyzed by computer-assisted microscopy systems. Sperm have high energetic demands for cell homeostasis, motility, and signalling. Bioenergetics can be analyzed by various means, including extracellular flux analyses to characterize glycolysis and mitochondrial respiration. Finally, cell signalling during capacitation has received much attention and can be assessed by microscopy (conventional or computer-assisted) or flow cytometry. Recent advances in image-flow cytometry affords analyses of high cell numbers with spatial localization of subcellular changes, which will have a big impact in the development of functional tests for the andrology clinic and in sperm preservation and use in artificial insemination.

Artificial intelligence in reproductive medicine

Artificial intelligence (AI) has experienced rapid growth over the past few years, moving from the experimental to the implementation phase in various fields, including medicine. Advances in learning algorithms and theories, the availability of large datasets and improvements in computing power have contributed to breakthroughs in current AI applications. Machine learning (ML), a subset of AI, allows computers to detect patterns from large complex datasets automatically and uses these patterns to make predictions. AI is proving to be increasingly applicable to healthcare, and multiple machine learning techniques have been used to improve the performance of assisted reproductive technology (ART). Despite various challenges, the integration of AI and reproductive medicine is bound to give an essential direction to medical development in the future. In this review, we discuss the basic aspects of AI and machine learning, and we address the applications, potential limitations and challenges of AI. We also highlight the prospects and future directions in the context of reproductive medicine.

An update on boar semen assessments by flow cytometry and CASA

In the quest for predicting fertility of an individual, enhancing semen handling, dilution and storage protocols, and understanding the impact of environment and, andrologists have changed their approaches to semen analysis. The technologies used today are fast developing and readily implemented in research. Semen is one of a few naturally occurring monocellular suspensions, so sperm function analysis by flow cytometry (FC) and utilization of fluorochromes is an ideal technique for high throughput, objective and accurate analysis. The complementary use of microscopical assessments by Computer-Assisted Semen Analysis (CASA), where sperm cell parameters can be objectively assessed is equally important. The objectivity and repeatability of these techniques have driven research on the function, identification of heterogeneity and fertility of the ejaculate. The wealth of knowledge obtained from the application of these powerful methods has changed our view of the spermatozoon. Although there is some application of these methods in the industry producing boar semen for artificial insemination (AI) and to eliminate sires of sub-standard semen quality, uptake of advanced methods is still slow. Instruments are becoming cheaper and technically more user friendly. Standardization of methodology and optimization of instrument settings is important for full implementation of these systems, including comparison between labs. This review provides an update on two technologies: flow cytometry and CASA for objective analysis of boar semen quality.