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This study was designed to analyze the sperm kinematic and morphometric subpopulations in the different fractions of the ejaculate in normozoospermic men. Ejaculates from eight normozoospermic men were collected by masturbation in three fractions after 3-5 days of sexual abstinence. Analyses of sperm motility by computer-assisted sperm analysis （CASA-Mot）, and of sperm morphometry by computer-assisted sperm morphometry analysis （CASA-Morph） using fluorescence were performed. Clustering and discriminant procedures were performed to identify sperm subpopulations in the kinematic and morphometric data obtained. Clustering procedures resulted in the classification of spermatozoa into three kinematic subpopulations （slow with low ALH [35.6% of all motile spermatozoa], with circular trajectories [32.0%], and rapid with high ALH [32.4%]）, and three morphometric subpopulations （large-round [33.9% of all spermatozoa], elongated [32.0%], and small [34.10%]）. The distribution of kinematic sperm subpopulations was different among ejaculate fractions （P 〈 0.001）, with higher percentages of spermatozoa exhibiting slow movements with low ALH in the second and third portions, and with a more homogeneous distribution of kinematic sperm subpopulations in the first portion. The distribution of morphometric sperm subpopulations was also different among ejaculate fractions （P〈 0.001）, with more elongated spermatozoa in the first, and of small spermatozoa in the third, portion. It is concluded that important variations in the distribution of kinematic and morphometric sperm subpopulations exist between ejaculate fractions, with possible functional implications.

In this study, the quality of frozen bull semen was evaluated with the proAKAP4 level test. Sixty straws of frozen bull semen from various batches (n = 30) belonging to six bulls were used in the current study. The frozen bull semen samples were analysed in terms of proAKAP4 levels, sperm morphology and sperm movement parameters at hour 0 and hour 3 after thawing. The semen samples were divided into three groups according to the proAKAP4 levels: low concentration (<25 ng/10x106 spermatozoa), moderate concentration (25 to 39 ng/10x106 spermatozoa) and high concentration (≥40 ng/10x106 spermatozoa). A positive correlation was found between the proAKAP4 level and total motility (TM3), progressive motility (PM3), VSL3 and VCL3 values obtained after the third‐hour thermoresistance test (p < .05). There was a negative correlation between the percentage of sperm abnormal tail and the proAKAP4 level (p < .01). In addition, it was observed that the semen samples with proAKAP4 concentrations of 25 ng/106 spermatozoa and higher preserved the TM3 and PM3 motility characteristics. In conclusion, the proAKAP4 has the potential to become a biomarker protein to evaluate in the quality analysis of frozen‐thawed semen.

For sperm analysis, important inter‐laboratory variations have been observed in manual analyses. In this study, a computer‐aided sperm analysis (CASA) system was assessed versus manual technique, and specific software modifications were operated to fit the David's classification already used in the laboratory. Four parameters were studied (concentration, motility, vitality and morphology), and at least 30 semen samples from 30 different patients have been tested. Manual and automated analyses were compared using a least‐squares regression line analysis, Student's t test, Bland–Altman plots and Passing–Bablok regressions. Repeatability was also assessed, and coefficients of variation (CV) were calculated. Both manual and automated methods gave similar results for sperm concentration (n = 150), motility (n = 30), vitality (n = 90) and morphology (n = 90). Repeatability always showed a decrease in the CV with automated analysis; for example in normal range of sperm values, CV for manual and CASA analyses were, respectively, 9.0% versus 4.4% for sperm concentration, 5.2% versus 4.1% for motility, 7.3% versus 4.2% for vitality and 11.4% versus 4.1% for morphology. All parameters were comparable between automated and manual analysis, and repeatability measures confirm the more reliable values of the SCA compared to those of manual analysis.

Current semen analysis still commonly depends on a manual microscopy method in clinical laboratories worldwide. However, some of the major disadvantages of this technique are that it is labour‐intensive, subjective, laboratory‐based and time‐consuming. Although computer‐assisted semen analysers (CASAs) have enabled partial automation of routine semen analysis, they lack wider acceptance due to their complicated operation. Therefore, the development of an accessible, rapid and standardised method for semen analysis is urgently needed. Here, we describe the development and clinical testing of a novel, automated, artificial intelligence optical microscopic (AIOM)‐based technology, LensHooke™ X1 PRO (X1 PRO), designed for the quantitative measurement of sperm concentration, motility and seminal pH. We observed high degree of correlation in the results of concentration, progressive motility and progressively motile sperm concentration between the X1 PRO semen analyser and manual method using 135 clinical semen samples. In addition, the seminal pH results obtained by X1 PRO and manual methods were comparable (p = .12). In summary, our results showed that new X1 PRO semen analyser is a reliable diagnostic tool for routine semen analysis providing clinically acceptable results based on World Health Organization (WHO) 5th Edition guidelines.

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.

Background The performance evaluation of each computer‐assisted sperm analysis (CASA) system may provide a basis for the interpretation of clinical results and further improvement of the CASA system. Methods The accuracy of the GSA‐810 CASA system was evaluated by detecting latex bead quality control products. The precision of sperm concentration, morphology, and percentages of progressively motile sperm (PR) were evaluated by coefficient of variation (CV). Three samples with sperm concentration of about 100 × 106/mL were diluted to evaluate the linear range. Results The detection values of latex beads were within the range of target values. The CVs of sperm concentration and PR were significantly and negatively correlated with sperm concentration (r = −0.561, p = 0.001) and PR value (r = −0.621, p < 0.001), respectively. The R2 values of the linear range of sperm concentration were ≥0.99. There was no significant difference in sperm motility and PR within 1–10 min at 36.5°C ± 0.5°C. The coincidence rates of sperm morphology and sperm head morphology for 36 semen samples analyzed by the GSA‐810 system and manual method were 99.40% and 99.67%, respectively. The CVs of the percentage of sperm with abnormal morphology and percentage of sperm with abnormal head morphology were less than 5%. Conclusion The GSA‐810 system can accurately analyze normal semen samples, but the repeatability of the results is poor for oligozoospermia and asthenozoospermia samples. The future CASA system for analyzing sperm morphology should focus on recognizing the middle and tail segments of a spermatozoon. The GSA‐810 system can accurately detect sperm concentration in semen samples with sperm concentrations in the range of (2–100) × 106/mL. Semen samples with a sperm concentration between 50 × 106/mL and 100 × 106/mL can be directly detected using the GSA‐810 system without dilution. The higher the sperm concentration and PR, the better the repeatability of the detection results.

Purpose Sperm DNA fragmentation (SDF) has recently received attention as a cause of male infertility. However, SDF cannot be fully assessed using conventional semen parameter evaluations alone. Therefore, the authors aimed to elucidate the relationship between SDF and sperm parameters via computer‐assisted sperm analysis (CASA) to improve treatment strategies in reproductive medicine. Methods This retrospective observational study analyzed the relationship between sperm parameters assessed by CASA and SDF values determined by the TUNEL assay in 359 patients who visited the Mie University Hospital for infertility treatment. The methodology involved semen analyses covering concentration, motility, and morphology, followed by SDF quantification using the flow cytometry. Results Statistical analysis revealed significant correlations between SDF and various factors, including age, sexual abstinence period, and specific CASA‐measured parameters. Notably, lower sperm motility rates and abnormal head dimensions were associated with higher SDF values, indicating that these parameters were predictive of SDF. Conclusions This study highlights the importance of sperm motility and head morphology as indicators of SDF, suggesting their usefulness in assessing male fertility. These findings demonstrate the efficacy of detailed sperm analysis, potentially increasing the success rate of assisted reproductive technologies by improving sperm selection criteria. This study investigates the relationship between sperm DNA fragmentation (SDF) and conventional sperm parameters using computer‐assisted sperm analysis (CASA) in a bid to enhance fertility treatment strategies. Findings indicate significant correlations between SDF and factors such as sperm motility and head morphology, underscoring their predictive value for assessing male fertility and improving assisted reproductive technology outcomes.

Summary Computer‐aided sperm analysis (CASA) system has been accepted and used commonly as a routine semen analysis instrument in hospital clinical laboratories worldwide. However, technicians in clinical laboratories have little informed knowledge about the principles of CASA system and the sources of analysis errors. In this review, we focus on the concept of CASA, the development course of CASA technology, the clinical application of CASA systems and the factors influencing the accuracies of results, such as frame rate, sperm counting chambers affiliated to the CASA system, algorithms and sperm concentration. These factors and lack of internal quality control may result in huge errors of the CASA between systems and laboratories. It is therefore necessary to perform the standardisation and quality control for CASA.

Spermatozoa retrieved from the testis of men with high levels of sperm DNA fragmentation （SDF） in the neat semen tend to have better DNA quality. Given the negative impact of SDF on the outcomes of Assisted Reproductive Technology （ART）, an increased interest has emerged about the use of testicular sperm for intracytoplasmic sperm injection （Testi-ICSI）. In this article, we used a SWOT （strengths, weaknesses, opportunities, and threats） analysis to summarize the advantages and drawbacks of this intervention. The rationale of Testi-ICSI is bypass posttesticular DNA fragmentation caused by oxidative stress during sperm transit through the epididymis. Hence, oocyte fertilization by genomically intact testicular spermatozoa may be optimized, thus increasing the chances of creating a normal embryonic genome and the likelihood of achieving a live birth, as recently demonstrated in men with high SDF. However, there is still limited evidence as regards the clinical efficacy of Testi-ICSI, thus creating opportunities for further confirmatory clinical research as well as investigation of Testi-ICSI in clinical scenarios other than high SDF. Furthermore, Testi-ICSI can be compared to other laboratory preparation methods for deselecting sperm with damaged DNA. At present, the available literature supports the use of testicular sperm when performing ICSI in infertile couples whose male partners have posttesticular SDF. Due to inherent risks of sperm retrieval, Testi-ICSI should be offered when less invasive treatments for alleviating DNA damage have failed. A call for continuous monitoring is nonetheless required concerning the health of generated offspring and the potential complications of sperm retrieval.

The aim of this study was to compare the sperm nuclear and acrosomal morphometry of three species of domestic artiodactyls; cattle （Bos taurus）, sheep （Ovis aries）, and pigs （Sus scrofa）. Semen smears of twenty ejaculates from each species were fixed and labeled with a propidium iodide-Pisum sativum agglutinin （PI/PSA） combination. Digital images of the sperm nucleus, acrosome, and whole sperm head were captured and analyzed. The use of the PI/PSA combination and CASA-Morph fluorescence-based method allowed the capture, morphometric analysis, and differentiation of most sperm nuclei, acrosomes and whole heads, and the assessment of acrosomal integrity with a high precision in the three species studied. For the size of the head and nuclear area, the relationship between the three species may be summarized as bull 〉 ram 〉 boar. However, for the other morphometric parameters （length, width, and perimeter）, there were differences in the relationships between species for sperm nuclei and whole sperm heads. Bull sperm acrosomes were clearly smaller than those in the other species studied and covered a smaller proportion of the sperm head. The acrosomal morphology, small in the bull, large and broad in the sheep, and large, long, and with a pronounced equatorial segment curve in the boar, was species-characteristic. It was concluded that there are clear variations in the size and shape of the sperm head components between the three species studied, the acrosome being the structure showing the most variability, allowing a clear distinction of the spermatozoa of each species.