Automated Semen Analysis Research Articles

O-308 Is AI the future of sperm quality assessment? A comparative study of AI-enhanced and conventional semen analysis systems

Abstract Study question How does the accuracy of an artificial intelligence (AI)-enhanced semen analysis system compare to conventional semi-automated methods when assessing semen quality? Summary answer Compared to conventional semi-automated methods for sperm quality assessment, the AI-enhanced system tends to overestimate progressive sperm motility and normal sperm morphology. What is known already Male factor infertility, specifically poor sperm quality, accounts for over 40% of all infertility cases. Accurate semen analysis is thus a critical step in guiding appropriate treatment strategies in male reproductive health. Past decades have witnessed the development of semi-automated systems for semen analysis, overcoming the limitations of traditional microscopy. While these systems offer precise data on kinetics and concentration, manual intervention remains necessary for assessing certain parameters, potentially affecting reproducibility. AI-based systems have been recently introduced into clinical practice, promising more objective and standardized analysis. Yet, the extent to which these methods surpass conventional approaches remains to be established. Study design, size, duration This is a single-centre, prospective, consecutive, paired study, conducted from February to September 2022. The study included 84 sperm samples from patients undergoing medically assisted reproduction. Participants/materials, setting, methods All sperm samples were analyzed using the AI-enhanced automated system (LENSHooke X1 Pro, Bonraybio®, Fertil Ibérica) and conventional methods: CASA semi-automatized device (ISAS, Proiser), Diff-Quik staining for manual morphology assessment, and pH test strips. We measured and compared several semen parameters, including morphology (% normal sperm), concentration (million/mL), motility (% progressive, % non-progressive, % total motility), and pH, using both approaches. Spearman and Kruskal-Wallis tests were used for statistical analyses. Main results and the role of chance We observed significant differences among several semen parameters when comparing the AI-enhanced system and conventional approaches. Mean normal sperm morphology, as assessed by the AI-enhanced automated device, was significantly higher than that evaluated by conventional microscopy (4.62% versus 3.07%, p < 0.00001). We also observed significant differences for motility and pH parameters (57.98 versus 25.66, p = 0.0001 and 7.86 versus 8.38, p = 0.0001, respectively). Correlations between variables assessed using both methods also varied. Sperm concentration showed a strong correlation between the AI-enhanced and conventional systems (Spearmann’s Rho=0.828), however a weak correlation was observed for total and progressive motility, as well as the percent of immotile sperm (69.54% versus 28.98% R2=0.541; 57.98% versus 25.66% R2=0.566, and 30.45% versus 47.12%, R2=0.541, respectively). There was no significant correlation for non-progressive motility between the two methods (6.53% versus 11.60%, R2=0.157). Limitations, reasons for caution This study exclusively compared two analysis methods among numerous AI-enhanced systems available on the market. Given the rapidly evolving landscape of AI technologies, caution is warranted when generalizing these findings to other AI models, as their performance may vary. Wider implications of the findings Observed differences between the AI-enhanced system and conventional methods require careful consideration. While fully automated semen analysis systems are designed to reduce subjectivity, extensive comparative research is crucial. A comprehensive market assessment will be essential for safeguarding patient treatment outcomes and advancing AI capabilities in semen analysis. Trial registration number not applicable

Sperm YOLOv8E-TrackEVD: A Novel Approach for Sperm Detection and Tracking.

Male infertility is a global health issue, with 40-50% attributed to sperm abnormalities. The subjectivity and irreproducibility of existing detection methods pose challenges to sperm assessment, making the design of automated semen analysis algorithms crucial for enhancing the reliability of sperm evaluations. This paper proposes a comprehensive sperm tracking algorithm (Sperm YOLOv8E-TrackEVD) that combines an enhanced YOLOv8 small object detection algorithm (SpermYOLOv8-E) with an improved DeepOCSORT tracking algorithm (SpermTrack-EVD) to detect human sperm in a microscopic field of view and track healthy sperm in a sample in a short period effectively. Firstly, we trained the improved YOLOv8 model on the VISEM-Tracking dataset for accurate sperm detection. To enhance the detection of small sperm objects, we introduced an attention mechanism, added a small object detection layer, and integrated the SPDConv and Detect_DyHead modules. Furthermore, we used a new distance metric method and chose IoU loss calculation. Ultimately, we achieved a 1.3% increase in precision, a 1.4% increase in recall rate, and a 2.0% improvement in mAP@0.5:0.95. We applied SpermYOLOv8-E combined with SpermTrack-EVD for sperm tracking. On the VISEM-Tracking dataset, we achieved 74.303% HOTA and 71.167% MOTA. These results show the effectiveness of the designed Sperm YOLOv8E-TrackEVD approach in sperm tracking scenarios.

The Clinical Embryologist: Past, Present and Future Challenges

Embryologist is an essential part of infertility care defined as a highly skilled and well-trained person who can work in teamwork to execute continuous tasks with near-zero error and pay attention to detail with excellent clinical judgment. At the very beginning, embryologist’s routine daily tasks were quite simple including processing the sperm and eggs for natural insemination. Following that, advanced infertility treatment emerged quickly including intracytoplasmic sperm injection (ICSI), vitrification-warming, embryo shipping, intracytoplasmic morphologically sperm injection (IMSI), as well as trophectoderm biopsy as a source of chromosomal copy number testing or monogenic disorders analysis. Collectively, the implementation of such improved treatments renders complexity in the IVF laboratory that could be simplified in the future. Apparently, the implementation of advanced technology in the field of IVF nowadays has two main purposes. The first is to improve the IVF success rate including finding precise markers for embryo selection such as genomics, proteomics, and metabolomics fingerprint and images-based artificial intelligence algorithm for embryo selection. The second is to standardize or simplify routine daily tasks in the embryology laboratory by implementing automated software such as for laboratory quality control maintenance, a microfluidic system that allows standardization of handling gametes, micro-robotic for immobilizing sperm for ICSI, fully automated semen analysis, electronic tagging of laboratory devices to improve traceability. All such automated systems will serve as advanced clinical decision tools to boost IVF success rate and infertility care quality. An elevated automated system in the future in an embryology laboratory would impact the clinical embryologist in terms of reduced quantity and conversely, increased qualities of highly scientific embryologists with proper education. Embryologist roles may change from conventional routine daily tasks to well-trained and experienced embryologists who are able to scientifically evaluate the effectiveness of certain approaches or potential clinical use of such implementation in their clinical laboratory setting.

P–011 Automated sperm morphology assessment using artificial intelligence technology

Abstract Study question Can LensHooke X1 PRO semen analyzer be used to evaluate sperm morphology in men with infertility? Summary answer Morphology results generated by X1 PRO are highly reliable when normal sperm forms are ≥4% and therefore they can be reported in such cases . What is known already Most laboratories rely on manual evaluation of sperm morphology smears, which is a time-consuming procedure and its results are subjected to a relatively high variability. However, in recent years the computer-assisted semen analyzers are being increasingly used to evaluate sperm morphology. The X1 PRO semen quality analyzer was designed for in vitro diagnostic use to analyze sperm concentration, total, progressive and non-progressive motility as well as sperm morphology based on WHO 5th edition criteria. Evaluation of sperm morphology using X1 PRO based on AIOM (Artificial Intelligence Optical Microscopic)-based technology requires no fixation steps or staining unlike the manual method. Study design, size, duration This cross-sectional study used 31 semen samples from 8 normozoospermic healthy volunteers and 5 infertile men with a minimum abstinence period between 2 - 3 days. While the 8 healthy semen donors produced a total of 26 ejaculates, which were split into 88 aliquots, the 5 infertile patients produced 5 ejaculates that were split into 13 aliquots. Participants/materials, setting, methods A total of 101 aliquots were prepared from the native semen samples either by dilution or concentration using seminal plasma of the respective donors. Automated semen analysis was performed by the X1 PRO semen analyzer and the results of sperm morphology were compared with manual morphology results using Diff-Quik staining. Statistical analysis was carried out to calculate the positive predictive value (PPV) and negative predictive value (NPV) of X1 PRO semen analyzer. Main results and the role of chance The X1 PRO sperm morphology results show a weak non-significant (P = 0.2441) correlation (r = 0.119) with the manual results. However, X1 PRO demonstrated a high PPV (97.7%) and a low NPV (9.1%) for correct assessment of sperm morphology (≥4%) when compared to manual results. Due to its high PPV, laboratories can report the morphology results generated by X1 PRO in all such cases when normal sperm forms are ≥4%. However, a manual evaluation is necessary in patients with abnormal morphology (<4%). Limitations, reasons for caution One of the limitation of this study is that X1 PRO morphology values did not correlate with manual results. The low NPV seen in our study is due to the inclusion of very few samples with abnormal sperm forms (<4%) in the analysis. Wider implications of the findings: The X1 PRO’s combination of speed, ease of use, accuracy and portability makes it a good choice of device for small medical offices to large IVF centers. High PPV of X1 PRO allows it to correctly identify normal sperm forms for diagnostic use. Trial registration number 18–771

P–105 Clinical validation of mojo AISA, an artificial intelligence robotic CASA system

Abstract Study question Can a CASA system based on Artificial Intelligence perform as well as manual semen assessment, within the WHO error margins? Summary answer The AI-based CASA systems that mimic high quality assessments show great potential for reducing clinical workloads while increasing treatment efficacy. What is known already The field of male-factor fertility investigation is still lacking an automated semen analysis system that can be widely clinically adopted. By leveraging state-of-the-art robotics and Artificial Intelligence (AI), it was possible to build mojo AISA which is an AI and robotic platform designed according to WHO recommendation for semen analysis. This system is based on AI software with a unique convolutional neural network (CNN) that detects and measures sperm concentration and motility while ruling out unwanted cells and debris in raw samples. Study design, size, duration This study presents and validates the mojo AISA device. A total of 60 patient samples at ANOVA Karolinska University Hospital were collected and results from manual assessment were compared to mojo AISA for concentration and motility. Semen samples were assessed manually (WHO 2010) and concurrently with Mojo AISA. Manual measurements ranged from 1–206M/ml. This study lasted from May 2020 to December 2020 following informed consent and ethics committee practices of ANOVA. Participants/materials, setting, methods Sample preparation protocol for mojo AISA consisted of placing two 10ul drops and covering with two 22x22mm coverslip. Manual assessment followed ANOVA EQA procedures akin to the WHO. A CNN was trained using videos captured with mojo AISA as input data. Images were annotated to form a validation set by which the AI was trained. To account for sampling error, videos of Hamilton Thorne Accubeads+ were captured using mojo AISA and the mojo counting chambers. Main results and the role of chance Comparing the concentration measured by mojo AISA with the known value for each microbead, results are in agreement of 86%, within the confidence interval of the microbeads. The mean relative error was 6.7% and maximum error was 11%. Therefore, Accubeads+ validation proved no observational error regarding the use of mojo AISA microscope. As for comparing mojo AISA to manual assessment for concentration, Pearson (Spearman) correlation was 0.95 (0.97). The mean relative error was 24.8% and maximum relative error was 71.1%, where 90% of samples were below 50% error. By looking at the concentration range between 10 and 20 M/ml, mojo AISA displayed a mean error of 18.5%. For motility, as comparing mojo AISA to manual assessment, a result of 35.4% mean relative error was obtained. To conclude, mojo’s robotic solution shows promise for clinical practice as the AI continues to improve. In 6 months, sperm concentration correlation improved by 3-fold. Next, the AI will be further clinically trained for low concentration. Limitations, reasons for caution mojo AISA requires further development, especially for very low concentration ranges, below 5M/ml, due to high sensibility to false positive detections. The same applies to post-vasectomy samples. Additionally, the necessity to compute the motility of each sperm scales poorly with high concentration generating a poor experience for high volume clinics. Wider implications of the findings: Automation is crucial in several industries. It enables fertility clinics & andrologists to standardize male factor infertility measurements (if paired with widespread standardization of protocols for automation) while enabling them to put more focus on demanding activities of their profession and removes human biases of inter-laboratory performance. Trial registration number Not applicable

Standardized Laboratory Procedures, Quality Control and Quality Assurance Are Key Requirements for Accurate Semen Analysis in the Evaluation of Infertile Male.

Semen analysis is a basic test for evaluating male fertility potential, as it plays an essential role in driving the future management and treatment of infertility in couples. Manual semen analysis includes the evaluation of both macroscopic and microscopic parameters, whereas automated semen analysis is conducted through a computer-aided sperm analysis system and can include additional parameters that are not evaluated by manual analysis. Both quality control (QC) and quality assurance (QA) are important to ensure reproducible results for semen analysis, and represent fundamental checks and balances of all stages (pre-analytical, analytical, and post-analytical) of semen analysis. To ensure accuracy and precision, the laboratory technicians' performance should be evaluated biannually. This narrative review aims to describe standardized laboratory procedures for an accurate assessment of semen parameters that incorporate both QC and QA practices.

Estudio comparativo de los parámetros del seminograma en una población de varones subfértiles consumidores de marihuana

IntroductionThe aim of this work, is to find the prevalence of marijuana use in a subfertile population, and to carry out a comparative prospective study of the seminogram parameters of a group of subfertile patients, who are habitual marijuana users, versus a group of nested control cases of non-users. Material and methods2320 men were studied, 70% of patients from Primary Care Centers and 30% from hospital outpatient consultations. The analysis of sperm concentration and motility was carried out with a SCA® automated semen analyzer. The comparative study has been carried out, by applying a novel statistical methodology called «case-control nested», which is a hybrid case-control variation. ResultsThe prevalence of marijuana use has been calculated in a population of subfertile men. Statistical analysis of the semen values of the group of marijuana users versus the control group shows that there are no significant differences between them. ConclusionsIn the group of subfertile men studied, a prevalence of 10.26% of habitual marijuana users was observed. In our results, no significant differences were observed between the two groups studied, so we are considering the additional performance of new sperm functionalism tests, to explain the subfertility that has been observed in some of these patients who use marijuana, who present a normal seminogram.

An Image Processing Algorithm for an Automated Smartphone-based Semen Analyzer

This paper deals with the implementation of an image processing algorithm for an automated semen analyzer. The analysis of semen is the most important diagnostic tool in the initial investigation of male fertility. Semen analysis is best performed in a specialized laboratory with extensive experience in using the approved methods of the World Health Organization. Semen analysis in a specialized laboratory is labor-intensive, expensive, and time-consuming, and the accuracy depends on staff experience only. So, the use of image processing technology becomes very necessary in order to overcome these disadvantages. In this study, to improve the procedures involved in motion detection and prediction algorithms, we study Kalman filter-based object motion prediction. Furthermore, to improve accuracy and quality in the rate of object detection, the visual background extractor (ViBe) is employed. The experimental results of the proposed technique are evaluated and validated for performance and quality analysis from video data based on visual experiments. The experimental result achieved low root mean square error (RMSE) and relative root mean square error (RMSE%) values, demonstrating the effectiveness of the proposed technique for detecting and tracking sperm. The combination of two image processing approaches is proven to be effective in analyzing sperm condition.

The Effectiveness of LenshookeTM Semen Quality Analyzer X1 Pro for Human Semen Analysis

Background: LenshookeTM Semen Quality Analyzer (SQA) X1 Pro is an automated semen analysis. The accuracy of LenshookeTM SQA X1 Pro has never been analyzed with World Health Organization (WHO) standard method. Aim: This study aims to examine whether the LenshookeTM SQA X1 Pro method provides reliable results according to the WHO standard method. Methods: This study was a laboratory analytic observational study using 60 patients in Andrology clinic of Dr. Soetomo Hospital. The concentration, progressive motility (PR), total motile sperm count (TMSC), and morphology results of the LenshookeTM SQA X1 Pro and standard method were analyzed statistically using correlation, Bland Altman, and diagnostic test. Results: Significant correlation between two methods were found in all parameters (concentration: r = 0,970; PR: r = 0,781; TMSC: r = 0,952; morphology: r = 0,568). The mean difference for concentration, PR, TMSC, and morphology between the two examination methods were 1,165 million/ml, 7,05%, 7,584 million/ejaculate, and 2,25%. However, it found that the correlation and agreement were weaker in sample with low number of spermatozoa per high power field. The results revealed a sensitivity of 100%, 81%, and 59% for oligozoospermia, astenozoospermia, and teratozoospermia, respectively. The specificities were shown to be 100%, 74%, and 100% for oligozoospermia, astenozoospermia, and teratozoospermia, respectively. Conclusion: The LenshookeTM SQA X1 Pro gives a reliable result for determining oligozoospermia and asthenozoospermia, but in the situation that the clinicians need the accurate data, standard method should be used.

Automated semen analysis by SQA Vision® versus the manual approach-A prospective double-blind study.

Next to clinical investigations, the evaluation of male fertility relies mainly on detailed sperm analyses, for example, cell counting, motility, cell morphology and vitality testing. The manual creation of a spermiogram is time- and material-consuming. Therefore, reliable high-throughput systems that may be substituted for manual methods are urgently needed. The present study aimed to compare conventional sperm analysis performed as per WHO 5th guidelines and semen analysis performed with the SQA Vision® machine. SQA Vision® is a commercial device for automated sperm analysis. Data obtained independently by both methods were compared by statistical analyses using Bland-Altman plots and Passing-Bablok regression analyses. The analyses revealed that the results for sperm concentration and total motility were comparable. The agreement for progressive motility was poor, and there were clear deviations in the determination of normal sperm morphology. Passing-Bablok regression analyses and the consideration of the 95% confidence intervals pointed out systematic and proportional differences between the manual semen analysis and the automated approach.

029 Rooster sperm plasma membrane protein and phospholipid organization and reorganization attributed to cooling and cryopreservation

Cholesterol to phospholipid ratio is used as a representation for membrane fluidity, and predictor of cryopreservation success but results are not consistent across species and ignore the impact of membrane proteins. Therefore, this research explored the modulation of membrane fluidity and protein organization of rooster sperm during cooling and cryopreservation using the fluorescent stains Merocyanine 540 (phospholipid order) and Rhodamine 640 (protein order). Rooster semen samples (3 roosters and breeds per pool; 4 pools total) were diluted in Lakes Low Temperature (LLT) and Sasaki diluent and cooled to 5 °C over 30 min (Step 1). The samples were then diluted with the penetrating cryoprotectants (CPA) glycerol (LLT) or methylacetamide (Sasaki), equilibrated for 30 min (Step 2), loaded into straws and cryopreserved. The cryopreservation and thawing (Step 3) was performed using the optimized procedures for each diluent. Computer automated semen analysis (CASA) was used to analyze motility characteristics and flow cytometry was used to analyze plasma membrane phospholipid, protein organization and plasma membrane integrity (PMI) at each step. Percent values from CASA and flow cytometry fluorescent medians (FM) were transformed using arcsine and Box–Cox, respectively. The GLM ANOVA was used to detect differences in motility characteristics and membrane organization and included the effects of cryopreservation step and rooster semen pool. In the total motility analyses cryopreservation diluent/CPA was a significant ( P P P P P Source of funding: USDA-ARS-NCGRP National Animal Germplasm Program. Conflict of interest: None declared. phil.purdy@ars.usda.gov

Automated semen analysis…the new gold standard? a comprehensive study comparing manual and automated semen analysis

Automated semen analysis…the new gold standard? a comprehensive study comparing manual and automated semen analysis

Validation and usefulness of the Sperm Quality Analyzer V equine for equine semen analysis

Routine semen analysis includes evaluation of concentration combined with seminal volume, morphology and motility. Subjective analysis of these parameters is known to be inaccurate, imprecise and subject to variability. Automated semen analysis could lead to an increased standardization in and between laboratories but for that to happen automated devices need to be validated. A new device, the sperm quality analyzer V equine (SQA-Ve) version 1.00.43, was evaluated for its repeatability and agreement with light microscopy (LM), for raw and extended equine semen. Results were compared with computer assisted sperm analysis (CASA), which was also tested for its repeatability and agreement with LM. The SQA-Ve showed a good repeatability and fine agreement for assessing sperm concentration of raw semen based on scatter and Bland-Altman plots. This was in contrast with the motility parameters, which had a low repeatability. Morphology assessment with SQA-Ve was poorly repeatable as well as in poor agreement with LM. For extended semen, the findings were comparable. The SQA-Ve did well for concentration, whereas for the motility parameters repeatability was only just acceptable, with no agreement with LM. This sharply contrasted the CASA findings that were highly repeatable and almost in perfect agreement with LM. Based on these findings, the tested version of the SQA-Ve is insufficiently accurate to be used for analyzing raw or extended equine semen.

Compact and Light-Weight Automated Semen Analysis Platform Using Lensfree on-Chip Microscopy

We demonstrate a compact and lightweight platform to conduct automated semen analysis using a lensfree on-chip microscope. This holographic on-chip imaging platform weighs ∼46 g, measures ∼4.2 × 4.2 × 5.8 cm, and does not require any lenses, lasers or other bulky optical components to achieve phase and amplitude imaging of sperms over ∼24 mm(2) field-of-view with an effective numerical aperture of ∼0.2. Using this wide-field lensfree on-chip microscope, semen samples are imaged for ∼10 s, capturing a total of ∼20 holographic frames. Digital subtraction of these consecutive lensfree frames, followed by appropriate processing of the reconstructed images, enables automated quantification of the count, the speed and the dynamic trajectories of motile sperms, while summation of the same frames permits counting of immotile sperms. Such a compact and lightweight automated semen analysis platform running on a wide-field lensfree on-chip microscope could be especially important for fertility clinics, personal male fertility tests, as well as for field use in veterinary medicine such as in stud farming and animal breeding applications.

Implications of the pH and temperature of diluted, cooled boar semen on fresh and frozen-thawed sperm motility characteristics

Boar semen is typically collected, diluted and cooled for AI use over numerous days, or frozen immediately after shipping to capable laboratories. The storage temperature and pH of the diluted, cooled boar semen could influence the fertility of boar sperm. Therefore, the purpose of this study was to determine the effects of pH and storage temperature on fresh and frozen-thawed boar sperm motility end points. Semen samples (n = 199) were collected, diluted, cooled and shipped overnight to the National Animal Germplasm Program laboratory for freezing and analysis from four boar stud facilities. The temperature, pH and motility characteristics, determined using computer automated semen analysis, were measured at arrival. Samples were then cryopreserved and post-thaw motility determined. The commercial stud was a significant source of variation for mean semen temperature and pH, as well as total and progressive motility, and numerous other sperm motility characteristics. Based on multiple regression analysis, pH was not a significant source of variation for fresh or frozen-thawed boar sperm motility end points. However, significant models were derived which demonstrated that storage temperature, boar, and the commercial stud influenced sperm motility end points and the potential success for surviving cryopreservation. We inferred that maintaining cooled boar semen at approximately 16 °C during storage will result in higher fresh and frozen-thawed boar sperm quality, which should result in greater fertility.

The Cellsoft computerized Semen Analysis System. II. on the Optimalization of running Conditions concerning Gray Scale and cell size Range/Das “CellSoft computerized semen analysis system”. II. Zur Optimierung der Grauwert-Zuordnung sowie des Einstellungs

The CellSoft automated semen analysis system was studied concerning the effect of gray scale (GSc) variation on cell motion parameters and to establish an appropriate setting for human spermatozoal sizes (PixMin and PixMax) based on the cell's instant velocities (InsVels). GSc could be set within a range from "optimum" till +10 units without, except for curvilinear velocity, the CellSoft generated sperm measures being altered (p greater than 0.05). The aspect of a sample specific GSc setting according to certain criteria is stressed. Considering the area of immobilized spermatozoa (at GSc + 20) and of motile cells with low InsVel, PixMin should be set at 3 pixels. Correspondingly, the InsVel determined setting for PixMax (at a maximum velocity threshold set at 200 microns/sec.) was 28 pixels. A final recommendation on the setting for cell sizes can, however, only be determined in considering sizes of nonsperm seminal elements and in studying the appropriate setting for the maximum velocity threshold.

The post-thaw quality of ram sperm held for 0 to 48 h at 5 °C prior to cryopreservation

The effects of holding diluted ram semen at 5 °C for up to 48 h prior to cryopreservation were investigated. Semen from six rams was collected by electro-ejaculation in the autumn and again from six different rams in the spring. The sperm concentration and motility were determined using spectrophotometry and computerized automated semen analysis, respectively. Samples were diluted at 23 °C to 400 × 10 6 cells/ml in a one-step Tris–egg yolk–glycerol (5%, v/v) media, cooled to 5 °C over 2 h and maintained at 5 °C for the duration of the experiments. Aliquots were loaded into 0.5 ml French straws at 0, 24 or 48 h after cooling, frozen in liquid nitrogen vapor for 12–13 min, 4.5 cm above the liquid nitrogen, and plunged into liquid nitrogen for storage. After thawing, autumn samples frozen after 0, 24, or 48 h of storage exhibited similar percentages of motility (29, 31, 36%, respectively), progressively motility (16, 15, 17%, respectively), plasma membrane integrity (28, 35, 29%, respectively) and live acrosome-reacted cells (0.4, 0.6, 0.8%, respectively; P > 0.05). In addition, the quantity of sperm that bound to hen's egg perivitelline membranes after being held at 5 °C for 0, 24, or 48 h was not significantly different when the values were expressed as means of the quantity of sperm (155, 177, 106 sperm, respectively) or as the proportion of sperm inseminated (0.39, 0.49, 0.34, respectively; P > 0.05). Likewise, ram sperm collected in the spring and frozen at 0, 24 and 48 h after cooling had similar ( P > 0.05) total motility (21, 25, 20%, respectively), progressive motility (14, 15, 11%, respectively), plasma membrane integrity (26, 33, 31%, respectively) and live acrosome-reacted cells (3.7, 3.5, 3.2%, respectively; P > 0.05). The 0 h holding time had significantly less sperm bound to a hen's egg perivitelline membrane compared to the 48 h holding time (250 and 470 sperm, respectively) although the 24 h holding time was not different from the 0 or 48 h holding time (281 sperm; P < 0.05) but analysis of the proportion of the total sperm inseminated resulted in no significant differences observed ( P > 0.05). These results indicate that ram sperm can be held at 5 °C for up to 48 h prior to freezing with no injurious effects on motility, membrane integrity, or fertilizing potential as indicated by membrane binding ability.

Effect of plasmin on movement characteristics of ejaculated bull spermatozoa

Proteolytic enzymes appear to have an essential role in multiple phases of mammalian fertilization. Several observations suggest that the plasminogen activator/plasmin system might also play a role in mammalian fertilization. Movement characteristics of bovine sperm incubated with different concentrations of plasmin were investigated using a computer-assisted automated semen analysis system. Sperm were incubated up to 4h in a modified Tyrode’s medium (control) and 0.1, 1, 10 and 100mU/ml of plasmin. The percentage motile sperm was significantly higher at 0h for sperm incubated in 1, 10, and 100mU of plasmin. Relative to sperm incubated in control medium, lateral head displacement (ALH), curvilinear velocity, beat cross frequency, path velocity and straight line velocity (VSL) of sperm treated with 100mU of plasmin for 0h were increased. After 2h of incubation, sperm treated with 100mU of plasmin showed an increase in ALH, but a decrease in VSL, straightness and linearity. The effect of plasmin on most motility parameters appears to be direct since all these parameters were affected at 0h of incubation. Our results support the notion of hyperactivation of bovine spermatozoa following incubation with different concentrations of plasmin. The present work provides additional information to further characterize motility movement of bovine sperm associated with final preparation for fertilization.

Automated semen analysis: 'zona pellucida preferred' sperm morphometry and straight-line velocity are related to pregnancy rate in subfertile couples.

Standard semen analysis has low objectivity and reproducibility and is not closely related to fertility. We assess the prognostic value of automated measurements of sperm motility and morphology. During 1997-1999, 1191 infertile couples with no known absolute barrier to conception were assessed by conventional semen analysis, and automated measurements of average straight-line velocity (VSL) and the percentage of sperm with characteristics that conform to those of sperm which bind to the zona pellucida of the human oocyte (%Z). During follow-up to 2001, there were 336 natural pregnancies. Only %Z, VSL and female age were independently significantly related to pregnancy rate by Cox regression analysis. Pregnancy rate was higher with above average %Z and VSL, indicating a continuous rather than a threshold relationship. The likelihood of pregnancy within 12 cycles can be evaluated for specific values of %Z, VSL and female age using the Cox regression model. The automated semen measures of sperm morphometry (%Z) and velocity (VSL) are related to pregnancy rates in subfertile couples and should assist clinicians in counselling subfertile patients about their prognosis for a natural pregnancy. Objective automated methods should replace the traditional manual assessments of semen quality.

The rate at which human sperm are immobilized and killed by mild acidity

Objective: To determine the rate at which mild acidity immobilizes and kills human sperm and to evaluate an acidic microbicide, BufferGel, for sperm immobilization. Design: Controlled in vitro study. Setting: An academic research university and hospital andrology lab. Patient(s): Eight volunteer male sperm donors. Intervention(s): Semen samples were treated with hydrochloric acid (HCl) or BufferGel. Main Outcome Measure(s): Sperm motility was measured by using a computerized automated semen analyzer and video microscopy. Sperm membrane permeability and intracellular pH were measured by using fluorescent techniques. Result(s): In semen acidified with HCl to pH 4.0, sperm were rapidly immobilized (within 1 min) and were irreversibly immobilized (killed) within 10 minutes. The speed of immobilization and of killing were both linearly proportional to hydrogen ion activity over a pH range of 7.5–4.0. Across the same range, the intracellular pH of human sperm equilibrated to within 0.5 pH units of extracellular pH within 1–2 minutes. BufferGel immobilized sperm significantly faster than HCl from pH 4.0–6.0. Conclusion(s): Exposure to mild acidity rapidly acidifies the intracellular pH of human sperm and is rapidly spermicidal. BufferGel accelerates acid immobilization of sperm.