Investigation of the Effect of Hafnium Chloride on Sperm Viability and Motility in Normospermic Cases: An In Vitro Study.

INTRODUCTION: Hafnium alloys are employed in medical applications due to their biocompatibility and high corrosion resistance. These alloys have demonstrated osteogenic and antimicrobial activities in surgical implants and have been utilized in the treatment of sarcoma. Additionally, a sensor based on hafnium nanoparticles has been reported for the detection of coronavirus disease 2019. Despite the increasing usage of hafnium, a literature review reveals no studies examining its effects on sperm in both human and animal species. METHODS: Semen samples were analyzed according to the 2010 World Health Organization (WHO) criteria, and 20 normospermic specimens were included in the study. Three groups were formed: control, hafnium chloride 2 mg/mL, and 4 mg/mL. Motility and viability were assessed in all groups at the 20th and 40th minutes. RESULTS: The decrease in viable sperm count was found to be significant in the 2 mg/ml HfCl4 group (difference: 12.73 ± 0.8, p<0.001) and the 4 mg/ml HfCl4 group (difference: 41.72 ± 1.34, p<0.001) compared to the control group. A time-dependent decrease in sperm viability was significant across all groups (difference: 8.93 ± 0.59, p<0.001). The decrease in viable sperm count in the 4 mg/ml HfCl4 group was significant when compared to the 2 mg/ml HfCl4 group (difference: 29 ± 1.27, p<0.001). The decrease in total motile sperm count was observed in both the 2 mg/ml HfCl4 group (difference: 12.80 ± 1.30, p<0.001) and the 4 mg/ml HfCl4 group (difference: 35.63 ± 1.12, p<0.001) compared to the control group. Additionally, the decrease in total motile sperm count in the 4 mg/ml HfCl4 group was significant compared to the 2 mg/ml HfCl4 group (difference: 22.80 ± 1.60, p<0.001). A time-dependent decrease in total motile sperm count was also significant (difference: 6.03 ± 0.49, p<0.001). CONCLUSION: The study determined that hafnium chloride negatively affects sperm motility and viability in vitro. These effects may be due to the presence of an acidic environment. It has been demonstrated that instruments containing this element may pose a potential risk.

Correlation of Sperm DNA Fragmentation Index With Semen Parameters, Lifestyle and Clinical Pregnancy Outcome After Intracytoplasmic Injection.

Objective: This study aimed to measure the correlation of sperm DNA fragmentation with semen parameters, lifestyle, and fertility outcomes after intracytoplasmic injection (ICSI). Materials and methods: The partners who were candidates for ICSI with a history of one In vitro fertilization (IVF) failure or male factor were recruited in the study. Semen parameters including sperm count, motility, and morphology as well as DNA fragmentation index (DFI) (that were divided into 2 groups as high (>15%), and low (≤15%) fragmentation scales) were evaluated either. The correlation of DFI with semen parameters, lifestyle, and clinical pregnancy after ICSI were compared between groups. Results: In 120 included couples, 59 men (49.2%) had DFIs ≤ 15% and 61 (50.8%) cases had DFIs >15%. In the group with higher DFI, abnormal morphology (p=0.010) was higher whereas, progressive motility (p=0.001), total motility (p<0.001), and total count (p<0.001) of sperm were significantly lower. In addition, the DFI was significantly higher in the subgroup of male infertility (0.012). Logistic regression showed that a lower risk of DFI>15% was associated with higher values of progressive motility (OR=0.97, p=0.001), total motility (OR=0.96, p=<0.001), count (OR=0.96, p=<0.001) and even clinical pregnancy (OR=0.27, p=0.011). However, a history of testicular surgery was associated with a higher risk of DFI>15% (OR=3.37, p=0.046). Although no correlation was found between male age and lifestyle components with DFI, the number of embryos was lower in DFI≥15% (p<0.001). Conclusion: DFI provide a clinically important measurement of sperm quality and have an impact on IVF outcomes; however, lifestyle components may not correlate with DFI.

Contraceptive efficacy: Determining the threshold for effective suppression based on sperm concentration, motility, and morphology.

INTRODCTION: Human spermatogenesis is a complex process that transforms spermatogonial stem cells through mitosis and meiosis to spermatozoa. Testosterone is the key regulator of the terminal stages of meiosis, adherence of spermatids to Sertoli cells, and spermiation. Follicle-stimulating hormone (FSH) may be required for early spermatogenesis and is important for maintaining normal spermatogenesis in men. Hormonal contraception suppresses FSH, luteinizing hormone, and intratesticular testosterone concentration, resulting in marked suppression of sperm output. RESULTS: Clinical trials using testosterone alone or testosterone plus progestin demonstrate that sustained suppression of sperm concentration to ≤1 million/mL is sufficient to prevent pregnancy in the female partner. New agents that target spermatogenesis could use this as a target for contraceptive efficacy while others that block sperm function or transport may require a lower threshold. When sperm concentrations are suppressed to such low levels, measurement of sperm motility and morphology is technically difficult and unnecessary. With current data from fertile and infertile men, it is not possible to establish a lower limit of sperm motility or percent normal morphology that equates to the prevention of conception. New compounds that decrease sperm motility or alter sperm morphology may need to demonstrate a complete absence of sperm motility or altered morphology in all spermatozoa in the ejaculate. Sperm function tests may be useful depending on the mechanism of action of each new compound. CONCLUSION: Monitoring of sperm surrogate markers to ensure effective contraception relies on laboratories experienced in semen analyses. The development of at-home tests to assess sperm parameters has progressed rapidly. Some tests have been assessed in clinical trials and approved by regulatory agencies for at-home use for fertility assessment. However, caution must be exercised in using these tests as many have not been rigorously validated against semen parameters measured in laboratories by trained technologists using standardized tests defined in the World Health Organization Semen Manual.

One out of two idiopathic infertile men has pathologic sperm DNA fragmentation values: Potential implications for clinical practice.

OBJECTIVES: To investigate the distribution of sperm DNA fragmentation (SDF) values and their association with clinical and seminal parameters in idiopathic infertile men. DESIGN, PATIENTS, MEASUREMENTS: Data from 3224 primary infertile men (belonging to couples having failed to conceive a pregnancy within 12 months) who underwent a thorough diagnostic work-up were analysed. A SDF value ≥ 30% (according to Sperm Chromatin Structure Assay) was considered pathologic. We excluded: (1) men with genetic abnormalities; (2) men with history of cryptorchidism; (3) men with biochemical hypogonadism; (4) men with clinical varicocele; and (5) men with other possible known aetiological factors. Descriptive statistics and logistic regression analyses were used to describe the whole cohort. RESULTS: Of all, 792 (23%) men with at least one abnormal WHO semen parameter but without any identified aetiologic factor for infertility, were considered as idiopathic infertile men. Of 792, 418 (52.7%) men had SDF ≥30%. Men with pathologic SDF were older (p = .02), had higher Follicle-stimulating hormone (FSH) (p = .04) but lower total testosterone (p = .03) values than those with SDF <30%. The homoeostatic model assessment index for insulin resistance (HOMA-IR) was higher in men with SDF ≥30% (p = .01). Idiopathic infertile men with SDF ≥30% presented with lower sperm concentration (p < .001) and lower progressive sperm motility (p < .01) than those with SDF < 30%. Logistic regression analysis revealed that older age (OR: 1.1, p = .02) and higher HOMA-IR score (OR: 1.8, p = .03) were associated with SDF ≥ 30%, after accounting for FSH and sperm concentration values. CONCLUSIONS: Approximately half of infertile men categorized as idiopathic had pathologic SDF values. Idiopathic infertile men with pathologic SDF showed worse clinical, hormonal and semen parameters than those with normal SDF values. These results suggest that including SDF testing could be clinically relevant over the real-life management work-up of infertile men.

Contemporary Diagnostic Work-Up for Male Infertility: Emphasizing Comprehensive Baseline Assessment.

Infertility is a prevalent issue affecting many couples during their reproductive years, with a significant number facing challenges in conceiving despite regular unprotected intercourse. Male factor infertility (MFI) contributes significantly to these cases, with a significant proportion of men lacking an identifiable etiology. As such, a thorough assessment of MFI has become increasingly vital for personalized management. This position paper from the Andrology team at IRCCS Ospedale San Raffaele emphasizes a comprehensive and individualized approach to MFI work-up, addressing the evolving challenges encountered in clinical practice. Our approach involves a thorough diagnostic work-up to identify the underlying causes of MFI, integrating insights from extensive literature review and our proprietary data. Our data demonstrates that an extensive diagnostic assessment allows us to identify at least one underlying cause of MFI in most infertile men. However, challenges persist in diagnosing less severe phenotypes with unclear etiology. We discuss the importance of individualized MFI work-up and its implications for developing rational therapeutic protocols. Lastly, this paper highlights the necessity for a personalized diagnostic assessment, addressing the daily clinical challenges and emphasizing tailored approaches to try to improve outcomes among couples seeking first medical help for infertility.

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.

Evaluation of structural problems in the application of strict criteria for sperm morphology assessment.

BACKGROUND: The WHO manual for basic semen analysis and ISO 23162 describe sperm morphology assessment as a standard part of semen analysis. Older studies showed a correlation between morphology results and (artificial) conception. In more recent studies this relationship was less apparent and there is more emphasis on sperm morphology as a marker for healthy spermatogenesis (and general male health). Meantime, many laboratories ceased morphology assessment, probably due to unfamiliarity with this paradigmatic shift and to technical difficulties in the assessment, like the interpretation of morphological criteria. OBJECTIVES: The aim of this study was to identify morphological criteria with high variability in results in the Dutch External Quality Control (EQC) program. MATERIAL AND METHODS: Over the period 2015-2020, a total of 72 photos of sperm cells along with dichotomous propositions based on 14 criteria as defined in WHO5 (2010) were distributed in the Dutch EQC program for semen analysis. The EQC results were evaluated for variability per criterion and for trends in time. RESULTS: Between 2015 and 2020, 40 to 60 laboratories assessed the photos. Criteria with low variability between participants were related to acrosomal vacuoles, excessive residual cytoplasm, and tail metrics. In contrast, head ovality, regularity of head and midpiece contours, and alignment of the major axis of the midpiece and head led to the highest variability in outcomes. In general, there was a slightly positive trend (lower variability) in time, except for the criteria with the highest variability (stable or declining trend). DISCUSSION AND CONCLUSION: This study indicates that there are (high) variabilities in the interpretation of the morphological criteria, leading to inconsistent outcomes of morphology assessment. The results are discussed from the perspective of imperfections in definitions and examples of the criteria as given in the WHO manuals.

Type 1 diabetes mellitus and sperm quality: A case-control study.

BACKGROUND: The potential impact of diabetes mellitus type 1 (DM1) on male fertility is currently poorly defined. Hyperglycaemia and insulin deficiency may affect spermatogenesis. Some evidence suggests that men with DM1 have a significant reduction in progressive sperm motility, sperm morphology and semen volume, without significant changes in sperm concentration and count, but definite data are lacking. OBJECTIVES: To evaluate the impact of DM1 on clinical parameters related to male fertility and semen analysis. MATERIALS AND METHODS: We compared a court of 42 male DM1 patients with 43 nondiabetic subjects overlapping in age and remaining clinical data in an observational case-control study. All subjects underwent a comprehensive andrological reproductive evaluation, including medical history, physical examination, and semen analysis. We collected biochemical data in all patients with DM1, while diabetic patients with any alteration in semen parameters underwent sperm culture and scrotal ultrasound. In addition, all men completed the IIEF-5 questionnaire (International Index of Erectile Function-5) and the AMS (Aging Male Symptom score) questionnaire. RESULTS: Patients with DM1 had a higher prevalence of infertility, erectile dysfunction and worse semen parameters compared with controls. In particular, semen volume, total sperm count, and total and progressive sperm motility were significantly lower (p < 0.001, p = 0.003, p = 0.048, and p = 0.022 respectively). In addition, the rate of semen anti-sperm antibody positivity, the AMS score and FSH levels were higher. DISCUSSION AND CONCLUSION: Several mechanisms may contribute to these semen alterations in DM1 patients, such as oxidative damage to spermatogenesis, seminal infections and pelvic neurological changes. These data suggest that patients with DM1 should be counselled from an andrological-reproductive point of view.

Comparison of Testicular Sonography and Elastography Findings With Semen Parameters in Cases Investigated for Infertility.

OBJECTIVES: This study aimed to investigate the correlation between testicular shear wave elastography (SWE) values and semen analysis results in men with infertility. METHODS: This was a retrospective case-control study. Patients were categorized as normal, abnormal, or azoospermic based on sperm analysis results. Testicular volume was measured using B-mode ultrasonography using the Lambert formula. Subsequently, 40-80 regions of interest measuring 1.5 × 1.5 mm were manually positioned in both testicles based on their size, and two-dimensional SWE was applied through virtual touch imaging quantification software. RESULTS: The patients had a mean age of 33.79 ± 6.3 years, with semen analysis revealing normal results in 15 patients (22.4%), pathological findings in 35 patients (52.2%), and azoospermia in 17 patients (25.4%). Right, left, total, and mean testicular volumes were significantly lower in patients with azoospermia compared to those in both normal and impaired semen parameters (P < .05). Conversely, testicular elastography scores were higher in patients with azoospermia than in the other groups (P < .05). The significant negative correlation between volume and elastographic findings remained independent of age (r = 0.4, P < .001). The accuracy rates for detecting impaired semen parameters and azoospermia were 94.3% and 94.1%, respectively, after considering factors such as age, testicular volume (right/left/total), and elastography (right/left/total). Notably, the total mean elastography score ranked first, with 100% in the independent normalized importance distribution of these variables. CONCLUSION: SWE can be used effectively alone or in combination with other diagnostic tools to evaluate histopathological changes in the testicles of male patients with infertility.

Recent decline in sperm motility among donor candidates at a sperm bank in Denmark.

STUDY QUESTION: Has there been variation in semen quality among men applying to be sperm donors (i.e. donor candidates) in Denmark in recent years (2017-2022)? SUMMARY ANSWER: The motile sperm concentration and total motile sperm count (TMSC) in ejaculates-both measures of sperm quality-declined by as much as 22% from 2019 to 2022. WHAT IS KNOWN ALREADY: Questions remain about whether human semen quality has declined in recent years. Whilst some studies provide evidence for a decline in human semen quality, these findings have been disputed owing to potential biases in the populations studied or in the methods used to measure semen quality. Resolution of this issue has important implications for human fertility, as well as for those involved in the recruitment of sperm donors for use in medically assisted reproduction. STUDY DESIGN, SIZE, DURATION: We obtained data on the semen quality of ejaculates previously collected from 2017 to 2022 at sperm bank locations in four cities in Denmark: Aarhus, Aalborg, Copenhagen, and Odense. Our study focuses on the single semen samples provided by 6758 donor candidates aged between 18 and 45 years old to determine whether their sperm quality met a minimum criterion for them to be accepted as sperm donors. PARTICIPANTS/MATERIALS, SETTING, METHODS: All ejaculates were analyzed within 1 hour of production. Semen volume (ml) was estimated by weight and both the concentration (106/ml) of sperm as well as the concentration of motile sperm (World Health Organization grades a and b) were measured using the same protocols and computer-assisted semen analysis system across all years at each site. Statistical analyses of the semen variables were controlled for age and donation site, as well as the average monthly high temperature when the ejaculate was produced. MAIN RESULTS AND THE ROLE OF CHANCE: From 2017 to 2019, semen volume, sperm concentration, and total sperm count in the ejaculates of donor candidates increased by 2-12%. Then, from 2019 to 2022, sperm concentration and total sperm count changed by 0.1-5% from year to year, but none of those changes were statistically significant. In contrast, both motile sperm concentration and TMSC declined significantly, by 16% and 22%, respectively, between 2019 and 2022. Thus, the concentration of motile sperm in donor candidates declined from 18.4 [95% CL: 17.0, 20.0] million/ml in 2019 to 15.5 [14.4, 16.7] million/ml in 2022, and TMSC declined from 61.4 [55.8, 67.5] million per ejaculate in 2019 to 48.1 [44.1, 52.4] million in 2022. LIMITATIONS, REASONS FOR CAUTION: We cannot determine from the available data the causes of the decline in semen quality of donor candidates from 2019 to 2022. However, as this period coincides with lockdowns and changes in work patterns during the coronavirus disease 2019 pandemic, it is possible that changes in motile sperm concentration and TMSC were the result of changes in the lifestyles of the men whose semen was analyzed. WIDER IMPLICATIONS OF THE FINDINGS: Men providing initial semen samples at sperm banks, when applying to be sperm donors, are a useful population in which to monitor changes in human semen quality over time. Our results have implications for human fertility and the recruitment of sperm donors for medically assisted reproduction, where motile sperm concentration is an essential selection criterion because it influences fertility. We suggest that gathering health and lifestyle data on donor candidates at sperm banks might help to identify causal factors for the decline of sperm quality that could be addressed and intervention, if desired, could be personalized for each accepted donor. STUDY FUNDING/COMPETING INTEREST(S): No external funding was obtained for this study. E.L. and A.-B.S. are employees of Cryos International. AP reports paid consultancy for Cryos International, Cytoswim Ltd, Exceed Health, and Merck Serono in the last 2 years of this study, but all monies were paid to the University of Sheffield (former employer). AP is also an unpaid trustee of the Progress Educational Trust (Charity Number 1139856). RM declares support from Cryos International to present results of this research at ESHRE 2023. None of the authors were directly involved in the collection or physical analysis of semen samples. TRIAL REGISTRATION NUMBER: N/A.

The Association of Sperm DNA Fragmentation With Serum Lipid Profile Among Males With Abnormal Semen Parameters: An Analytical Cross-Sectional Study.

BACKGROUND: Through the ages, infertility, affecting 8% to 12% of couples worldwide, has been a perturbing clinical problem. Approximately 40% to 50% of all infertility cases are due to 'male factor' infertility. Semen analysis is crucial in routinely evaluating idiopathic male infertility. Studies support the idea that semen parameters are associated with serum lipids and sperm DNA fragmentation (SDF). Therefore, it is possible to evaluate male infertility by serum lipid levels, especially before assisted reproduction technology, and modify it by bringing about lifestyle modifications. This study aimed to measure the correlation of SDF with levels of total cholesterol (TC), triglycerides (TG), very low-density lipoprotein (VLDL), low-density lipoprotein (LDL), and high-density lipoprotein (HDL) among males with abnormal semen parameters. METHODS: A cross-sectional analytical study was conducted in the infertility clinic of a tertiary care hospital. A total of 106 infertile males with abnormal semen analysis as per the WHO criteria (2010) were enrolled in the study. After routine semen analysis, SDF was studied using the comet assay. The serum fasting lipid profile was analyzed using the spectrophotometric kit in the autoanalyzer. The relationship of SDF with serum lipid profile parameters was analyzed. RESULTS: Out of 106 infertile men, 52% (n = 55) had severe SDF. A modest positive correlation was observed between SDF (percentage of DNA in comet tail) and serum lipid values (serum TG, serum LDL, and serum VLDL). CONCLUSIONS: Our study is novel in its research on the correlation between SDF and serum lipid values. Based on the findings of our study, it can be concluded that a significant level of SDF was observed in men with high levels of serum TG, LDL, and VLDL. This provokes a potential relationship between sperm DNA integrity and serum lipid profile, which warrants further research.

Size matters: Total testicular volume predicts sperm count in Tanner V varicocele patients.

INTRODUCTION: It is known the prevalence of varicoceles in adolescent men is 14-29% but there is debate surrounding implications on fertility. As obtaining a semen analysis (SA) may be challenging, there is need for objective tests as measures of fecundity. Our aim was to investigate the relationship between testicular volume differential (TVD), varicocele grade, and total testicular volume (TTV) on seminal parameters including total motile sperm count (TMSC). MATERIALS AND METHODS: We conducted a retrospective single-center chart review over 14 years of 486 Tanner V adolescent males. Three hundred and four met inclusion of palpable, non-operated left-sided varicocele who underwent at least one SA and ultrasound. Abnormal TMSC was defined by World Health Organization 2010 criteria for minimal reference ranges. Multivariate logistic regression, receiver operating characteristic analysis with Youden J-statistic and descriptive statistics were performed. RESULTS: Three hundred and four Tanner V adolescents with median age of 18.0 years (18.0-19.0), median TTV of 34.5 cc (28.9, 40.2) and median TMSC of 62.5 million/ejaculate (25.4, 123.4) were evaluated. TTV cutoff of 29.5 cc was found to predict TMSC of <9 million/ejaculate with negative predictive value of 96.2% and odds ratio of 6.08 ([2.13-17.42], p < 0.001). TVD greater than 20% did not reach statistical significance with an odds ratio of 1.66 ([0.41-6.62], p = 0.50). DISCUSSION: In clinical practice, each patient will need to have an individualized plan. Based on our data, for older adolescents (17 or 18 years) with varicocele and an abnormal TTV, clinicians may have a lower threshold for advising SA, and if unable to obtain, surgical intervention and/or closer surveillance should be stressed. Patients should be informed of their six-fold increase in abnormal SA. Patients with normal TTV should be advised they are at lower risk of having abnormal SA. Younger patients with varicocele and an initial TVD>20%, should be followed closely but intervention delayed until 17 or 18 to better assess TTV. The importance of trending patient data should be emphasized as a single measurement has low predictive value for developing adolescents. Limitations of our study include a retrospective design and the lack of uniform correlation between adolescent SA and paternity. CONCLUSIONS: Total testicular volume less than 29.5 cc increased odds of abnormal semen analysis by over six times and had a negative predictive value of 96.2%. Ultrasound results may be useful for risk stratification and counselling on appropriateness of surgical intervention.

Dietary Glycemic Index and Load and Semen Quality: A Cross-Sectional and Prospective Analysis within the FERTINUTS Trial.

PURPOSE: Infertility is a global health issue and nutrition plays a significant role in fertility outcomes. We aimed to investigate the cross-sectional and prospective associations of glycemic index (GI) and glycemic load (GL) with semen quality parameters in a cohort of healthy young men. MATERIALS AND METHODS: The study included 106 men aged 18-35 years from the FERTINUTS trial. Dietary intake was estimated through 3-day dietary records and several semen parameters were assessed. Multivariable linear regression analysis with the Least Absolute Shrinkage and Selection Operator (LASSO) approach was employed. RESULTS: The cross-sectional analysis revealed positive associations between GI and GL and total sperm count, sperm concentration, and total motility. In the prospective analysis, baseline GI was associated with increases in pH, vitality, immotile sperm or abnormal midpiece and decreases in total sperm count and motility. Conversely, GL was positively associated with changes in vitality and total sperm count. CONCLUSIONS: While these findings suggest that GI may have adverse effects on several sperm quality parameters, the results were not consistently observed in the cross-sectional analysis. However, GL was consistently associated with better sperm quality in both analyses. The impact of carbohydrate quality and quantity on fertility remains uncertain and larger prospective studies are needed.

Phase angle at bioelectric impedance analysis is associated with detrimental sperm quality in idiopathic male infertility: a preliminary clinical study.

Background: In 2020, 38% of adults were affected by obesity, while infertility globally affected 1 in 6 people at some stage of their lives.Body mass index (BMI) provides an easy but occasionally inaccurate estimation of body composition. To achieve a more precise assessment, bioelectric impedance analysis serves as a validated tool that administers electrical energy through surface electrodes. Phase angle as a function of the relationship between tissues resistance and reactance, is a trustworthy predictor of body composition and cell membrane integrity. Objectives: We aim to assess whether there is an association between phase angle and seminal parameters, as well as sperm DNA fragmentation percentage. Design: Semen samples of 520 idiopathic infertile patients were analyzed according to 2021 World Health Organization guidelines and evaluated for sperm DNA fragmentation rate. Each participants underwent bioelectric impedance analysis. Results: Median age was 40 years old, median BMI was 26.3 kg/m2, median phase angle was 6.2°. In the logistic regression analysis adjusted for age and total intracorporeal water, phase angle (continuous) was significantly associated with oligozoospermia (odds ratio [OR]:0.4; p<0.01) and sperm morphology (OR: 0.65; p=0.05) and slightly with sperm DNA fragmentation (OR: 0.98; p=0.07). In subgroup analysis, the logistic regression analysis adjusted for the mentioned parameters showed that a phase angle between 6.2 and 7 (°) (OR: 0.63; p=0.02) and >7 (°) (OR: 0.12; p<0.01) were associated with a reduced risk of oligozoospermia compared to values <6.2 (°). Similarly, a phase angle between 6.2 and 7 (°) (OR: 0.57; p< 0.01 and OR: 0.58; p= 0.01) and PA > 7 (°) (OR: 0.12; p= 0.03 and OR: 0.21; p< 0.01) were associated with a reduced risk of lower sperm concentration and lower total sperm count, respectively, compared to a phase angle < 6.2 (°). Conclusion: Our study suggests a negative association between phase angle and detrimental sperm parameters in male idiopathic infertility.

Testing the generalizability and effectiveness of deep learning models among clinics: sperm detection as a pilot study.

BACKGROUND: Deep learning has been increasingly investigated for assisting clinical in vitro fertilization (IVF). The first technical step in many tasks is to visually detect and locate sperm, oocytes, and embryos in images. For clinical deployment of such deep learning models, different clinics use different image acquisition hardware and different sample preprocessing protocols, raising the concern over whether the reported accuracy of a deep learning model by one clinic could be reproduced in another clinic. Here we aim to investigate the effect of each imaging factor on the generalizability of object detection models, using sperm analysis as a pilot example. METHODS: Ablation studies were performed using state-of-the-art models for detecting human sperm to quantitatively assess how model precision (false-positive detection) and recall (missed detection) were affected by imaging magnification, imaging mode, and sample preprocessing protocols. The results led to the hypothesis that the richness of image acquisition conditions in a training dataset deterministically affects model generalizability. The hypothesis was tested by first enriching the training dataset with a wide range of imaging conditions, then validated through internal blind tests on new samples and external multi-center clinical validations. RESULTS: Ablation experiments revealed that removing subsets of data from the training dataset significantly reduced model precision. Removing raw sample images from the training dataset caused the largest drop in model precision, whereas removing 20x images caused the largest drop in model recall. by incorporating different imaging and sample preprocessing conditions into a rich training dataset, the model achieved an intraclass correlation coefficient (ICC) of 0.97 (95% CI: 0.94-0.99) for precision, and an ICC of 0.97 (95% CI: 0.93-0.99) for recall. Multi-center clinical validation showed no significant differences in model precision or recall across different clinics and applications. CONCLUSIONS: The results validated the hypothesis that the richness of data in the training dataset is a key factor impacting model generalizability. These findings highlight the importance of diversity in a training dataset for model evaluation and suggest that future deep learning models in andrology and reproductive medicine should incorporate comprehensive feature sets for enhanced generalizability across clinics.

Prevalence of infertility and barriers to family building among male physicians.

BACKGROUND: Fertility declines with increasing age and physicians often delay childbearing beyond prime reproductive years for the sake of medical training. However, the risks of infertility in male physicians compared to the general population remain poorly studied. OBJECTIVES: To characterize rates of infertility among male physicians and identify barriers in access to fertility care and family building. MATERIALS & METHODS: Between June 2022 and December 2022, male physicians were invited to complete a questionnaire regarding fertility and family building. Surveys were disseminated electronically via social media and professional medical societies using Qualtrics (Provo, UT). RESULTS: Two hundred thirty-five responses were included in the final analysis. The mean age of respondents was 36.3 ± 7.4 years. Of 151 respondents with children or currently attempting to have children, 66 (43.7%) delayed family building due to their medical training or career. The most influential factors affecting timing of children were lack of flexibility in schedule, lack of time, stress, and financial strain. Forty-three (18.3.%) respondents had seen a doctor for fertility evaluation; an additional 12 (5.1%) said they considered doing so but did not, mostly due to being too busy. Sixty (25.5%) had undergone semen testing in the past. Thirty-one (13.2%) reported a diagnosis of fertility issues in either themselves or their partner. Twenty-seven (11.5%) endorsed either them or their partner having undergone assistive reproductive technologies or other procedures for infertility. DISCUSSION: A significant proportion of male physicians delayed building their family or seeking fertility evaluation due to their medical career. Around 23.4% of male physicians have either seen or considered seeing a physician for fertility evaluation, suggesting a high prevalence of infertility in this cohort. CONCLUSION: Our results indicate a need for interventions to support family building and fertility evaluation and treatment among male physicians.

[Clinical guidelines for male infertility: controversial issues and the need to reach interdisciplinary consensus].

A review of controversial issues about the terminology on male infertility and reproductive function, which is currently used, as well as proposals for updating clinical guidelines for the diagnosis and treatment of male infertility and men in infertile couples are presented in the article. An algorithm is described, the elements of which ensure referral of patients based on the possibility and timing of restoration of reproductive function, taking into account the reproductive health of a woman, as well as increasing the likelihood of successful treatment aimed at the birth of a healthy child.

Reproductive Urology Consultation Is an Opportunity to Evaluate for Medical Comorbidity: The Prevalence of Elevated Blood Pressure and Obesity at Fertility Evaluation.

Purpose To evaluate the prevalence of elevated blood pressure (EBP), hypertension (HTN), and obesity among men presenting for fertility evaluation. Methods We retrospectively evaluated all men presenting for male infertility consultation at a single institution from 2000 to 2018. Blood pressure (BP) measurements were abstracted from the electronic health record, and EBP/HTN was defined according to American Heart Association/American College of Cardiology guidelines (systolic blood pressure (SBP) ≥ 120 mmHg or diastolic blood pressure (DBP) ≥ 80 mmHg). Descriptive statistics were used to compare demographic and clinical characteristics of men with and without EBP/HTN or obesity (BMI ≥ 30 kg/m2), and logistic regression was utilized to determine associations with EBP/HTN. Results Among 4,127 men, 1,370 (33.2%) had a recorded SBP and DBP within one year of their initial visit. EBP/HTN was noted in 857 (62.6%) men. A total of 249 (18.2%) men were obese, 863 (63.0%) were non-obese, and 258 (18.8%) did not have BMI recorded. HTN and obesity were jointly present in 195 (17.5%) men. There was no significant difference in age, ethnicity, or total motile sperm count between men with and without EBP/HTN. On multivariable analysis, BMI was significantly associated with EBP/HTN (OR: 1.13, 95% CI: 1.08-1.18, p < 0.001). Conclusion More than half of men presenting for initial fertility consultation have either EBP, obesity, or both. Reproductive urologists should consider routinely screening for these conditions and encourage men to seek further evaluation and treatment, when appropriate.

Correlation between standard sperm parameters and sperm DNA fragmentation from 11,339 samples.

Conventional semen parameters have long been considered fundamental in male fertility analyses. However, doubts have been raised regarding the clinical utility of the assessment of spermatozoa (sperm) DNA damage. In this retrospective study, we investigated the potential correlation between conventional semen parameters and semen DNA fragmentation (SDF) assessed as sperm DNA damage, in 11,339 semen samples collected between January 2019 and June 2022. We observed significant negative correlations between the DNA fragmentation index (DFI) and sperm viability (correlation coefficient [r] = -0.514) as well as progressive sperm motility (r = -0.512, p < 0.05). Samples were categorized into three groups according to DFI levels (Groups A, B, and C: ≤15%, 15 < DFI ≤30%, and >30%, respectively). Furthermore, the percentage of semen samples with normal sperm conventional parameters in Groups A, B, and C was 76.7% (4369/5697), 61.4% (2351/3827), and 39.7% (721/1815), respectively. Moreover, according to the reference values of conventional sperm parameters, the samples were divided into Groups F, G, and H with all normal, only one abnormal, and > two abnormal parameters, respectively. In addition, the proportions of samples with abnormal DFI values (>30) in Groups F, G, and H were 9.7% (721/7441), 23.1% (618/2676), and 39.0% (476/1222), respectively. Multivariate logistic regression models demonstrated that sperm vitality, progressive sperm motility, normal sperm form, total sperm count, semen volume, age, and some sperm kinematics collectively improved the area under the receiver operating characteristic curve (AUROC) to 0.861, surpassing the predictive value of a single predictor of pathologically damaged sperm DNA. Our study suggests that samples with abnormal sperm parameters may have a higher likelihood of high DNA fragmentation. Furthermore, certain semen parameters could be potential indicators of sperm DNA fragmentation, aiding sperm selection in assisted reproductive procedures.

Introducing a New Smartphone Applied Semen Analyzer, SpermCell™: A Cross-Sectional Validation Study with a Comparative Analysis and a Mini Patient Questionnaire on a Large Sample Cohort.

(1) Background: Standard semen analysis methods may exhibit variability between observers and/or human error; therefore, additional methods are needed to overcome these handicaps. We aimed to present a new smartphone-applied semen analyzer, Sperm Cell™, investigate its diagnostic efficacy by comparing it with the standard analysis method, and determine its user-friendly nature. (2) Methods: A cross-sectional study was conducted on a large sample cohort, including 102 men. Three semen analyses were performed for each semen sample. The first employed the standard manual method, whereas the others were smartphone-based analyses performed by technicians and patients. We compared major semen parameters between the three semen analyses. The user-friendly nature of the analyzer was also evaluated with a mini-questionnaire completed by the participants. (3) Results: The determined median sperm count, motile sperm count, and percentage of motile sperms, on standard manual semen analysis, were 50.00 × 106/mL (0-160 × 106/mL), 23.94 × 106/mL (0-108 × 106/mL) and 50.00% (0-73.00%), respectively. Median sperm count and motile sperm count were 50.52 × 106/mL (<1-150 × 106/mL) vs. 55.77 × 106/mL (<1-160 × 106/mL) and 23.34 × 106/mL (0-105 × 106/mL) vs. 23.53 × 106/mL (0-104 × 106/mL) for SpermCell™-based semen analysis performed by a technician and patients themselves, respectively. The percentages of motile sperms were 47.40% (0-67.00%) vs. 47.61% (0-80.20%), respectively. All the parameters were statistically similar between the three semen analysis methods (p > 0.05 for each). The SpermCell™ analysis results were correlated with the standard manual method with up to 0.85 correlation coefficients. Moreover, substantial diagnostic accuracy, sensitivity and specificity were obtained in determining the oligospermia and asthenozoospermia via the device-based analyses performed by technician and patients. The mini-questionnaire results revealed that the analyzer is useful. (4) Conclusions: The novel smartphone-applied semen analyzer is a helpful tool with acceptable diagnostic accuracy in determining the major semen parameters. It can be used as an efficient at-home point-of-care testing method in the initial assessment of couples with infertility concerns.