Asian journal of andrology最新文献

Abstract: A growing global trend indicates a decline in semen quality, with a lack of physical activity identified as one of the contributing factors. Exercise is medication, and numerous studies have explored its effects on semen quality. However, there is no consensus on the most effective type and intensity of exercise for improving semen quality, owing to inconsistent findings across studies. These discrepancies may be attributable to variations in study populations ( e.g. , healthy versus infertile individuals) and research methodologies ( e.g., observational versus interventional studies). This paper reviews the existing literature from the databases PubMed, Web of Science, and Google Scholar, reclassifying articles on their subject and research designs to delineate the relationship between exercise and semen quality. It also summarizes the mechanisms through which exercise influences semen quality, including hormonal regulation, oxidative stress, and inflammatory factors.

Abstract: Androgen deprivation therapy (ADT) can negatively affect sexual function, and only a minority of patients report sexual activity. We reviewed the existing literature regarding the proportion of men who remained sexually active during and after ADT. The PubMed database was searched for studies published over the past 20 years. We selected and reviewed randomized clinical trials that provided sexual function data at baseline and during and after ADT. The primary outcome measure was the sexual function. Studies assessed sexual function using quality of life patient-reported outcome measures, which included sexual potency/activity evaluation. Information from 2947 patients was analyzed in this review. The median age of patients was 70 years. At baseline, a median of 49.9% (95% confidence interval [CI]: 49.1%-50.7%) of the patients reported being sexually active. At 6 months, 12 months, and 2 years or later of ADT treatment, a median of 10.3% (95% CI: 10.2%-10.5%), 8.9% (95% CI: 8.6%-9.2%), and 8.3% (95% CI: 8.2%-8.5%) of the patients reported being sexually active, respectively. Considering that half of the patients were sexually active at baseline, it seems probable that more than 10% of the patients who were sexually active before starting ADT remained sexually active when undergoing ADT. In conclusion, despite the common belief that ADT eliminates sexual activity, this analysis found that approximately 1 in 10 men are sexually active when on ADT, and this proportion is likely increased in men who are sexually active before starting ADT. Attention to sexual activity should not be dismissed in men on ADT.

Abstract: Varicocele (VC) is a common cause of male infertility, yet there is a lack of molecular information for VC-associated male infertility. This study investigated alterations in the seminal plasma metabolomic and lipidomic profiles of infertile male VC patients. Twenty infertile males with VC and twenty-three age-matched healthy controls (HCs) were recruited from Peking Union Medical College Hospital (Beijing, China) between October 2019 and April 2021. Untargeted metabolite and lipid profiles from seminal plasma were analyzed using mass spectrometry. Four hundred and seventy-six metabolites and seventeen lipids were significantly different in infertile male VC patients compared to HCs. The top enriched pathways among these significantly different metabolites are protein digestion and absorption, aminoacyl-transfer RNA (tRNA) biosynthesis, and biosynthesis of amino acids. Different key lipid species, including triglyceride (TG), diacylglycerol (DG), ceramides (Cer), and phosphatidylserine (PS), varied between VC and HC groups. The distinct metabolites and lipids were moderately correlated. DL-3-phenyllactic acid is a potential diagnostic biomarker for VC-related male infertility (area under the curve [AUC] = 0.893), positively correlating with sperm count, concentration, and motility. Furthermore, DL-3-phenyllactic acid is the only metabolite shared by all four comparisons (VC vs HC, VC-induced oligoasthenospermia [OAS] vs VC-induced asthenospermia [AS], OAS vs HC, and AS vs HC). DL-3-phenyllactic acid significantly decreased in OAS than AS. Metabolite-targeting gene analysis revealed carbonic anhydrase 9 (CA9) might be the strongest candidate associated with the onset and severity of VC. The seminal plasma metabolite and lipid profiles of infertile males with VC differ significantly from those of HCs. DL-3-phenyllactic acid could be a promising biomarker.

Abstract: Researchers commonly use cyclization recombination enzyme/locus of X-over P1 (Cre/loxP) technology-based conditional gene knockouts of model mice to investigate the functional roles of genes of interest in Sertoli and Leydig cells within the testis. However, the shortcomings of these genetic tools include high costs, lengthy experimental periods, and limited accessibility for researchers. Therefore, exploring alternative gene silencing techniques is of great practical value. In this study, we employed adeno-associated virus (AAV) as a vector for gene silencing in Sertoli and Leydig cells. Our findings demonstrated that AAV serotypes 1, 8, and 9 exhibited high infection efficiency in both types of testis cells. Importantly, we discovered that all three AAV serotypes exhibited exquisite specificity in targeting Sertoli cells via tubular injection while demonstrating remarkable selectivity in targeting Leydig cells via interstitial injection. We achieved cell-specific knockouts of the steroidogenic acute regulatory ( Star ) and luteinizing hormone/human chorionic gonadotropin receptor (Lhcgr) genes in Leydig cells, but not in Sertoli cells, using AAV9-single guide RNA (sgRNA)-mediated gene editing in Rosa26-LSL-Cas9 mice. Knockdown of androgen receptor ( Ar ) gene expression in Sertoli cells of wild-type mice was achieved via tubular injection of AAV9-short hairpin RNA (shRNA)-mediated targeting. Our findings offer technical approaches for investigating gene function in Sertoli and Leydig cells through AAV9-mediated gene silencing.

Abstract: Individuals with congenital absence of the vas deferens (CAVD) may transmit cystic fibrosis (CF)-causing variants of the cystic fibrosis transmembrane conductance regulator ( CFTR ) gene to their offspring through assisted reproductive technology (ART). We aimed to delineate the spectrum and estimate the prevalence of CF-causing variants in Chinese individuals with CAVD through a cohort analysis and meta-analysis. CFTR was sequenced in 145 Chinese individuals with CAVD. CFTR variants were classified as CF-causing or non-CF-causing variants regarding clinical significance. A comprehensive genotype analysis was performed in Chinese individuals with CAVD, incorporating previous studies and our study cohort. The prevalence of CF-causing variants was estimated through meta-analysis. In our cohort, 56 different CFTR variants were identified in 108 (74.5%) patients. Twenty variants were categorized as CF-causing and were detected in 28 (19.3%) patients. A comprehensive genotype analysis of 867 patients identified 174 different CFTR variants. Sixty-four were classified as CF-causing variants, 56.3% of which had not been previously reported in Chinese patients with CF. Meta-analysis showed that 14.8% (95% confidence interval [CI]: 11.0%-18.9%) CAVD cases harbored one CF-causing variant, and 68.6% (95% CI: 65.1%-72.0%) CAVD cases carried at least one CFTR variant. Our study underscores the urgent need for extensive CFTR screening, including sequencing of whole exons and flanking regions and detection of large rearrangements and deep intronic CF-causing variants, in Chinese individuals with CAVD before undergoing ART. The established CF-causing variants spectrum may aid in the development of genetic counseling strategies and preimplantation diagnosis to prevent the birth of a child with CF.

The management of data from computer-aided sperm analysis (CASA) systems is crucial for understanding sperm motility. CASA systems generate motility parameters derived from tracking individual sperm cells, producing raw data as spermatozoa coordinates, which form the basis for sperm trajectory construction. These parameters and trajectories allow statistical descriptions of motility and identification of sperm heterogeneity. The substantial information provided by CASA enables the application of artificial intelligence (AI) techniques to interpret their biological significance. However, the type and format of CASA data, whether raw or condensed, pose challenges for analysis using conventional statistical methods. Advances in machine learning and deep learning have addressed these limitations by leveraging motility parameters and trajectory representations for automated classification and clustering of motility patterns. These methods, including supervised and unsupervised learning, have been employed to identify kinematic subpopulations within sperm samples, offering deeper insights into sperm dynamics. Open-source tools and CASA systems have facilitated this progress by providing accessible platforms for AI applications in sperm motility analysis. Although the use of machine learning in this field remains limited, integrating CASA-derived data with AI techniques shows potential for automating sperm classification and identifying motility patterns, advancing reproductive biology and fertility assessments. This work reviews the traditional use of CASA data, the analytical constraints, and the promising role of machine learning in enhancing the understanding of the heterogeneity of sperm kinematics.

Recent studies have begun to investigate the metabolic and microbiota profiles in semen, yet their association with abnormal sperm morphology, particularly in teratozoospermia, remains insufficiently characterized. Identifying specific metabolites and microbial taxa linked to this condition could improve diagnostics and management for male infertility. This study analyzed semen samples from 231 patients, including 30 patients with teratozoospermia and 30 patients with normal sperm morphology, collected over four seasons in Chongqing, China. Metabolomic profiling by gas chromatography-mass spectrometry (GC-MS) and microbiota composition analysis via 16S ribosomal ribonucleic acid (rRNA) sequencing revealed distinct seasonal metabolomic shifts, with significant changes in summer and autumn. After excluding seasonally affected metabolites, 14 key metabolites were associated with teratozoospermia, including reduced levels of 4-hydroxyphenylpyruvic acid, phenylpyruvic acid, and N-acetyl-L-aspartic acid. These metabolites are involved in pathways related to oxidative stress and energy metabolism in spermatozoa, suggesting that their depletion may contribute to sperm abnormalities. Proteobacteria, Firmicutes, and Actinobacteriota were predominant phyla across all seasons and groups, but significant genus-level fluctuations, such as Acinetobacter and Staphylococcus, were observed. In teratozoospermia, genera such as Lactobacillus and Limnochordaceae showed differential abundance, correlating with key metabolites and suggesting potential functional interactions. Limnochordaceae showed a significant positive correlation with undecanoic acid, whereas Lactobacillus showed a negative correlation. These findings highlight that while seasonal changes significantly influence semen metabolomics and microbiota composition, teratozoospermia is characterized by specific, season-independent metabolic and microbial signatures. Our study provides insights into the metabolic and microbial dynamics of semen, suggesting the possibility of developing novel diagnostic tools and therapeutic strategies for male infertility.