Varicocele (VC) is a common correctable factor in male infertility, yet its effect on fertility and response to repair vary markedly among patients. This narrative review examines whether mitochondrial injury links the hemodynamic lesion to oxidative stress, sterile inflammation, and persistent spermatogenic damage. Venous stasis, hyperthermia, hypoxia, and metabolic disturbance can impair mitochondrial respiration, membrane potential, ATP production, and quality control. These changes increase mitochondrial reactive oxygen species and favor mitochondrial DNA (mtDNA) oxidation and release. Oxidized mtDNA can engage cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) and NOD-like receptor family pyrin domain-containing 3 (NLRP3) signaling in nucleated testicular cells, but the evidence is uneven. Human studies mainly document sperm mitochondrial dysfunction, oxidative injury, DNA fragmentation, and altered inflammasome-related factors in seminal plasma. The integrated mtDNA-cGAS-STING-NLRP3 sequence is supported chiefly by animal and non-VC mechanistic models and has not been causally demonstrated in human VC. Anatomical and temporal context is therefore critical. Events in testicular somatic, germ, and immune cells during spermatogenesis cannot be inferred from epididymal, ejaculated-sperm, seminal-plasma, or female-tract findings. Endoplasmic reticulum stress and autophagy or mitophagy may modify mitochondrial injury, whereas programmed cell death, blood-testis barrier disruption, and epigenetic alterations may extend its consequences. Most of these links still require cell-resolved and longitudinal validation. Guideline-directed varicocele repair remains the clinical foundation. Sperm DNA fragmentation and other mechanism-related markers are useful research tools but lack source specificity or validated treatment thresholds, and pathway-directed therapies remain preclinical. The distinctive contribution of this review is a compartment-resolved and evidence-graded model that separates demonstrated findings from plausible links. It also defines the experiments needed to determine whether residual mitochondrial-inflammatory injury predicts reproductive outcomes or response to safe adjunctive treatment.
Abstract Background Large language models (LLMs) are increasingly used by patients and clinicians to obtain medical information, yet their performance may change over time as models are updated. Male infertility is a guideline-sensitive field in which inaccurate or incomplete information may affect diagnostic evaluation, counseling, and treatment expectations. This study evaluated the year-on-year evolution of ChatGPT, Perplexity, and DeepSeek in responding to guideline-derived male infertility questions between 2025 and 2026. Results A total of 528 chatbot responses were evaluated from 88 European Association of Urology (EAU) guideline-derived male infertility questions answered by ChatGPT, Perplexity, and DeepSeek in 2025 and 2026. In 2025, significant inter-model differences were observed across all four scored domains, with Perplexity achieving the highest content-quality and expert-rated scores and DeepSeek showing the weakest performance. In 2026, DISCERN scores converged across models, whereas significant differences persisted for readability, Global Quality Score, and expert opinion. ChatGPT showed significant improvement across all four scored domains and achieved the highest Global Quality Score in 2026. DeepSeek demonstrated the most pronounced improvement, particularly in DISCERN and expert opinion scores. Perplexity improved in readability but did not show a parallel positive change in Global Quality Score or expert-rated clinical usefulness. Potential patient-safety concerns were identified in seven of the 88 DeepSeek responses from 2025, whereas no such concern was identified in the 2026 responses. None of the 528 responses contained an explicit recommendation considered likely to cause immediate or serious patient harm. Conclusions Performance changed in a model-specific rather than uniformly progressive manner. The findings represent sampled first-pass responses to clearly formulated guideline-derived questions rather than stable estimates of model performance or reproducibility. LLMs may support access to male infertility information, but verification against authoritative sources and appropriate human oversight remain necessary.
Abstract Background Asthenozoospermia (AZS) is a leading cause of male-factor infertility, yet the contribution of the urinary microbiota to sperm motility remains poorly defined, because previous work has focused almost exclusively on the seminal and gut microbiota. Here we used 16S rRNA gene sequencing to characterize the composition and functional profiles of the urinary microbiota in men with AZS and in fertile controls. Results Isolated AZS and age-matched fertile controls were enrolled, and urinary specimens from participants were sequenced successfully. Alpha diversity of the urinary microbiota did not differ between the two groups. In contrast, beta diversity analysis revealed a statistically significant difference in overall community structure, although the group effect was modest in magnitude (PERMANOVA on Bray-Curtis dissimilarities, R 2 = 0.13, p = 0.001). Eighteen genera differed significantly in relative abundance. Porphyromonas, Corynebacterium , and Finegoldia were more abundant in men with AZS, whereas Blautia and Bacteroides were more abundant in controls. Predicted functional analysis identified multiple metabolic and genetic-information-processing pathways that differed between the groups, including replication and repair modules, peptidoglycan biosynthesis, one-carbon pool by folate, and nicotinate and nicotinamide metabolism. Conclusions It appears that men with AZS exhibit altered urinary microbiota structure and predicted functional profile. These associations extend the microbiome-male-infertility axis beyond the seminal and gut compartments and may inform biomarker discovery and microbiome-modulating strategies, although longitudinal and mechanistic studies are required to establish causality.
Bisphenol A (BPA) has been associated with altered male reproductive hormones and semen endpoints in epidemiological studies and produces endocrine, oxidative, mitochondrial, apoptotic, and developmental injury in experimental models. This narrative review evaluates BPA-specific evidence for naringenin and naringin separately from supportive evidence in other reproductive stress models. It also distinguishes directly exposed F1 outcomes from transgenerational inheritance and links sperm endpoints to hormones, histology, and molecular measures. This narrative review synthesizes evidence published mainly between January 2019 through September 2026, while retaining older studies of direct mechanistic relevance. Evidence was identified through targeted searches of PubMed, Scopus-indexed sources, Google Scholar, and publisher databases and was organized by exposure timing, biological mechanism, model type, and reproductive endpoint. The strongest evidence for BPA-related male reproductive toxicity comes from convergent cellular and animal data supported by heterogeneous human observational studies. The strongest evidence for naringenin or naringin is preclinical and includes BPA-specific Sertoli-cell and rat models as well as related oxidative, metabolic, and phthalate stress models. Across the broader preclinical literature, the flavanones modify redox, mitochondrial, inflammatory, and steroidogenic endpoints, but differences in model, dose, route, and bioavailability prevent quantitative comparison. The evidence supports mechanistic research, not clinical supplementation, and exposure reduction remains the primary public-health approach. BPA affects male reproduction through endocrine, redox, mitochondrial, apoptotic and developmental pathways. Naringenin and naringin evidence is promising but remains mainly cellular and rodent-based. F1 sperm endpoints should be interpreted as intergenerational outcomes when exposure occurs during gestation. Sperm count, motility, morphology and viability require companion hormone, histology and molecular endpoints. Flavanone research should complement exposure reduction and chemical regulation, not replace them.
Abstract Background The Bergmann-Kliesch Score is a histopathological grading system used to evaluate spermatogenesis in testicular biopsies, quantifying the fraction of seminiferous tubules containing elongated spermatids. It serves as a key parameter in the clinical process of men with non-obstructive azoospermia (NOA) undergoing testicular sperm extraction (TESE) for subsequent intracytoplasmic sperm injection (ICSI). Manual Bergmann-Kliesch Score assessment is time-consuming and subject to inter- and intraobserver variability. This study aimed to develop and validate an artificial intelligence (AI)-based computational pipeline for automated Bergmann-Kliesch Score assessment from digitized testicular biopsy whole-slide images (WSIs). Results A retrospective monocentric cohort of 74 patients who underwent TESE at the University Medical Center Frankfurt was analyzed. A dual-model machine-learning pipeline was used to process paired haematoxylin-eosin (HE) and OCT3/4 immunohistochemically stained WSIs. A U-Net architecture with a ResNet-34 backbone was trained on 60 HE-stained slides for tubular segmentation, monitored by a multi-class Dice coefficient of 0.897 on the validation set. A second U-Net model with a ResNet-34 backbone was trained on 15 OCT3/4-stained slides comprising 14,226 manually annotated elongated spermatids for spermatid detection. Both modalities were integrated via multimodal image registration combining rigid alignment and B-spline warping, enabling spatial projection of spermatid detections onto tubular segmentations. On the patient-level held-out test set of 15 patients, AI-derived Bergmann-Kliesch Scores showed strong agreement with pathologist-assigned reference scores (Pearson r = 0.957, Spearman ρ = 0.856, R 2 = 0.916, mean absolute error = 0.93, root mean squared error = 1.28). At the clinical cutoff of Bergmann-Kliesch Score ≥ 1, the pipeline correctly classified all test-set cases. Across the full evaluation cohort of 74 patients, agreement remained robust (Pearson r = 0.851, Spearman ρ = 0.829, mean absolute error = 1.52, root mean squared error = 2.20). Conclusions This AI-based pipeline enables automated, reproducible Bergmann-Kliesch Score assessment from routinely stained testicular biopsy WSIs, demonstrating strong agreement with manual pathologist evaluation. The system shows promise as a clinical decision-support tool in TESE workflows. External multicentric validation and prospective correlation with ICSI outcome data are warranted in future studies.
