Purpose: Testicular cancer (TC) is the most common malignancy among young adult males. The etiology is multifactorial, and both environmental and genetic factors play an essential role in the origin and development of this tumor. In particular, exposure to environmental endocrine disruptors (EEDs), resulting from industrialization and urbanization, seems crucial both in pre-and postnatal life. However, the lack of long-term studies on a wide caseload and the difficulty in evaluating their toxic effects in vivo make it challenging to establish a causal link. This review aims to discuss the main human epidemiological studies currently available in the literature to define a possible association between these chemicals and TC. Methods: A comprehensive Medline/PubMed and Embase search was performed, selecting all relevant, peer-reviewed papers in English published from 2002 to January 2022. Other relevant papers were selected from the reference lists. Results: To date, literature evidence is limited due to the scarcity and heterogeneity of human studies and shows controversial data, highlighting the complexity of the topic. However, most human epidemiological studies seem to point toward a correlation between EEDs exposure and TC. Conclusion: Although the molecular mechanisms are not yet fully understood, the role of EEDs in TC onset is plausible, but several factors, such as the individual genetic background, the exposure time, and the complex mechanism of action of these chemicals, do not allow defining the causal link with certainty and make further studies necessary to investigate this complex topic.

Purpose: Sexual dysfunctions are often experienced by male patients with acromegaly, due to a combination of hypogonadism and other comorbidities, but are a scarcely investigated complication. Erectile dysfunction is also closely related to cardiovascular diseases through endothelial dysfunction. Therefore, this project aimed to assess the prevalence of erectile dysfunction in a population of acromegalic men and evaluate its association with cardio-metabolic disorders, also exploring associations with androgen and estrogen receptor gene polymorphisms. Methods: Sexually active men aged 18–65 with previous diagnosis of acromegaly were recruited. Clinical and laboratory data were retrospectively collected. Each patient also provided a blood sample for AR and ERβ gene polymorphisms analyses and filled out the IIEF-15 questionnaire. Results: Twenty men with previous diagnosis of acromegaly (mean age 48.4 ± 10.0 years) were recruited. 13/20 subjects (65%) had erectile dysfunction, but only four had a concurrent biochemical hypogonadism, with no significant correlation with IIEF-15 scores. Total testosterone negatively correlated with sexual intercourse satisfaction domain (ρ = − 0.595; p = 0.019) and general satisfaction domain (ρ = − 0.651; p = 0.009). IGF-1 levels negatively correlated with biochemical hypogonadism (ρ = − 0.585; p = 0.028). The number of CAG and CA repeats in AR and ERβ receptors genes was not significantly associated with IIEF-15 scores or with GH/IGF-1 levels, but a negative correlation between CA repeats and the presence of cardiomyopathy (ρ = − 0.846; p = 0.002) was present. Conclusions: Men with acromegaly have a high prevalence of erectile dysfunction, but it does not appear to be correlated with treatments, testosterone levels and AR/ER-beta signaling. Nonetheless, a shorter CA polymorphic trait (ERbeta) is associated with the presence of cardiomyopathy. If confirmed, these data may suggest an association between an incorrect hormonal balance and increased cardiovascular risk in acromegaly subjects.

Background: Male factors contribute to approximately half of all cases of couple infertility, and semen analysis remains the cornerstone of the diagnostic evaluation. In recent years, artificial intelligence (AI) has emerged as a promising tool to improve the objectivity and reproducibility of semen analysis and sperm selection in assisted reproductive technologies (ART). Materials and Methods: This narrative review provides an overview of the current applications of AI in seminology, focusing on sperm motility, morphology, DNA fragmentation, sperm selection for intracytoplasmic sperm injection (ICSI), and sperm retrieval in men with nonobstructive azoospermia. Beyond laboratory applications, the review also highlights the emerging role of machine learning in predicting reproductive outcomes and supporting clinical decision‐making in andrology. Results and Discussion: Although the available evidence is encouraging, most studies remain limited by small and highly selected datasets, a lack of external validation, and scarce evidence on clinically meaningful outcomes. Future progress in the field will likely depend not only on improvements in algorithm performance, but also on the availability of high‐quality, representative datasets to enable robust validation and reliable clinical translation. While issues related to data quality, algorithmic bias, and regulatory and ethical aspects still need to be addressed, AI has the potential to become a valuable decision‐support tool in reproductive medicine. Conclusions: Nonetheless, further prospective multicenter studies are needed before these technologies can be routinely integrated into clinical practice.

Background/Objectives: Aberrant DNA methylation of imprinted genes and increased sperm DNA fragmentation (SDF) have been implicated in male infertility. However, their impact on assisted reproductive technology (ART) outcomes remains unclear. This pilot study aimed to investigate SDF and methylation status of H19, IGF2, and PEG1/MEST in relation to fertilisation and embryo development following intracytoplasmic sperm injection (ICSI). Methods: Twenty male partners of women undergoing ICSI were recruited and classified according to ART outcome into viable embryos (VEs, n = 7), non-viable embryos (NVEs, n = 7), and no fertilisation (NF, n = 6). Before sperm selection, an aliquot of each seminal sample was used for semen analysis according to WHO, 2021, SDF assessment (TUNEL assay), and sperm DNA methylation analysis of H19, IGF2, and PEG1/MEST (pyrosequencing). Results: Semen parameters were above the fifth percentile. SDF was significantly lower in the VE group compared with the other groups. H19 CpG1 methylation correlated positively with viable embryos (p = 0.016), while H19 CpG2 island showed a positive correlation with sperm concentration (p = 0.028). In male/couple infertility cases, total H19 methylation correlated negatively with SDF (p = 0.050). IGF2 CpG3 island methylation correlated positively with viable embryos (p = 0.027). Total PEG1/MEST methylation was positively correlated with fertilisation events (p = 0.002) and viable embryos (p = 0.011). PEG1/MEST CpG2 island also positively correlated with sperm motility (p = 0.034), while CpG3 and CpG4 showed significant correlations with fertilisation (p < 0.001; p = 0.004). Conclusions: This pilot study shows that SDF and sperm methylation levels of H19, IGF2, and PEG1/MEST are related to ICSI outcomes, supporting that sperm molecular and epigenetic features may influence fertilisation and embryo development.