Background/Objectives: Y chromosome microdeletions in the azoospermia factor (AZF) regions are a major genetic cause of severe male infertility, yet their relationship with hormonal profiles in azoospermic men remains unclear. This study aimed to investigate AZF microdeletions and associated hormonal parameters in azoospermic patients. Methods: Azoospermic patients were screened for AZFa, AZFb, and AZFc microdeletions using multiplex real-time PCR targeting sequence-tagged site (STS) markers (sY84, sY127, and sY254). Patients were categorized into AZF-negative and AZF-positive groups, with the latter further stratified according to their deletion subtype. Serum follicle-stimulating hormone (FSH), testosterone, and inhibin B levels were measured. Hormonal parameters were compared between groups using the Mann–Whitney U test, and a logistic regression analysis was performed to evaluate associations between hormonal variables and AZF deletion status. Results: AZF microdeletions were detected in 18.7% (17/91) of patients. Patients without AZF deletions showed a median FSH level of 17.40 (7.12–31.27) IU/L. In contrast, AZFc deletion carriers exhibited an intermediate median FSH level of 21.10 (16.11–26.10) IU/L and lower median inhibin B concentrations (25.50 [25.25–26.00] pg/mL) compared with AZF-negative patients (56.00 [33.50–106.50] pg/mL). Median testosterone levels in AZFc patients (3.61 [2.87–4.35] ng/mL) remained within the expected physiological range. However, no statistically significant differences were observed between the AZF subgroups for age (p = 0.262), FSH (p = 0.506), testosterone (p = 0.615), or inhibin B (p = 0.524). The logistic regression analysis also showed no significant association between hormonal parameters and AZF deletion status. Conclusions: Hormonal parameters alone are insufficient to predict the presence of AZF microdeletions in azoospermic men. These findings highlight the importance of routine genetic screening for accurate diagnosis, clinical management, and reproductive counseling in male infertility.

Background: Reactive oxygen species (ROS) are required for normal sperm function, but when they accumulate, they cause oxidative stress, DNA damage, impaired motility, and loss of viability. Heat stress—scrotal hyperthermia, in particular—also degrades sperm quality. How thermal and oxidative stress jointly lead to sperm dysfunction is still poorly understood, which hinders the setting of evidence-based occupational exposure limits and the design of sperm preservation protocols. Objective: We developed a mathematical framework that combines oxidative stress (ROS kinetics) with thermal stress (heat diffusion) to estimate sperm survival and to derive dose–response relationships. The model is meant to generate hypotheses that independent experiments can test; it is not a validated clinical predictor of male infertility. Materials and methods: Exposure ranges, biological thresholds, and dose–response parameters were taken from published in vitro studies on human and animal sperm (1995–2024). Records were retrieved from PubMed and Web of Science with the search terms “ROS sperm”, “thermal stress male reproduction”, and “hydrogen peroxide spermatozoa”. Studies were retained if they quantified ROS concentration, H₂O₂ exposure, or thermal dose in relation to sperm motility, viability, or DNA integrity; reviews, single case reports, and studies without quantitative dose–response data were excluded. Each data set was labeled by species (human, rat, bull, and others) and by sperm source (ejaculated or testicular), and differences in experimental conditions, medium composition, and temperature were recorded. A probit model was combined with a diffusion–reaction equation for ROS and with Fourier’s heat equation to simulate predefined exposure scenarios. The Python 3.14.5 script was compiled in the online interface, was used for probit fitting and plotting. To reflect differences in cellular antioxidant capacity, protected, normal, and vulnerable sperm were modeled as three separate phenotypic populations. Results: Predicted survival depended mainly on ROS concentration, thermal dose, and exposure time. Changing the rates of ROS generation and degradation altered the predicted oxidative exposure and survival probability appreciably. In the thermal simulations, viability declined with increasing dose, and the critical thermal distance varied inversely with thermal severity. The model separated four biological zones: signaling (about 100 nM H₂O₂), impaired motility (15 μM H₂O₂, roughly 1–2 h of exposure), DNA damage (50 μM H₂O₂), and lethality (≥200 μM H₂O₂). Antioxidant capacity and exposure duration strongly shaped the response to both oxidative and thermal stress. Conclusions: Sperm survival depends strongly on the magnitude and duration of oxidative and thermal exposure. The framework offers a quantitative basis for studying stress-dependent changes in sperm viability and yields hypotheses that can be tested experimentally. Before any clinical use, it needs independent validation under standardized, prospectively defined protocols; for now, it serves as a research tool for generating hypotheses and comparing exposures.