Stochastic Modeling and Environmental Parameterization of Sperm Chemotaxis Dynamics Reveal Critical Determinants of Fertilization Success Under Physiological Constraints

In mammalian reproduction, the ability of sperm cells to move across diverse physiological conditions and reach the oocyte is crucial to the success of fertilization. In this work, we create a thorough stochastic computer model that simulates the dynamics of sperm chemotaxis in a limited two-dimensional microenvironment. This model takes into account important biological factors such as temperature, pH fluctuations, ambient flow, and chemotactic strength. Through comprehensive parameter sweeps and duplicate simulations, we measure fertilization success rates and timing distributions under various situations in order to systematically investigate the impact of these parameters on fertilization efficiency. Our model incorporates stochastic sperm mortality to represent chemical and immunological challenges, and environmental barriers to replicate physical and metabolic heterogeneities found in the female reproductive system. Using survival analytic frameworks such as log-rank tests and Kaplan-Meier curves, fertilization time distributions were examined. The results showed statistically significant variations in fertilization kinetics among chemotactic regimes and environmental variables. Furthermore, sperm density heatmaps emphasize the crucial role that directed motility plays in fertilization outcomes by highlighting spatial clustering dynamics that are influenced by external fluxes and the intensity of chemotaxis. The robustness of the observed effects is confirmed by statistical comparisons using the ANOVA and Kolmogorov-Smirnov tests. Our results give a prediction framework for comprehending sperm behavior in vivo and quantitative insights into the relative contributions of biophysical and biochemical elements influencing fertilization success. By clarifying the mechanics behind sperm navigation and egg encounter efficiency, this integrative modeling method paves the way for future experimental validation and could influence assisted reproductive technologies and fertility therapies.