MODELLING SPERMIOGRAM USING HISTOLOGICAL, HORMONAL AND BIOCHEMICAL PARAMETERS IN WISTAR RATS EXPOSED TO MONOSODIUM GLUTAMATE

Background Spermiogram remains central to male fertility diagnosis, yet sperm parameters, reproductive hormones, oxidative-stress biomarkers, and testicular histology are typically evaluated as separate, unlinked measures rather than as components of one interacting biological system. Integrating these domains into a single predictive model could substantially improve the interpretive power of the spermiogram, but such modelling requires data spanning a wide physiological range of testicular function.ObjectivesThis study developed and evaluated a multivariate model linking testicular histomorphometric, hormonal, and biochemical parameters to spermiogram outcomes in Wistar rats. Graded, chronic oral monosodium glutamate (MSG) exposure was used purely as an experimental paradigm to generate this physiological range of testicular variation, rather than as an object of toxicological investigation.Method. Twenty-five male Wistar rats were randomly assigned to five groups (n = 5/group): a control group and four groups receiving MSG at 30, 100, 300, or 1000 mg/kg body weight daily via oral gavage for 70 consecutive days. Spermiogram parameters (sperm concentration, motility, morphology), serum LH, FSH, and testosterone, testicular oxidative markers (MDA, SOD, GSH, CAT), caspase-3 activity, and testicular histomorphometry (germinal epithelium height, tubular diameter, luminal diameter, cross-sectional area) were subsequently assessed. Data were analysed by one-way ANOVA with Dunnett&apos;s test, Pearson&apos;s correlation, and multiple linear regression to identify independent predictors of sperm concentration.ResultsThe five exposure groups produced a graded range of testicular change, from near-normal parameters at the lowest dose to marked disruption at the highest (p < 0.05). Sperm concentration count correlated strongly with testicular histomorphometric indices (r = 0.696–0.812), oxidative markers (r = 0.592–0.728), and caspase-3 (r = -0.702). Among the regression models built, the histomorphometric model explained the greatest proportion of variance in sperm concentration (R² = 0.754, adjusted R² = 0.688, p < 0.001), with luminal diameter as the strongest individual predictor (p = 0.004), outperforming the hormonal model (R² = 0.644, p = 0.003) and the oxidative/apoptotic model (R² = 0.519, p = 0.022).Conclusion Testicular histomorphometry provides the strongest predictive link to spermiogram outcome among the parameter domains examined, ahead of hormonal and oxidative/apoptotic markers. These findings support an integrated, multi-parameter modelling approach, anchored in testicular structural indices, as a more powerful strategy for predicting spermiogram outcomes than single-marker assessment.