Edo University, Iyamho

Abstract Nanotechnology is a rapidly growing, transformative approach in the field of male reproductive health, addressing dire challenges connected with infertility. This review explores the application of nanotechnology in enhancing sperm selection and processing, which are vital for improving reproductive outcomes in assisted reproductive technologies (ART). Traditional methods, such as swim-up assay and density gradient centrifugation, often yield variable recovery rates and may not be efficient with poor sperm samples. In contrast, innovative techniques utilizing nanoparticles, especially magnetic-activated cell sorting (MACS), demonstrate superior efficacy in selective isolation of viable sperm by targeting specific biomarkers. The unique properties of nanoparticles, including tunable size and surface charge, enhance their binding capabilities, thereby improving the precision of sperm selection.C Additionally, advancements in assisted reproductive technologies, showcase the potential of nanoparticles in sperm transport and gamete preservation. Despite the potential benefits, challenges remain, including the need for standardized protocols and addressing safety concerns associated with nanoparticle use. This review underscores the necessity for future studies to fully harness the potential of nanotechnology in overcoming male infertility, ultimately contributing to improved ART success rates and better reproductive health outcomes.

Industrialization has significantly increased human exposure to co-occurring psychological stressors and environmental toxicants, including heavy metal contamination. The combined exposures to chronic stressors and heavy metal exposures are common, but their effects on the kidney and liver are not known. Hence, this study investigates how exposure to heavy metals, manganese (Mn) and nickel (Ni), in combination with a chronic stress paradigm in the rat model, impacts the structural and functional integrity of the kidney and liver. Adult Wistar rats were divided into the control, stress-only, Mn-only, stress + Mn, Ni-only, and stress + Ni groups. The rats were treated intraperitoneally with either vehicle, Mn (25 mg/kg), or Ni (25 mg/kg) with/without a restraint stress paradigm for two weeks. Blood, liver, and kidney samples were collected after sacrifice to measure hematological parameters, perform liver and kidney function tests, perform histological examinations, and assess oxidative stress markers. Our results showed significant liver and kidney damage, evidenced by the increased alkaline phosphatase, aspartate aminotransferase, alanine aminotransferase, bilirubin (total, direct, and indirect), urea, uric acid, and creatinine levels in all treatment groups when compared to the control. Histological examinations revealed cell degeneration and necrosis, as well as glomeruli atrophy, tubular degeneration, and parenchymal disintegration in the liver and kidney, respectively. Also, there was increased lipid peroxidation, accompanied by a concomitant decrease in endogenous antioxidants, such as superoxide dismutase, catalase, and glutathione peroxidase, in the liver and kidney. When combined, these factors lead to severe inflammation, cell degeneration, and necrosis, especially with Ni exposure. In conclusion, this study reveals that co-exposure to stress and metals exacerbated hepatorenal disruptions, likely due to worsened oxidative damage.

Hypertension is a major cause of cardiovascular morbidity and mortality worldwide, necessitating the search for safe and effective therapeutic alternatives. Moringa oleifera Lam., a medicinal plant rich in bioactive phytochemicals, is traditionally used in cardiovascular management, but its effects under normotensive conditions remain insufficiently defined. This study evaluated the acute and sub-acute cardiovascular effects of M. oleifera leaf extract in normotensive rats. Wistar rats of both sexes received oral doses of 100, 200, or 400 mg/kg extract, while controls received acacia solution. Acute responses were assessed at 0, 1, 2, 4, and 8 h, and sub-acute effects over 28 days. Blood pressure, pulse rate, and mean arterial pressure were measured non-invasively. Cardiac tissues were examined histologically using haematoxylin and eosin staining. The extract produced mild, time- and dose-dependent cardiovascular modulation without statistically significant changes or sustained hypotension. Cardiac histoarchitecture remained largely preserved, with only mild, non-progressive vascular changes at higher doses. These findings indicate a favourable cardiovascular safety profile and support further evaluation in hypertensive models.

This study examined into how the removal of fuel subsidies impacted Nigerian small firms' operational costs and growth constraints. Regression, correlation, and descriptive analyses were performed on a sample of 112 respondents using a structured questionnaire. Findings indicate that the removal of fuel subsidies greatly increased the cost of transportation, raw materials, energy, inflation, and overall operational costs. These cost constraints resulted in lower profit margins, lower sales turnover, fewer job opportunities, difficulties finding fairly priced raw materials, and greater threats to corporate viability. While regression results showed that fuel subsidy removal accounts for 44.7% of the variance in growth constraint (R² = 0.447, β = 0.668, p < 0.001), correlation analysis showed a significant positive relationship between fuel subsidy removal and growth constraints (r = 0.668, p < 0.01). The study concludes that small business survival is severely impacted by the policy change, despite the fact that it is economically strategic to sustain national fiscal stability. In order to mitigate the negative effects on small businesses, policy solutions include a strong emphasis on focused cushioning measures, easy access to capital, and supportive infrastructure.

Credit card fraud is a menace to financial institutions, but detection is compromised by highly imbalanced transaction datasets. This study proposes an advanced machine learning framework optimized for fraud detection. To address the issue of data imbalance, SMOTE-Tomek Links is applied to synthetically generate minority fraud cases while removing noisy, overlapping majority-class instances. Recursive Feature Elimination (RFE) is deployed to identify the optimal features, and RandomizedSearchCV automates hyperparameter optimization. The study introduces a Stacked Logistic Regression ensemble to combine the predictive capacity of optimized Random Forest and XGBoost base classifiers. The model’s effectiveness is assessed using seven evaluation methods: accuracy, recall, precision, confusion matrix, F1-score, Receiver Operating Characteristic Area Under the Curve (ROC-AUC) score and the Area Under the Precision-Recall Curve (AUC-PR) score. Findings reveal that the proposed stacked model performance surpasses both individual base models. While achieving deceptively high baseline accuracy across all models, the stacked ensemble delivers a superior AUC-PR score of 0.8207 and an F1-score of 0.93. This minimizes the confusion matrix misclassifications to just 20 False Negatives and 5 False Positives. The framework provides a cost-optimized operational engine that aggressively mitigates bank fraud losses while successfully shielding legitimate cardholders from accidental checkout declines.