University of Maiduguri

ObjectivesSubstance abuse among adolescents is a major concern not only in developing countries but also worldwide. Datura metel (D. metel), commonly known as Datura or Devil’s Trumpet, is a plant containing several toxic compounds, including alkaloids (such as scopolamine, hyoscyamine, and atropine). However, consuming D. metel or its derivatives can significantly impact the brain, though its mechanism remains elusive. Therefore, this study evaluated the effects of D. metel and alcohol cocktail on the hepato-prefrontal-cortical axis.MethodsThirty-five male Sprague Dawley rats were divided randomly into five groups (A–E). Group A received distilled water, Group B received 300 mg/kg of D. metel, and Group C received 700 mg/kg of alcohol. Group D received 300 mg/kg of D. metel + 700 mg/kg of alcohol, while Group E received 150 mg/kg of D. metel + 350 mg/kg of alcohol. Tissues from the liver and prefrontal cortex (PFC) were collected for morphological, histological, and immunohistochemical studies.ResultsThere was a significant increase in body weight in control group A compared to other experimental groups. Hematoxylin and eosin staining revealed a mild attenuation in the cytoarchitecture of the liver and PFC with increased necrosis, apoptosis, vacuolation, and neuronal death in experimental groups compared to control group A. Increased microglial activity was observed in groups B–E, whereas group A showed normal neuronal arrangement with the NeuN antibody compared to experimental groups. Serum liver function biomarkers (alkaline phosphatase, alanine transaminase, and aspartate aminotransferase) were statistically significantly higher in Groups C and D when compared to Group A.ConclusionCombined D. metel and alcohol negatively impact the liver and PFC of experimental rats.

ABSTRACT Background Informal food supply chains in regions affected by conflict present significant risks associated with the transmission of foodborne pathogens and the development of antimicrobial resistance (AMR). The objective of this research is to investigate the prevalence and AMR patterns of Salmonella spp., Shigella spp., and Listeria monocytogenes in poultry feeds and ready-to-eat (RTE) foods available for sale in Maiduguri, located in northeastern Nigeria. Methods A cross-sectional survey was conducted involving the collection of 120 poultry feed samples and approximately 251 samples of RTE foods, with 120 samples specifically designated for the analysis of Listeria. Pathogen isolation was performed using standardized microbiological protocols (ISO/FDA-BAM), and the assessment of AMR was conducted utilizing the disk diffusion method in accordance with Clinical and Laboratory Standards Institute (CLSI) guidelines for Shigella (n=5), Salmonella (n=15), and Listeria (n=3) isolates. Prevalence rates were calculated with 95% confidence intervals derived from the Wilson score method. Results The study revealed a prevalence of Salmonella spp. at 10.0% (95% CI 5.8–16.8) in poultry feeds, with a maximum occurrence of 25.0% identified in the Monday Market, contrasting with a prevalence of 2.3% (0.8–6.7) reported in RTE foods, particularly in Bulumkutu fruits and meats from the Custom Market. Shigella spp. was identified in 3.33% (1.3–8.1) of feed samples and in 0.76% (0.1–4.2) of RTE foods, specifically within pineapple. L. monocytogenes was detected in 2.5% (0.8–7.1) of RTE foods, exclusively sourced from Baga Road market, including meat and sala sour milk. The isolates of Salmonella obtained from feeds demonstrated high levels of multidrug resistance (100% to tetracycline and 83.33% to fluoroquinolones), while Salmonella from RTE foods maintained resistance to tetracycline but exhibited a loss of resistance to fluoroquinolones. Notably, L. monocytogenes exhibited 100% resistance to both fluoroquinolones and cephalosporins while remaining sensitive to tetracycline. The presence of coliforms indicated inadequate hygiene conditions in the feeds, with 60.0% of samples showing contamination. Conclusion This initial study, which encompasses multiple pathogens within the conflict-affected region of Maiduguri, reveals significant upstream contamination of Salmonella in poultry feeds. It delineates the risks associated with ready-to-eat (RTE) foods and highlights the exclusive presence of L. monocytogenes in RTE products. Furthermore, the study indicates divergence in antimicrobial resistance (AMR) based on the food matrix. The findings underscore the urgent need for enhanced One Health surveillance, the implementation of improved hygiene practices in feed production, and the regulation of antimicrobial usage in informal poultry systems. Such measures are essential to effectively mitigate foodborne threats and the emergence of antimicrobial resistance in similarly underserved regions.

The distinguishing number is an important invariant used to measure the extent to which symmetries of graphs and permutation group actions can be broken by vertex labelings. In this paper, we investigate distinguishing labelings arising from permutation group actions with particular emphasis on Cartesian power constructions and wreath product actions. We establish structural bounds for distinguishing numbers in terms of orbit structure, stabilizers, and base size of permutation groups. Furthermore, we analyze the behavior of distinguishing numbers under Cartesian powers of sets and derive bounds for wreath product actions of the form G ≀ Sm acting on Xm.

Nanomedicine has enabled major advances in targeted therapeutics by improving drug bioavailability, precision delivery, and safety profiles. However, the rational design and reproducible synthesis of nanoparticles with tightly controlled physicochemical attributes such as size, morphology, and surface characteristics remain significant challenges due to the complex, nonlinear interplay of formulation and process parameters. Artificial intelligence (AI) and machine learning (ML) have emerged as powerful tools to address these limitations by enabling data-driven optimization, predictive modeling, and automated analysis across nanoparticle synthesis and characterization workflows. Recent advances demonstrate that AI-based models can accurately predict nanoparticle properties, optimize synthesis conditions, interpret high-dimensional characterization data, and forecast biological performance, thereby reducing experimental burden and accelerating translation. This review critically examines current AI and ML strategies applied to nanoparticle synthesis, optimization of key physicochemical attributes, characterization, and biological evaluation for nanomedicine applications. Emphasis is placed on comparative model performance, integration of experimental and computational pipelines, and emerging challenges related to data quality, interpretability, and generalizability. Collectively, this work highlights the transformative potential of AI-enabled nanotechnology while outlining key directions required for its reliable clinical translation. Automated Synthesis Platforms: Integrating AI and ML for Next-Generation Nanomaterials

Polycyclic aromatic hydrocarbons (PAHs) are environmental contaminants known for their persistence, toxicity, and potential health risks. Understanding their bioaccumulation in aquatic ecosystems is crucial for assessing environmental and human health hazards. This study examines the concentrations, toxic equivalency factors (TEFs), and human health risks associated with polycyclic aromatic hydrocarbons (PAHs) in fish samples collected from Tiga Dam, Kano State, Nigeria, during both rainy and dry seasons. Four fish species (Tilapia zilli, Oreochromis niloticus, Clarias anguillaris, and Heterotis niloticus) were analyzed for PAH contamination in their flesh, gills, liver, and intestines. PAH concentrations were determined using gas chromatography equipped with a flame ionization detector (GC-FID). The mean concentrations of total PAHs in Tilapia zilli ranged from 3.00E-03 to 7.39E-02 mg/kg in liver tissue, while concentrations in Oreochromis niloticus liver ranged from 2.66E-02 to 3.44E-01 mg/kg. The highest BaP equivalent concentration (BaPeq) was observed in the intestines of Tilapia zilli during the dry season, with a value of 1.64E-01 mg/kg. Hazard quotient (HQ) values for non-carcinogenic risk assessment exceeded the safety threshold (HQ > 1) in several fish tissues, particularly in the liver and intestines of Tilapia zilli and Oreochromis niloticus. Incremental lifetime cancer risk (ILCR) values also suggested significant carcinogenic risks, with ILCR values exceeding the acceptable risk level of 1.00E-05 in liver and intestinal tissues for Heterotis niloticus. This study highlights the seasonal and tissue-specific accumulation of PAHs in fish from Tiga Dam, with potential health implications for consumers. This study reveals significant seasonal bioaccumulation of PAHs in fish from Tiga Dam, with liver and intestines showing the highest contamination. The associated health risks highlight the need for continuous monitoring and regulatory action to protect consumers and the environment.

This study examines the effect of intellectual capital and corporate governance on the firm value of listed non-financial companies in Nigeria over the period 2014–2023. Anchored on the Knowledge-Based View and Agency Theory, the study employs panel data from 56 firms listed on the Nigerian Exchange Group and applies fixed effects regression techniques to control for unobservable firm-specific heterogeneity. Intellectual capital is measured using the Value Added Intellectual Coefficient (VAIC) framework, decomposed into human capital efficiency, structural capital efficiency, and relational capital efficiency, while firm value is proxied by Tobin’s Q. Corporate governance mechanisms include board size, board independence, board meetings, board financial expertise, gender diversity, and ownership concentration. The results reveal that intellectual capital, particularly human capital efficiency, exerts a positive and statistically significant effect on firm value, underscoring the strategic importance of knowledge-based resources in emerging economies. Relational capital exhibits a weak positive effect, while structural capital is insignificant. Among governance mechanisms, board gender diversity is the only attribute with a positive and significant influence on firm value. The findings suggest that intellectual capital and inclusive governance structures play complementary roles in enhancing firm valuation. The study contributes to the limited Nigerian literature by providing long-term empirical evidence on the joint impact of intellectual capital and corporate governance on firm value and offers policy-relevant insights for regulators, managers, and investors.

This study investigates the regime-dependent effects of exchange rate movements on stock market performance in Nigeria from 1999Q1 to 2023Q4 using a Markov-Switching Vector Autoregression (MS-VAR) framework. The primary objective is to assess how the relationship between the Real Effective Exchange Rate (REER) and the All-Share Index (ASI) varies across different economic regimes. Preliminary analysis revealed a strong positive correlation (0.796) between REER and ASI, with both series being non-stationary at levels but integrated of order one. The MS-VAR model identified two distinct regimes: Regime 1, a stable state with 94.5% persistence representing normal economic conditions, and Regime 2, a volatile state representing short-term economic stress. In Regime 1, exchange rate movements positively influenced stock market performance (coefficient = 0.056), while in Regime 2, the impact was stronger (coefficient = 0.079). Impulse response analysis indicated that exchange rate shocks exert their highest effect on the stock market in the short term (0.047), diminishing to 0.022 in the long term. The findings underscore the importance of considering economic regimes in understanding the exchange rate–stock market nexus, offering insights for policymakers, investors, and financial analysts in managing market risks.

Breastfeeding is a cornerstone of child survival, growth, and development, yet exclusive breastfeeding (EBF) rates in Nigeria remain suboptimal. This cross-sectional study assessed breastfeeding practices among 242 lactating mothers in Nassarawa Local Government Area, Kano State. Data were collected using a semi-structured, interviewer-administered questionnaire and analyzed with SPSS (version 25). Descriptive and inferential statistics, including chi-square tests, were applied at a significance level of p<0.05. Findings revealed that 61.6% of mothers, initiated breastfeeding within the first hour after birth, while 67.8% fed their infants colostrum. Approximately 79.3% practiced exclusive breastfeeding, though only 65.1% sustained it for the recommended six months. Responsive breastfeeding practices were mixed: 80.6% practiced rooming-in, but only 47.9% breastfed on demand. Prelacteal feeding was reported by 21% of mothers, primarily involving water, honey, and herbal preparations, contrary to WHO/UNICEF guidelines. Significant associations were observed between breastfeeding practices and maternal socio-demographic factors, including age, parity, education, income, and occupation. Mothers with higher education and stable occupations were more likely to initiate early breastfeeding, sustain EBF, and avoid harmful practices. Despite relatively high initiation and colostrum use rates, EBF duration remains below the WHO target of 50% coverage by 2025. Cultural norms, socioeconomic conditions, and maternal employment were key barriers. This study underscores the urgent need for targeted interventions to address socio-cultural and economic barriers to optimal breastfeeding. Strengthening community education, healthcare counseling, and workplace breastfeeding support can significantly improve child nutrition outcomes in the study area.