Contributions to the environment of priority Polynuclear Aromatic Hydrocarbons from the Coal Camp Mechanic Village (CCMV) in Enugu, Nigeria

ABSTRACT The Coal Camp Mechanic Village(CCMV) in Enugu,Nigeria generates automobile oily wastes which could contain the Polynuclear Aromatic Hydrocarbons (PAHs) and distribute them to the proximal segments of the environment. The current study investigated the presence and levels of the PAHs in soils of the CCMV, as well as in water and sediments of the nearby Okpete Stream. Samples were collected using standard methods and PAHs detected with a Gas Chromatograph interfaced with Flame Ionization Detector. Mean concentrations of the PAHs [except 1,2-Benzanthracene and Benzo(k) fluoranthene] exceeded the World Health Organization's permissible limit of 0.2µg/L for drinking water. Two Principal Components (PCs) formed the extraction solution, with a cumulative percentage variability contribution of 96.6% in the original 16 variables; with PC 1 most highly correlated with Fluorene/1,2,5,6-Dibenzanthracene (0.979) and PC 2 with Acenaphthene (0.982). There was significant spatial heterogeneity in mean levels of the PAHs in water samples (Sig. F=0.013) at P<0.05, and Indeno (1,2,3-cd) pyrene (16.13429 µg/L) and Fluoranthene (92.30784 µg/L) contributed the difference most. Results raise public health alert as PAHs are known carcinogens. Recycling of waste/used oils is recommended for environmental sustainability

Assessment of Hepatoprotective and Antioxidant Effect of Acioa barteri Extract (ABE) in Alloxan-Induced Diabetic Rats

This study aimed to investigate the effects of Acioa barteri extract (ABE) on hepatocellular enzyme activity, hepatic function, and antioxidant stress indices in diabetic rats induced with alloxan. The antidiabetic effect of ABE was evaluated in six experimental groups: normal controls, diabetics untreated, diabetics treated with 200mg/kg, 400mg/kg, or 800 mg/kg ABE, and diabetics treated with 3 mg/kg Glibenclamide. ABE was orally administered to induce diabetes, and alloxan-monohydrate was intraperitoneally administered. Diabetic untreated rats exhibited significantly elevated levels of alkaline phosphatase, aspartate, and alanine transaminase activities, as well as higher concentrations of total bilirubin, conjugated bilirubin, and malondialdehyde. They also showed decreased levels of total protein, albumin, globulin, and protein-bound iodine, along with reduced antioxidant enzyme activity. In contrast, diabetic rats administered ABE demonstrated reduced hepatocellular enzyme activity and improved hepatic function. These rats exhibited increased levels of total protein, globulin, and albumin, as well as higher levels of glutathione, superoxide dismutase, glutathione peroxidase, and catalase activities, compared to diabetic untreated rats. The findings suggest that ABE may help prevent oxidative stress and improve hepatic functions in diabetic rats. ABE treatment led to decreased hepatocellular enzyme activity and improved hepatic function, along with increased antioxidant enzyme activities. These results highlight the potential of ABE as a therapeutic option for diabetes-induced liver dysfunction. Further research is warranted to explore its mechanisms of action and potential clinical applications

Computer-aided drug design in anti-cancer drug discovery: What have we learnt and what is the way forward?

The escalating prevalence of cancer on a global scale, coupled with the inadequacies of present-day therapies and the emergence of drug-resistant cancer strains, has necessitated the development of additional anticancer drugs. The traditional drug discovery process is long and complex, and the high failure rate of new drugs in clinical trials further highlights the need for computational approaches in anticancer drug discovery. Computer-aided drug design (CADD), including molecular docking, molecular dynamics simulations, QSAR analysis, and machine learning, are employed to predict the efficacy of potential drug compounds and pinpoint the most auspicious compounds for subsequent testing and advancement. This article provides an overview of contemporary computational approaches employed in the design of anti-cancer drugs. It highlights a range of small molecules that have been identified as capable of impeding cancer growth and migration through various mechanisms, including cell cycle arrest/apoptosis, signal transduction inhibition, angiogenesis, epigenetics, and the hedgehog pathway. It also examines the constraints of computational techniques and presents remedies to surmount these limitations in the development and identification of efficacious anticancer compounds