COAST

Thermal stability study of metal carboxylates of Cucurbita pepo seed oil

O.M. Folarin — 2024-10-07

No Abstract

Comparative wood anatomy of four vernonia delile species (Asteraceae) in southwestern Nigeria

T.A. Abeegunrin — 2024-10-07

Wood anatomy of four Vernonia Delile species in Southwestern States of Nigeria was investigated with a view to identifying the anatomical features of the genus that could be used to delimit the taxa. Plant samples were collected from Oyo, Ekiti, Osun and Ondo States. Transverse, tangential and radial longitudinal sections were made from the wood of the species of Vernonia using Reichert sliding microtome at 10µm thickness. The woods were also macerated with Schultze's fluid to separate the tissues and cells. The macerates and cut sections were stained with Safranine O reagent to reveal the differences in tissue arrangements, shapes and cell inclusions. The four species showed common anatomical features: pore shape at transverse plane are oval, round, rectangular circular to cylindrical, simple pitting of vessel elements and presence of - uniseriate, biseriate and multiseriate rays. The wood characteristics that can be used to distinguish the taxa are absent and presence of : tylose, fibre length and percentage of solitary vessel, axial parenchyma type and its absence. These features conferred significant taxonomic difference in the species and members were categorized into three major groups. These findings serve as baseline for further research such as molecular studies.

Synthesis of structured zinc selenide for optoelectronic applications

O. Olubosede — 2024-10-07

In this paper, synthesis of Zinc Selenide (ZnSe) based photovoltaic materials deposited by electrode position method. The material films have been characterized for their optical properties using UV-VIS spectrophotometer with wavelength range of 300 nm – 900 nm and electrical conductivity using photoelectrochemical (PEC) cell measurement. The conductivity type of the electrodeposited materials was investigated together with the tuning of the optical phenomena. The materials deposited were obtained by varying deposition time from 5 minutes to 15 minutes for ZnSe. It was observed that the optical properties of the materials increased with an increase in the time of deposition. The optical band gap of ZnSe was found to be in the range between 2.03 and 2.46 eV. The PEC signal results revealed ZnSe as an n-type material.

Deciphering human estrogen receptor-2 inhibitor from Momordica charantia: Computational models against breast cancer

J.A. Saliu — 2024-10-07

HER-2, or Human Epidermal Growth Factor Receptor-2, is a constituent of the epidermal growth factor receptor family, possessing tyrosine kinase properties. Its over-expression has been correlated with breast cancer. On the other hand, the pharmacological potential of Momordica charantia has been attributed to the phytocompounds. Herein, the inhibiting potential of phytocompounds from M. charantia against HER-2 was investigated using computational approaches. Maestro Schrodinger software (2021 v 12.1) was used to perform molecular docking, molecular mechanics generalized Born surface area (MM/GBSA), and pharmacokinetics prediction of a hundred phytocompounds from M. charantia against HER-2. The result revealed that among the phytocompounds, five (5) showed promising inhibitory potential comparable to the standard drug, Gefitinib. The MM/GBSA result showed that Rutin, Quercetin, Isoquerrcitrin, Folic Acid, and riboflavin formed a more stable complex with HER-2 than Gefitinib. The pharmacokinetics profile of the hit compounds showed that the hit compounds except riboflavin violated two or more of Lipinski's rule of five. In conclusion, the bioactive compounds found in M. charantia could potentially act as primary candidates for the creation of effective inhibitors targeting HER-2 in the treatment of breast cancer.

Detection of unhealthy websites using machine learning

O.A. Gbadamosi — 2024-10-07

In recent years, advancements in Internet and cloud technologies have led to a significant increase in electronic trading in which consumers make online purchases and transactions. Accompanying this achievement are vices like unauthorized access to users' sensitive information and damages to enterprise resources. Phishing is one of the familiar attacks that trick users to access malicious content and gain their information. This study aims to develop an efficient machine-learning program to detect phishing websites with high accuracy. Most phishing webpages look identical to the actual web pages and various strategies for detecting phishing websites, such as blacklisting, and heuristics, among others have been suggested. Existing research works showed that the performance of the phishing detection system is limited and there is a demand for intelligent techniques to protect users from cyber-attacks. A Uniform resource locator (URL) detection technique based on a supervised machine learning approach – Naïve Bayes is employed and implemented in Python programming language. The efficacy of this approach was determined on a phishing dataset made up of 7900 malicious and 5800 legitimate sites, respectively. The results show that using the proposed methodology an accuracy of 96% can be achieved by using stacking, filtering along the Naïve Bayes and logistic regression. This study thoroughly investigates the use of machine laearning with features extracted from the URLs and was able to showcase common words for the identification of either phishing (unhealthy) or good websites and proffered a guide to end users against the recent approaches in malicious URLs detection.

Exploring the therapeutic potential of tomato varieties in Alzheimer's disease: A focus on radical scavenging abilities and acetylcholinesterase inhibition

O.Y. Adeniran — 2024-10-07

Alzheimer's disease presents a significant global health challenge, with limited effective treatments available. Natural compounds, particularly those found in fruits and vegetables, have garnered attention for their potential therapeutic benefits in Alzheimer's disease. In this study, investigation was carried out on the antioxidant and neuroprotective properties of three tomato varieties Trichosanthes cucumerina (Snake tomato), Solanum lycopersicum Linn (Hausa variety), and Solanum lycopersicum Linn (Yoruba variety) in an Alzheimer's disease model induced by aluminum chloride using Drosophila melanogaster. Through in vivo and in vitro analysis, the radical scavenging abilities and acetylcholinesterase inhibition of each tomato variety was assessed. Findings reveal that Snake tomato exhibits potent radical scavenging abilities and significant AChE inhibition, suggesting its therapeutic potential in mitigating Alzheimer's disease pathology. Additionally, the antioxidant properties of Snake tomato correlated with its phenolic and flavonoid contents, highlighting its neuroprotective effects. While Solanum lycopersicum Linn (Hausa and Yoruba varieties) also demonstrated antioxidant properties, Snake tomato emerged as the most promising candidate for Alzheimer's disease management. These results show the importance of exploring natural compounds as alternative therapeutic approaches for Alzheimer's disease and warrant further investigation into the mechanisms underlying the therapeutic effects of tomato varieties.