Sumerianz Journal of Medical and Healthcare

    
Online ISSN: 2663-421X
Print ISSN: 2706-8404

Quarterly Published (4 Issues Per Year)

Journal Website: https://www.sumerianz.com/?ic=journal-home&journal=31

Archive

Volume 7 Issue 3 (2024)

Heavy Metal Pollutants Or Contaminant In Soil Samples Obtained From Wash Boreholes Within Pantisawa, Yorro L.G.A. Of Taraba State

Authors : Bashir K. Bello ; Hassan Braimah Yesufu ; Hamza Hananiyah Milagawanda ; Garba Tom Mohammed
DOI : doi.org/10.47752/sjmh.73.67.76
Abstract:
The problem of environmental pollution and its compartments due to an increase in contamination as a result of the accumulation of heavy metals and microorganisms from soil has raised wide-spread of concerns in different parts of the nations and this has compromised the ability of the environments to foster life and render them an intrinsic value. Hence the study aimed to ascertain the level of environmental pollution in soil from wash borehole within Pantisawa Yorro Local Government Area of Taraba State, Nigeria. A total of 45 samples for soil were collected aseptically from the five different zones (Pantisawa Main Market YM, Kapazang YG, Dola YD, Kallau YK and Zabi YZ) of Pantisawa. The levels of trace metals in soil samples were determined using Atomic Absorption Spectroscopy (AAS) PG-990. The results were analyzed using SPSS Version 20. The soil samples result for these metals revealed that iron concentration was between 3000-4010mg/kg most especially for site SD which is higher than all other elements analyzed. Zinc ranges from 2.54-6800mg/kg which is above the standard as prescribed by WHO and FEPA in soil and also exceeded the dutch target values of (Zn: 50mg/kg and Cu: 30mg/kg) in some of the sampling sites. Nickel was between 8.47-19.09 mg/kg in soil samples, this is below the toxicity threshold limit of 35mg/kg for safe environment as stated by WHO. Arsenic ranges from 53.06mg/kg–141mg/kg, which is higher than the admissible limit of 50mg/kg in soil recommended by UNEP. The order of all the metal concentration in the areas was Fe>Zn>Mn>As>Pb>Cu>Mn>Co and Cd respectively.  Based on this study, the high concentration of the metals such as Zn, As, Cd, Pb, and Co in some of these sites most especially SK, SM and SD within Pantisawa revealed that some of the soil samples collected from these areas were contaminated with heavy metal pollutants which may have serious health risk to the people using it for various activities. The higher concentrations of these toxic metals in soils need to be monitored regularly for heavy metal enrichment.

Pages: 67-76

Potential Application of Essential Oils in the Treatment of Neurodegenerative Diseases: a Case Study of Essential oil from  Hyptis Suaveolens (L.) Poit

Authors : Owokotomo Ignatius Adekunle ; Ayeye Mojisola
DOI : doi.org/10.47752/sjmh.73.57.66
Abstract:
The main method for treating nerve-signaling disorders like Alzheimer’s disease has been chemical suppression of acetylcholinesterase. Limited treatment options have driven the research into extracts from indigenous plants. In this study, the chemical constituents, anti-cholinesterase, and radical scavenging potentials of the essential oil and the polar constituents (decoction water) of a Nigerian variety of the medicinal plant, Hyptis suaveolens (L.) Poit, were investigated. Essential oil from the leaves of the medicinal plant was obtained through hydro-distillation, and the chemical composition was determined using gas chromatography-mass spectrometry (GC-MS). Radical scavenging activity potential and acetylcholinesterase inhibition activity were carried out using the colorimetric method. The GC-MS analysis revealed 24 chemical compounds, including β-Caryophyllene (15.31%), β-Phellandrene (9.73%), trans-α-Bergamotene (6.94%) and Fenchone (5.79%) as major components. The phytochemicals present in the polar constituent (the decoction water) of the leaves of H. suaveolens were alkaloids, glycosides, flavonoids, tannins, steroids, terpenoids, and saponins. Bioactivity assessment revealed significant antioxidant activities in essential oil extracts with values ranging from (DPPH = 38.80 ± 0.04 to 69.33 ± 0.12 %, ABTS = 2.84 ± 0.01 to 11.26 ± 0.26 mg TEAC /g, FRAP = 10.89 ± 0.01 to 15.79 ± 0.33 mg AAE /g and NOx = 26.06 ± 0.03 to 71.87 ± 0.21 %). Higher acetyl-cholinesterase inhibition activity was recorded for the essential oil compared to the polar constituents with values ranging from 10.42 ± 0.12 to 46.50 ± 0.19 %. Findings from this study highlight the antioxidant and anticholinesterase potential of extracts from Hyptis suaveolens (L.) Poit.

Pages: 57-66

An Enhanced Adaptive Medical Diagnostic Model Driven By Genetic–Neuro-Fuzzy Algorithms

Authors : O. Ohwo Stephen ; O. Erihri Jonathan ; N. Okwor Anthony ; A. Adeyeye Emmanuel
DOI : doi.org/10.47752/sjmh.73.41.56
Abstract:
This research aims at developing adaptive medical diagnostic system driven by genetic, neural network and fuzzy logic algorithms for effective diagnosis of tuberculosis. Medical diagnosis for tuberculosis disease is a complex decision process that involves a lot of vagueness and uncertainty management, since the disease has multiple symptoms. The use of several algorithms has been explored in clinical diagnosis models for diagnosing and prescribing therapy for tuberculosis, but has challenges in transforming the vagueness and uncertainty of multiple symptoms due to the noisy nature of the disease data and over fitting of the models, this had led to the challenge of accurate classification, training, optimization, diagnosis and prescription of therapy. Object Oriented Analysis and Design (OOAD) and System Structured Analysis and Design (SSAD) methodologies were adopted in the research. The methodology involved obtaining four hundred and thirty (430) clinical data from patients with tuberculosis records at the Tuberculosis and Leprosy Hospital, Eku, Delta State. The obtained data were pre-processed using missing values imputation and numeric data encoding methods. Thereafter, a genetic algorithm was applied to the processed data to select six relevant features from the initial number of 16 features (Cough, Night sweats, Fever, Systolic Blood Pressure, Difficulty in Breathing, Loss of appetite, Sputum, Chills, Loss of pleasure, Immune Suppression, Chest Pain, Lack of concentration, Irritation, Loss of energy, Lymph Node Enlargement, Body Mass Index). The reduced dataset was split into training and test sets. The ANFIS (Adaptive Neuro-Fuzzy Inference System) was applied to perform diagnosis in which it was trained and validated on training and test sets respectively. The ANFIS was driven by Mamdani’s inference mechanism with sixty-four (64) generated rules with confidence and support scores of above 10% and 15% respectively.  The developed model performance on the test sets gave an accuracy of 90% precision, sensitivity, and specificity of 100%. The results showed that all the attributes of tuberculosis contributed to the degree of the diseases based on their respective weights. Conclusively, the system accurately classified, trained attributes, and predicts the severity of tuberculosis.

Pages: 41-56