Covenant Journal of Physical and Life Sciences

Tissue antioxidant enzyme activities and lipid profile of experimental rats fed with Waltheria indica leaf diets

2024-09-18T23:18:02+00:00

Hypercholesterolemia is a specific genetic condition characterized by excessively increased plasma cholesterol concentrations. Although treatments through statins have recorded exponential success over time, regrettably, several patients have yet to attain the minimum levels of low-density lipoprotein-cholesterol (LDL-Ch), evidenced by the high cardiovascular outcomes after treatment. Hence, this research aimed at evaluating the effect of Waltheria indica leaf diets on the lipid profiles and antioxidant activities in male albino rats weighing 40-45 g, which were grouped into three: Group A (basal group without cholesterol), Group B control (diet + 1% cholesterol) and Group C test diet (1% cholesterol + 10% Waltheria indica leaf sample) and fed for 21 days and weighed before sacrifice. After the last day of feeding, the Serum and liver were excised, and lipid profile and antioxidant enzyme activities were analyzed using standard methods. Serum total cholesterol (mg/dl) decreased significantly (p<0.05) from 83.88 ± 2.74 in control rats (group B) to 23.14 ± 1.05 in group C rats. Also, serum high-density lipoprotein (mg/dl) increased significantly (p<0.05) from 17.09 ± 0.71 in control rats to 33.25 ± 4.01 in group C rats. The serum malondialdehyde level decreased markedly from 8.68 ± 0.07 in group B rats to 5.74 ± 0.40 in group C rats. The activity of Serum Catalase significantly increased from 2.29 ± 0.15 in group B rats to 3.75 ± 0.13 in group C rats. This study demonstrates the lipid-lowering potential of Waltheria indica leaf diets and its protective effects against oxidative stress, which holds promise in managing and treating hypercholesterolemia.

AUTOMATED DIAGNOSIS OF SCHISTOSOMIASIS USING CONVOLUTIONAL NEURAL NETWORKS: A COMPARATIVE STUDY WITH K-NEAREST NEIGHBORS

2024-09-26T12:32:17+00:00

Schistosomiasis, a prevalent neglected tropical disease, continues to burden populations in resource-constrained regions globally. Conventional diagnostic methodologies are labour-intensive and demand significant time and resources. This study investigates the efficacy of advanced machine learning algorithms, particularly Convolutional Neural Networks (CNNs) and K-Nearest Neighbors (KNN), for automating the detection of Schistosoma eggs in microscopic images. Comparative performance analysis revealed that although the KNN algorithm achieved superior metrics in accuracy, precision, recall, and F1 score, its limitations in feature extraction and handling complex image patterns hindered its applicability as the primary diagnostic tool. Conversely, despite slightly lower
preliminary metrics, the CNN model demonstrated robust feature extraction capabilities and adaptability to intricate patterns, making it the optimal choice for the automated diagnosis of Schistosomiasis. The selected CNN model exhibited high diagnostic performance, with significant accuracy, precision, recall, and F1 scores, thereby offering a viable solution for enhancing the efficiency and accuracy of Schistosomiasis diagnostics. This approach could revolutionize diagnostic workflows, particularly in low-resource settings, by minimizing procedural complexity and improving diagnostic outcomes.

MICROBIAL CONTAMINATION AND ANTIBIOTIC RESISTANCE IN SELECTED YOGHURT BRANDS IN ELELE, RIVERS STATE, NIGERIA

2024-09-16T23:18:50+00:00

Yogurt, a widely consumed fermented dairy product, offers numerous nutritional benefits but is susceptible to microbial contamination, posing potential public health risks. This study evaluates the microbial contamination in twelve brands of yogurt sold in Elele, Rivers State, Nigeria, analyzing ambient and frozen samples. The results revealed higher bacterial loads in yogurt stored at room temperature, with Bacillus sp (40%) being the most prevalent contaminant, followed by Lactobacillus bulgaricus (30%) and Salmonella sp (35%)., the latter of which is particularly concerning due to its potential to cause foodborne illnesses. Additionally, antibiotic susceptibility testing demonstrated that the isolated bacteria exhibited significant multi-drug resistance, especially Salmonella sp., which was resistant to eight of ten antibiotics tested. These findings highlight the importance of proper storage conditions, strict hygiene practices, and the need for enhanced safety measures during yogurt production to minimize health risks associated with contaminated yogurt products.

Patients’ Satisfaction with waiting time and healthcare givers’ attitude: outcome of patient’s compliance to treatment at the University of Benin Teaching Hospital and Central Hospital, Benin City Edo State, Nigeria

2024-09-18T23:09:42+00:00

The growing concern about the importance of patient satisfaction as an essential tool in assessing the quality of care is a recent trend in the health sector in Nigeria. This study underscores the urgent need for a shift towards patient-centred care, a model that has proven successful in developed countries. The same cannot be said of developing countries like Nigeria and Ghana. This study evaluated patients' satisfaction with service delivery in tertiary and secondary health institutions in South-South Nigeria. It was a quantitative and qualitative study on 200 inpatients and outpatients at the University of Benin Teaching Hospital (UBTH) and Central Hospital, both located in Benin City, Edo state, Nigeria Data were collected using a pretested structured questionnaire, Focus Group Discussion, and Non-participant Observation. Data from the quantitative study were analysed using the statistical package for Social Science (SPSS) version (20) in the form of frequencies, percentages and chi-square to determine the association among variables. Reports of Focus Group Discussions and Observations were written in summary paragraphs. Findings revealed that patients' dissatisfaction with waiting times and workers’ attitudes did not deter them from complying with the treatment process; they continued using health units and recommended health units to others. Patients’ satisfaction with waiting time and staff patients’ relationships were poor. These, though, do not affect patients’ compliance with the treatment process, continued utilisation of health units and recommendation of health units to others.

Pipeline Conflict in Processors: An Approach for Examining and Resolving Pipeline Conflict Using Machine Learning

2024-10-22T13:22:27+00:00

This study explores the impact of pipeline conflicts on processor reliability and performance, focusing specifically on data hazards, one of three primary types of pipeline conflicts (the others being control hazards and structural conflicts). Data hazards arise from dependencies between instructions, causing stalls that reduce pipeline efficiency. The research applies machine learning to detect and mitigate these conflicts, using a dataset of artificial instruction sequences, each labeled as either conflict-free or containing one of three data hazard types: Read After Write (RAW), Write After Read (WAR), or Write After Write (WAW). Two machine learning models—logistic regression and Support Vector Machine (SVM)-were evaluated for their effectiveness in identifying pipeline conflicts. The logistic regression model achieved 96% accuracy and high precision, recall, and F1-scores across all categories, indicating its strong ability to accurately classify pipeline conflicts. In contrast, the SVM model achieved lower accuracy (83%) and performed inconsistently across classes, excelling in some but struggling with others, suggesting difficulties in recognizing certain conflict patterns.

PREVALENCE AND CO-INFECTION OF HELICOBACTER PYLORI AND HEPATITIS C VIRUS AMONG HIV PATIENTS ON ART IN PORT HARCOURT, NIGERIA

2024-10-27T23:25:39+00:00

Helicobacter pylori is one of the most common and medically prominent infections worldwide and has been implicated in various gastric disorders including peptic ulcer disease (PUD). Several investigators have reported a high prevalence of H. pylori infection in patients with chronic liver diseases. Some have suggested that it might contribute to the mechanism of hepatitis C (HCV) related hepatocellular carcinoma (HCC). The relationship between H. pylori and chronic hepatitis C (CHC) remains controversial. This cross-sectional study aimed to investigate the seroprevalence of H. pylori co-infection with Hepatitis C among HIV-positive patients receiving antiretroviral therapy (ART) and its correlation with viral load at the Rivers State University Teaching Hospital (RSUTH), Nigeria. A total of two hundred (200) participants were recruited and screened for Helicobacter pylori and HCV antibodies using rapid diagnostic tests (RDTs) while HIV viral load was performed using Reverse Transcription-polymerase chain reaction (RT-PCR), Questionnaires were used to obtain demographic data of the participant. The results revealed a 60.5% prevalence of H. pylori, with none testing positive for antibodies to HCV (Anti-HCV). The majority of the participants were within the age range of 33-40 years, predominantly females 69.0%, married 46.0%, secondary education 54.0%, and participants with viral load less than 20 copies/ml 74%. Across all viral load ranges, the prevalence of the specific outcome appears to be relatively consistent, ranging from 60.1% to 63.3%. There was no statistical association between the demographic variable and the infection (p > 0.05). In conclusion, while the prevalence of H. pylori is high with no HCV infections among HIV-infected individuals in Port Harcourt, the specific outcome or characteristic of viral load is somewhat consistent, indicating despite the difference in counts, the prevalence within each range is quite similar.

SEROLOGICAL EVIDENCE OF HBc IgM AMONG HIV-INFECTED INDIVIDUALS ATTENDING SELECTED HOSPITALS IN ANAMBRA STATE, NIGERIA

2024-11-04T18:18:08+00:00

The South-Eastern area of Nigeria does not currently have data on the serological evidence of anti-HBc-IgM antibodies. The study aimed to show the serological evidence of anti-HBc-IgM antibody biomarkers among HIV-infected individuals in selected hospitals in Anambra State, Nigeria. This study also investigates the prevalence of Hepatitis B core IgM (HBc IgM) among HIV-infected individuals in Anambra State, Nigeria, highlighting its sociodemographic correlates, CD4 counts, and viral load implications. Following the manufacturer's standard operating procedures, 372 participants were tested for anti-HBc IgM antibodies during a cross-sectional study. Of the 372 participants, 27.7% tested positive for HBc IgM. The overall prevalence of anti-HBc IgM antibodies (27.7%). The serological evidence of anti-HBc- IgM antibody was higher among females (32.1%), older age groups (33.8%), other marital categories (41.7%), monogamous family type (29.7%), primary educational level (41.5%), unemployed (38.5%), Christian religion (30.8%), and having HIV-positive spouse (31.7%). Among the immunological markers, a higher prevalence of anti-HBc IgM antibodies occurred in participants with CD4 counts <200 cells/µl (52.5%). For the virological markers, a higher prevalence of anti-HBc IgM antibodies occurred among participants with a plasma viral load of >1000 copies/ml (61.3%). This study identifies a possible danger of HBV transmission from HIV-infected individuals to the general population. Anti-HBc-IgM antibodies are prevalent in Anambra State, Nigeria and this represents the first evaluation of anti-HBc IgM in the South-Eastern region of the nation. The findings underscore the need for integrated healthcare approaches, emphasising comprehensive screening and tailored interventions to manage co-infections effectively.

Computational Analysis of Fractional Integro-Differential Equations using Chebyshev series solution of second kind.

2024-12-10T17:09:04+00:00

A new numerical scheme via a Chebyshev series method is used to solve a family of linear fractional integro-differential equations, especially the Fredholm and Volterra equations. The linear fractional integro-differential equation can be transformed into a system of equations for the unknown function itself and its m derivatives by taking into account the mth order Chebyshev series of the unknown function at any point. Using MATLAB 2009 software, this approach provides a straightforward and closed-form solution to a linear fractional integro-differential equation. Finally, examples are provided to illustrate comparisons between the proposed Chebyshev series solution and some existing methods in this direction. The results obtained performed better in terms of quick convergence and stability over the existing Taylor series expansion methodologies.