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Euclea (Ebenaceae) is a genus of flowering shrubs and trees widely distributed in Africa, the Comoro Islands, and Arabia. This review aimed to evaluate the ethnobotanical uses, phytochemistry, and biological activities of the genus Euclea on available research reports. This was achieved through PubMed, Medline, Google Scholar, Science Direct, Taylor and Francis Online, Wiley Online Library which provides access to scientific and medical research. The extensive literature survey revealed that plants that belong to this genus are used as folkloric medicine for the treatment of diabetes mellitus, toothache, diarrhea, cancer, malaria, leprosy, and genital and oral diseases in the case of HIV/AIDS-related diseases. To date, more than 40 secondary metabolites have been isolated and identified from these plants, especially from E natalensis and E. divinorum. Among these, naphthoquinones, terpenes, and flavonoids are potential secondary metabolites with profound biological activities. Euclea plant extracts and their bioactive compounds possess outstanding pharmacological properties, especially antimalarial, antidiabetic, anticancer, antimicrobial, and antioxidant properties.
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Background: Highly active antiretroviral therapy (HAART) improves clinical outcomes by suppressing viral replication and allowing immune reconstitution. It also reduces HIV-related complications including morbidity, mortality, and extended hospitalizations for HIV-positive individuals. Regular assessment for antiretroviral treatment response is fundamentally important to address the factors associated with the poor clinical outcome including immunologic failures among HIV-positive patients on HAART. Therefore, this study aimed to investigate the immuno-virological status and describe its determinants among HIV-positive patients receiving HAART at Delgi primary hospital, Northwest Ethiopia. Methods: A hospital-based cross-sectional study was conducted at Delgi primary hospital from October 25th through June 19th 2021 among a total of 442 study participants. A systematic random sampling technique was employed to enrol participants in the study. Socio-demographic and clinically related data were collected using a semi-structured questionnaire. About 3-5 ml of venous blood was collected aseptically for CD4+ T cell count and viral load test. SPSS version 20 software was used for statistical analysis. Bivariate and multivariate logistic regression analyses were conducted to determine the factors associated with immuno-virologic status among HIV-positive patients on HAART. The odds ratio with 95% CI was computed to determine the strength of association. Then, a p-value < 0.05 was considered a statistically significant association. For this study, the results were presented by using frequency summary tables, and texts. Results: Among the total study participants, 283 (64%) were males and the mean age of the study participants was 37 ± 11.5. The overall immunological and virological failure among highly active antiretroviral therapy (HAART) receiving participants was found to be 9.5% (42/442, 95%CI:3.23-15.09) and 12.2% (54/442, 95% CI: 2.81-23.04) respectively. In the multivariate analysis, study participants with age ≥50 years old [AOR = 1.97, p = 0.01, 95%CI (0.02-4.03)], participants having current viral load count greater ≥1000 copies/ml [AOR = 3.97, p = 0.03, 95%CI (1.09-5.01)] and having TB-co-infection [AOR = 2.51, p = 0.05, 95%CI (1.02-7.51)] were statistically associated with increased risk of immunological failure. Similarly, TB-coinfected participants were 1.88 (95%CI = 0.89-10.02) times at greater risk for virological failure. Conclusion: In this study, the magnitude of immuno-virological failure is alarming. This may be shown the need for integrated and substantial commitment to enhancing patient antiretroviral treatment adherence in the study area. Also, regular assessment for antiretroviral treatment response is fundamentally important to address the determinants associated with virological and immunologic failures among HIV-positive patients taking HAART. Furthermore, early initiation of HAART may be imperative to achieve favourable virological suppression and immunological reconstitution.
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Text classification is the process of categorizing documents based on their content into a predefined set of categories. Text classification algorithms typically represent documents as collections of words and it deals with a large number of features. The selection of appropriate features becomes important when the initial feature set is quite large. In this paper, we present a hybrid of document frequency (DF) and genetic algorithm (GA)-based feature selection method for Amharic text classification. We evaluate this feature selection method on Amharic news documents obtained from the Ethiopian News Agency (ENA). The number of categories used in this study is 13. Our experimental results showed that the proposed feature selection method outperformed other feature selection methods utilized for Amharic news document classification. Combining the proposed feature selection method with Extra Tree Classifier (ETC) improves classification accuracy. It improves classification accuracy up to 1% higher than the hybrid of DF, information gain (IG), chi-square (CHI), and principal component analysis (PCA), 2.47% greater than GA and 3.86% greater than a hybrid of DF, IG, and CHI.
