Introduction: The persistence of tuberculosis (TB) infection in some patients after treatment has highlighted the importance of drug susceptibility testing (DST). This study aimed to determine the drug susceptibility patterns of Mycobacterium tuberculosis (M. tuberculosis) isolates from pulmonary TB (PTB) patients in Central and Southern Ethiopia.
View Article and Find Full Text PDFInt J Tuberc Lung Dis
December 2019
complex (MTBC) and its human host are the most competent organisms with co-evolutionary trajectory. This review determined the phylogeography, clinical phenotype-related genotype and transmission dynamics of MTBC in Africa. Spoligotyping and mycobacterial interspersed repetitive units-variable number tandem repeats (MIRU-VNTR) based articles from Africa published in the English language were included.
View Article and Find Full Text PDFBackground: Validation of previously identified candidate biomarkers and identification of additional candidate gene expression profiles to facilitate diagnosis of tuberculosis (TB) disease and monitoring treatment responses in the Ethiopian context is vital for improving TB control in the future.
Methods: Expression levels of 105 immune-related genes were determined in the blood of 80 HIV-negative study participants composed of 40 active TB cases, 20 latent TB infected individuals with positive tuberculin skin test (TST+), and 20 healthy controls with no Mycobacterium tuberculosis (Mtb) infection (TST-), using focused gene expression profiling by dual-color Reverse-Transcription Multiplex Ligation-dependent Probe Amplification assay. Gene expression levels were also measured six months after anti-TB treatment (ATT) and follow-up in 38 TB patients.
The molecular epidemiology of Mycobacterium tuberculosis (M. tuberculosis, Mtb) is poorly documented in Ethiopia. The data that exists has not yet been collected in an overview metadata form.
View Article and Find Full Text PDFPurpose: Advances in technology and computing play an increasingly important role in the evolution of modern surgical techniques and paradigms. This article reviews the current role of machine learning (ML) techniques in the context of surgery with a focus on surgical robotics (SR). Also, we provide a perspective on the future possibilities for enhancing the effectiveness of procedures by integrating ML in the operating room.
View Article and Find Full Text PDFAdmixture mapping affords a powerful approach to genetic mapping of complex traits and may be particularly suited to investigation in cattle where many breeds and populations are hybrids of the two divergent ancestral genomes, derived from Bos taurus and Bos indicus. Here we design a minimal genome wide SNP panel for tracking ancestry in recent hybrids of Holstein-Friesian and local Arsi zebu in a field sample from a region of high bovine tuberculosis (BTB) endemicity in the central Ethiopian highlands. We first demonstrate the utility of this approach by mapping the red coat color phenotype, uncovering a highly significant peak over the MC1R gene and a second peak with no previously known candidate gene.
View Article and Find Full Text PDFObjectives: In the presurgical analysis for drug-resistant focal epilepsies, the definition of the epileptogenic zone, which is the cortical area where ictal discharges originate, is usually carried out by using clinical, electrophysiological and neuroimaging data analysis. Clinical evaluation is based on the visual detection of symptoms during epileptic seizures. This work aims at developing a fully automatic classifier of epileptic types and their localization using ictal symptoms and machine learning methods.
View Article and Find Full Text PDFBackground: Chronic meningitis is inflammation of the meninges where signs and symptoms develop and last for at least four weeks without alleviation. Little is known about the current etiology and incidence of the disease in adults living in developing countries.
Objective: The objective of this study was to elucidate the most common etiologies of chronic meningitis in adult Ethiopian patients and give an aid in the empiric therapy.
We examine two methods which are used to deal with complex machine learning problems: compressed sensing and model compression. We discuss both methods in the context of feed-forward artificial neural networks and develop the backpropagation method in compressed parameter space. We further show that compressing the weights of a layer of a multilayer perceptron is equivalent to compressing the input of the layer.
View Article and Find Full Text PDFAlthough waste from coffee processing is a valuable resource to make biogas, compost, and nutrient-rich animal food, it is usually dumped into nearby water courses. We carried out water quality assessment at 44 sampling sites along 18 rivers that receive untreated waste from 23 coffee pulping and processing plants in Jimma Zone, Ethiopia. Twenty upstream sampling sites free from coffee waste impact served as control, and 24 downstream sampling sites affected by coffee waste were selected for comparison.
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