Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/86331
Title: Measurement of IL-6, IL-8, IL-18 and VEGF in human plasma to detect active tuberculosis
Authors: Fenech, Elaine (2021)
Keywords: Mycobacterium tuberculosis -- Malta
Blood plasma
Cytokines
Interleukins
Interleukin-6
Interleukin-8
Interleukin-18
Vascular endothelial growth factors -- Malta
Issue Date: 2021
Citation: Fenech, E. (2021). Measurement of IL-6, IL-8, IL-18 and VEGF in human plasma to detect active tuberculosis (Bachelor's dissertation).
Abstract: Mycobacterium tuberculosis infection is the cause of Active Tuberculosis (ATB) where the main organ affected is the lungs. Diagnosis of ATB through microbiology can be a lengthy process taking up to 2-4 weeks for the formation of any visible growth. This would therefore allow the infection to worsen without proper treatment. Upon infection through droplets, the M. tuberculosis could evade the innate immune system and thus allowing macrophages in the lungs to produce cytokines to combat the bacterium, namely IL-6, IL-8, IL-18 and VEGF. Therefore, a rise in these cytokines would indicate the presence of Mycobacterium tuberculosis. The Luminex bead-based multiplexing assay will be used to measure the levels of these cytokines in patients with Active tuberculosis, Latent Tuberculosis and healthy controls. The samples are to be stored at -80°C for increased stability of the cytokines. The aim of this study is to obtain a faster and reliable diagnosis for active tuberculosis and consequently, faster administration of treatment. It was observed that the concentration levels of the four cytokines were significantly increased in the presence of a Mycobacterium tuberculosis infection when compared to the healthy controls, and no significant change was identified in the latent Tuberculosis participants, allowing for a distinction to be made between the active infection, the latent infection and the healthy controls. Active Tuberculosis was found to be more predominant in males than in females. The use of predictive models allows for the classification of an unknown specimen into one of the three patient populations (active Tuberculosis, Latent Tuberculosis or Healthy Control) with an 81.58% accuracy based on the available dataset.
Description: B.Sc. (Hons)(Melit.)
URI: https://www.um.edu.mt/library/oar/handle/123456789/86331
Appears in Collections:Dissertations - FacHSc - 2021
Dissertations - FacHScABS - 2021

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