Theses and Dissertations from UMD

Permanent URI for this communityhttp://hdl.handle.net/1903/2

New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a give thesis/dissertation in DRUM

More information is available at Theses and Dissertations at University of Maryland Libraries.

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Author: search.filters.author.Swain, Trevon BrandonSubject: search.filters.subject.Proteins

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    Impact of lipopolysaccharide administration on novel RNA biomarkers for systemic inflammation in swine
    (2020) Swain, Trevon Brandon; Dayie, Theodore K; Myers, Michael J; Biochemistry; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    In veterinary medicine, inflammation in swine is evaluated solely by clinical signs. This method is often unreliable when assessing large animal populations because of inconsistent interpretations of clinical observations between different clinicians. The lack of a validated swine animal model prevents an accurate measurement of inflammation and inhibits the development of new veterinary effective drugs for swine. This study examined whether changes in miRNA expression can predict the severity of the inflammatory response in swine after administration of lipopolysaccharide (LPS) from Escherichia coli (E.coli). Identification of a reliable biomarker from a systemic inflammatory response needs to be easily obtained, safe, and provide the lowest risk of discomfort to the subject. The correlation of the clinical signs with individual miRNA levels may establish a plasma biomarker that can determine the severity of inflammation in swine. The long-term goal is to determine the most powerful tool for analysis and biomarker discovery. Exploring the different methodologies and monitoring different miRNAs increases the likelihood for potential advancements in disease detection applications