<mods:mods xmlns:mods="http://www.loc.gov/mods/v3" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-7.xsd"><mods:titleInfo><mods:title>Developing a Predictive Diagnostic for COVID-19</mods:title></mods:titleInfo><mods:typeOfResource authority="primo">dissertations</mods:typeOfResource><mods:name type="personal"><mods:namePart>Lu, Christine</mods:namePart><mods:role><mods:roleTerm type="text">creator</mods:roleTerm></mods:role></mods:name><mods:name type="personal"><mods:namePart>Nau, Gerard</mods:namePart><mods:role><mods:roleTerm type="text">Advisor</mods:roleTerm></mods:role></mods:name><mods:name type="personal"><mods:namePart>Monaghan, Sean</mods:namePart><mods:role><mods:roleTerm type="text">Reader</mods:roleTerm></mods:role></mods:name><mods:name type="personal"><mods:namePart>Fredericks, Alger</mods:namePart><mods:role><mods:roleTerm type="text">Reader</mods:roleTerm></mods:role></mods:name><mods:name type="corporate"><mods:namePart>Brown University. Biology and Medicine: Biotechnology</mods:namePart><mods:role><mods:roleTerm type="text">sponsor</mods:roleTerm></mods:role></mods:name><mods:originInfo><mods:copyrightDate>2023</mods:copyrightDate></mods:originInfo><mods:physicalDescription><mods:extent>5, 30 p.</mods:extent><mods:digitalOrigin>born digital</mods:digitalOrigin></mods:physicalDescription><mods:note type="thesis">Thesis (Sc. M.)--Brown University, 2023</mods:note><mods:genre authority="aat">theses</mods:genre><mods:abstract>Objective: SARS-CoV-2 is an ongoing threat to human health. A predictive diagnostic would be helpful for providing information regarding the future progression of COVID-19 in hospitalized patients, however, none have been deployed. There are polymerase chain reaction (PCR) primers based on the sequences used by the CDC (CDC-N1) for diagnostics from nasopharyngeal swabs, but these primers are not effective for measuring RNAemia in all hospitalized COVID-19 patients. The objective of this project was to use deep RNA sequencing to develop a test with greater sensitivity than that of current diagnostics and provide a lead for developing a predictive diagnostic.&#13;
Methods: Primers targeting the ORF1ab and N genes were designed and validated through reverse transcription polymerase chain reaction (RT-PCR). The performance of our primers was compared to that of the CDC-N1. RNA was extracted from whole blood of COVID-19 patients admitted to the ICU. Primer designs were evaluated by reverse transcription quantitative polymerase chain reaction (RT-qPCR).&#13;
Results: An optimized RT-qPCR protocol was developed that minimizes background signal and detects SARS-CoV-2 sequences in whole blood. Higher levels of SARS-CoV-2 RNA were found in COVID-19 patients using our primers than with the CDC-N1 primers.&#13;
Conclusions: We found that our primers are consistently more sensitive than the CDC-N1 primers for the samples tested. Therefore, further studies of our primers should be conducted to elucidate their potential as a predictive diagnostic.</mods:abstract><mods:subject authority="fast" authorityURI="http://id.worldcat.org/fast" valueURI="http://id.worldcat.org/fast/01984643"><mods:topic>COVID-19 (Disease)</mods:topic></mods:subject><mods:subject><mods:topic>RT-qPCR</mods:topic></mods:subject><mods:language><mods:languageTerm authority="iso639-2b">English</mods:languageTerm></mods:language><mods:recordInfo><mods:recordContentSource authority="marcorg">RPB</mods:recordContentSource><mods:recordCreationDate encoding="iso8601">20230602</mods:recordCreationDate></mods:recordInfo></mods:mods>