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        <identifier>oai:figshare.com:article/32826269</identifier>
        <datestamp>2026-10-01T16:09:24Z</datestamp>
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          <dc:title>Micro-managing infection: discovery of microRNA signatures with diagnostic potential for paediatric infections</dc:title>
          <dc:creator>Oenone Theresa Wyness Oakley Rodgers (24304517)</dc:creator>
          <dc:subject>PUREID: 676302117</dc:subject>
          <dc:subject>Paediatric</dc:subject>
          <dc:subject>infection</dc:subject>
          <dc:subject>biomarker discovery</dc:subject>
          <dc:subject>miRNA</dc:subject>
          <dc:subject>bacterial infections</dc:subject>
          <dc:subject>viral infections</dc:subject>
          <dc:subject>emergency care</dc:subject>
          <dc:subject>CRP</dc:subject>
          <dc:subject>PCT</dc:subject>
          <dc:subject>diagnostic</dc:subject>
          <dc:description>&lt;b&gt;Background: &lt;/b&gt;Young children are at high risk of serious bacterial infection (SBI), yet rapidly distinguishing bacterial from viral illness in febrile emergency presentations remains challenging. Current biomarkers, including C-reactive protein (CRP) and procalcitonin (PCT), have limited diagnostic performance, contributing to uncertainty in early management and antibiotic overuse. With rising antimicrobial resistance, there is an urgent need for improved biomarkers. MicroRNAs (miRNAs) are stable, disease-specific biomarkers with strong potential for paediatric infection diagnosis, but remain underexplored.&lt;br&gt;&lt;br&gt;&lt;b&gt;Methods:&lt;/b&gt; Two experimental pipelines, discovery (n = 85) and validation (n = 256), were used to identify novel miRNA biomarkers. Samples were classified as bacterial, viral, inflammatory, or healthy controls. RNA was extracted from 100µl plasma using the miRNeasy Serum/Plasma kit. miRNA libraries were prepared with the QIAseq UDI Library kit and sequenced on the Illumina NextSeq 2000; data were analysed using GeneGlobe and R to identify candidate miRNAs. Validation was performed by RT-qPCR, normalised to UniSp6. Fold-change and machine learning analyses identified an optimal biomarker panel for ruling out SBI, with performance compared to CRP and PCT.&lt;br&gt;&lt;br&gt;&lt;b&gt;Results: &lt;/b&gt;Small RNA sequencing identified 21 candidate miRNA biomarkers of potential diagnostic relevance, and 17 miRNAs were validated by RT-qPCR. Optimal diagnostic performance was achieved using a combined biomarker panel of miRNAs, CRP, and PCT (AUC = 0.83, sensitivity = 90%, specificity = 59%), outperforming CRP alone (AUC = 0.70, sensitivity = 75%, specificity = 54%). The novel panel is predicted to prevent 55 unnecessary antibiotic prescriptions per 1,000 children, representing a possible 11% reduction in inappropriate antibiotic use.&lt;br&gt;&lt;br&gt;&lt;b&gt;Conclusion:&lt;/b&gt; This study identifies and validates miRNA biomarkers that enhance diagnostic accuracy for paediatric infection when combined with existing tests. While further validation in larger cohorts is required, these findings support the potential of miRNA-based diagnostic panels to improve early clinical decision-making and reduce inappropriate antibiotic use.&lt;br&gt;&lt;br&gt;&lt;i&gt;Thesis is embargoed until 31 July 2031.&lt;/i&gt;&lt;br&gt;</dc:description>
          <dc:date>2026-10-01T16:09:24Z</dc:date>
          <dc:type>Text</dc:type>
          <dc:type>Thesis</dc:type>
          <dc:identifier>10.17034/32826269.v1</dc:identifier>
          <dc:relation>https://figshare.com/articles/thesis/Micro-managing_infection_discovery_of_microRNA_signatures_with_diagnostic_potential_for_paediatric_infections/32826269</dc:relation>
          <dc:rights>All Rights Reserved</dc:rights>
          <dc:rights>Open Access after 2031-07-31</dc:rights>
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