ArticlePloS one2020
Aptamer based proteomic pilot study reveals a urine signature indicative of pediatric urinary tract infections.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- RaptScore: a large language model-based algorithm for versatile aptamer evaluation.Nucleic acids research · 2026Article
- Diagnostic tests for urinary tract infections and antimicrobial resistance-a reality check between diagnostic innovation and implementation: a critical narrative review.Frontiers in cellular and infection microbiology · 2026Review
- Gut microbiome shifts in adolescents after sleeve gastrectomy with increased oral-associated taxa and pro-inflammatory potential.Gut microbes · 2025Article
- Urinary Complement proteome strongly linked to diabetic kidney disease progression.Nature communications · 2025Article
- Intercalated cell function, kidney innate immunity, and urinary tract infections.Pflugers Archiv : European journal of physiology · 2024Review
- Recent progress in mass spectrometry-based urinary proteomics.Clinical proteomics · 2024Review
- Placental proteins with predicted roles in fetal development decrease in premature infants.Pediatric research · 2022Article
- Analytical Considerations of Large-Scale Aptamer-Based Datasets for Translational Applications.Cancers · 2022Review
- Novel urine biomarkers to distinguish UTI from culture-negative pyuria.Pediatric nephrology (Berlin, Germany) · 2022Article
- Harnessing the Potential of Multiomics Studies for Precision Medicine in Infectious Disease.Open forum infectious diseases · 2021Review
- Advances in Aptamer-Based Biomarker Discovery.Frontiers in cell and developmental biology · 2021Review
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
objectiveCurrent urinary tract infection (UTI) diagnostic strategies that rely on leukocyte esterase have limited accuracy. We performed an aptamer-based proteomics pilot study to identify urine protein levels that could differentiate a culture proven UTI from culture negative samples, regardless of pyuria status.
methodsWe analyzed urine from 16 children with UTIs, 8 children with culture negative pyuria and 8 children with negative urine culture and no pyuria. The urine levels of 1,310 proteins were quantified using the Somascan™ platform and normalized to urine creatinine. Machine learning with support vector machine (SVM)-based feature selection was performed to determine the combination of urine biomarkers that optimized diagnostic accuracy.
resultsEight candidate urine protein biomarkers met filtering criteria. B-cell lymphoma protein, C-X-C motif chemokine 6, C-X-C motif chemokine 13, cathepsin S, heat shock 70kDA protein 1A, mitogen activated protein kinase, protein E7 HPV18 and transgelin. AUCs ranged from 0.91 to 0.95. The best prediction was achieved by the SVMs with radial basis function kernel.
conclusionsBiomarkers panel can be identified by the emerging technologies of aptamer-based proteomics and machine learning that offer the potential to increase UTI diagnostic accuracy, thereby limiting unneeded antibiotics.
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