ArticleSensors (Basel, Switzerland)2022
Inflammatory Stimuli Responsive Non-Faradaic, Ultrasensitive Combinatorial Electrochemical Urine Biosensor.
Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed.
- Wearable Electrochemical Biosensors for Monitoring and Management of Chronic Wounds.Biosensors · 2025Review
- Transforming cytokine diagnostics: AI, multiplexing, and point-of-care biosensing technologies.Mikrochimica acta · 2025Review
- Development and benchtop testing of an aptamer-based sweat sensor for CRP detection.Mikrochimica acta · 2025Article
- USENSE: A proof-of-concept self-screening tool for home-based recurrent urinary tract infection management.Bioengineering & translational medicine · 2025Article
- Capacitive Sensors for Label-Free Detection in High-Ionic-Strength Bodily Fluids: A Review.Biosensors · 2025Review
- AI-Empowered Electrochemical Sensors for Biomedical Applications: Technological Advances and Future Challenges.Biosensors · 2025Review
- Machine Learning in Bioelectrocatalysis.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Review
- Advancing chirality analysis through enhanced enantiomer characterization and quantification via fast Fourier transform capacitance voltammetry.Scientific reports · 2023Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this work, we propose a novel diagnostic biosensor that can enable stratification of disease states based on severity and hence allow for clear and actionable diagnoses. The scheme can potentially boost current Point-Of-Care (POC) biosensors for diseases that require time-critical stratification. Here, two key inflammatory biomarkers—Interleukin-8 and Interleukin-6—have been explored as proof of concept, and a four-class stratification of inflammatory disease severity is discussed. Our method is superior to traditional lab techniques as it is faster (<4 minutes turn-around time) and can work with any combination of disease biomarkers to categorize diseases by subtypes and severity. At its core, the biosensor relies on electrochemical impedance spectroscopy to transduce subtle inflammatory stimuli at the input for IL-8 and IL-6 for a limit of detection (LOD) of 1 pg/mL each. The biosensing scheme utilizes a two-stage random forest machine learning model for 4-state output disease classification with a 98.437% accuracy. This scheme can potentially boost the diagnostic power of current electrochemical biosensors for better precision therapy and improved patient outcomes.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.