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Self-Contained Lateral-Flow Microfluidic Bead-Based Assay for Rapid Quantification of Early-Stage Kidney Biomarkers
Gloria Porro1, Micaela Siria Cristofori1, Céline Gagnieux2
1Laboratory of Life Science Electronics, École Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland.
A new lateral-flow microfluidic bead-based assay (LMBA) enables rapid, decentralized measurement of kidney disease biomarkers neutrophil gelatinase-associated lipocalin (NGAL) and cystatin C (CysC). This technology offers a scalable platform for improved diagnostics and preclinical research.
Area of Science:
- Biomedical Engineering
- Clinical Diagnostics
- Biomarker Discovery
Background:
- Kidney diseases are difficult to diagnose due to complex, asymptomatic progression.
- Neutrophil gelatinase-associated lipocalin (NGAL) and cystatin C (CysC) are key biomarkers for early kidney disease detection.
- Current NGAL and CysC quantification requires centralized laboratory analysis, limiting accessibility.
Purpose of the Study:
- To develop a rapid, self-contained diagnostic system for NGAL and CysC.
- To create a scalable platform for decentralized kidney disease biomarker analysis.
- To validate a novel assay against established methods for accuracy and efficiency.
Main Methods:
- Development of a lateral-flow microfluidic bead-based assay (LMBA) integrating microfluidic chips and paper components.
- Automated high-resolution immunoassays performed within 20 minutes.
- Validation of LMBA performance against ELISA using blood or urine samples.
Main Results:
- LMBA demonstrated comparable sensitivity and an extended dynamic range to ELISA.
- The assay requires only 1 μL of sample, with results available in 20 minutes.
- Successful application in neonatal mouse models of polycystic kidney disease, correlating biomarker levels with cyst progression.
Conclusions:
- LMBA is the first rapid, self-contained system for NGAL and CysC analysis.
- The assay's modular design offers flexibility for various applications.
- LMBA shows significant potential for decentralized kidney disease diagnostics and preclinical research.
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