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RNA profiling in biofluids holds promise as both diagnostic and prognostic markers. High expression levels of distinctive cell free circulating miRNAs in serum, plasma and cerebral spinal fluid (CSF), have been utilized as classifiers to detect and characterize disorders of the central nervous system (CNS).   We formulated the quantitative theory showing how the results of surprisal analysis enable a reliable inference if tumor cells are present in the sample from a single measurement.  Subsequently, we develop a molecular beacon-based microfluidic chip that enables for fluorescence detection of miRNAs without amplification in low volumes of human CSF.  Using surprisal analysis, we identified a miRNA classifier that enables high fidelity detection and characterization of human brain tumors. We anticipate that this micro-fluidic platform will provide a critical translational tool with point of care potential for CNS disorders.

Microfluidic Chip with Molecular Beacons Detects miRNAs in Human CSF to Reliably Characterize CNS-specific Disorders