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Journal Article

Citation

Haselwood BA, La Belle JT. Biosens. Bioelectron. 2014; 67: 752-756.

Affiliation

School of Biological and Health Systems Engineering, Arizona State University, 550 E. Orange St., Tempe, AZ 85287, USA; School of Medicine, Mayo Clinic Arizona, 13400 E. Shea Blvd., Scottsdale, AZ 85259, USA. Electronic address: JEFFREY.LABELLE@asu.edu.

Copyright

(Copyright © 2014, Elsevier Publishing)

DOI

10.1016/j.bios.2014.09.032

PMID

25248324

Abstract

As awareness of traumatic brain injury (TBI) increases, the need to detect mild forms and distinguish between the different severities of TBI becomes more apparent. The goal of this work is to develop a point-of-care sensor to detect whole blood biomarkers for rapid and sensitive diagnosis of TBI severity. Presented herein is the enzymatic detection of norepinephrine through the use of immobilization chemistry and impedance techniques. Sustained elevation of norepinephrine concentrations in the blood has been correlated to negative long-term outcomes in TBI cases, often resulting in permanent cognitive or physical deficits. Novel analysis techniques have been used to identify an optimal binding frequency (371.1Hz) of norepinephrine to the immobilized enzyme on a gold disk electrode. This form of analysis yielded a logarithmic fit characterized by exceptional responsivity (20.89Ω/pgmL(-1)), reproducibility (R(2)=0.96), and lower limit of detection (98pg/mL) first in purified samples, then in rabbit whole blood solutions. Once the optimal binding frequency was determined, the preliminary use of an impedance-time technique was attempted in this work. This technique more closely resembles the amperometric detection method used in commercial self-monitoring blood glucose meters, allowing for continuous or instantaneous measurement of blood borne biomarkers without compromising sensitivity. Future directions include exploration of simultaneous multi-marker detection with the impedance-time technique and experimentation with novel mesoporous materials to filter large blood components.


Language: en

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