Traumatic brain injury (TBI) is a major national health problem. Every year at least 1.7 million people suffer from TBI in the USA. 52,000 civilians die due to the TBI-related injuries every year. Currently, initial assessment of TBI is based on either the response to stimuli/questions or the symptoms such as losses of consciousness and altered behaviors. The outcome of initial assessment will then be used to justify the need of neuroimaging with computed tomography (CT) scanning or magnetic resonance imaging (MRI). The current assessment techniques have low sensitivity and specificity for mild brain injuries. In addition, no in vitro diagnostic tool is commercially available to rapidly identify and differentiate between mid and severe concussions. There is a critical need to develop a point-of-care (POC) device to rapidly determine if brain injury has happened and its severity in an emergency department or in a clinic. The objective of the project is to develop a lateral-flow device based on surface enhanced Raman scattering (SERS) for multiplexed detection of TBI biomarkers in blood. The proposed device is able to measure three most recognized TBI biomarkers including S-100?, neuron-specific enolase (NSE) and glial fibrillary acidic protein (GFAP). In this lateral flow device, three SERS sensors are integrated with the microfluidic modules on a single chip, which enables the plasma separation from whole blood, transportation of sample and reagents, and sensing measurement. For the SERS sensors, a plasmonic nanostructure is developed by nanotechnology to enhance the sensitivity. The portable device can be used as a point-of-care (POC) device for directly measuring multiple TBI biomarkers in blood without the need of blood sample pretreatment in a centralized laboratory prior to biomarker detection. The device can provide the data for early TBI prognosis, and guide additional confirmatory testing. Hence, it is able to assist rapid screening of TBI patients in an emergency department or in a clinic. The data obtained by the device can also be used for guiding the TBI treatment. The proposed research lies at the interface of nanotechnology, materials science, biology and health science. The inherently interdisciplinary nature of this proposed project offers opportunities for training students in diverse research areas.
A portable sensor will be developed for detection of traumatic brain injury biomarkers in a blood sample. The device is used to assist the rapid diagnosis of brain injury and to help the treatment of traumatic brain injury. The developed technique will bring benefits to patients and save costs.
|Zheng, Peng; Kasani, Sujan; Shi, Xiaofei et al. (2018) Detection of nitrite with a surface-enhanced Raman scattering sensor based on silver nanopyramid array. Anal Chim Acta 1040:158-165|
|Sun, Jianbo; Liu, Yuxin (2018) Matrix Effect Study and Immunoassay Detection Using Electrolyte-Gated Graphene Biosensor. Micromachines (Basel) 9:|
|Kasani, Sujan; Zheng, Peng; Wu, Nianqiang (2018) Tailoring Optical Properties of a Large-Area Plasmonic Gold Nanoring Array Pattern. J Phys Chem C Nanomater Interfaces 122:13443-13449|
|Betancur, Veronica; Sun, Jianbo; Wu, Nianqiang et al. (2017) Integrated Lateral Flow Device for Flow Control with Blood Separation and Biosensing. Micromachines (Basel) 8:|
|Gao, Xuefei; Zheng, Peng; Kasani, Sujan et al. (2017) Paper-Based Surface-Enhanced Raman Scattering Lateral Flow Strip for Detection of Neuron-Specific Enolase in Blood Plasma. Anal Chem 89:10104-10110|
|Tang, Haibin; Zheng, Peng; Meng, Guowen et al. (2016) Fabrication of hexagonally patterned flower-like silver particle arrays as surface-enhanced Raman scattering substrates. Nanotechnology 27:325303|
|Li, Ming; Cushing, Scott K; Wu, Nianqiang (2015) Plasmon-enhanced optical sensors: a review. Analyst 140:386-406|
|Zheng, Peng; Cushing, Scott K; Suri, Savan et al. (2015) Tailoring plasmonic properties of gold nanohole arrays for surface-enhanced Raman scattering. Phys Chem Chem Phys 17:21211-9|
|Geng, Zongyu; Yang, Feng; Chen, Xi et al. (2015) Gaussian process based modeling and experimental design for sensor calibration in drifting environments. Sens Actuators B Chem 216:321-331|