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Mass Sensor Coupled with an Optical Array Imager for Diagnosing Type of Diabetes

质量传感器与光学阵列成像仪结合用于诊断糖尿病类型

基本信息

批准号：
8773252
负责人：
Sadagopan Krishnan
金额：
$ 43.16万
依托单位：
OKLAHOMA STATE UNIVERSITY STILLWATER
依托单位国家：
美国
项目类别：
财政年份：
2014
资助国家：
美国
起止时间：
2014-06-17 至 2018-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8773252
关键词：
Address Adult American Antibodies Autoimmune Diseases Binding Biological Assay Biological Markers Blood Blood specimen Body Fluids Chemicals Chemistry Child Clinical Complex Computer-Assisted Image Analysis Coupled Coupling Detection Diabetes Mellitus Diagnosis Diagnostic Diagnostic Procedure Environment Epidemic Exposure to Fluorescence Frequencies Generic Drugs Gestational Diabetes Glucose Goals Health Health Professional Heart Human Immune System Diseases Immunoassay Insulin Insulin Antibodies Insulin Resistance Label Life Literature Measurement Measures Methods Mission Modeling Monitor Native Americans Non-Insulin-Dependent Diabetes Mellitus Obesity Oklahoma Optics Output Patients Performance Physical activity Population Postdoctoral Fellow Prediabetes syndrome Preparation Procedures Property Protocols documentation Qualifying Quartz Radio Reagent Refractive Indices Research Sampling Serum Signal Transduction Specificity Students Surface Surface Plasmon Resonance Testing Time Training United States United States National Institutes of Health Universities Whole Blood Work base career clinical Diagnosis clinically relevant cost disability electric impedance improved innovation instrument iron oxide method development nanoparticle nanostructured novel operation outreach oxidation particle public health relevance sensor treatment planning type I and type II diabetes user-friendly

项目摘要

DESCRIPTION: Diabetes is an emerging epidemic condition worldwide, and some of its causes include obesity, autoimmune disorder, and lack of physical activity. The 2011 National Diabetes Fact Sheet released by the American Diabetes Association revealed that nearly 26 million adults and children in the United States had diabetes (8.3 % population), and about 80 million people were estimated to have pre-diabetes (a condition before type-2 diabetes). Challengingly, the presence of ultra-low levels of insulin in blood serum (on the order of pM) even under healthy conditions demands the need for highly sensitive assay methods to measure serum or blood insulin and diagnose the presence of type of diabetes. The commercial glucometers can only infer the levels of glucose in blood and presence of a diabetes condition, but cannot identify the type of diabetes and the associated obesity, heart/immune diseases, for which the detection of insulin levels is necessary. S sensitivity, simplicity of detection protocol and ability to detect insulin present in a complex clinical matrix are crucial. The commercial serum insulin immunoassays based on absorbance, fluorescence, chemiluminescence, and radiometric detection methods require special, chemically labeled detection antibodies, which involve difficult time consuming preparations and separation procedures, along with the need for expensive materials and special instruments. These properties add to the high-cost of such assay kits. Thus, there exists a critical need to provide the diabetes clinical centers with sensor that are robust in operation, highly sensitive, simple-to- use, and involve label-free detection of serum and blood insulin levels. To accomplish this, the PI's objective in this R15 application is t develop a novel sensor that can selectively measure clinically relevant pM serum and blood insulin levels with high specificity based on signal changes in frequency, impedance, and insulin- oxidation currents in a single assay, and additionally enable the coupling to an optical microarray imager based detection for the first time. The proposed label-free sensor research is innovative because it involves the direct measurements of insulin in both the serum and whole blood with multi-detection features, offering unprecedented precision and accuracy. In the absence of such advanced insulin sensors, the specific identification of the type of diabetes and the associated management plan will likely remain problematic. By c completing the proposed plan of work and the proposed outreach activities of the PI on research exposure to Native American students in Oklahoma, it is expected that this application will strengthen the research environment of Oklahoma State University, create an independent health-related research career for the PI, and deliver an innovative, simple, reliable, and highly sensitive insulin-sensor to significantly improve the present diagnostic procedures in identifying the diabetes-type in clinical samples.

糖尿病是一种新兴的世界性流行病，其原因包括肥胖、自身免疫性疾病和缺乏身体活动。美国糖尿病协会发布的2011年全国糖尿病概况表显示，美国有近2600万成人和儿童患有糖尿病（占人口的8.3%），估计约有8000万人处于糖尿病前期（2型糖尿病之前的一种状况）。具有挑战性的是，即使在健康条件下，血清中存在超低水平的胰岛素（以pM为数量级），因此需要高灵敏度的测定方法来测量血清或血液中的胰岛素并诊断是否存在糖尿病类型。商用血糖仪只能推断血液中的葡萄糖水平和是否患有糖尿病，但不能确定糖尿病的类型和相关的肥胖、心脏/免疫疾病，而检测胰岛素水平是必要的。S的敏感性，检测方案的简单性和检测胰岛素存在于复杂的临床基质的能力是至关重要的。基于吸光度、荧光、化学发光和放射检测方法的商业血清胰岛素免疫测定需要特殊的、化学标记的检测抗体，这涉及到困难的、耗时的制备和分离过程，以及对昂贵的材料和特殊仪器的需求。这些特性增加了这种检测试剂盒的高成本。因此，迫切需要为糖尿病临床中心提供操作稳健、高灵敏度、使用简单、无标签检测的传感器