SGER: Early Detection of Human Bacterial Pathogens Using Electronic Nose Technology

这项调查将系统地探索应用新兴的“电子鼻”技术来快速检测和分析各种细菌病原体的潜力。快速识别引起疾病的细菌病原体将大大减少诊断医生开出特定抗生素所需的时间。在为期12个月的研究中，研究人员试图回答三个问题：1)现有的气体传感器能否检测到各种各样的人类细菌病原体？2)现有的气体传感器能否用于培养物中一种或多种人类病原体的早期识别？3)能否通过精确控制有源传感材料的几何形状来提高导电聚合物传感器的灵敏度？由金属氧化物、导电聚合物和压电元件组成的气体传感器阵列将在北卡罗来纳州立大学的生物医学仪器和生物医学微传感器实验室进行组装。这些传感器阵列将被整合到一个电子鼻仪器中，该仪器已经在北卡罗来纳州制造。北卡罗来纳州立大学的设备和商用电子鼻仪器（杜克大学味觉和嗅觉实验室的AromaScan A32S）将用于在杜克大学医学中心的临床研究单元#2中对细菌培养物的顶空取样。然后，传感器数据将在北卡罗来纳州立大学使用归一化、特征提取和模式分类算法进行分析。将评估传感器阵列和数据处理算法在区分培养菌株方面的性能。将对传感器进行测试，以确定它们检测十种重要耐药微生物中的至少四种的能力。这些初步实验室研究的结果有望指导未来制造和测试用于快速诊断细菌培养的手持式原型仪器的工作。这项探索性调查被认为是第一个对潜在传感器技术的价值进行全面和系统调查的研究项目。调查的成功可能会导致医生在确定致病病原体之前，开一种针对特定疾病的抗生素，而不是使用广谱抗生素。因此，人们相信细菌产生耐药性的风险将会降低。* * *

9807617 Nagle The investigation will methodically explore the potential for applying emerging "electronic nose" technologies to the rapid detection and analysis of a wide variety of bacterial pathogens. Rapid identification of disease-causing bacterial pathogens would significantly reduce the time required for the diagnostician to prescribe a specific antibiotic. The researchers seek to answer three questions during the twelve months term of their work: 1) Can existing gas sensors detect a wide range of human bacterial pathogens? 2) Can existing gas sensors be used for early identification of one or more human pathogens in culture? 3) Can the sensitivity of conducting polymer sensors be improved for this application by precisely controlling the geometry of the active sensing material? Gas sensor arrays of metal oxide, conducting polymers, and piezoelectric elements are to be assembled in the Biomedical Instrumentation and Biomedical Microsensors Laboratories at NC State University. These sensor arrays will be incorporated into an electronic nose instrument that has been fabricated at NC State. The NC State device and a commercial electronic nose instrument (the AromaScan A32S from the Duke University Taste and Smell Lab) will be used to sample the headspace of bacterial cultures in the Clinical Research Unit #2 at Duke University Medical Center. The sensor data will then be analyzed using normalization, feature extraction, and pattern classification algorithms at NC State University. The performance of the sensor arrays and data processing algorithms in differentiating cultured bacteria strains will be evaluated. Sensors will be tested to determine their abilities to detect at least four of ten important drug-resistant microbes. The results of these preliminary laboratory studies are expected to guide future efforts to fabricate and test a hand-held prototype instrument designed for rapid diagnosis of bacterial cultures. This exploratory investigation is believed to be the first research project to make a comprehensive and methodical investigation of the value of the underlying sensor technologies. Success from the investigation could lead to physicians prescribing a disease-specific antibiotic rather than using a broad-spectrum antibiotic until the offending pathogen is identified. Consequently, it is believed the risk will be lowered of the bacteria developing drug resistance. ***