Toward Rapid, Non-Invasive, Highly Sensitive, Multiplex Detection of Respiratory Pathogens
实现呼吸道病原体的快速、非侵入性、高灵敏度、多重检测
基本信息
- 批准号:9005094
- 负责人:
- 金额:$ 25.24万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2016
- 资助国家:美国
- 起止时间:2016-03-10 至 2018-02-28
- 项目状态:已结题
- 来源:
- 关键词:AcuteAddressAdenovirusesAdultAffectAgeAnimal ModelAnimalsAntibiotic ResistanceAntibiotic TherapyAntibiotic susceptibilityBacterial InfectionsBacterial PneumoniaBiological MarkersBreath TestsBronchoalveolar LavageCause of DeathCenters for Disease Control and Prevention (U.S.)ChildChildhoodClinicClinicalClinical assessmentsCommunicable DiseasesDataDetectionDevelopmentDevicesDiagnosisDiagnosticDiagnostic ProcedureEngineeringEtiologyEvaluationExhalationFeverGenerationsHaemophilus influenzaeHealthHumanHuman DevelopmentImmune systemInfectionInfectious AgentInfluenza A virusKlebsiella pneumonia bacteriumLegionella pneumophilaLifeLungMeasurableMeasuresMissionMolecularMonitorMoraxella (Branhamella) catarrhalisNational Institute of Allergy and Infectious DiseaseOrganismOutcomePathogen detectionPatientsPhenotypePneumoniaPopulationProductionPseudomonas aeruginosaPublic HealthResearchResearch Project GrantsResistance profileRespiratory SystemRespiratory Tract InfectionsRespiratory syncytial virusRodentRodent ModelSamplingSchoolsSeriesSpecificitySputumStaphylococcus aureusStreptococcus pneumoniaeTechniquesTechnologyTimeUnited States National Institutes of HealthVermontViralVirus DiseasesWorkbaseclinically relevantco-infectionimprovedinnovationinterestmouse modelmultiplex detectionnovelnovel strategiesoutcome forecastpathogenpersonalized diagnosticspublic health relevancerapid diagnosisresearch studyrespiratoryresponsesample collectiontool
项目摘要
DESCRIPTION (provided by applicant): Current clinical diagnostic methods for pneumonia typically take days or weeks and always require a sample from the patient, typically sputum. If sputum cannot be produced, it can sometimes be induced or lung lavage can be taken, both invasive techniques. Pneumonia is still one of the world's leading causes of death for children under the age of 5 according to the WHO and one of the top killers for adults in the USA, according to the CDC. Hence, there is a critical need for improved diagnostic tools to detect lung infections. Research groups at Dartmouth's Thayer School of engineering and the Vermont Lung Center have developed a technique allowing for rapid, non-invasive diagnosis of airway infections by analyzing infection-specific volatiles in the exhaled breath for singular infections,
which can generate a diagnosis within minutes. The proposed work will complete the remaining experiments necessary before this technology is taken to a human population. The hypothesis is that that exhaled breath volatiles can be used to diagnose infections of the lung, and specifically, to distinguish between different pathogens, even during co-infection, for acute febrile illnesses. The hypothesis will be addressed in two specific aims: SA1: To determine whether breath volatile molecules can be used to distinguish between respiratory bacterial infections during clinical-relevant scenarios in a murine model. These experiments will demonstrate that a subset of breath molecules reflect infection etiology. The validity and specificity of the approach will be determined using confounding scenarios such as bacterial co-infection (in the lung and elsewhere) as well as during antibiotic treatment. This aim will also demonstrate determination of antibiotic susceptibility using breath for two organisms of high clinical interest (K. pneumoniae and S. aureus). SA2: To establish the utility of breath volatile molecules to distinguish between viral and bacterial infections. It will be determined how bacterial and viral co-infection affects the diagnostic precision of the exhaled breath analysis. Using influenza A virus, adenovirus and respiratory syncytial virus, it will be demonstrated that the immune system response to viral infection leads to the generation of molecules that can be detected in the breath and are diagnostic of infection etiology. All bacterial and viral experiment will use known human pathogens and will take place in well-developed animal models. The research in this proposal is innovative because it utilizes the best tools currently available to measure breath molecules in a systematic series of clinically-relevant experimental scenarios. The outcomes will represent a robust and substantial step towards a novel conceptual system for respiratory pathogen detection. The data from this study is expected to support forthcoming studies in humans and the development of an analytical device for use in the clinic. Ultimately, the technology shows promise for radically improved patient diagnosis, monitoring, and prognosis.
描述(由申请人提供):目前肺炎的临床诊断方法通常需要几天或几周的时间,并且总是需要患者的样本,通常是痰。如果不能产生痰,有时可以诱导痰,或者可以进行肺冲洗,这两种侵入性技术。根据世界卫生组织的数据,肺炎仍然是世界上5岁以下儿童死亡的主要原因之一,根据美国疾病控制与预防中心的数据,肺炎仍然是美国成年人的头号杀手之一。因此,迫切需要改进诊断工具来检测肺部感染。达特茅斯大学塞耶工程学院和佛蒙特州肺脏中心的研究小组开发了一种技术,通过分析呼气中感染特有的挥发物来诊断呼吸道感染,从而快速、非侵入性地诊断呼吸道感染。
它可以在几分钟内产生诊断结果。这项拟议的工作将完成在这项技术应用于人类之前所需的剩余实验。假设呼出的呼吸挥发物可以用来诊断肺部感染,具体地说,可以用来区分不同的病原体,甚至在急性发热性疾病的合并感染期间也是如此。这一假设将在两个具体目标中得到解决:SA1:在小鼠模型的临床相关场景中,确定呼吸挥发性分子是否可以用于区分呼吸道细菌感染。这些实验将证明呼吸分子的一个子集反映了感染的病原学。该方法的有效性和特异性将通过混淆的情况来确定,例如细菌合并感染(在肺部和其他地方)以及在抗生素治疗期间。这一目标还将展示使用呼吸测定两种临床上高度感兴趣的生物(肺炎克雷伯菌和金黄色葡萄球菌)的抗生素敏感性。SA2:建立呼吸挥发性分子在区分病毒感染和细菌感染方面的效用。将确定细菌和病毒混合感染如何影响呼气分析的诊断精度。利用甲型流感病毒、腺病毒和呼吸道合胞病毒,将证明免疫系统对病毒感染的反应导致在呼吸中可以检测到的分子的产生,并对感染病原学进行诊断。所有的细菌和病毒实验都将使用已知的人类病原体,并将在发展良好的动物模型中进行。这项提案中的研究是创新的,因为它利用了目前可用的最好的工具来测量一系列与临床相关的系统实验情景中的呼吸分子。这一结果将是朝着呼吸道病原体检测的新概念系统迈出的有力和实质性的一步。这项研究的数据有望支持即将进行的人体研究和临床使用的分析设备的开发。最终,这项技术显示出从根本上改善患者诊断、监测和预后的前景。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Jane HIll其他文献
Jane HIll的其他文献
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{{ truncateString('Jane HIll', 18)}}的其他基金
Prospective Longitudinal Assessment of Culture-Independent Molecular Airway Markers of Nontuberculous Mycobacteria
非结核分枝杆菌培养独立分子气道标志物的前瞻性纵向评估
- 批准号:
10063561 - 财政年份:2019
- 资助金额:
$ 25.24万 - 项目类别:
Prospective Longitudinal Assessment of Culture-Independent Molecular Airway Markers of Nontuberculous Mycobacteria
非结核分枝杆菌培养独立分子气道标志物的前瞻性纵向评估
- 批准号:
10321599 - 财政年份:2019
- 资助金额:
$ 25.24万 - 项目类别:
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