权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

Research Supplements to Promote Diversity

促进多样性的研究补充

基本信息

批准号：
10889729
负责人：
Mathew Thoppil Mathew
金额：
$ 8.47万
依托单位：
ILLINOIS INSTITUTE OF TECHNOLOGY
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-09-01 至 2025-08-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10889729
关键词：
Actinobacillus actinomycetemcomitans Address Award Biological Markers Categories Cells Clinical Collection Complex Data Detection Development Devices Dimensions Enzymes Event Forsythia Fusobacterium nucleatum Future Gingiva Glass Goals Health Health Sciences Individual Industry Inflammation Ions Knowledge Label Lasers Machine Learning Measurement Measures Mediator Medical Metals Methods MicroRNAs Microfluidic Microchips Microfluidics Modality Molecular Monitor Output Parents Particle Size Patients Periodontal Diseases Periodontal Pocket Periodontitis Phenotype Play Porphyromonas gingivalis Preparation Prevotella intermedia Protocols documentation Raman Spectrum Analysis Reaction Research Research Project Grants Research Support Resolution Role Saliva Salivary Sampling Signal Transduction Signaling Protein Slide Spectrum Analysis Streptococcus mutans Structure Surface Testing Tissues Tooth structure Training Translational Research Treponema denticola bone career clinical application comorbidity density design detection method doctoral student experience high throughput screening imaging approach improved insight interdisciplinary collaboration lithography machine learning method machine learning model medical specialties microbial microorganism mobile sensor multiplex detection nano nanoparticle novel parent grant pathogen periodontopathogen personalized medicine point of care potential biomarker pre-doctoral prototype saliva sample sensor soft tissue tool

项目摘要

On-chip multiplex detection of periodontal pathogens by Raman imaging at single cell level Project Summary: Periodontitis is initiated by complex bacterial interaction in tissues surrounding the teeth. Periodontal pathogens accumulate in periodontal pockets and induce periodontal destruction in a cooperative manner, leading to gingival inflammation, soft tissue destruction, and bone destruction. These pathogens can serve as biomarkers to inform periodontal status. Surface- enhanced Raman spectroscopy (SERS) has emerged as a powerful label-free detection tool to discriminate bacterial phenotypes due to the Raman signatures of their unique molecular composition. To facilitate SERS utility in clinical applications, it is imperative to develop a platform that warrants simple and universal sample preparation method with minimal technical demand. We address this critical need in this study by pre-loading Ag nanoparticles (Ag-NPs) on all bacterial cells in a sample in a one-pot reaction. The reaction is quick and no species-specific label is needed. Following the parent grant's microbial compartmentalization concept, the pathogens will be disseminated to microchambers that are interconnected by parallel microchannels. By design, each microchamber accommodates one cell. Ag-NP enables the collection of well-resolved Raman spectrum at a single-cell level (Aim 1). Machine learning in combination with the snap-shot hyperspectral imaging approach will enable confident identification and enumeration of pathogen species with spatial resolution to facilitate on-chip multiplex detection (Aim 2). This is a versatile detection method that can be integrated on a portable sensor device as proposed in the parent grant. Integrating with other components of the parent grant, this research contributes to the development of a prototype salivary sensor that will offer detailed medical data from frequent and progressive monitoring, and it will be an effective tool for future personalized medicine and is expected to dramatically improve the patient's overall health. In addition to technical training, the predoctoral student will gain experience through engaging in interdisciplinary collaborations, providing him with insights into the intricacies of workflow within an interdisciplinary project and the pivotal role that each specialty subject would play in supporting research in diverse fields, preparing him to become capable of tackling multifaceted challenges in his future career.

牙周致病菌的芯片复合检测通过单细胞水平的拉曼成像项目概要：牙周炎是由牙齿周围组织中复杂的细菌相互作用引起的。牙周病病原体在牙周袋中积累并引起牙周破坏，合作的方式，导致牙龈炎症，软组织破坏，和骨杀伤性这些病原体可以作为生物标志物来告知牙周状况。表面- 增强的拉曼光谱（Sers）已经作为一种强大的无标记检测工具出现，由于细菌独特分子的拉曼特征，混合物.为了促进Sers在临床应用中的实用性，必须开发一个平台，这保证了简单和通用的样品制备方法，具有最小的技术要求。我们在本研究中通过在所有材料上预加载银纳米颗粒（Ag-NP）来解决这一关键需求在一锅反应中将样品中的细菌细胞分离出来。反应迅速，无种属特异性标签是必须的。根据父母格兰特的微生物区室化概念，病原体将传播到通过平行连接的微室中，微通道通过设计，每个微室容纳一个细胞。Ag-NP使在单细胞水平上收集良好分辨的拉曼光谱（目标1）。机器学习与快照高光谱成像方法相结合，以空间分辨率识别和计数病原体种类以促进芯片上多重检测（Aim 2）。这是一种通用的检测方法，可以集成在便携式传感器设备中提出的父母补助金。结合父母补助金的其他组成部分，这项研究有助于唾液传感器原型的开发，将提供详细的医疗数据，渐进式监测，它将是未来个性化医疗的有效工具，有望显著改善患者的整体健康状况。除了技术培训外，博士前学生将通过从事跨学科合作获得经验，为他提供了对跨学科项目中工作流程复杂性的见解，每个专业科目在支持不同领域的研究方面将发挥关键作用，使他能够在未来的职业生涯中应对多方面的挑战。