Research Supplements to Promote Diversity

促进多样性的研究补充

• 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
• 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

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.

牙周病原体的片上多重检测 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发的。 牙周病原菌在牙周袋中积聚并引起牙周破坏 以合作的方式，导致牙龈炎症、软组织破坏和骨质破坏 破坏。这些病原体可以作为了解牙周状态的生物标志物。表面- 增强拉曼光谱（SERS）已成为一种强大的无标记检测工具 根据细菌独特分子的拉曼特征来区分细菌表型 作品。为了促进SERS在临床应用中的应用，开发一个平台势在必行 这保证了简单且通用的样品制备方法，且技术要求极低。 我们在本研究中通过在所有材料上预载银纳米颗粒（Ag-NP）来解决这一关键需求。 一锅反应中样品中的细菌细胞。反应速度快且无物种特异性 需要标签。遵循母基金的微生物区划概念， 病原体将传播到并联互连的微室中 微通道。根据设计，每个微室可容纳一个细胞。 Ag-NP 使 在单细胞水平上收集高分辨率的拉曼光谱（目标 1）。机器学习在 与快照高光谱成像方法相结合将能够自信地 具有空间分辨率的病原体种类的识别和计数，以促进片上 多重检测（目标 2）。这是一种多功能检测方法，可以集成在 父资助中提出的便携式传感器设备。 与家长资助的其他组成部分相结合，这项研究有助于 开发唾液传感器原型，该传感器将提供来自频繁和频繁接触的详细医疗数据 渐进式监测，它将成为未来个性化医疗的有效工具， 预计将显着改善患者的整体健康状况。除了技术培训外， 博士前学生将通过跨学科合作获得经验， 让他深入了解跨学科项目中复杂的工作流程 每个专业学科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。

项目成果

A Review on Saliva-Based Health Diagnostics: Biomarker Selection and Future Directions.

基于唾液的健康诊断综述：生物标志物选择和未来方向。

• 发表时间: 2023-06-06
• 作者: Kumari, Swati;Samara, Mesk;Ampadi Ramachandran, Remya;Gosh, Sujoy;George, Haritha;Wang, Rong;Pesavento, Russell P;Mathew, Mathew T
• 通讯作者: Mathew, Mathew T

Early Predicting Tribocorrosion Rate of Dental Implant Titanium Materials Using Random Forest Machine Learning Models.

使用随机森林机器学习模型早期预测种植牙钛材料的摩擦腐蚀率。

• DOI: 10.1016/j.triboint.2023.108735
• 发表时间: 2023-09-01
• 期刊: Tribology international
• 影响因子: 6.2
• 作者: Remya Ampadi Ramach;ran;ran;V. Barão;D. Ozevin;C. Sukotjo;Pai P Srinivasa;M. Mathew
• 通讯作者: M. Mathew