POLYCYCLIC AROMATIC HYDROCARBONS: ULTRASENSITIVE DETECTION, EARLY LIFE EXPOSURES-CLINICAL OUTCOMES (PRETERM BIRTHS, CHRONIC LUNG DISEASE, AND NEUROCOGNITIVE DEFICITS), PREVENTION AND REMEDIATION
多环芳烃:超灵敏检测、生命早期暴露-临床结果(早产、慢性肺病和神经认知缺陷)、预防和补救
基本信息
- 批准号:10401127
- 负责人:
- 金额:--
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2020
- 资助国家:美国
- 起止时间:2020-02-28 至 2021-07-24
- 项目状态:已结题
- 来源:
- 关键词:AirAreaAromatic CompoundsAromatic Polycyclic HydrocarbonsBenchmarkingBiologicalChemicalsChemistryChronic lung diseaseClinicalClutteringsComplexDataData ScienceDetectionDevelopmentEffectivenessEnvironmentFamilyFoundationsGeometryGoalsHealthHumanImageInvestigationMachine LearningMass FragmentographyMethodsMolecularMonitorNeurocognitive DeficitOutcomeParentsPartition CoefficientPatient MonitoringPolymersPremature BirthPreventionResearchSamplingSoilSpectrum AnalysisSurfaceTestingTrainingVariantVisualWaterWorkbasedesigndetection sensitivityearly life exposureeffectiveness testingexposed human populationhazardimprovedinnovationinterestlearning classifiermachine learning algorithmmachine learning methodmonolayernanoparticleremediationspectroscopic surveysuperfund sitesurface coatingsynergismtooltraining opportunityvibration
项目摘要
Project Summary
The overarching goal of this project is the development of new and innovative approaches to ultrasensitive
detection and identification of polycyclic aromatic hydrocarbon (PAH) molecules and their functionalized
derivatives (polycyclic aromatic compounds, or PACs). Ms. Mary Bajomo, will pursue research central to these
project goals, as outlined by both Specific Aims. The Specific Aims of this Diversity Supplement form a central,
essential subset of the work required to achieve the project goals, and provide an essential foundation for the
sensing methods to be developed over the course of this project. They also lay the groundwork for bringing
Machine Learning methods into the subfield of spectroscopic chemical sensing. Pursuing research at the
interface between Chemistry and Machine Learning presents an exceptional training opportunity for Ms.
Bajomo, and will allow her to interact strongly with the three PIs and their research groups in three fields: the
Halas group, for experimental chemistry in the area of surface-enhanced spectroscopic sensing, the
Nordlander group, on nanoparticle-based substrate design, and the Patel group, experts in Machine Learning
and Data Science. Our hypothesis is that Machine Learning classifiers can be developed and used to
distinguish between specific PAH and PAC molecules found in environmental or biological samples through
their vibrational spectroscopic signatures. An essential aspect of this approach is the identification of PAH and
PAC molecules while embedded in a molecular or polymer capture layer that has been designed to extract
PAH/PAC molecules from environmental and/or biological samples that has its own specific spectroscopic
signature “background”. These investigations are foundational to the detection of multicomponent mixtures of
PAH/PAC molecules from realistic environmental or biological samples, using a combination of surface-
enhanced spectroscopies and Machine Learning algorithms analogous to image recognition in cluttered,
complex background environments. The two Specific Aims that Ms Bajomo will pursue are: Specific Aim 1: The
identification and quantitative characterization of a universal capture layer for the wide range of PAH and PAC
compounds encountered in biological and environmental samples. This capture layer would be serve as a
universal coating for surface-enhanced Raman and Infrared spectroscopic substrates, and allow for the
extraction of PAH and PAC molecules from solution in concentrations suitable for detection, consistent with
concentrations of these chemicals found in samples of interest. Specific Aim 2: To develop surface-enhanced
chemical sensing data as input to Machine Learning classifiers, to benchmark their effectiveness in identifying
specific PAH molecules and distinguishing PAH/PAC molecules from each other by ML methods. This close
synergy between experimental spectroscopic studies and ML classifier testing presents an outstanding
opportunity for graduate training at the interface between two extremely important and dynamic research field
for Ms. Bajomo.
项目摘要
这个项目的首要目标是开发新的和创新的方法来处理超敏感
多环芳烃(PAH)分子及其功能化的检测与鉴定
衍生物(多环芳香化合物,或PAC)。Mary Bajomo女士将进行以这些为中心的研究
项目目标,由两个具体目标概述。这份多样性补充文件的具体目标形成了一个中心,
实现项目目标所需工作的基本子集,并为
将在该项目过程中开发的传感方法。它们还为带来
将机器学习方法引入光谱化学传感的子领域。在大学从事研究工作
化学和机器学习之间的接口为MS提供了一个特殊的培训机会。
Bajomo,并将使她能够在三个领域与三个PI及其研究小组进行强有力的互动:
哈拉斯小组,表面增强光谱传感领域的实验化学,
Nordlander小组,基于纳米颗粒的基板设计,Patel小组,机器学习专家
和数据科学。我们的假设是,机器学习分类器可以被开发并用于
通过以下方法区分环境或生物样品中发现的特定PAH和PAC分子
它们的振动光谱特征。这种方法的一个基本方面是识别PAH和
当PAC分子嵌入分子或聚合物捕获层时,该捕获层被设计为提取
来自环境和/或生物样品的PAH/PAC分子,具有自己的特定光谱
签名“背景”。这些研究是检测多组分混合物的基础
PAH/PAC分子来自现实的环境或生物样品,使用表面-
增强的光谱和机器学习算法,类似于杂乱无章、
复杂的背景环境。巴约莫女士将追求的两个具体目标是:具体目标1:
广谱PAH和PAC通用捕获层的鉴定和定量表征
在生物和环境样品中遇到的化合物。该捕获层将被用作
用于表面增强拉曼和红外光谱衬底的通用涂层,并允许
从溶液中提取适合于检测的浓度的PAH和PAC分子,与
在感兴趣的样本中发现这些化学物质的浓度。具体目标2:开发表面增强技术
将化学传感数据作为机器学习分类器的输入,以衡量其在识别
并用ML方法对PAH/PAC分子进行了区分。如此接近
实验光谱研究和ML分类器测试之间的协同提供了一个突出的
在两个极其重要和充满活力的研究领域之间的交界处提供研究生培训的机会
给巴乔莫女士。
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)
数据更新时间:{{ journalArticles.updateTime }}
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
BHAGAVATULA MOORTHY其他文献
BHAGAVATULA MOORTHY的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('BHAGAVATULA MOORTHY', 18)}}的其他基金
Mechanisms of exacerbation of COVID-19 pathogenesis in mice expressing human ACE2 by polycyclic aromatic hydrocarbons (PAHs), and its protection by inhibition of soluble epoxide hydrolase (sEH)
多环芳烃 (PAH) 表达人 ACE2 的小鼠中 COVID-19 发病机制恶化,以及通过抑制可溶性环氧化物水解酶 (sEH) 对其进行保护
- 批准号:
10156460 - 财政年份:2021
- 资助金额:
-- - 项目类别:
Mechanisms of exacerbation of COVID-19 pathogenesis in mice expressing human ACE2 by polycyclic aromatic hydrocarbons (PAHs), and its protection by inhibition of soluble epoxide hydrolase (sEH)
多环芳烃 (PAH) 表达人 ACE2 的小鼠中 COVID-19 发病机制恶化,以及通过抑制可溶性环氧化物水解酶 (sEH) 对其进行保护
- 批准号:
10337295 - 财政年份:2021
- 资助金额:
-- - 项目类别:
Proj3:Role of cytochrome P450 (CYP)1A/1B1 enzymes in the potentiation of neonatal lung injury in newbron mice exposed prenatally to PHs, and increased risk of premature infants to chronic lung disease
Proj3:细胞色素 P450 (CYP)1A/1B1 酶在产前暴露于 PH 的新生小鼠中增强新生儿肺损伤中的作用,并增加早产儿患慢性肺病的风险
- 批准号:
10116394 - 财政年份:2020
- 资助金额:
-- - 项目类别:
Proj3:Role of cytochrome P450 (CYP)1A/1B1 enzymes in the potentiation of neonatal lung injury in newbron mice exposed prenatally to PHs, and increased risk of premature infants to chronic lung disease
Proj3:细胞色素 P450 (CYP)1A/1B1 酶在产前暴露于 PH 的新生小鼠中增强新生儿肺损伤中的作用,并增加早产儿患慢性肺病的风险
- 批准号:
10559705 - 财政年份:2020
- 资助金额:
-- - 项目类别:
POLYCYCLIC AROMATIC HYDROCARBONS: ULTRASENSITIVE DETECTION, EARLY LIFE EXPOSURES-CLINICAL OUTCOMES (PRETERM BIRTHS, CHRONIC LUNG DISEASE, AND NEUROCOGNITIVE DEFICITS), PREVENTION AND REMEDIATION
多环芳烃:超灵敏检测、生命早期暴露-临床结果(早产、慢性肺病和神经认知缺陷)、预防和补救
- 批准号:
10382017 - 财政年份:2020
- 资助金额:
-- - 项目类别:
POLYCYCLIC AROMATIC HYDROCARBONS: ULTRASENSITIVE DETECTION, EARLY LIFE EXPOSURES-CLINICAL OUTCOMES (PRETERM BIRTHS, CHRONIC LUNG DISEASE, AND NEUROCOGNITIVE DEFICITS), PREVENTION AND REMEDIATION
多环芳烃:超灵敏检测、生命早期暴露-临床结果(早产、慢性肺病和神经认知缺陷)、预防和补救
- 批准号:
10559666 - 财政年份:2020
- 资助金额:
-- - 项目类别:
Core A: Administrative and Research Translation Core (ARTC)
核心 A:行政和研究翻译核心 (ARTC)
- 批准号:
10116385 - 财政年份:2020
- 资助金额:
-- - 项目类别:
Core A: Administrative and Research Translation Core (ARTC)
核心 A:行政和研究翻译核心 (ARTC)
- 批准号:
10559668 - 财政年份:2020
- 资助金额:
-- - 项目类别:
POLYCYCLIC AROMATIC HYDROCARBONS: ULTRASENSITIVE DETECTION, EARLY LIFE EXPOSURES-CLINICAL OUTCOMES (PRETERM BIRTHS, CHRONIC LUNG DISEASE, AND NEUROCOGNITIVE DEFICITS), PREVENTION AND REMEDIATION
多环芳烃:超灵敏检测、生命早期暴露-临床结果(早产、慢性肺病和神经认知缺陷)、预防和补救
- 批准号:
10116383 - 财政年份:2020
- 资助金额:
-- - 项目类别:
Mechanistic role of P4501 enzymes in the prevention of PAH carcinogenesis by omega 3 fatty acids
P4501 酶在 omega 3 脂肪酸预防 PAH 致癌中的机制作用
- 批准号:
10163846 - 财政年份:2018
- 资助金额:
-- - 项目类别:
相似国自然基金
层出镰刀菌氮代谢调控因子AreA 介导伏马菌素 FB1 生物合成的作用机理
- 批准号:2021JJ40433
- 批准年份:2021
- 资助金额:0.0 万元
- 项目类别:省市级项目
寄主诱导梢腐病菌AreA和CYP51基因沉默增强甘蔗抗病性机制解析
- 批准号:32001603
- 批准年份:2020
- 资助金额:24.0 万元
- 项目类别:青年科学基金项目
AREA国际经济模型的移植.改进和应用
- 批准号:18870435
- 批准年份:1988
- 资助金额:2.0 万元
- 项目类别:面上项目
相似海外基金
Onboarding Rural Area Mathematics and Physical Science Scholars
农村地区数学和物理科学学者的入职
- 批准号:
2322614 - 财政年份:2024
- 资助金额:
-- - 项目类别:
Standard Grant
TRACK-UK: Synthesized Census and Small Area Statistics for Transport and Energy
TRACK-UK:交通和能源综合人口普查和小区域统计
- 批准号:
ES/Z50290X/1 - 财政年份:2024
- 资助金额:
-- - 项目类别:
Research Grant
Wide-area low-cost sustainable ocean temperature and velocity structure extraction using distributed fibre optic sensing within legacy seafloor cables
使用传统海底电缆中的分布式光纤传感进行广域低成本可持续海洋温度和速度结构提取
- 批准号:
NE/Y003365/1 - 财政年份:2024
- 资助金额:
-- - 项目类别:
Research Grant
Point-scanning confocal with area detector
点扫描共焦与区域检测器
- 批准号:
534092360 - 财政年份:2024
- 资助金额:
-- - 项目类别:
Major Research Instrumentation
Collaborative Research: Scalable Manufacturing of Large-Area Thin Films of Metal-Organic Frameworks for Separations Applications
合作研究:用于分离应用的大面积金属有机框架薄膜的可扩展制造
- 批准号:
2326714 - 财政年份:2024
- 资助金额:
-- - 项目类别:
Standard Grant
Collaborative Research: Scalable Manufacturing of Large-Area Thin Films of Metal-Organic Frameworks for Separations Applications
合作研究:用于分离应用的大面积金属有机框架薄膜的可扩展制造
- 批准号:
2326713 - 财政年份:2024
- 资助金额:
-- - 项目类别:
Standard Grant
Unlicensed Low-Power Wide Area Networks for Location-based Services
用于基于位置的服务的免许可低功耗广域网
- 批准号:
24K20765 - 财政年份:2024
- 资助金额:
-- - 项目类别:
Grant-in-Aid for Early-Career Scientists
RAPID: Collaborative Research: Multifaceted Data Collection on the Aftermath of the March 26, 2024 Francis Scott Key Bridge Collapse in the DC-Maryland-Virginia Area
RAPID:协作研究:2024 年 3 月 26 日 DC-马里兰-弗吉尼亚地区 Francis Scott Key 大桥倒塌事故后果的多方面数据收集
- 批准号:
2427233 - 财政年份:2024
- 资助金额:
-- - 项目类别:
Standard Grant
Postdoctoral Fellowship: OPP-PRF: Tracking Long-Term Changes in Lake Area across the Arctic
博士后奖学金:OPP-PRF:追踪北极地区湖泊面积的长期变化
- 批准号:
2317873 - 财政年份:2024
- 资助金额:
-- - 项目类别:
Standard Grant
RAPID: Collaborative Research: Multifaceted Data Collection on the Aftermath of the March 26, 2024 Francis Scott Key Bridge Collapse in the DC-Maryland-Virginia Area
RAPID:协作研究:2024 年 3 月 26 日 DC-马里兰-弗吉尼亚地区 Francis Scott Key 大桥倒塌事故后果的多方面数据收集
- 批准号:
2427232 - 财政年份:2024
- 资助金额:
-- - 项目类别:
Standard Grant