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OCE-PRF Chemical Imaging for Molecular Detection and Classification of Microplastics and their Influence on Zebrafish

OCE-PRF Chemical Imaging for Molecular Detection and Classification of Microplastics and their Influence on Zebrafish
用于微塑料分子检测和分类的 OCE-PRF 化学成像及其对斑马鱼的影响
批准号:
2205819
负责人:
Matthew Confer
金额:
$30.78万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2022
资助国家:
美国
项目状态:
已结题
起止时间:
2022-07-01 至 2024-06-30

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中文摘要
翻译
塑料使用的环境影响是现代社会最令人担忧的方面之一,因为它们不仅会破坏海洋种群,还会损害人类健康。微塑料(MP,小于5毫米的塑料)是海洋环境中的常见污染物,预计随着时间的推移,其流行率会增加,尺寸会减小。海洋生物通过直接摄入和营养转移(沿食物链向上转移)对多氯联苯进行生物累积,会降低海洋的健康水平,从而影响人类的食物供应。该项目的第一个目标是表征微塑料的生物累积以及不同聚合物材料、形状和尺寸组合在鱼类中产生的组织变化。这些知识对于确定哪些塑料对环境最有害非常重要。目前用于确定MP聚合物身份的方法是低效且耗时的。本研究的第二个目标是减少使用材料之间内在特性的差异来识别塑料所需的时间和数据。这项研究不仅将提供有关MP对鱼类健康影响的信息,还将提供有关MP如何影响人类的初步信息。目前关于MP在海洋生物中生物累积的研究将MP表征和计数与MP暴露引起的组织化学变化分离开来。该项目的主要目标是使用基于量子级联激光(QCL)的离散频率红外成像(DFIR)来表征不仅在斑马鱼(Danio rerio)中MP生物累积的位置,而且在不使用组织化学染色的情况下在同一样品中产生的组织变化。基于QCL的DFIR允许时间高效、数据丰富、无瑕疵的生物医学成像,但在很大程度上仅限于使用人体组织的概念验证。基于QCL的DFIR比标准傅里叶变换红外显微镜更省时,因为它只允许获取感兴趣的IR波段。对照斑马鱼组织(包括脾、心脏、鳃、肾、肠、肝、肌肉和脑)的文库将用DFIR成像并与相邻的HE染色切片相关联,以便开发人工智能(AI)管道来确定细胞的类型及其变化,从而建立第一个全面的斑马鱼组织化学成像(CI)数据库。将相对于对照组织库,研究具有不同几何形状(球体和纤维)、平均尺寸(2和10 µm)、剂量(0.5和10 mg/L)和暴露时间(3和14天)的聚对苯二甲酸乙二醇酯(PET)和聚四氟乙烯(PTFE)MP对斑马鱼组织的影响。该项目的次要产品将是一个时间和数据效率高的AI管道,用于基于DFIR的MP成分分析,适用于非生物相关样本。这项工作的总体目标是不仅研究MP在模型物种中的生物累积,而且为将基于QCL的DFIR成像扩展到MP表征和进一步的斑马鱼研究奠定基础,该奖项反映了NSF的法定使命,并被认为值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估来支持。
英文摘要
Environmental impacts of plastic use are amongst the most concerning aspects of modern society as they can not only destroy marine populations but also harm human health. Microplastics (MP, plastic less than 5 mm) are common pollutants in marine environments and are expected to increase in prevalence, and decrease in size, with time. Bioaccumulation of MPs in marine life via direct ingestion and trophic transfer (transfer up the food chain) degrades the health of the oceans and, as a result, human food supply. The first goal of this project is characterization of microplastic bioaccumulation and resulting tissue changes in fish across different polymer material, shape, and size combinations. This knowledge is important for determining which plastics are most harmful to the environment. Current methods for determining MP polymer identity are inefficient and time consuming. The second goal of this study is to decrease the time and data required to identify plastics using the difference in intrinsic properties between materials. This study will not only provide information regarding the effect of MPs on fish health, but also provide preliminary information on how MPs affect humans. Current studies of MP bioaccumulation in marine life decouple MP characterization and counting from chemical variations in tissues caused by MP exposure. The primary goal of this project is to use quantum cascade laser (QCL) based discrete frequency infrared imaging (DFIR) to characterize not only the location of MP bioaccumulation in zebrafish (Danio rerio), but also the resulting tissue changes in the same sample without the use of histochemical staining. QCL based DFIR allows for time-efficient, data-rich, stainless biomedical imaging but has largely been limited to proof of concept using human tissue. QCL based DFIR is more time-efficient than standard Fourier transform infrared microscopy as it allows only IR bands of interest to be acquired. A library of control zebrafish tissue (including spleen, heart, gills, kidney, intestine, liver, muscle, and brain) will be imaged with DFIR and correlated with adjacent H&E-stained sections in order to develop an artificial intelligence (AI) pipeline to determine the types of cells and their variation into a first of its hind comprehensive zebrafish tissue chemical imaging (CI) database. The effects of polyethylene terephthalate (PET) and polytetrafluoroethylene (PTFE) MPs with different geometries (sphere and fibers), average sizes (2 and 10 µm), doses (0.5 and 10 mg/L), and exposure times (3 and 14 days) on zebrafish tissue will be studied relative to the control tissue library. A secondary product of this project will be a time and data efficient AI pipeline for DFIR based MP composition analysis that is applicable to non-biologically associated samples. The overarching goal of this work is to not only study MP bioaccumulation in a model species, but also to lay the groundwork for expansion of QCL based DFIR imaging to MP characterization and further zebrafish studies across biomedical sciences.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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