CAS-MNP: Real time analysis of impact of nanoplastics on marine species using AI integrated microfluidics

必须量化微（5毫米）和纳米（100纳米）塑料堆积对海洋生态系统的影响，以便为从制造和废物处理协议到制定海洋物种消费营养指南等可持续实践提供信息。本项目将促进对纳米塑料暴露对海洋鱼类早期（胚胎和幼虫）发育影响的基本认识；由于这些阶段是最易受影响的，任何异常都可能对可持续的未来产生深远的影响。本研究的重点是鲯鳅（棘鱼科），一种在世界各地发现的商业和营养重要的鱼类。微流体技术将用于密切调节模拟海洋环境和纳米塑料暴露，而人工智能将用于将纳米塑料消耗和鱼类形态的实时可视化与环境条件相关联，从而产生影响纳米塑料消耗的因素（例如，大小、浓度、暴露阶段）及其对生长和发育的影响（例如，细胞和遗传变化）的基本数据。器官发育异常，生长迟缓，进食方式改变)。将在多个教育层次对广泛的非专业受众进行数据传播和教育推广，包括为佛罗里达国际大学的“车轮上的工程师”项目开发一系列适合年龄的模块，名为“钓鱼塑料”，学生和教师向不同教育层次的学生进行示范。在“捕捞塑料”课程中，学生将探索塑料在海洋中积聚的途径，对生态系统的影响以及减少传播的策略。该项目的跨学科性质还为罗德岛大学水产养殖专业的学生和佛罗里达国际大学的工程师提供了学习彼此语言的机会，并通过资助本科生、本科生顶点项目和研究生奖学金，将学术研究与技术结合起来。在纳米尺度上研究环境影响是气候变化和污染端到端研究的一个新范式，主要集中在宏观尺度上的表现。本研究采用一种机械方法，严格测量纳米塑料的生物积累作为环境（大小、浓度）和吸收机制（主动与被动）的函数，以及由此产生的鱼类从胚胎到幼虫阶段的发育变化。这种方法将使我们了解这些因素之间的关系，以及纳米塑料在毒性和形态方面的作用，从而深入了解导致这些结果的细胞过程。传感器嵌入含有单个胚胎/幼虫的微流体室中，生成实时电化学数据，与透明/半透明鱼的连续视觉测量相关联。环境影响将使用机器学习严格分类，以建立应用条件（纳米塑料成分/浓度），发育阶段，摄取机制（被动呼吸/饮用与主动喂养）和生物积累和形态的视觉测量之间的关系，这将与代谢指标氧气（O2）和总氨氮（TAN:NH3/NH4）的连续测量相关。利用人工智能来关联实时和原位获得的多种数据类型是一种独特的方法，可以更全面地了解环境影响，并为未来的比较研究铺平道路。将在多个教育层次上向广泛的非专业受众进行数据传播和教育推广，包括为佛罗里达国际大学的“车轮上的工程师”项目开发一系列适合年龄的关于塑料对环境影响的模块。该项目的跨学科性质也为罗德岛大学水产养殖专业的学生和佛罗里达国际大学的工程师提供了合作的机会，通过资助本科生、专注于微流体系统设计和传感器集成的Capstone项目以及研究生奖学金。该奖项反映了美国国家科学基金会的法定使命，并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，被认为值得支持。

The impact of micro (5mm) and nano (100nm) plastic accumulation on marine ecosystems must be quantified to inform sustainable practices ranging from manufacturing and waste processing protocols to the development of nutritional guidelines for marine species consumption. This project will advance the fundamental understanding of the impacts of nanoplastic exposure on the early stage (embryonic and larval) development of marine fish; as these phases are most susceptible, any abnormalities could have far-reaching ramifications for the sustainable future. The present study focuses on mahi-mahi (Coryphaenae hippurus), a commercially and nutritionally important fish species found around the world. Microfluidic technology will be used to closely regulate the simulated marine environment and nanoplastic exposure, while artificial intelligence will be implemented to correlate real time visualization of nanoplastic consumption and fish morphology with environmental conditions – yielding essential data on the factors affecting nanoplastic consumption (e.g., size, concentration, stage of exposure) and the resultant effects on growth and development (e.g., cellular and genetic changes, abnormal organ development, growth retardation, changed feeding patterns). Data dissemination and educational outreach to broad, non-specialized audiences will be conducted at multiple educational levels –including the development of a series of age-appropriate modules titled “Fishing plastics” for Florida International University’s “Engineers on Wheels” program, where students and faculty give hands on demonstrations to students at multiple educational levels. In “Fishing plastic” students will explore pathways through which plastics accumulate in the ocean, the impact on the ecosystem and strategies to minimize transmission. The interdisciplinary nature of the project also offers aquaculture students at the University of Rhode Island and engineers at Florida International University the opportunity to learn one another’s languages and integrate academic research with technology through funding for undergraduate students, undergraduate Capstone projects and a graduate fellowship.Examining environmental impact at the nanoscale is a new paradigm for end-end research into climate-change and pollution where the predominant focus is on macroscale manifestations. This study applies a mechanistic approach to rigorously measure - in situ and in real time – the bioaccumulation of nano plastics as a function of environment (size, concentration) and uptake mechanism (active vs passive) and the resultant developmental changes in fish from the embryonic through larval stages. This approach will inform our fundamental understanding of the relationship between these factors and the role of nano plastics beyond the black and white terms of toxicity and morphology to provide insight into the cellular processes that cause these outcomes. Sensors embedded in microfluidic chambers containing a singly embryo/larvae generate real-time electrochemical data to be correlated with continuous visual measurements of the transparent/semi-transparent fish. Environmental impact will be rigorously categorized using machine learning to establish a relationship between applied conditions (nanoplastic composition/concentration), developmental stage, uptake mechanism (passive respiration/drinking versus active feeding) and visual measurement of bioaccumulation and morphology which will be correlated with continuous measurement of metabolic indicators Oxygen (O2) and total ammonia nitrogen (TAN:NH3/NH4). The implementation of artificial intelligence to correlate multiple data types obtained in real time and in situ is a unique approach which enables a more comprehensive understanding of the environmental impact as well as paving the way for future comparative studies. Data dissemination and educational outreach to broad, non-specialized audiences will be conducted at multiple educational levels –including the development of a series of age-appropriate modules on the environmental impact of plastics for Florida International University’s “Engineers on Wheels” program. The interdisciplinary nature of the project also offers aquaculture students at the University of Rhode Island and engineers at Florida International University the opportunity to collaborate through funding for undergraduate students, Capstone projects focusing on microfluidic system design and sensor integration and a graduate fellowship.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.