Population monitoring of stress markers in underserved communities

服务欠缺社区压力标记的人口监测

• 批准号: 10766447
• 负责人: Avni A Argun
• 金额: $ 28.22万
• 依托单位: GINER, INC.
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-15 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10766447
• 关键词: Accident and Emergency department; Acute; Address; Adult; Algorithms; Area; Back; Benchmarking; Biological Assay; Biological Markers; Biosensor; Boston; Buffers; Caffeine; Chronic; Clinics and Hospitals; Collaborations; Collection; Communities; Community Health; Consumption; Cortisone; Data; Data Collection; Data Correlations; Detection; Development; Devices; Disasters; Discrimination; Disease; Emotional; Epidemiologist; Epidemiology; Event; Feces; Goals; Health; Health Professional; Health Status; Heart Diseases; High Pressure Liquid Chromatography; Hormones; Human; Human body; Hydrocortisone; Individual; Intervention; Label; Laboratories; Life; Massachusetts; Measures; Methodology; Methods; Minority Groups; Monitor; Mouth Diseases; National Heart, Lung, and Blood Institute; Neighborhood Health Center; Neighborhoods; Neurologic; Nucleic Acids; Opioid; Oral Diagnosis; Outcome; Peptides; Phase; Physics; Physiological; Population; Population Distributions; Poverty; Public Health; Resource Allocation; Resource-limited setting; Resources; Risk; Rural Community; Saliva; Salivary; Sampling; Scientist; Sensitivity and Specificity; Shapes; Site; Specificity; Stream; Stress; Structural Racism; Students; Surveys; System; Technology; Testing; Time; Transistors; Transportation; United States; Urban Community; Urine; Validation; Work; acute stress; aptamer; college; cost; cost effective; cross reactivity; design; detection limit; experience; graphene; health assessment; health disparity; heart disease risk; improved; instrument; minority communities; neuropeptide Y; pandemic disease; pandemic impact; performance tests; population survey; portability; post-pandemic; professor; programs; prototype; racism; research and development; response; sample collection; sensor; septic; social; statistics; success; tool; underserved community; vulnerable community; wastewater epidemiology; wastewater monitoring; wastewater samples; wastewater sampling; wastewater testing

PROJECT SUMMARY/ABSTRACT Daily stresses, as well as social, emotional, and financial challenges, can activate physiological stress. Current public health monitoring systems cannot quantify community stress levels for millions of low-resource and underserved communities. By identifying communities experiencing high levels of stress using wastewater- based epidemiology, public health professionals can allocate resources to communities in need. Additionally, proactively (rather than retrospectively) identifying stress crises can help alleviate the long-term consequences of stress such as chronic heart diseases as well as neurological and life-threatening diseases and fatalities. Wastewater monitoring is a proven strategy to identify areas needing intervention instead of relying on population surveys or emergency-room, hospital/clinics data statistics. However, current wastewater analysis requires costly laboratory-based tests that involve labor-intensive sample collection, transportation, and analysis, resulting in long (days) turnaround times. Giner proposes to develop a compact, portable, label-free Graphene Field Effect Transistor (G-FET) sensor utilizing high-specificity aptamers for rapid, accurate, cost- effective, and multiplexed monitoring of well-established stress biomarkers in wastewater samples. Since the sensor generates rapid results compared to incumbent methods which rely on batch sampling of wastewater streams followed by expensive, time-consuming analysis, this technology will provide actionable real-time data at a fraction of the cost of incumbent methods, encouraging widespread use. The overall goal of the program is to demonstrate a test methodology and a field-ready prototype for simultaneous detection of multiple stress biomarkers in wastewater at pg/mL levels. To support the proof of concept and alleviate risk, Giner has successfully detected peptide biomarkers in wastewater solutions including one of the target stress markers, Neuropeptide Y (NPY). We will add two additional stress biomarkers, Cortisol and Cortisone, as well as a population marker Paraxanthine in Phase I. Multiple samples from various wastewater sites will be analyzed with Giner’s sensor and the results will be cross-validated in house using the gold standard HPLC-MS/MS method. Giner will achieve this by using its prior expertise in biosensors and wastewater testing and in close collaboration with an interdisciplinary team of scientists, social scientists, and public health epidemiologists. Once developed, the technology will also be suitable for the detection of any additional target wastewater biomarkers for which an aptamer can be prepared.

项目概要/摘要 日常压力以及社交、情感和财务挑战会引发生理压力。 公共卫生监测系统无法量化数百万资源匮乏和贫困人口的社区压力水平 通过识别使用废水而面临高压力的社区。 基于流行病学，公共卫生专业人员可以向有需要的社区分配资源。 主动（而不是回顾性地）识别压力危机有助于减轻长期后果 慢性心脏病以及神经系统和危及生命的疾病和死亡等压力。 废水监测是一种行之有效的策略，可以识别需要干预的领域，而不是依赖 人口调查或急诊室、医院/诊所的数据统计 然而，当前的废水分析。 需要昂贵的实验室测试，涉及劳动密集型样本采集、运输和 Giner 建议开发一种紧凑、便携式、无标签的设备。 石墨烯场效应晶体管 (G-FET) 传感器利用高特异性适体实现快速、准确、成本低廉 自那时以来，对废水样品中成熟的应激生物标志物进行了有效的、多重的监测。 与依赖废水批量采样的现有方法相比，传感器可以快速生成结果 流，然后进行昂贵且耗时的分析，该技术将提供可操作的实时数据 成本仅为现有方法的一小部分，鼓励广泛使用。 该计划的总体目标是展示测试方法和现场就绪原型 同时检测废水中 pg/mL 水平的多种生物标志物应力以支持证明。 概念并降低风险，Giner 成功检测废水溶液中的肽生物标志物 包括目标应激标记物之一，神经肽 Y (NPY)，我们将添加两个额外的应激。 生物标志物皮质醇和可的松，以及第一阶段的群体标志物副黄嘌呤。多个样本 来自不同废水处理场的废水将使用 Giner 的传感器进行分析，结果将在 使用金标准 HPLC-MS/MS 方法的公司将利用其先前的专业知识来实现​​这一目标。 生物传感器和废水测试，并与跨学科的科学家团队、社会 一旦开发出来，该技术也将适用于科学家和公共卫生流行病学家。 检测可以制备适配体的任何其他目标废水生物标志物。