课题基金 / 基金详情

Development of Nanomembrane Electronics and Machine-Learning Algorithms for Quantitative Screening of Dysphagia Therapeutics

Development of Nanomembrane Electronics and Machine-Learning Algorithms for Quantitative Screening of Dysphagia Therapeutics
开发用于定量筛选吞咽困难治疗药物的纳米膜电子学和机器学习算法
批准号:
10373326
负责人:
Woon-Hong Yeo
金额:
$21.19万
依托单位国家:
美国
项目类别:
财政年份:
2021
资助国家:
美国
项目状态:
已结题
起止时间:
2021-09-23 至 2024-07-31

项目摘要

项目成果

Woon-Hong Yeo的其他基金

相似基金

相关文献

中文摘要
翻译
项目摘要 吞咽困难是吞咽反射的神经和肌肉功能受损, 导致衰弱和潜在的致命情况,如窒息、营养不良、脱水 或吞咽时的肺炎。吞咽困难困扰着近1500万美国人,尤其是 50-60岁或以上的人吞咽困难的可能性高达20%。然而,无论 对于吞咽困难的原因,目前还没有可用的治疗方法。限制 临床前研究吞咽困难的工具和方法是缺乏 吞咽困难的治疗。视频透视吞咽研究(VFSS)已被 在临床研究和药物动物模型研究中用于诊断吞咽困难 发展。然而,VFSS方法在临床研究中的应用有赖于 人体受试者,如摄入含钡(口服造影剂)的食物和运动 在X射线成像过程中的固定。VFSS工具在动物研究中显示了严重的问题 由于靶标不可控,导致图像质量差,药物不可靠 发展。总体而言,现有的商业系统都不能提供可移植的、实时的、 持续监测人类或动物的吞咽情况。 在这里,这个项目将开发一种新型的纳米膜电子系统,它提供了一种 持续的、定量的非侵入性吞咽活动评估 这将有助于开发潜在的吞咽困难药物。具体来说,我们将发展 柔软、超薄、轻便、小型化的可穿戴电子设备,可监控随时间变化的情况 通过无线实时记录肌电记录吞咽肌肉功能 吞咽困难大鼠模型的肌肉。在这个项目中,我们初步研究了对 吞咽困难的治疗将侧重于ALS相关的吞咽困难,因为有公认的 幼年严重吞咽困难的动物模型(转基因超氧化物歧化酶;SODG93A) 年龄。SODG93A动物模型已被广泛用于筛选潜在的治疗方法 化合物,包括FDA批准的两种ALS药物:依达拉奉和利鲁唑。总体来说,如果 如果成功,新开发的纳米膜电子产品将改变游戏规则 肌萎缩侧索硬化症相关吞咽困难及其他疾病候选药物的疗效评价- 相关的吞咽困难。这一研究成果有望为有效的治疗提供一种新的药物 吞咽困难的治疗,这最终将降低死亡率,提高患者的生活质量 吞咽困难的病人。
英文摘要
Project Summary Dysphagia is an impairment of the swallow reflex's neurological and muscular functions that causes a debilitating and potentially deadly condition such as choking, malnutrition, dehydration or pneumonia during swallowing. Dysphagia afflicts almost 15 million Americans, particularly individuals 50-60 years or older with up to a 20% chance of dysphagia. However, regardless of the cause of dysphagia, currently there are no available therapeutic treatments. Limitation of preclinical tools and methods to study dysphagia is one of the biggest reasons for the lack of therapeutic treatment for dysphagia. Video-fluoroscopic swallowing study (VFSS) has been used to diagnose dysphagia in a clinical study as well as research with animal models for drug development. However, the VFSS method in clinical study relies on the active cooperation of a human subject, such as ingestion of food with barium (oral contrast agent) and movement immobilization during X-ray imaging. The VFSS tool shows the severe issue in an animal study due to uncontrollable target, which results in poor image quality and unreliable drug development. Overall, none of the existing commercial systems can offer a portable, real-time, continuous monitoring of swallowing with either humans or animals. Here, this project will develop a novel, nanomembrane electronic system that offers a continuous, quantitative assessment of swallowing activities in a non-invasive way on the skin of rat models, which will help to develop potential dysphagia drugs. Specifically, we will develop soft, ultrathin, lightweight, miniaturized wearable electronics to monitor time-dependent changes of swallowing muscle functions via wireless, real-time recording of electromyograms on swallowing muscles of a dysphagia rat model. In this project, our initial study in the evaluation of dysphagia therapeutics will focus on ALS-related dysphagia since there are well-established animal models (transgenic superoxide dismutase; SODG93A) with severe dysphagia at a young age. SODG93A animal models have been widely used to screen potential therapeutic compounds, including two FDA-approved ALS drugs: edaravone and riluzole. Collectively, if successful, the newly developed nanomembrane electronics will be a game-changer in the therapeutic evaluation of candidate drugs for ALS-related dysphagia as well as other diseases- related dysphagia. The research outcome is expected to provide a new drug for an effective treatment of dysphagia, which will eventually reduce mortality and improve the quality of life of dysphagia patients.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
Development of Nanomembrane Electronics and Machine-Learning Algorithms for Quantitative Screening of Dysphagia Therapeutics
  • 批准号:
    10493361
  • 项目类别:
  • 资助金额:
    $19.71万
  • 财政年份:
    2021
  • 负责人:
    Woon-Hong Yeo
  • 依托单位:
Development of Nanomembrane Electronics and Machine-Learning Algorithms for Quantitative Screening of Dysphagia Therapeutics
  • 批准号:
    10675556
  • 项目类别:
  • 资助金额:
    $23.65万
  • 财政年份:
    2021
  • 负责人:
    Woon-Hong Yeo
  • 依托单位:
海外基金