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Developing a prototype device for point-of-care non-alcoholic fatty liver disease diagnostics

Developing a prototype device for point-of-care non-alcoholic fatty liver disease diagnostics
开发用于即时诊断非酒精性脂肪肝疾病的原型设备
批准号:
10027783
负责人:
金额:
$30.12万
依托单位:
依托单位国家:
英国
项目类别:
Collaborative R&D
财政年份:
2022
资助国家:
英国
项目状态:
已结题
起止时间:
2022 至 --

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中文摘要
翻译
非酒精性脂肪性肝病(NAFLD)是由肝脏脂肪堆积引起的,影响全球20-30%的成年人,其中约20%的人发展为更严重的疾病,称为非酒精性脂肪性肝炎(NASH)。nash相关的肝损害是可逆的,但前提是早期诊断。然而,NASH的诊断率极低,对大多数患者来说,诊断为时已晚,无法进行干预。需要新的检测方法,让更多的患者接受NASH检测,从而实现早期诊断和治疗。鉴于NASH很常见,理想情况下,这些测试需要由全科医生提供,因此必须是低成本的,并且需要很少的设备。现有的测试和正在开发的测试不能满足这些要求,因此需要采用创新的方法来填补这一空白。该提案利用Rosa Biotech的传感平台Pandra解决了这一需求,该平台可以高精度地检测患者血液样本中的NASH。Pandra利用嗅觉原理(嗅觉)来检测疾病。嗅觉系统使用蛋白质受体阵列,当气味进入鼻子时与之结合。大脑识别受体刺激的模式,并将这种模式解释为气味。当应用于生物传感时,这一原理被称为差分传感。它允许对样品总含量的微小变化进行分析,而不依赖于预先识别的疾病标记。罗莎的传感技术“Pandra”使用的是一组设计好的蛋白质,可以结合有色染料,而不是嗅觉受体,这是一项具有挑战性的工作。将该阵列暴露在含有脂肪的样品中,会在不同程度上取代蛋白质中的染料,导致整个阵列的颜色发生变化。这为样品产生了一个独特的“指纹”。人工智能(AI)算法经过训练,可以识别已知样本中与疾病相关的指纹之间的差异。该算法随后被用于检测未知样本中的疾病。Pandra生产成本低廉,非专业人士也可以使用,而且对脂肪成分的微小变化很敏感。这使得它非常适合NASH诊断。这个项目旨在生产一个早期的Pandra传感器原型,可以部署在全科医生手术的护理点。这将为临床医生提供一种宝贵的新工具,用于初步评估NASH高危患者并决定最佳转诊途径。最终,它将产生一种新的检测方法,使更多的患者能够接受NASH检测,减少发展为更严重的肝脏疾病、癌症和死亡的人数。
英文摘要
Non-alcoholic fatty liver disease (NAFLD) is caused by fat accumulation in the liver and affects 20-30% of adults globally, ˜20% of whom progress to a more serious condition called non-alcoholic steatohepatitis (NASH). NASH-related liver damage is reversible, but only if diagnosed early. However, NASH diagnosis rates are extremely low, and for most patients diagnosis occurs too late for intervention. New tests are needed that allow more patients to be tested for NASH, resulting in earlier diagnosis and treatment. Given that NASH is common, these tests ideally need to be provided by a GP and, therefore, must be low-cost and require little equipment. Existing tests and those in development do not meet these requirements, and there is a need for innovative approaches that fill this gap.This proposal addresses this need using Rosa Biotech's sensing platform, Pandra, which can detect NASH in patient blood samples with high accuracy. Pandra detects disease using the principle of olfaction (the sense of smell). The olfactory system uses arrays of protein receptors that bind to odorants as they enter the nose. The brain recognises patterns of receptor stimulation and interprets the pattern as a smell. When applied to biosensing, this principle is called differential sensing. It allows small changes in a sample's total contents to be analysed, without relying on pre-identified markers of disease.Rather than olfactory receptors, which are challenging to work with, Rosa's sensing technology, Pandra, uses arrays of designed proteins that bind coloured dyes. Exposing the array to samples containing fats displaces the dyes from the proteins to different extents, resulting in colour changes across the array. This produces a unique 'fingerprint' for the sample. An artificial intelligence (AI) algorithm is trained to recognise differences between fingerprints associated with disease in known samples. The algorithm is then used to detect disease in unknown samples. Pandra is cheap to produce, usable by non-experts, and sensitive to small changes in fat composition. This makes it well-suited to NASH diagnostics.This project aims to produce an early prototype Pandra sensor that could be deployed at the point-of-care in a GPs surgery. This would provide clinicians with an invaluable new tool for initially assessing high-risk patients for NASH and deciding the best referral route. Ultimately, it will result in a new test that will enable more patients to be tested for NASH, reducing the number progressing to more severe liver disease, cancer, and death.
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A study on prototype flexible multifunctional graphene foam-based sensing grid (柔性多功能石墨烯泡沫传感网格原型研究)
  • 批准号:
    --
  • 项目类别:
    --
  • 资助金额:
    20万元
  • 批准年份:
    2020
  • 负责人:
    SAGAR RIZWAN UR REHMAN
  • 依托单位: