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Technologies for an in-vitro carbon copy of lung disease

Technologies for an in-vitro carbon copy of lung disease
肺部疾病的体外复制技术
批准号:
EP/W004453/1
负责人:
Pietro Cicuta
金额:
$38.58万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2021
资助国家:
英国
项目状态:
已结题
起止时间:
2021 至 --

项目摘要

项目成果

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中文摘要
翻译
我们提出的工作重点是肺,解决它如何维持粘液产生和清除的生理平衡的物理方面,这是任何空气传播感染的第一道屏障。慢性肺病可导致慢性阻塞性肺疾病(COPD)的发展,正如2020年广泛报道的那样,它可能是由身体对SARS-Cov-2等病毒作出反应时引发的严重炎症过程引起的。还有一些常见的遗传性疾病会影响肺部。例如,囊性纤维化(CF)主要表现为粘膜纤毛清除受损,患者出现气道阻塞、慢性感染和随后的炎症性肺损伤。纤毛病是影响纤毛运动细胞器本身的遗传疾病。在所有这些疾病中,在疾病的特定原因与更广泛的肺器官的健康和功能之间存在相互作用,并且存在非常大且知之甚少的患者间变异性。如果有一种方法可以迅速、可靠地创建一个代表特定患者及其疾病状态的模型系统,并在其上快速测试治疗方法,那么临床实践可能会大大提高效率。这意味着使用患者肺部的原代细胞,其常驻巨噬细胞和任何其他相关感染/合并感染/微生物群。然后可以建立一个高保真度的疾病模型,以及可以代表感兴趣的细胞外基质的支架,以及任何血管和几何/结构边界。很明显,生命科学是时候从对病原体、宿主、干细胞等的孤立研究中走出来了。我们在这里提出的是一系列的技术步骤,目的是能够快速、可靠地在没有密集劳动的情况下,在严重疾病的时刻创造一个特定器官(我们将重点放在肺上)的复本,以优化治疗。这与越来越多的常见测序管道非常吻合,一些医院的高通量设备能够对样品进行测序,直到单细胞分辨率。我们的碳复制平台将重建相关的器官表型,并使生理和物理读数以及分子。我们特别关注我们将要开发的技术的可持续性(规模和成本)。
英文摘要
Our proposed work focuses on the lung, addressing physical aspects of how it maintains a physiological balance of mucus production and clearance, which is the first barrier to any airborne infection. Chronic lung disease can lead to development of a common condition known as chronic obstructive pulmonary disease (COPD) and, as reported widely in 2020, can result from the severe inflammatory processes triggered as the body responds to viruses such as SARS-Cov-2. There are also a number of prevalent genetic conditions that affect the lung. Cystic Fibrosis (CF), for example, manifests fundamentally as problem of impaired muco-ciliary clearance with patients developing airway obstruction, chronic infection, and subsequent inflammatory lung damage. Ciliopathies are genetic conditions that affect the motile cilia organelles themselves. In all these diseases, there is interplay between the specific cause of disease, and the health and function of the lung organ more broadly, and there is extremely large and poorly understood patient-to-patient variability. Clinical practice could be vastly more effective if there was a way to promptly and reliably create a model system that represented the particular patient, with their state of disease, and on which to rapidly test therapies. This means using the patient's primary cells from lungs, their resident macrophages, and any other relevant infection/co-infection/microbiota. A high fidelity disease model can then be built, together with scaffolds that can represent the extracellular matrix of interest, and any vasculature and geometric/structural boundaries. It is clearly time for life-sciences to move on from studying pathogens, hosts, stem cells, etc. each in isolation from each other. What we propose here are a series of technological steps in the direction of being able to rapidly and reliably, and without intensive labour, create a carbon copy of a certain organ (we will focus on lung) at the moment of serious disease, for the purpose of optimising treatment. This dovetails very well with increasing common pipelines of sequencing, with high throughput facilities in some hospital able to sequence samples down to single cell resolution. Our carbon copy platforms will recreate the relevant organ phenotypes, and enable physiological and physical readouts as well as molecular. We pay particular attention to the sustainability (scale and cost) of the technologies that we will propose to develop.
期刊论文(2)
专著(0)
科研奖励(0)
会议论文
Measuring Biophysical Properties of Cilia Motility from Mammalian Tissues via Quantitative Video Analysis Methods.
通过定量视频分析方法测量哺乳动物组织纤毛运动的生物物理特性。
DOI: 10.1007/978-1-0716-3507-0_16
发表时间: 2024
期刊: Methods in molecular biology (Clifton, N.J.)
影响因子: --
作者: [Causa E]
通讯作者: Causa E
DOI: 10.1098/rsos.230185
发表时间: 2023-08
期刊: ROYAL SOCIETY OPEN SCIENCE
影响因子: 3.5
作者: [Fradique, Ricardo, Causa, Erika, Delahousse, Clara, Kotar, Jurij, Pinte, Laetitia, Vallier, Ludovic, Vila-Gonzalez, Marta, Cicuta, Pietro]
通讯作者: Cicuta, Pietro
Cells to Fields: crop movement characterisation across scales of order
  • 批准号:
    BB/X005275/1
  • 项目类别:
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  • 资助金额:
    $7.5万
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    2022
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