Multimodal smart imaging of critical inflammatory processes in murine models of pulmonary fibrosis

小鼠肺纤维化模型中关键炎症过程的多模态智能成像

• 批准号: G0800969/1
• 负责人: Christopher Haslett
• 金额: $ 79.24万
• 依托单位: University of Edinburgh
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2009
• 资助国家: 英国
• 起止时间: 2009 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=G0800969%2F1
• 关键词: Multimodal; smart; imaging; critical; inflammatory

Model systems that exist today may not accurately reflect what is actually going on in human disease. One crucial problem is that we have been unable to visualise molecular events within animal models and humans until cutting edge technology has been launched. We wish to improve the treatment of a condition called idiopathic pulmonary (lung) fibrosis. This condition has a worse mortality than most cancers and there are currently no effective drug treatments. The fibrotic (scarring) process in pulmonary fibrosis is similar to that in other parts of the body such as liver and kidney. This research will apply cutting edge imaging to discover what key mechanisms are being switched on and off at different stages of the disease process. Extrapolating this to human disease is of utmost importance and will lead to new targeted therapies for inflammatory/scarring conditions of the lung and other organs.

目前存在的模型系统可能无法准确反映人类疾病的实际情况。一个关键的问题是，在尖端技术推出之前，我们一直无法可视化动物模型和人类体内的分子事件。我们希望改善对特发性肺纤维化的治疗。这种疾病的死亡率比大多数癌症都要高，目前还没有有效的药物治疗方法。肺纤维化的纤维化（瘢痕形成）过程与身体其他部位（如肝脏和肾脏）的纤维化过程相似。这项研究将应用最先进的成像技术来发现在疾病过程的不同阶段，哪些关键机制正在被打开和关闭。将其外推到人类疾病中是至关重要的，并且将导致针对肺部和其他器官的炎症/瘢痕形成病症的新的靶向疗法。