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Effects of cornea epithelial barrier disruption on the cornea trigeminal neural circuit

Effects of cornea epithelial barrier disruption on the cornea trigeminal neural circuit
角膜上皮屏障破坏对角膜三叉神经回路的影响
批准号:
10586519
负责人:
RUI CHEN
金额:
$119.33万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2022
资助国家:
美国
项目状态:
未结题
起止时间:
2022-09-30 至 2027-08-31

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中文摘要
翻译
摘要 该建议调查角膜三叉神经回路,特别强调 角膜上皮与上皮内神经的关系,以探讨角膜上皮内神经的功能。 假设涉及短暂和/或长期角膜病变眼表病变 上皮屏障破坏将引起更大的伤害感受器刺激、不适、疼痛和 上皮和基质神经密度的代偿性降低。单细胞RNA与表观遗传 将在角膜和三叉神经节细胞中进行分析和原位杂交, 在稳态条件下以及在由于干燥而导致的上皮屏障破坏之后, 眼和角膜上皮清创术。将对这些测定的数据进行整合, 将生成正常和应激条件下的角膜和三叉神经节图谱 基于独特的表达谱来识别细胞。细胞将在空间上解决这些 组织,以确定角膜细胞和神经轴突之间的通信和三叉神经之间的通信, 神经元和非神经元细胞。在神经节中,时间和空间分辨的转录组学 数据将与角膜上皮神经形态和敏感性的变化相关联 在屏障破坏后发生,以确定维持角膜上皮神经的基因, 健康和促进屏障破坏后的病理变化。三个具体目标是 打算研究角膜三叉神经回路目标1将调查屏障的影响 干眼和上皮清创术对角膜上皮转录组学谱的破坏 神经形态和神经功能。目的2:探讨保存上皮细胞的效果 MMP-9敲除菌株在干眼症和上皮损伤中对这些参数的影响, 目的3研究两种神经致敏趋化因子对正常人和 眼睛干涩。 所提出的实验研究角膜上皮三叉神经感觉电路在一个 协调的深层水平,以确定影响健康和 疾病在本项目结束时,我们将更好地了解 角膜上皮细胞和完整的屏障通过其抑制神经激活, 由角膜细胞在屏障破坏的角膜中产生,导致神经变性, 提高敏感性。该项目的基准成就将是一个基本的 对常见的角膜上皮屏障破坏影响的新认识 角膜疾病对角膜上皮神经网络的完整性和功能的影响。
英文摘要
Abstract This proposal investigates the cornea-trigeminal neural circuit with particular emphasis on the relationship between the cornea epithelium and the intraepithelial nerves to investigate the hypothesis that ocular surface pathologies that involve transient and/or prolonged corneal epithelial barrier disruption will cause greater nociceptor stimulation, discomfort, pain and a compensatory reduction in epithelial and stromal nerve density. Single cell RNA and epigenetic profiling and in situ hybridization will be performed in corneal and trigeminal ganglion cells that project to the cornea in homeostatic conditions and after epithelial barrier disruption due to dry eye and corneal epithelial debridement. Data from these assays will be integrated and single cell atlases of the cornea and trigeminal ganglion under normal and stressed conditions will generated that identify cells based on unique expression profiles. Cells will be spatially resolved in these tissues to identify communications between corneal cells and nerve axons and between trigeminal neuronal and non-neuronal cells. In the ganglion, temporally and spatially resolved transcriptomic data will be associated with the changes in corneal epithelial nerve morphology and sensitivity that occur after barrier disruption to identify genes that maintain the corneal epithelial nerves in health and promote the pathological changes after barrier disruption. Three specific aims are proposed to investigate the cornea-trigeminal circuit. Aim 1 will investigate the effects of barrier disruption from dry eye and epithelial debridement on transcriptomic profiles, corneal epithelial nerve morphology and nerve function. Aim 2 will investigate the effects of preserving epithelial barrier in the MMP-9 knockout strain in dry eye and epithelial wounding on these parameters, and Aim 3 will investigate the effects of two neural sensitizing chemokines on the circuit in normal and dry eyes. The proposed experiments investigate the cornea epithelial-trigeminal sensory circuit at a coordinated deep level to identify factors that impact the intraepithelial nerves in health and disease. At the conclusion of this project, we will have a better understanding of the mechanisms by which corneal epithelial cells and intact barrier suppress nerve activation and the factors produced by cornea cells in barrier disrupted corneas that cause nerve degeneration and heightened sensitivity. The benchmark accomplishments of this project will be a fundamental new understanding of the impact of corneal epithelial barrier disruption that occurs in common corneal diseases on the integrity and function of the corneal epithelial nerve network.
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Comprehensive Somatic Variant Characterization at the HGSC
  • 批准号:
    10662645
  • 项目类别:
  • 资助金额:
    $250.0万
  • 财政年份:
    2023
  • 负责人:
    RUI CHEN
  • 依托单位:
Single Cell Spatial Transcriptomics Shared Instrument at the BCM Core Facility
  • 批准号:
    10414324
  • 项目类别:
  • 资助金额:
    $30.4万
  • 财政年份:
    2022
  • 负责人:
    RUI CHEN
  • 依托单位:
Deep-Learning-Derived Endophenotypes from Retina Images
Deep-Learning-Derived Endophenotypes from Retina Images
海外基金