In vivo label-free characterization of aged skin to predict delayed wound healing

老化皮肤的体内无标记表征以预测伤口愈合延迟

基本信息

项目摘要

Project Summary: Age-related delays in wound healing have been attributed to altered dermal microstructure, mitochondrial dysfunction, and reduced cellular proliferation. However, an inability to non-destructively measure these characteristics has limited their use in guiding wound care and product development. The long-term goal of this project is to establish non-invasive, real-time, quantitative optical biomarkers to predict age-related delays in skin wound healing. The specific objective of this proposal is to utilize label-free multiphoton microscopy techniques, including two-photon excited fluorescence, fluorescence lifetime imaging, and second harmonic generation to identify and develop metabolic and microstructural biomarkers of aged skin that are associated with delayed closure and susceptibility to mechanical re-injury. Our central hypothesis is that the natural fluorescence of cells and their surrounding matrix can be quantified to provide sensitive biomarkers of age- related wound healing impairment. To test this hypothesis and evaluate the effect of aging, controlled pre- clinical studies will be performed using mice with ages ranging from 12.5-75% of their life expectancy, independent of common chronic wound comorbidities such as diabetes mellitus. In Aim 1, we will non- invasively monitor wound healing dynamics in individual live mice and identify differences in wound metabolism during the healing process using the natural fluorescence of NADH and FAD. In Aim 2, we quantify extracellular matrix organization and composition using multiphoton microscopy to predict wound strength through image-based multiscale modeling. In Aim 3, we will evaluate the effect of diabetes mellitus on the age-related optical biomarkers of wound healing developed in Aims 1 and 2. Quantitative comparisons of cellular and extracellular biomarkers will be made across different ages and validated against histology and immunohistochemistry. The expected outcome of this project is a set of candidate biomarkers for use in guiding therapy that are capable of discriminating age-related alterations and common comorbidities known to impair healing. With multiphoton microscopy technology already making its way into the clinic, the imaging methods developed here have the potential for immediate impacts in the clinical assessment and management of wounds.
项目总结: 年龄相关的伤口愈合延迟被归因于真皮微结构、线粒体的改变 功能障碍,细胞增殖减少。然而,无法非破坏性地测量这些 这些特性限制了它们在指导伤口护理和产品开发方面的使用。的长期目标是 该项目旨在建立非侵入性、实时、定量的光学生物标记物来预测与年龄相关的延迟 在皮肤伤口愈合方面。这项提议的具体目标是利用无标记多光子显微镜 技术,包括双光子激发荧光、荧光寿命成像和二次谐波 识别和开发与衰老皮肤相关的代谢和微结构生物标记物的一代 具有延迟闭合和机械再损伤的敏感性。我们的中心假设是自然的 细胞及其周围基质的荧光可以被量化,以提供敏感的年龄生物标志物- 与伤口愈合相关的损害。为了检验这一假设并评估衰老的影响,受控的预 临床研究将使用年龄为预期寿命的12.5%-75%的小鼠进行, 不受糖尿病等常见慢性伤口合并症的影响。在目标1中,我们将不 侵入性监测活体小鼠伤口愈合动态,识别伤口代谢差异 在愈合过程中使用NADH和FAD的天然荧光。在目标2中,我们量化 用多光子显微镜预测创伤强度的细胞外基质组织和组成 通过基于图像的多尺度建模。在目标3中,我们将评估糖尿病对 在AIMS 1和AIMS 2中开发的伤口愈合的年龄相关光学生物标记物。 细胞和细胞外生物标记物将跨越不同的年龄并与组织学和 免疫组织化学。该项目的预期结果是一组候选生物标志物,用于 指导治疗,能够区分与年龄相关的改变和已知的常见共病 损害了治疗效果。随着多光子显微镜技术已经进入临床,成像 这里开发的方法在临床评估和管理中具有立竿见影的作用 伤口的痕迹。

项目成果

期刊论文数量(3)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Multiscale Computational Model Predicts Mouse Skin Kinematics Under Tensile Loading.
多尺度计算模型预测拉伸载荷下的小鼠皮肤运动学。
  • DOI:
    10.1115/1.4052887
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Witt,NathanJ;Woessner,AlanE;Quinn,KyleP;Sander,EdwardA
  • 通讯作者:
    Sander,EdwardA
Three-Dimensional Quantification of Collagen Microstructure During Tensile Mechanical Loading of Skin.
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Kyle Patrick Quinn其他文献

Kyle Patrick Quinn的其他文献

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{{ truncateString('Kyle Patrick Quinn', 18)}}的其他基金

Administrative Core
行政核心
  • 批准号:
    10090744
  • 财政年份:
    2021
  • 资助金额:
    $ 34.67万
  • 项目类别:
Administrative Core
行政核心
  • 批准号:
    10867195
  • 财政年份:
    2021
  • 资助金额:
    $ 34.67万
  • 项目类别:
Administrative Core
行政核心
  • 批准号:
    10357743
  • 财政年份:
    2021
  • 资助金额:
    $ 34.67万
  • 项目类别:
Arkansas Integrative Metabolic Research Center
阿肯色州综合代谢研究中心
  • 批准号:
    10574555
  • 财政年份:
    2021
  • 资助金额:
    $ 34.67万
  • 项目类别:
Non-invasive automated wound analysis via deep learning neural networks
通过深度学习神经网络进行非侵入性自动伤口分析
  • 批准号:
    10631196
  • 财政年份:
    2021
  • 资助金额:
    $ 34.67万
  • 项目类别:
Acquisition of rodent metabolic and behavioral phenotyping system
啮齿动物代谢和行为表型系统的获取
  • 批准号:
    10799014
  • 财政年份:
    2021
  • 资助金额:
    $ 34.67万
  • 项目类别:
Acquisition of a confocal Raman microscope for molecular fingerprinting of cells and tissue
获取用于细胞和组织分子指纹分析的共焦拉曼显微镜
  • 批准号:
    10582119
  • 财政年份:
    2021
  • 资助金额:
    $ 34.67万
  • 项目类别:
Non-invasive automated wound analysis via deep learning neural networks
通过深度学习神经网络进行非侵入性自动伤口分析
  • 批准号:
    10183917
  • 财政年份:
    2021
  • 资助金额:
    $ 34.67万
  • 项目类别:
Non-invasive automated wound analysis via deep learning neural networks
通过深度学习神经网络进行非侵入性自动伤口分析
  • 批准号:
    10460416
  • 财政年份:
    2021
  • 资助金额:
    $ 34.67万
  • 项目类别:
Arkansas Integrative Metabolic Research Center
阿肯色州综合代谢研究中心
  • 批准号:
    10357742
  • 财政年份:
    2021
  • 资助金额:
    $ 34.67万
  • 项目类别:

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激素治疗、绝经年龄、既往产次和 APOE 基因型会影响老年人的认知。
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