PREDICTION OF OUTCOME OF PERIPHERAL NERVE INJURIES - A PROBABILITY MODEL

周围神经损伤结果的预测 - 概率模型

• 批准号: 3968561
• 负责人: L DEMEDINACELLI
• 金额: --
• 依托单位: NATIONAL INSTITUTE OF MENTAL HEALTH
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/3968561
• 关键词: mathematical model; model design /development; nervous system regeneration; peripheral nervous system; trauma

The long term functional consequences of peripheral nerve injuries are notoriously unpredictable. We hypothesized that considering the individual regrowth of the elementary components of a nerve (the neurites) rather than the global regeneration of the organ could lead to a better understanding of the mechanisms of nerve repair. We postulated that the regrowth of any individual neurite can be defined in terms of its influence on recovery, the three main possibilities being valid, neutral and invalid regrowth. We have designed a probability model describing the prospects of regrowth for nerve composed of several types of fibers. This model is being tested in pre-determined situations to judge its validity. We found that possible variations in the outcome of nerve injuries could be explained by a parsimonious hypothesis: the randomness of regrowth.

周围神经损伤的长期功能后果是 出了名的不可预测 我们假设，考虑到个人 再生的基本组成部分的神经（神经突），而不是 器官的全面再生可以让我们更好地理解 神经修复的机制 我们假设，任何单个神经突的再生都可以定义为 就其对复苏的影响而言，三种主要的可能性是 有效、中性和无效再生。 我们设计了一个概率模型 描述了由几种类型的神经组成的神经再生的前景， 纤维 这个模型正在预先确定的情况下进行测试， 其有效性。 我们发现，在神经的结果可能的变化， 伤害可以用一个简单的假设来解释： 的再生。