Department of Physiology, Biosciences Institute, University of São Paulo.
DAN Europe Research Division, Roseto degli Abruzzi, Italy.
Undersea Hyperb Med. 2022 Second Quarter;49(2):207-226.
Inert gas bubbles in tissues and in blood have been historically considered as the only triggering factors for DCS, but now many other factors are considered to affect the final outcome of a decompression profile for a certain individual. In this sense, inflammation seems to play a relevant role, not only due to the physical damage of tissues by the bubbles, but as a potentiator of the process as a whole. The present study aims to put forward a mathematical model of bubble formation associated with an inflammatory process related to decompression. The model comprises four state-variables (inert gas pressure, inert gas bubbles, proinflammatory and inflammatory factors) in a set of non-linear differential equations. The model is non-extensive: inert gas transitions between liquid and gaseous phases do not change the concentration of the dissolved gas. The relationship between bubbles and inflammation is given through parameters that form a positive feedback loop. The results of the model were compared with the experimental results of echocardiography from volunteers in two dive/decompression profiles; the model shows a very good agreement with the empirical data and previews different inflammatory outcomes for different experimental profiles. We suggest that slight changes in the parameters' values might turn the simulations from a non-inflammatory to an inflammatory profile for a given individual. Therefore, the present model might help address the problem of DCS on a particular basis.
在组织和血液中的惰性气体气泡在历史上一直被认为是 DCS 的唯一触发因素，但现在许多其他因素被认为会影响个体减压过程的最终结果。从这个意义上说，炎症似乎起着重要的作用，不仅因为气泡对组织造成的物理损伤，还因为它是整个过程的增强剂。本研究旨在提出一种与减压相关的炎症过程相关的气泡形成的数学模型。该模型由一组非线性微分方程中的四个状态变量（惰性气体压力、惰性气体气泡、促炎和炎症因子）组成。该模型是非扩展性的：惰性气体在液相和气相之间的转变不会改变溶解气体的浓度。气泡和炎症之间的关系通过形成正反馈回路的参数给出。该模型的结果与志愿者在两种潜水/减压过程中的超声心动图实验结果进行了比较；该模型与经验数据非常吻合，并为不同的实验过程预览了不同的炎症结果。我们建议，参数值的微小变化可能会使给定个体的模拟从非炎症转变为炎症。因此，该模型可能有助于在特定基础上解决 DCS 问题。
