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高分辨率血管舒缩分析揭示了新的小动脉生理特征和中风对脑血管网络的渐进性调节。

High-resolution vasomotion analysis reveals novel arteriole physiological features and progressive modulation of cerebral vascular networks by stroke.

机构信息

College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang, China.

Key Laboratory of Growth Regulation and Translation Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China.

出版信息

J Cereb Blood Flow Metab. 2024 Nov;44(11):1330-1348. doi: 10.1177/0271678X241258576. Epub 2024 May 31.

Abstract

Spontaneous cerebral vasomotion, characterized by ∼0.1 Hz rhythmic contractility, is crucial for brain homeostasis. However, our understanding of vasomotion is limited due to a lack of high-precision analytical methods to determine single vasomotion events at basal levels. Here, we developed a novel strategy that integrates a baseline smoothing algorithm, allowing precise measurements of vasodynamics and concomitant Ca dynamics in mouse cerebral vasculature imaged by two-photon microscopy. We identified several previously unrecognized vasomotion properties under different physiological and pathological conditions, especially in ischemic stroke, which is a highly harmful brain disease that results from vessel occlusion. First, the dynamic characteristics between SMCs Ca and corresponding arteriolar vasomotion are correlated. Second, compared to previous diameter-based estimations, our radius-based measurements reveal anisotropic vascular movements, enabling a more precise determination of the latency between smooth muscle cell (SMC) Ca activity and vasoconstriction. Third, we characterized single vasomotion event kinetics at scales of less than 4 seconds. Finally, following pathological vasoconstrictions induced by ischemic stroke, vasoactive arterioles entered an inert state and persisted despite recanalization. In summary, we developed a highly accurate technique for analyzing spontaneous vasomotion, and our data suggested a potential strategy to reduce stroke damage by promoting vasomotion recovery.

摘要

自发性脑血管运动,其特征为约 0.1Hz 的节律性收缩,对脑内稳态至关重要。然而,由于缺乏高精度的分析方法来确定基础水平下的单个血管运动事件,我们对血管运动的理解受到限制。在这里,我们开发了一种新策略,该策略整合了基线平滑算法,从而能够通过双光子显微镜对小鼠脑血管进行成像,精确测量血管动力学和伴随的 Ca 动力学。我们在不同的生理和病理条件下发现了几个以前未被识别的血管运动特性,特别是在缺血性中风中,这是一种由血管阻塞引起的高度有害的脑部疾病。首先,SMC Ca 和相应的小动脉血管运动之间的动态特征是相关的。其次,与之前基于直径的估计相比,我们基于半径的测量揭示了各向异性的血管运动,能够更精确地确定平滑肌细胞 (SMC) Ca 活性与血管收缩之间的潜伏期。第三,我们在不到 4 秒的时间尺度上对单个血管运动事件的动力学进行了特征描述。最后,在缺血性中风引起的病理性血管收缩后,血管活性小动脉进入无活动状态,并持续存在,尽管已经再通。总之,我们开发了一种分析自发性血管运动的高度精确技术,我们的数据提出了一种通过促进血管运动恢复来减少中风损伤的潜在策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba59/11542124/44638efa101a/10.1177_0271678X241258576-fig1.jpg

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