| Literature DB >> 31920472 |
Xuecong Lu1,2, Mohammad Moeini3, Baoqiang Li4, Yuankang Lu1,2, Rafat Damseh1,2, Philippe Pouliot1,2, Éric Thorin2,5, Frédéric Lesage1,2.
Abstract
Dysfunction in neurovascular coupling that results in a mismatch between cerebral blood flow and neuronal activity has been suggested to play a key role in the pathogenesis of Alzheimer's disease (AD). Meanwhile, physical exercise is a powerful approach for maintaining cognitive health and could play a preventive role against the progression of AD. Given the fundamental role of capillaries in oxygen transport to tissue, our pilot study aimed to characterize changes in capillary hemodynamics with AD and AD supplemented by exercise. Exploiting two-photon microscopy, intrinsic signal optical imaging, and magnetic resonance imaging, we found hemodynamic alterations and lower vascular density with AD that were reversed by exercise. We further observed that capillary properties were branch order-dependent and that stimulation-evoked changes were attenuated with AD but increased by exercise. Our study provides novel indications into cerebral microcirculatory disturbances with AD and the modulating role of voluntary exercise on these alterations.Entities:
Keywords: Alzheimer’s disease; capillary hemodynamics; neural stimulation; two-photon imaging; voluntary exercise
Year: 2019 PMID: 31920472 PMCID: PMC6915102 DOI: 10.3389/fnins.2019.01261
Source DB: PubMed Journal: Front Neurosci ISSN: 1662-453X Impact factor: 4.677
FIGURE 1Timeline of imaging experiments.
FIGURE 2Capillary RBC flow characteristics in different groups (four mice per group). (A) Capillary diameter, RBC velocity, flux, and hematocrit in different experimental groups. (B) Coefficient of variation (CV) for all capillary parameters. The CV in each capillary was computed based on multiple frames recorded each 0.25 s within a 5-s time window. Thus, CV represents the temporal variations of each property within a capillary. CV was computed as the standard deviation divided by the mean. ∗p < 0.05 and +p < 0.1.
FIGURE 3High temporal capillary fluctuations of RBC velocity and RBC flux. (A) Representative space-time images with higher fluctuations of RBC flux as a function of time, with 0.25 s intervals during a 5-s recording window. The flux was obtained using both longitudinal and perpendicular scans, and the average value was used. (B) Longitudinal equivalent RBC velocity was calculated from the angle of dark streaks in a specific recording frame. (C) The percentage of capillaries with high temporal fluctuations of RBC velocity in all groups. The “isoutlier” method in MATLAB was applied to detect outliers with a standard deviation of RBC velocity exceeding three standard deviations from the mean. (D) Same for RBC flux.
FIGURE 4Vascular distribution in different experimental groups and at different depths. (A) Binarization of microvascular angiograms was applied to calculate the vascular density. Left: MIP image with depths ranging from 100 to 550 μm under the brain surface with 5 μm steps. Right: an example of a binary segmentation of a single en face slice after removing the large horizontal vessels at a depth of 120 um (scale bar: 100 μm). (B) Average vascular density in different experimental groups as a function of depth from 100 to 550 μm under the brain surface. (C) Estimated vascular density (volume%). Results are presented as box plots with the median value (red line).
FIGURE 5(A,B) Typical 7-T MRI images, with coronal and axial views of the cortex. (C) Quantification of cerebral perfusion (ml/g/min) by MRI. (D) Averaged temporal response of oxy-hemoglobin (HBO) for all groups with 5-s stimulation (blue background). (E) Temporal dynamics of total hemoglobin (HBT) response to whisker stimulation. Stimulation lasted for 5 s, followed by a 15-s rest. (F) Averaged results for change in HBO (Δ[HBO](t)) and change in HBR (Δ[HBR](t)) over all mice. ∗p < 0.05 and +p < 0.1.