慢性低灌流モデルマウスにおける認知機能障害メカニズムの解明を目的とした病態評価と測定手法開発

博士（学術）岩手大

Distribution of intraperitoneally administered deuterium-labeled water in aquaporin-4-knockout mouse brain after middle cerebral artery occlusion

IntroductionAs the movement of water in the brain is known to be involved in neural activity and various brain pathologies, the ability to assess water dynamics in the brain will be important for the understanding of brain function and the diagnosis and treatment of brain diseases. Aquaporin-4 (AQP4) is a membrane channel protein that is highly expressed in brain astrocytes and is important for the movement of water molecules in the brain.MethodsIn this study, we investigated the contribution of AQP4 to brain water dynamics by administering deuterium-labeled water (D2O) intraperitoneally to wild-type and AQP4 knockout (AQP4-ko) mice that had undergone surgical occlusion of the middle cerebral artery (MCA). Water dynamics in the infarct region and on either side of the anterior cerebral artery (ACA) was monitored with proton-density-weighted imaging (PDWI) performed on a 7T animal MRI.ResultsD2O caused a negative signal change quickly after administration. The AQP4-ko mice showed a delay of the time-to-minimum in both the contralateral and ipsilateral ACA regions compared to wild-type mice. Also, only the AQP4- ko mice showed a delay of the time-to-minimum in the ipsilateral ACA region compared to the contralateral side. In only the wild-type mice, the signal minimum in the ipsilateral ACA region was higher than that in the contralateral ACA region. In the infarct region, the signal attenuation was slower for the AQP4-ko mice in comparison to the wild-type mice.DiscussionThese results suggest that AQP4 loss affects water dynamics in the ACA region not only in the infarct region. Dynamic PDWI after D2O administration may be a useful tool for showing the effects of AQP4 in vivo

Imaging of Neuronal Activity in Awake Mice by Measurements of Flavoprotein Autofluorescence Corrected for Cerebral Blood Flow

Green fluorescence imaging (e.g., flavoprotein autofluorescence imaging, FAI) can be used to measure neuronal activity and oxygen metabolism in living brains without expressing fluorescence proteins. It is useful for understanding the mechanism of various brain functions and their abnormalities in age-related brain diseases. However, hemoglobin in cerebral blood vessels absorbs green fluorescence, hampering accurate assessments of brain function in animal models with cerebral blood vessel dysfunctions and subsequent cerebral blood flow (CBF) alterations. In the present study, we developed a new method to correct FAI signals for hemoglobin-dependent green fluorescence reductions by simultaneous measurements of green fluorescence and intrinsic optical signals. Intrinsic optical imaging enabled evaluations of light absorption and scatters by hemoglobin, which could then be applied to corrections of green fluorescence intensities. Using this method, enhanced flavoprotein autofluorescence by sensory stimuli was successfully detected in the brains of awake mice, despite increases of CBF, and hemoglobin interference. Moreover, flavoprotein autofluorescence could be properly quantified in a resting state and during sensory stimulation by a CO2 inhalation challenge, which modified vascular responses without overtly affecting neuronal activities. The flavoprotein autofluorescence signal data obtained here were in good agreement with the previous findings from a condition with drug-induced blockade of cerebral vasodilation, justifying the current assaying methodology. Application of this technology to studies on animal models of brain diseases with possible changes of CBF, including age-related neurological disorders, would provide better understanding of the mechanisms of neurovascular coupling in pathological circumstances

Vasodilation mechanism of cerebral microvessels induced by neural activation under high baseline CBF level results from hypercapnia in awake mice

Objective: We investigated the effects of the baseline CBF level at resting state on neurovascular coupling.Methods: Diameters of arterioles, capillaries, and venulas in awake mouse brain were measured by a two-photon microscope. Vasodilation in each of the cerebral vessels was caused by three experimental conditions: (1) sensory stimulation, (2) 5% CO2 inhalation (hypercapnia), (3) simultaneous exposure to sensory stimulation and 5% CO2 inhalation. CBF and CBV were also measured by a microscope and a CCD camera.Results: Increases in CBF and CBV were observed under all experimental conditions. After the increases in CBF and CBV due to hypercapnia, additional increases in CBF and CBV occurred during sensory stimulation. Diameter changes in arterioles were significantly larger than those in capillaries and venulas under both sensory stimulation and 5% CO2 inhalation. Additional vasodilation from sensory stimulation was observed under hypercapnia. The diameter change in each vessel type during sensory stimulation was maintained under simultaneous exposure to sensory stimulation and hypercapnia.Conclusions:The diameter change of cerebral vessels during neural activation is reproducible regardless of whether baseline CBF has increased or not. Our finding directly demonstrates the concept of uncoupling between energy consumption and energy supply during cortical activation　　

Inhibitory effects of caffeine on gustatory plasticity in the nematode Caenorhabditis elegans.

The effects of caffeine on salt chemotaxis learning were investigated using the nematode Caenorhabditis elegans. To estimate the degree of salt chemotaxis learning, nematodes were placed in a mixed solution of NaCl and caffeine, and then the chemotaxis index of NaCl was obtained from the nematodes placed on agar medium after pre-exposure to caffeine concentrations of 0.01, 0.1, 0.3, and 1.0%. Locomotor activity and preference behavior for caffeine were also estimated under these caffeine conditions. Nematodes pre-exposed to 0.3% caffeine showed inhibition of salt chemotaxis learning. Additional experiments indicated that nematodes showed a preference response to the middle concentration of caffeine (0.1%), with preference behavior declining in the 0.3% caffeine condition. Stable locomotor activity was observed under 0.01-0.3% caffeine conditions. These results suggest that salt chemotaxis learning with 0.3% caffeine is useful for investigating the effects of caffeine on learning in nematodes

The Utility of Applying Various Image Preprocessing Strategies to reduce the ambiguity in Deep Learning-Based Clinical Image Diagnosis

PurposeA general problem of machine-learning algorithms based on the convolutional- neural-network (CNN) technique is that the reason for the output judgement is unclear. The purpose of this study was to introduce a strategy that may facilitate better understanding of how and why a specific judgement was made by the algorithm. The strategy is to preprocess the input image data in different ways to highlight the most important aspects of the images for reaching the output judgement.MethodsT2-weighted brain image series falling into two age-ranges were used. Classifying each series into one of the two age-ranges was the given task for the CNN model. The images from each series were preprocessed in five different ways to generate five different image sets: 1) subimages from the inner area of the brain, 2) subimages from the periphery of the brain, 3) - 5) subimages of brain parenchyma, gray matter area, and white matter area, respectively, extracted from the subimages of 2). The CNN model was trained and tested in five different ways using one of these image sets. The network architecture and all the parameters for training and testing remained unchanged.ResultsThe judgement accuracy achieved by training was different when the image set used for training was different. Some of the differences was statistically significant. The judgement accuracy decreased significantly when either extraparenchymal or gray matter area was removed from the periphery of the brain (P<0.05).ConclusionThe proposed strategy may help visualize what features of the images were important for the algorithm to reach correct judgement, helping humans to understand how and why a particular judgment was made by a CNN