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Mesenchymal stem cells (MSC) are increasingly being studied as a source of cell therapy for neurodegenerative diseases, and several groups have reported their beneficial effects on Alzheimer's disease (AD). In this study using AD model mice (APdE9), we found that transplantation of MSC via the tail vein improved spatial memory in the Morris water maze test. Using electron paramagnetic resonance imaging to evaluate the in vivo redox state of the brain, we found that MSC transplantation suppressed oxidative stress in AD model mice. To elucidate how MSC treatment ameliorates oxidative stress, we focused on amyloid-β (Aβ) pathology and microglial function. MSC transplantation reduced Aβ deposition in the cortex and hippocampus. Transplantation of MSC also decreased Iba1-positive area in the cortex and reduced activated ameboid shaped microglia. On the other hand, MSC transplantation accelerated accumulation of microglia around Aβ deposits and prompted microglial Aβ uptake and clearance as shown by higher frequency of Aβ-containing microglia. MSC transplantation also increased CD14-positive microglia in vivo, which play a critical role in Aβ uptake. To confirm the effects of MSC on microglia, we co-cultured the mouse microglial cell line MG6 with MSC. Co-culture with MSC enhanced Aβ uptake by MG6 cells accompanied by upregulation of CD14 expression. Additionally, co-culture of MG6 cells with MSC induced microglial phenotype switching from M1 to M2 and suppressed production of proinflammatory cytokines. These data indicate that MSC treatment has the potential to ameliorate oxidative stress through modification of microglial functions, thereby improving Aβ pathology in AD model mice. [ABSTRACT FROM AUTHOR]

OBJECTIVES: This work aims to explore more accurate pixel-driven projection methods for iterative image reconstructions in order to reduce high-frequency artifacts in the generated projection image. METHODS: Three new pixel-driven projection methods namely, small-pixel-large-detector (SPLD), linear interpolation based (LIB) and distance anterpolation based (DAB), were proposed and applied to reconstruct images. The performance of these methods was evaluated in both two-dimensional (2D) computed tomography (CT) images via the modified FORBILD phantom and three-dimensional (3D) electron paramagnetic resonance (EPR) images via the 6-spheres phantom. Specifically, two evaluations based on projection generation and image reconstruction were performed. For projection generation, evaluation was using a 2D disc phantom, the modified FORBILD phantom and the 6-spheres phantom. For image reconstruction, evaluations were performed using the FORBILD and 6-spheres phantom. During evaluation, 2 quantitative indices of root-mean-square-error (RMSE) and contrast-to-noise-ratio (CNR) were used. RESULTS: Comparing to the use of ordinary pixel-driven projection method, RMSE of the SPLD based least-square algorithm was reduced from 0.0701 to 0.0384 and CNR was increased from 5.6 to 19.47 for 2D FORBILD phantom reconstruction. For 3D EPRI, RMSE of SPLD was also reduced from 0.0594 to 0.0498 and CNR was increased from 3.88 to 11.58. In addition, visual evaluation showed that images reconstructed in both 2D and 3D images suffered from high-frequency line-shape artifacts when using the ordinary pixel-driven projection method. However, using 3 new methods all suppressed the artifacts significantly and yielded more accurate reconstructions. CONCLUSIONS: Three proposed pixel-driven projection methods achieved more accurate iterative image reconstruction results. These new and more accurate methods can also be easily extended to other imaging modalities. Among them, SPLD method should be recommended to 3D and four dimensional (4D) EPR imaging. [ABSTRACT FROM AUTHOR]

Electron paramagnetic resonance (EPR) Imaging (EPRI) is a robust method for measuring in vivo oxygen concentration (pO2). For 3D pulse EPRI, a commonly used reconstruction algorithm is the filtered backprojection (FBP) algorithm, in which the backprojection process is computationally intensive and may be time consuming when implemented on a CPU. A multistage implementation of the backprojection can be used for acceleration, however it is not flexible (requires equal linear angle projection distribution) and may still be time consuming. In this work, single-stage backprojection is implemented on a GPU (Graphics Processing Units) having 1152 cores to accelerate the process. The GPU implementation results in acceleration by over a factor of 200 overall and by over a factor of 3500 if only the computing time is considered. Some important experiences regarding the implementation of GPU-accelerated backprojection for EPRI are summarized. The resulting accelerated image reconstruction is useful for real-time image reconstruction monitoring and other time sensitive applications. [ABSTRACT FROM AUTHOR]