Doxycycline Suppresses Vasculogenic Mimicry in Human Pterygium Fibroblasts.

PURPOSE: To explore the effect of doxycycline on vasculogenic mimicry (VM) formation and the potential mechanism in human pterygium fibroblasts in order to find novel targets for pterygium therapy. METHODS: First, we demonstrate the existence of VM in 73 pterygium specimens by CD31 and periodic acid Schiff (PAS) dual staining. Then we used cell counting kit-8, clone formation assay and flow cytometry to prove the inhibitory effect of doxycycline on cell proliferation and apoptosis. The VM formation was evaluated through wound healing assay, cell transwell assay and three-dimensional cell culture combined with PAS staining. Finally, we used Western blot to testify the correlation of the VM and the factors in protein level preliminarily. RESULTS: Our results showed that VM existed in human pterygium specimens exactly. Otherwise, in human pterygium fibroblasts, doxycycline induced a dose-dependent inhibitory effect on cell proliferation and apoptosis induction. Besides, doxycycline significantly suppressed vasculogenic mimicry tube formation, cell migration and invasion. Furthermore, doxycycline impaired the expression of MMP-9, MMP-2 and VEGF which may related to pterygium VM formation. CONCLUSIONS: Doxycycline decelerated pterygium progression might be through inhibiting VM formation according to the downregulation of MMP-9, MMP-2 and VEGF, which may provide the basis of further studies involving doxycycline for pterygium treatment.

Accelerated MR diffusion tensor imaging using distributed compressed sensing.

PURPOSE: Diffusion tensor imaging (DTI) is known to suffer from long acquisition time in the orders of several minutes or even hours. Therefore, a feasible way to accelerate DTI data acquisition is highly desirable. In this article, the feasibility and efficacy of distributed compressed sensing to fast DTI is investigated by exploiting the joint sparsity prior in diffusion-weighted images. METHODS: Fully sampled DTI datasets were obtained from both simulated phantom and experimental heart sample, with diffusion gradient applied in six directions. The k-space data were undersampled retrospectively with acceleration factors from 2 to 6. Diffusion-weighted images were reconstructed by solving an l2-l1 norm minimization problem. Reconstruction performance with varied signal-to-noise ratio and acceleration factors were evaluated by root-mean-square error and maps of reconstructed DTI indices. RESULTS: Superiority of distributed compressed sensing over basic compressed sensing was confirmed with simulation, and the reconstruction accuracy was influenced by signal-to-noise ratio and acceleration factors. Experimental results demonstrate that DTI indices including fractional anisotropy, mean diffusivities, and orientation of primary eigenvector can be obtained with high accuracy at acceleration factors up to 4. CONCLUSION: Distributed compressed sensing is shown to be able to accelerate DTI and may be used to reduce DTI acquisition time practically.