Multi source translation based projection completion for interior region of interest tomography with CBCT.

Interior tomography by rotary computed tomography (RCT) is an effective method to improve the detection efficiency and achieve high-resolution imaging for the region of interest (ROI) within a large-scale object. However, because only the X-rays through the ROI can be received by detector, the projection data is inevitably truncated, resulting in truncation artifacts in the reconstructed image. When the ROI is totally within the object, the solution of the problem is not unique, which is named interior problem. Fortunately, projection completion (PC) is an effective technique to solve the interior problem. In this study, we proposed a multi source translation CT based PC method (mSTCT-PC) to cope with the interior problem. Firstly, mSTCT-PC employs multi-source translation to sparsely obtain the global projection which covered the whole object. Secondly, the sparse global projection is utilized to fill up the truncated projection of ROI. The global projection and truncated projection are obtained under the same geometric parameters. Therefore, it omits the registration of projection. To verify the feasibility of this method, simulation and practical experiments were implemented. Compared with the results of ROI reconstructed by filtered back-projection (FBP), simultaneous iterative reconstruction technique-total variation (SIRT-TV) and the multi-resolution based method (mR-PC), the proposed mSTCT-PC is good at mitigating truncation artifacts, preserving details and improving the accuracy of ROI images.

Novel method of boundary-free mesh parameterization.

Unless the targeted mesh is developable, metric distortion is inevitable during the process of surface mesh parameterization, thus one important objective of all involved parametric studies is to reduce the metric distortion. In order to further reduce area and angle distortion, a novel method of boundary-free mesh parameterization is presented in the paper. Firstly, the initial boundary-fixed conformal parameterization from 3D surface mesh patch to a plane is performed in the method. Then, based on the initial parameterization, the iterations of boundary-free quasi-harmonic parameterization are developed, where the tensor field is updated in each iterative step and the principal curvature direction is utilized to terminate the iteration. The solution of the novel method is convenient to calculate since it involves a series of linear systems. In our novel parameterization method, lower metric distortion and considerable efficiency have been obtained in experiments.

Tumor necrosis factor receptor-associated factor 6 mediated the promotion of salivary adenoid cystic carcinoma progression through Smad-p38-JNK signaling pathway induced by TGF-ß.

BACKGROUND: Tumor necrosis factor (TNF) receptor-associated factor 6 (TRAF6) has been proved to play an important role in tumorigenesis, invasion, and metastasis. However, its precise role salivary adenoid cystic carcinoma (SACC) has not been determined. The aim of this study was to explore the role of TRAF6 in SACC including invasion and metastasis of SACC cells. MATERIALS AND METHODS: Immunohistochemistry and quantitative real-time PCR were performed in SACC tissues paired with their adjacent normal tissues to analyze the expression of TRAF6. Downstream proteins expression was explored when TRAF6 was knockdown by siRNA. RESULTS: The results show that TRAF6 is upregulated in SACC samples, especially in SACC with metastasis, which is closely correlated with an aggressive phenotype (P = .0073) and shorter life survival span (P = .0061) in SACC patients. Knockdown of TRAF6 can attenuate the promotion effect of SACC cell invasion induced by TGF-ß. Western blot results also showed that silencing TRAF6 expression can inhibit the activation of SMAD2, SMAD3, ERK, p38, and JNK induced by TGF-ß in SACC cells. CONCLUSION: These data suggested that TRAF6 regulates TGF-ß-mediated SACC progression through SMAD2/3-ERK-p38-JNK cascades.

A shape-based inter-layer contours correspondence method for ICT-based reverse engineering.

The correspondence of a stack of planar contours in ICT (industrial computed tomography)-based reverse engineering, a key step in surface reconstruction, is difficult when the contours or topology of the object are complex. Given the regularity of industrial parts and similarity of the inter-layer contours, a specialized shape-based inter-layer contours correspondence method for ICT-based reverse engineering was presented to solve the above problem based on the vectorized contours. In this paper, the vectorized contours extracted from the slices consist of three graphical primitives: circles, arcs and segments. First, the correspondence of the inter-layer primitives is conducted based on the characteristics of the primitives. Second, based on the corresponded primitives, the inter-layer contours correspond with each other using the proximity rules and exhaustive search. The proposed method can make full use of the shape information to handle industrial parts with complex structures. The feasibility and superiority of this method have been demonstrated via the related experiments. This method can play an instructive role in practice and provide a reference for the related research.

Down-regulation of miR-125a-5p is associated with salivary adenoid cystic carcinoma progression via targeting p38/JNK/ERK signal pathway.

Salivary adenoid cystic carcinoma (SACC) is a relatively uncommon epithelial-like malignancy that can occur in the head and neck region. Despite its slow growth, this aggressive salivary gland tumor frequently recurs and metastasizes to distant organs since lacking effective chemotherapy treatment. MicroRNAs are key regulators in tumor metastasis and progression, but their roles during SACC progression have not been illustrated. In current study, we demonstrate that miR-125a-5p is down-regulated in SACC and closely related to the metastasis and progression in human SACC specimens. In vitro, miR-125a-5p mimic can suppress SACC cell migration and invasion; while blocking miR-125a-5p can relieve the inhibition effect. By using dual-luciferase assay, we confirmed that miR-125a-5p directly targeted to p38 and tissue samples of patients indicated the negative correlation between miR-125a-5p and p38; clinical analysis also showed that low level expression of miR-125a-5p is closely associated with poor prognosis of SACC. Furthermore, down-regulation of miR-125a-5p triggered downstream p38/JNK/ERK activation. Taken together, our results indicate that down-regulation of miR-125a-5p promotes SACC progression through p38 signal pathway and miR-125a-5p can be a potential therapeutic target of SACC.

A Triangle Mesh Standardization Method Based on Particle Swarm Optimization.

To enhance the triangle quality of a reconstructed triangle mesh, a novel triangle mesh standardization method based on particle swarm optimization (PSO) is proposed. First, each vertex of the mesh and its first order vertices are fitted to a cubic curve surface by using least square method. Additionally, based on the condition that the local fitted surface is the searching region of PSO and the best average quality of the local triangles is the goal, the vertex position of the mesh is regulated. Finally, the threshold of the normal angle between the original vertex and regulated vertex is used to determine whether the vertex needs to be adjusted to preserve the detailed features of the mesh. Compared with existing methods, experimental results show that the proposed method can effectively improve the triangle quality of the mesh while preserving the geometric features and details of the original mesh.

An Improved Approach of Mesh Segmentation to Extract Feature Regions.

The objective of this paper is to extract concave and convex feature regions via segmenting surface mesh of a mechanical part whose surface geometry exhibits drastic variations and concave-convex features are equally important when modeling. Referring to the original approach based on the minima rule (MR) in cognitive science, we have created a revised minima rule (RMR) and presented an improved approach based on RMR in the paper. Using the logarithmic function in terms of the minimum curvatures that are normalized by the expectation and the standard deviation on the vertices of the mesh, we determined the solution formulas for the feature vertices according to RMR. Because only a small range of the threshold parameters was selected from in the determined formulas, an iterative process was implemented to realize the automatic selection of thresholds. Finally according to the obtained feature vertices, the feature edges and facets were obtained by growing neighbors. The improved approach overcomes the inherent inadequacies of the original approach for our objective in the paper, realizes full automation without setting parameters, and obtains better results compared with the latest conventional approaches. We demonstrated the feasibility and superiority of our approach by performing certain experimental comparisons.