Guided mesh normal filtering

The joint bilateral filter is a variant of the standard bilateral filter, where the range kernel is evaluated using a guidance signal instead of the original signal. It has been successfully applied to various image processing problems, where it provides more flexibility than the standard bilateral filter to achieve high quality results. On the other hand, its success is heavily dependent on the guidance signal, which should ideally provide a robust estimation about the features of the output signal. Such a guidance signal is not always easy to construct. In this paper, we propose a novel mesh normal filtering framework based on the joint bilateral filter, with applications in mesh denoising. Our framework is designed as a two-stage process: first, we apply joint bilateral filtering to the face normals, using a properly constructed normal field as the guidance; afterwards, the vertex positions are updated according to the filtered face normals. We compute the guidance normal on a face using a neighboring patch with the most consistent normal orientations, which provides a reliable estimation of the true normal even with a high-level of noise. The effectiveness of our approach is validated by extensive experimental results

Overexpression of members of the microRNA-183 family is a risk factor for lung cancer: A case control study

<p>Abstract</p> <p>Background</p> <p>Lung cancer is the leading cause of cancer-related deaths worldwide. Early detection is considered critical for lung cancer treatment. MicroRNAs (miRNAs) have shown promise as diagnostic and prognostic indicators. This study was to identify specific miRNAs with diagnostic and prognostic value for patients with lung cancer, and to explore the correlation between expression profiles of miRNAs and patient survival.</p> <p>Methods</p> <p>Gene expression of members of the miR-183 family (miR-96, miR-182, and miR-183) were examined in 70 paired samples from lung cancer patients (primary cancer and non-cancerous tissues and sera), as well as 44 serum samples from normal volunteers and lung cancer cell lines by quantitative real-time reverse transcription polymerase chain reaction (RT-qPCR). The correlation between the expression of miRNAs in tissues, sera, and patient overall survival were also examined by log-rank and Cox regression analysis.</p> <p>Results</p> <p>Expression levels of members of the miR-183 family in lung cancer tumor and sera were higher than that of their normal counterparts. The miR-96 expression in tumors was positively associated with its expression in sera. Log-rank and Cox regression analyses demonstrated that high expression of tumor and serum miRNAs of the miR-183 family were associated with overall poor survival in patients with lung cancer.</p> <p>Conclusions</p> <p>Our results suggest that the expressions of miR-96, miR-182, and miR-183 in tumor and sera may be considered potential novel biomarkers for the diagnosis and prognosis of lung cancer.</p

Reconstruction of plant microstructure using distance weighted tessellation algorithm optimized by virtual segmentation

Abstract(#br)The accurate reconstruction model of plant microstructure is important for obtaining the mechanical properties of plant tissues. In this paper, a virtual segmentation technique is proposed to optimize Delaunay triangulation. Based on the optimized Delaunay triangulation, an Optimized Distance Weighted Tessellation (ODWT) algorithm is developed. Two different structures, namely carrot and retting maize vascular bundles, were reconstructed via the ODWT algorithm. The accuracy of ODWT is evaluated statistically by comparing with Centroid-based Voronoi Tessellation (CVT) and Area Weighted Tessellation (AWT). The results show that ODWT has distinct advantages over CVT and AWT. It is worth mentioning that ODWT has better performance than CVT when there exists large diversity in adjacent cell area. It is found that CVT and AWT fail to reconstruct cells with elongated and concave shapes, while ODWT shows excellent feasibility and reliability. Furthermore, ODWT is capable of establishing finite tissue boundary, which CVT and AWT have failed to realize. The purpose of this work is to develop an algorithm with higher accuracy to implement the preprocessing for further numerical study of plants properties. The comparison results of the simulated values of the longitudinal tensile modulus with the experimental value show that ODWT algorithm can improve the prediction accuracy of multi-scale models on mechanical properties

An Integrated Analysis of miRNA and mRNA Expressions in Non-Small Cell Lung Cancers

Using DNA microarrays, we generated both mRNA and miRNA expression data from 6 non-small cell lung cancer (NSCLC) tissues and their matching normal control from adjacent tissues to identify potential miRNA markers for diagnostics. We demonstrated that hsa-miR-96 is significantly and consistently up-regulated in all 6 NSCLCs. We validated this result in an independent set of 35 paired tumors and their adjacent normal tissues, as well as their sera that are collected before surgical resection or chemotherapy, and the results suggested that hsa-miR-96 may play an important role in NSCLC development and has great potential to be used as a noninvasive marker for diagnosing NSCLC. We predicted potential miRNA target mRNAs based on different methods (TargetScan and miRanda). Further classification of miRNA regulated genes based on their relationship with miRNAs revealed that hsa-miR-96 and certain other miRNAs tend to down-regulate their target mRNAs in NSCLC development, which have expression levels permissive to direct interaction between miRNAs and their target mRNAs. In addition, we identified a significant correlation of miRNA regulation with genes coincide with high density of CpG islands, which suggests that miRNA may represent a primary regulatory mechanism governing basic cellular functions and cell differentiations, and such mechanism may be complementary to DNA methylation in repressing or activating gene expression