Increased TCP11 gene expression can inhibit the proliferation, migration and promote apoptosis of cervical cancer cells.

BACKGROUND: Cervical cancer is a common gynecological malignancy. Gene microarray found that TCP11 gene was highly expressed in cervical cancer. However, the effect of TCP11 gene on the proliferation, apoptosis and migration of cervical cancer cells and its underlying molecular mechanisms are unclear. METHODS: GEPIA database, tissue microarray, western blot and qRT-PCR were used to analyze the expression of TCP11 gene in cervical cancer tissues and cells and its relationship with patients' survival rate. The cell cycle and apoptosis were detected by flow cytometry, and the expressions of cell cycle and apoptosis related molecules and EMT-related molecules were detected by Western blot and qRT-PCR. RESULTS: The results showed that TCP11 gene was highly expressed in cervical cancer tissues and cells compared with normal cervical tissues and cells, and its expression was positively correlated with patients' survival rate. The results of proliferation and migration assays showed that TCP11 overexpression inhibited the proliferation and migration of HeLa and SiHa cells. The results showed that TCP11 overexpression blocked the cell cycle of HeLa and SiHa cells, decreased the expression of CDK1 and Cyclin B1, and increased the apoptosis and the expression of caspase-3, cleaved-caspase-3 and cleaved-PARP. TCP11 overexpression increased the protein and mRNA expression of EMT-related molecules ZO-1 and E-cadherin. Conversely, TCP11 knockdown promoted the proliferation of HeLa and SiHa cells and the migration of HeLa cells. CONCLUSIONS: TCP11 overexpression significantly inhibited the occurrence and development of cervical cancer cells, it may be a potentially beneficial biomarker for cervical cancer.

C/EBPß expression decreases in cervical cancer and leads to tumorigenesis.

BACKGROUND: Cervical cancer is currently estimated to be the fourth most common cancer among women worldwide and the leading cause of cancer-related deaths in some of the world's poorest countries. C/EBPß has tumor suppressor effects because it is necessary for oncogene-induced senescence. However, C/EBPß also has an oncogenic role. The specific role of C/EBPß in cervical cancer as a tumor suppressor or oncoprotein is unclear. OBJECTIVE: To explore the role of the C/EBPß protein in cervical tumorigenesis and progression. METHODS: Quantitative RT-PCR was used to analyze C/EBPß (15 cervical cancer tissue samples and 15 corresponding normal cervical tissue samples), miR-661, and MTA1 mRNA expression in clinical samples (10 cervical cancer tissue samples and 10 corresponding normal cervical tissue samples). Immunohistochemistry was used to analyze C/EBPß (381 clinical samples), Ki67 (80 clinical samples) and PCNA ( 60 clinical samples) protein expression. MALDI-TOF MassARRAY was used to analyze C/EBPß gene methylation (13 cervical cancer tissues and 13 corresponding normal cervical tissues). Cell proliferation was analyzed by CCK-8 in cervical cancer cell lines. Western blotting and immunohistochemistry were performed to detect C/EBPß protein expression levels, and mRNA expression was analyzed by quantitative RT-PCR analysis. Flow cytometry was performed to measure cell cycle distribution and cell apoptosis. Colony formation, Transwell, cell invasion, and wound healing assays were performed to detect cell migration and invasion. RESULTS: C/EBPß protein expression was significantly reduced in cervical cancer tissues compared with cervicitis tissues (P < 0.01). Ki67 protein and PCNA protein expression levels were significantly higher in cervical cancer tissues compared with cervicitis tissues. The rate of C/EBPß gene promoter methylation of CpG12, 13, 14 and CpG19 in cervical cancer tissues was significantly increased compared with normal cervical tissue (P < 0.05). In addition, C/EBPß was overexpressed in cervical cancer cells and this overexpression inhibited cell proliferation, migration, invasion, arrested cells in S phase, and promoted apoptosis. CONCLUSIONS: We have demonstrated that C/EBPß decreased in cervical cancer tissues and overexpression of the C/EBPß gene in cervical cancer cells could inhibit proliferation, invasion and migration.

Design of a Smartphone Indoor Positioning Dynamic Ground Truth Reference System Using Robust Visual Encoded Targets.

Smartphone indoor positioning ground truth is difficult to directly, dynamically, and precisely measure in real-time. To solve this problem, this paper proposes and implements a robust smartphone high-precision indoor positioning dynamic real-time ground truth reference system using color visual scatter-encoded targets based on machine vision and photogrammetry. First, a kind of novel high-precision color vision scatter-encoded patterns with a robust recognition rate is designed. Then we use a smartphone to obtain a sequence of images of an experimental room and extract the base points of the color visual scatter-encoded patterns from the sequence images to establish the indoor local coordinate system of the encoded targets. Finally, we use a high-efficiency algorithm to decode the targets of a real-time dynamic shooting image to obtain accurate instantaneous pose information of a smartphone camera and establish the high-precision and high-availability smartphone indoor positioning direct ground truth reference system for preliminary real-time accuracy evaluation of other smartphone positioning technologies. The experimental results show that the encoded targets of the color visual scatter-encoded pattern designed in this paper are easy to detect and identify, and the layout is simple and affordable. It can accurately and quickly solve the dynamic instantaneous pose of a smartphone camera to complete the self-positioning of the smartphone according to the artificial scatter feature visual positioning technology. It is a fast, efficient and low-cost accuracy-evaluation method for smartphone indoor positioning.

An Effective Image Denoising Method for UAV Images via Improved Generative Adversarial Networks.

Unmanned aerial vehicles (UAVs) are an inexpensive platform for collecting remote sensing images, but UAV images suffer from a content loss problem caused by noise. In order to solve the noise problem of UAV images, we propose a new methods to denoise UAV images. This paper introduces a novel deep neural network method based on generative adversarial learning to trace the mapping relationship between noisy and clean images. In our approach, perceptual reconstruction loss is used to establish a loss equation that continuously optimizes a min-max game theoretic model to obtain better UAV image denoising results. The generated denoised images by the proposed method enjoy clearer ground objects edges and more detailed textures of ground objects. In addition to the traditional comparison method, denoised UAV images and corresponding original clean UAV images were employed to perform image matching based on local features. At the same time, the classification experiment on the denoised images was also conducted to compare the denoising results of UAV images with others. The proposed method had achieved better results in these comparison experiments.

Improved Seam-Line Searching Algorithm for UAV Image Mosaic with Optical Flow.

Ghosting and seams are two major challenges in creating unmanned aerial vehicle (UAV) image mosaic. In response to these problems, this paper proposes an improved method for UAV image seam-line searching. First, an image matching algorithm is used to extract and match the features of adjacent images, so that they can be transformed into the same coordinate system. Then, the gray scale difference, the gradient minimum, and the optical flow value of pixels in adjacent image overlapped area in a neighborhood are calculated, which can be applied to creating an energy function for seam-line searching. Based on that, an improved dynamic programming algorithm is proposed to search the optimal seam-lines to complete the UAV image mosaic. This algorithm adopts a more adaptive energy aggregation and traversal strategy, which can find a more ideal splicing path for adjacent UAV images and avoid the ground objects better. The experimental results show that the proposed method can effectively solve the problems of ghosting and seams in the panoramic UAV images.

Rapid Texture Optimization of Three-Dimensional Urban Model Based on Oblique Images.

Seamless texture mapping is one of the key technologies for photorealistic 3D texture reconstruction. In this paper, a method of rapid texture optimization of 3D urban reconstruction based on oblique images is proposed aiming at the existence of texture fragments, seams, and inconsistency of color in urban 3D texture mapping based on low-altitude oblique images. First, we explore implementing radiation correction on the experimental images with a radiation procession algorithm. Then, an efficient occlusion detection algorithm based on OpenGL is proposed according to the mapping relation between the terrain triangular mesh surface and the images to implement the occlusion detection of the visible texture on the triangular facets as well as create a list of visible images. Finally, a texture clustering algorithm is put forward based on Markov Random Field utilizing the inherent attributes of the images and solve the energy function minimization by Graph-Cuts. The experimental results display that the method is capable of decreasing the existence of texture fragments, seams, and inconsistency of color in the 3D texture model reconstruction.

Epipolar Rectification with Minimum Perspective Distortion for Oblique Images.

Epipolar rectification is of great importance for 3D modeling by using UAV (Unmanned Aerial Vehicle) images; however, the existing methods seldom consider the perspective distortion relative to surface planes. Therefore, an algorithm for the rectification of oblique images is proposed and implemented in detail. The basic principle is to minimize the rectified images' perspective distortion relative to the reference planes. First, this minimization problem is formulated as a cost function that is constructed by the tangent value of angle deformation; second, it provides a great deal of flexibility on using different reference planes, such as roofs and the façades of buildings, to generate rectified images. Furthermore, a reasonable scale is acquired according to the dihedral angle between the rectified image plane and the original image plane. The low-quality regions of oblique images are cropped out according to the distortion size. Experimental results revealed that the proposed rectification method can result in improved matching precision (Semi-global dense matching). The matching precision is increased by about 30% for roofs and increased by just 1% for façades, while the façades are not parallel to the baseline. In another designed experiment, the selected façades are parallel to the baseline, the matching precision has a great improvement for façades, by an average of 22%. This fully proves our proposed algorithm that elimination of perspective distortion on rectified images can significantly improve the accuracy of dense matching.