Dlx5 specifically regulates Runx2 type II expression by binding to homeodomain-response elements in the Runx2 distal promoter

Two major isoforms of the Runx2 gene are expressed by alternative promoter usage: Runx2 type I (Runx2-I) is derived from the proximal promoter (P2), and Runx2 type II (Runx2-II) is produced by the distal promoter (P1). Our previous results indicate that Dlx5 mediates BMP-2-induced Runx2 expression and osteoblast differentiation (Lee, M.-H., Kim, Y-J., Kim, H-J., Park, H-D., Kang, A-R., Kyung, H.-M., Sung, J-H., Wozney, J. M., Kim, H-J., and Ryoo, H-M. (2003) J. Biol. Chem. 278, 34387–34394). However, little is known of the molecular mechanisms by which Dlx5 up-regulates Runx2 expression in BMP-2 signaling. Here, Runx2-II expression was found to be specifically stimulated by BMP-2 treatment or by Dlx5 overexpression. In addition, BMP-2, Dlx5, and Runx2-II were found to be expressed in osteogenic fronts and parietal bones of the developing cranial vault and Runx2-I and Msx2 in the sutural mesenchyme. Furthermore, Runx2 P1 promoter activity was strongly stimulated by Dlx5 overexpression, whereas Runx2 P2 promoter activity was not. Runx2 P1 promoter deletion analysis indicated that the Dlx5-specific response is due to sequences between 756 and 342 bp of the P1 promoter, where three Dlx5-response elements are located. Dlx5 responsiveness to these elements was confirmed by gel mobility shift assay and site-directed mutagenesis. Moreover, Msx2 specifically suppressed the Runx2 P1 promoter, and the responsible region overlaps with that recognized by Dlx5. In summary, Dlx5 specifically transactivates the Runx2 P1 promoter, and its action on the P1 promoter is antagonized by Msx2.This work was supported by Grants 01-PJ1-PG1-01CH08-0001 and 01-PJ3-PG6- 01GN11-0002 from the Korea Health 21 R&D Project, Ministry of Health and Welfare, Republic of Korea. The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact

Calibration of time synchronization error in GPS/SDINS hybrid navigation

In this study, we analyzed the effect of a constant transmission delay that occurs in delivering measurements from a global positioning system receiver to a Kalman filter for an aided strapdown inertial navigation system and propose an efficient delay calibration algorithm. A new error model for the circular trajectories is derived to show that all the currently computed navigation variables converge not to the current true variables but to the neighborhood of the past true variables at the instant the delayed measurements were actually sampled. In order to eliminate the undesirable delay effects given various combinations of receivers and strapdown inertial measurement units, a simple delay calibration algorithm is proposed. The proposed algorithm is enabled by the vehicle's controlled maneuver, and advantageously requires no modification in onboard hardware. Keywords: GPS, SDINS, Calibration, Delay, Error model. 1

Performance Enhancement of Land Vehicle Positioning Using Multiple GPS Receivers in an Urban Area

The Global Positioning System (GPS) is the most widely used navigation system in land vehicle applications. In urban areas, the GPS suffers from insufficient signal strength, multipath propagation and non-line-of-sight (NLOS) errors, so it thus becomes difficult to obtain accurate and reliable position information. In this paper, an integration algorithm for multiple receivers is proposed to enhance the positioning performance of GPS for land vehicles in urban areas. The pseudoranges of multiple receivers are integrated based on a tightly coupled approach, and erroneous measurements are detected by testing the closeness of the pseudoranges. In order to fairly compare the pseudoranges, GPS errors and terms arising due to the differences between the positions of the receivers need to be compensated. The double-difference technique is used to eliminate GPS errors in the pseudoranges, and the geometrical distance is corrected by projecting the baseline vector between pairs of receivers. In order to test and analyze the proposed algorithm, an experiment involving live data was performed. The positioning performance of the algorithm was compared with that of the receiver autonomous integrity monitoring (RAIM)-based integration algorithm for multiple receivers. The test results showed that the proposed algorithm yields more accurate position information in urban areas

The Stability Analysis of the Adaptive Fading Extended Kalman Filter Using the Innovation Covariance

The well-known conventional Kalman filter gives the optimal solution but to do so, it requires an accurate system model and exact stochastic information. However, in a number of practical situations, the system model and the stochastic information are incomplete. The Kalman filter with incomplete information may be degraded or even diverged. To solve this problem, a new adaptive fading filter using a forgetting factor has recently been proposed by Kim and co-authors. This paper analyzes the stability of the adaptive fading extended Kalman filter (AFEKF), which is a nonlinear filter form of the adaptive fading filter. The stability analysis of the AFEKF is based on the analysis result of Reif and co-authors for the EKF. From the analysis results, this paper shows the upper bounded condition of the error covariance for the filter stability and the bounded value of the estimation error

The Stability Analysis of the Adaptive Fading Extended Kalman Filter

The well-known conventional Kalman filter gives the optimal solution but requires an accurate system model and exact stochastic information. Thus, the Kalman filter with incomplete information may be degraded or even diverged. In a number of practical situations, the system model and the stochastic information are incomplete. To solve this problem, a new adaptive fading Kalman filter (AFKF) using the forgetting factor has recently been proposed. This paper extends the AFKF to nonlinear system models to obtain an adaptive fading extended Kalman filter (AFEKF). The forgetting factor is generated from the ratio between the calculated innovation covariance and the estimated innovation covariance. Based on the analysis result of Reif for the EKF, the stability of the AFEKF is also analyzed.GNSS Receiver Technology BK21 Team in Konkuk Universit

Extended Line Map-Based Precise Vehicle Localization Using 3D LIDAR

An Extended Line Map (ELM)-based precise vehicle localization method is proposed in this paper, and is implemented using 3D Light Detection and Ranging (LIDAR). A binary occupancy grid map in which grids for road marking or vertical structures have a value of 1 and the rest have a value of 0 was created using the reflectivity and distance data of the 3D LIDAR. From the map, lines were detected using a Hough transform. After the detected lines were converted into the node and link forms, they were stored as a map. This map is called an extended line map, of which data size is extremely small (134 KB/km). The ELM-based localization is performed through correlation matching. The ELM is converted back into an occupancy grid map and matched to the map generated using the current 3D LIDAR. In this instance, a Fast Fourier Transform (FFT) was applied as the correlation matching method, and the matching time was approximately 78 ms (based on MATLAB). The experiment was carried out in the Gangnam area of Seoul, South Korea. The traveling distance was approximately 4.2 km, and the maximum traveling speed was approximately 80 km/h. As a result of localization, the root mean square (RMS) position errors for the lateral and longitudinal directions were 0.136 m and 0.223 m, respectively

Vertical Corner Feature Based Precise Vehicle Localization Using 3D LIDAR in Urban Area

Tall buildings are concentrated in urban areas. The outer walls of buildings are vertically erected to the ground and almost flat. Therefore, the vertical corners that meet the vertical planes are present everywhere in urban areas. These corners act as convenient landmarks, which can be extracted by using the light detection and ranging (LIDAR) sensor. A vertical corner feature based precise vehicle localization method is proposed in this paper and implemented using 3D LIDAR (Velodyne HDL-32E). The vehicle motion is predicted by accumulating the pose increment output from the iterative closest point (ICP) algorithm based on the geometric relations between the scan data of the 3D LIDAR. The vertical corner is extracted using the proposed corner extraction method. The vehicle position is then corrected by matching the prebuilt corner map with the extracted corner. The experiment was carried out in the Gangnam area of Seoul, South Korea. In the experimental results, the maximum horizontal position error is about 0.46 m and the 2D Root Mean Square (RMS) horizontal error is about 0.138 m

Regulation of cancer stem cells by CXCL1, a chemokine whose secretion is controlled by MCM2

Abstract Background A high expression pattern of minichromosome maintenance 2 (MCM2) has been observed in various cancers. MCM2 is a protein involved in the cell cycle and plays a role in cancer growth and differentiation by binding to six members of the MCM subfamily. The MCM protein family includes MCM2 through MCM7. Methods MCM2 has shown high expression in both lung cancer stem cells (LCSCs) and glioma stem cells (GSCs). We investigated the characteristics of CSCs and the regulation of the epithelial-to-mesenchymal transition (EMT) phenomenon in LCSCs and GSCs by MCM2. Additionally, we explored secreted factors regulated by MCM2. Results There was a significant difference in survival rates between lung cancer patients and brain cancer patients based on MCM2 expression. MCM2 was found to regulate both markers and regulatory proteins in LCSCs. Moreover, MCM2 is thought to be involved in cancer metastasis by regulating cell migration and invasion, not limited to lung cancer but also identified in glioma. Among chemokines, chemokine (C-X-C motif) ligand 1 (CXCL1) was found to be regulated by MCM2. Conclusions MCM2 not only participates in the cell cycle but also affects cancer cell growth by regulating the external microenvironment to create a favorable environment for cells. MCM2 is highly expressed in malignant carcinomas, including CSCs, and contributes to the malignancy of various cancers. Therefore, MCM2 may represent a crucial target for cancer therapeutics

A Doppler Smoothing Filter using Carrier Phase and Application to RTK

Recently, in the field of ITS (Intelligent Transportation System), accurate and precise position of a vehicle in the street is more demanding. They want to know which lane a car is driving in. The GNSS RTK could provide this accuracy. But, in urban street, due to its environment, the conventional code and carrier based RTK cant be a practical solution. The Doppler measurement from GNSS receiver could be considered as one more measurement to solve this problem. A carrier smoothing of Doppler measurement using Kalman Filter is proposed in this paper. This carrier smoothing technique for Doppler measurement can improve Doppler measurement noise level, especially for low cost GNSS receiver. For more robust RTK float solution, this carrier smoothed Doppler measurement is included in double differenced RTK measurement and the velocity estimation performance is much improved. And the innovation and covariance of the smoothing filter is found to be efficient in detecting carrier cycle slip. Field test in urban area shows effectiveness of using carrier smoothed Doppler measurement in RTK for precise positioning of vehicle in the street.This research was supported by a grant from Transportation System Innovation Program(TSIP) funded by Ministry of Land, Transport and Maritime Affairs(MLTM) of Korean government