Real-time profile measurement method for a large-scale satellite antenna.

To improve the detection capability of satellite-based synthetic aperture radar, a large antenna array with a length scale of 100 meters is urgently needed. However, the structural deformation of the large antenna leads to phase errors, which will significantly reduce the antenna gain; hence, real-time and high-precision profile measurements of the antenna are essential for active compensation of the phase and thus improving the antenna gain. Nevertheless, the conditions of antenna in-orbit measurements are rather severe because of limited installation locations of measurement instruments, large areas, and long distance to be measured, and unstable measurement environments. To deal with the issues, we propose a three-dimensional displacement measurement method for the antenna plate based on laser distance measuring and digital image correlation (DIC). The proposed method uses the DIC method to retrieve the in-plane displacement information in combination with a laser range finder to provide depth information. A Scheimpflug camera is used to overcome the limitation of the depth of field of traditional cameras and enable clear imaging of the full field. Moreover, a vibration compensation scheme is proposed to eliminate the measurement error of the target displacement caused by the random vibration (within 0.01°) of the camera support rod. The results of the experiment in a laboratory setting show that the proposed method can effectively eliminate the measurement error caused by camera vibration (50 mm) and reduce the displacement measurement error to within 1 mm with a measurement range of 60 m, which can meet the measurement requirements of next-generation large satellite antennas.

Efficient and automated initial value estimation in digital image correlation for large displacement, rotation, and scaling.

The initial value estimation for seed point is the first step in digital image correlation calculation. Among the existing algorithms, the Fourier-Mellin transform-based cross correlation (FMT-CC) algorithm is one of the most efficient and robust owing to its rotation- and scale-invariance. However, when the displacement is large (more than a hundred pixels), the FMT-CC algorithm fails. In this paper, an automated and efficient initial value estimation method based on an FMT-CC algorithm is presented to deal with large displacement, large rotation, and large isotropic scaling. The relationship between subset size and the maximal displacement in the FMT-CC algorithm is studied, and a strategy of setting the subset size according to the estimated displacement is proposed to improve the robustness of the FMT-CC algorithm. In addition, in cases of large displacement, a multi-scale search method is proposed to improve efficiency. The experimental results show that the proposed methods can realize rapid and automated initial value estimation even under conditions of large displacement, large rotation, and large isotropic scaling. The computational efficiency of the multi-scale search method is about one order of magnitude higher than the traditional FMT-CC method.

Theoretical analysis on performance of digital speckle pattern: uniqueness, accuracy, precision, and spatial resolution.

The performance of digital image correlation is closely associated with the quality of speckle pattern. In this paper, the performance of digital speckle pattern is analyzed theoretically concerning four critical factors: uniqueness, accuracy, precision, and spatial resolution. Pattern uniqueness could be characterized by secondary autocorrelation peak height; based on a theoretical analysis on autocorrelation function of digital speckle pattern, analytical formulas are derived to estimate the secondary autocorrelation peak height. Measurement accuracy and precision are descriptions of systematic error and random error respectively; by deriving analytical expression for power spectrum of digital speckle pattern, theoretical models are built for analyzing both systematic errors and random errors. Spatial resolution characterizes the ability of a given technique to distinguish close features; empirical formulas are presented to describe the dependence of spatial resolution upon subset size and shape function order; besides, a rudimentary model is proposed, which provides conservative estimates for spatial resolution. Considering all these four factors, we make recommendations for selection of generation parameters of digital speckle pattern, which can eventually improve the measurement performance of digital image correlation technique.

Statistical model for speckle pattern optimization.

Image registration is the key technique of optical metrologies such as digital image correlation (DIC), particle image velocimetry (PIV), and speckle metrology. Its performance depends critically on the quality of image pattern, and thus pattern optimization attracts extensive attention. In this article, a statistical model is built to optimize speckle patterns that are composed of randomly positioned speckles. It is found that the process of speckle pattern generation is essentially a filtered Poisson process. The dependence of measurement errors (including systematic errors, random errors, and overall errors) upon speckle pattern generation parameters is characterized analytically. By minimizing the errors, formulas of the optimal speckle radius are presented. Although the primary motivation is from the field of DIC, we believed that scholars in other optical measurement communities, such as PIV and speckle metrology, will benefit from these discussions.

Noise-induced bias for convolution-based interpolation in digital image correlation.

In digital image correlation (DIC), the noise-induced bias is significant if the noise level is high or the contrast of the image is low. However, existing methods for the estimation of the noise-induced bias are merely applicable to traditional interpolation methods such as linear and cubic interpolation, but are not applicable to generalized interpolation methods such as BSpline and OMOMS. Both traditional interpolation and generalized interpolation belong to convolution-based interpolation. Considering the widely use of generalized interpolation, this paper presents a theoretical analysis of noise-induced bias for convolution-based interpolation. A sinusoidal approximate formula for noise-induced bias is derived; this formula motivates an estimating strategy which is with speed, ease, and accuracy; furthermore, based on this formula, the mechanism of sophisticated interpolation methods generally reducing noise-induced bias is revealed. The validity of the theoretical analysis is established by both numerical simulations and actual subpixel translation experiment. Compared to existing methods, formulae provided by this paper are simpler, briefer, and more general. In addition, a more intuitionistic explanation of the cause of noise-induced bias is provided by quantitatively characterized the position-dependence of noise variability in the spatial domain.

Fourier-based interpolation bias prediction in digital image correlation.

Based on the Fourier method, this paper deduces analytic formulae for interpolation bias in digital image correlation, explains the well-known sinusoidal-shaped curves of interpolation bias, and introduces the concept of interpolation bias kernel, which characterizes the frequency response of the interpolation bias and thus provides a measure of the subset matching quality of the interpolation algorithm. The interpolation bias kernel attributes the interpolation bias to aliasing effect of interpolation and indicates that high-frequency components are the major source of interpolation bias. Based on our theoretical results, a simple and effective interpolation bias prediction approach, which exploits the speckle spectrum and the interpolation transfer function, is proposed. Significant acceleration is attained, the effect of subset size is analyzed, and both numerical simulations and experimental results are found to agree with theoretical predictions. During the experiment, a novel experimental translation technique was developed that implements subpixel translation of a captured image through integer pixel translation on a computer screen. Owing to this remarkable technique, the influences of mechanical error and out-of-plane motion are eliminated, and complete interpolation bias curves as accurate as 0.01 pixel are attained by subpixel translation experiments.

Genetic amplification of PPME1 in gastric and lung cancer and its potential as a novel therapeutic target.

Protein phosphatase methylesterase 1 (PPME1) is a protein phosphatase 2A (PP2A)-specific methyl esterase that negatively regulates PP2A through demethylation at its carboxy terminal leucine 309 residue. Emerging evidence shows that the upregulation of PPME1 is associated with poor prognosis in glioblastoma patients. By performing an array comparative genomic hybridization analysis to detect copy number changes, we have been the first to identify PPME1 gene amplification in 3.8% (5/131) of Chinese gastric cancer (GC) samples and 3.1% (4/124) of Chinese lung cancer (LC) samples. This PPME1 gene amplification was confirmed by fluorescence in situ hybridization analysis and is correlated with elevated protein expression, as determined by immunohistochemistry analysis. To further investigate the role of PPME1 amplification in tumor growth, short-hairpin RNA-mediated gene silencing was employed. A knockdown of PPME1 expression resulted in a significant inhibition of cell proliferation and induction of cell apoptosis in PPME1-amplified human cancer cell lines SNU668 (GC) and Oka-C1 (LC), but not in nonamplified MKN1 (GC) and HCC95 (LC) cells. The PPME1 gene knockdown also led to a consistent decrease in PP2A demethylation at leucine 309, which was correlated with the downregulation of cellular Erk and AKT phosphorylation. Our data indicate that PPME1 could be an attractive therapeutic target for a subset of GCs and LCs.

FGFR2 gene amplification in gastric cancer predicts sensitivity to the selective FGFR inhibitor AZD4547.

PURPOSE: FGFR gene aberrations are associated with tumor growth and survival. We explored the role of FGFR2 amplification in gastric cancer and the therapeutic potential of AZD4547, a potent and selective ATP-competitive receptor tyrosine kinase inhibitor of fibroblast growth factor receptor (FGFR)1-3, in patients with FGFR2-amplified gastric cancer. EXPERIMENTAL DESIGN: Array-comparative genomic hybridization and FISH were used to identify FGFR2 amplification in gastric cancer patient tumor samples. The effects of FGFR2 modulation were investigated in gastric cancer cells with FGFR2 amplification and in patient-derived gastric cancer xenograft (PDGCX) models using two approaches: inhibition with AZD4547 and short hairpin RNA (shRNA) knockdown of FGFR2. RESULTS: Amplification of the FGFR2 gene was identified in a subset of Chinese and Caucasian patients with gastric cancer. Gastric cancer cell lines SNU-16 and KATOIII, carrying the amplified FGFR2 gene, were extremely sensitive to AZD4547 in vitro with GI50 values of 3 and 5 nmol/L, respectively. AZD4547 effectively inhibited phosphorylation of FGFR2 and its downstream signaling molecules and induced apoptosis in SNU-16 cells. Furthermore, inhibition of FGFR2 signaling by AZD4547 resulted in significant dose-dependent tumor growth inhibition in FGFR2-amplified xenograft (SNU-16) and PDGCX models (SGC083) but not in nonamplified models. shRNA knockdown of FGFR2 similarly inhibited tumor growth in vitro and in vivo. Finally, compared with monotherapy, we showed enhancement of in vivo antitumor efficacy using AZD4547 in combination with chemotherapeutic agents. CONCLUSION: FGFR2 pathway activation is required for driving growth and survival of gastric cancer carrying FGFR2 gene amplification both in vitro and in vivo. Our data support therapeutic intervention with FGFR inhibitors, such as AZD4547, in patients with gastric cancer carrying FGFR2 gene amplification.

Vstm3 is a member of the CD28 family and an important modulator of T-cell function.

Members of the CD28 family play important roles in regulating T-cell functions and share a common gene structure profile. We have identified VSTM3 as a protein whose gene structure matches that of the other CD28 family members. This protein (also known as TIGIT and WUCAM) has been previously shown to affect immune responses and is expressed on NK cells, activated and memory T cells, and Tregs. The nectin-family proteins CD155 and CD112 serve as counter-structures for VSTM3, and CD155 and CD112 also bind to the activating receptor CD226 on T cells and NK cells. Hence, this group of interacting proteins forms a network of molecules similar to the well-characterized CD28-CTLA-4-CD80-CD86 network. In the same way that soluble CTLA-4 can be used to block T-cell responses, we show that soluble Vstm3 attenuates T-cell responses in vitro and in vivo. Moreover, animals deficient in Vstm3 are more sensitive to autoimmune challenges indicating that this new member of the CD28 family is an important regulator of T-cell responses.

The B7 family member B7-H6 is a tumor cell ligand for the activating natural killer cell receptor NKp30 in humans.

Cancer development is often associated with the lack of specific and efficient recognition of tumor cells by the immune system. Natural killer (NK) cells are lymphocytes of the innate immune system that participate in the elimination of tumors. We report the identification of a tumor cell surface molecule that binds NKp30, a human receptor which triggers antitumor NK cell cytotoxicity and cytokine secretion. This previously unannotated gene belongs to the B7 family and, hence, was designated B7-H6. B7-H6 triggers NKp30-mediated activation of human NK cells. B7-H6 was not detected in normal human tissues but was expressed on human tumor cells, emphasizing that the expression of stress-induced self-molecules associated with cell transformation serves as a mode of cell recognition in innate immunity.

Identification of the IL-17 receptor related molecule IL-17RC as the receptor for IL-17F.

The proinflammatory cytokines IL-17A and IL-17F have a high degree of sequence similarity and share many biological properties. Both have been implicated as factors contributing to the progression of inflammatory and autoimmune diseases. Moreover, reagents that neutralize IL-17A significantly ameliorate disease severity in several mouse models of human disease. IL-17A mediates its effects through interaction with its cognate receptor, the IL-17 receptor (IL-17RA). We report here that the IL-17RA-related molecule, IL-17RC is the receptor for IL-17F. Notably, both IL-17A and IL-17F bind to IL-17RC with high affinity, leading us to suggest that a soluble form of this molecule may serve as an effective therapeutic antagonist of IL-17A and IL-17F. We generated a soluble form of IL-17RC and demonstrate that it effectively blocks binding of both IL-17A and IL-17F, and that it inhibits signaling in response to these cytokines. Collectively, our work indicates that IL-17RC functions as a receptor for both IL-17A and IL-17F and that a soluble version of this protein should be an effective antagonist of IL-17A and IL-17F mediated inflammatory diseases.

Gene finding for the helical cytokines.

MOTIVATION: Gene finding remains an open problem well after the sequencing of the human genome. The low gene sensitivity of current methods is a problem for divergent protein families, because fairly accurate exon assemblies are required before sensitive fold recognition algorithms can be applied. This paper presents a new genomic threading algorithm which integrates the gene finding and fold recognition steps into a single process. The method is applicable to evolutionarily divergent protein families that have retained some trace of their common ancestry, number and phase of introns, sizes of exons and placement of structural elements on specific exons. Such conserved structural signals may be visible despite dramatic evolution of protein sequence. RESULTS: The method is evaluated on the family of helical cytokines by cross-validation sensitivity analysis. The method has also been applied to all intergenic regions of the human genome, and an expression and cloning approach has been coupled with the predictions of the method. Two genes discovered by this method are discussed. SUPPLEMENTARY INFORMATION: All data used and the results obtained in the cross-validation analysis are available at http://www.soi.city.ac.uk/~conklin/papers/GT/