Spot Matching Research Articles

Large field-of-view Shack–Hartmann wavefront sensor based on a high-density lens transfer function retrieval

The Shack–Hartmann wavefront sensor (SHWS) is known for its high accuracy and robust wavefront sensing capabilities. However, conventional compact SHWS confronts limitations in measuring field-of-view to meet emerging applications’ increasing demands. Here, we propose a high-density lens transfer function retrieval (HDLTR)-based SHWS to expand its field-of-view. In HDLTR-SHWS, an additional lens is introduced into the measurement system, which converges input wavefront with large aperture onto detectable aperture of sensor. A densely sampling set of phase delays is first employed to retrieve the transfer function of the lens and to isolate lens distortion, which is used to accurately demodulate convergent wavefronts and reconstruct incident wavefronts. We also utilize a global spot matching method to reconstruct the converged wavefront with a large dynamic range. Our experimental results demonstrate that the HDLTR-SHWS expands the field-of-view of SHWS by a factor of 24.9 and achieves an accuracy of less than λ/80.

Integrated Circuit Bonding Distance Inspection via Hierarchical Measurement Structure.

Bonding distance is defined by the projected distance on a substrate plane between two solder points of a bonding wire, which can directly affect the morphology of the bonding wire and the performance between internal components of the chip. For the inspection of the bonding distance, it is necessary to accurately recognize gold wires and solder points within the complex imagery of the chip. However, bonding wires at arbitrary angles and small-sized solder points are densely distributed across the complex background of bonding images. These characteristics pose challenges for conventional image detection and deep learning methods to effectively recognize and measure the bonding distances. In this paper, we present a novel method to measure bonding distance using a hierarchical measurement structure. First, we employ an image acquisition device to capture surface images of integrated circuits and use multi-layer convolution to coarsely locate the bonding region and remove redundant background. Second, we apply a multi-branch wire bonding inspection network for detecting bonding spots and segmenting gold wire. This network includes a fine location branch that utilizes low-level features to enhance detection accuracy for small bonding spots and a gold wire segmentation branch that incorporates an edge branch to effectively extract edge information. Finally, we use the bonding distance measurement module to develop four types of gold wire distribution models for bonding spot matching. Together, these modules create a fully automated method for measuring bonding distances in integrated circuits. The effectiveness of the proposed modules and overall framework has been validated through comprehensive experiments.

Large dynamic range Shack-Hartmann wavefront sensor based on adaptive spot matching

Large dynamic range Shack-Hartmann wavefront sensor based on adaptive spot matching

Control Optimization of Scenic Spot Navigation System Based on Map Matching Algorithm

In order to solve the problem that the smart phone GPS positioning technology cannot guarantee the location accuracy in the scenic spot navigation system, a tourist spot matching method based on the improved HMM model was proposed. Firstly, the traditional linear road model is improved in electronic map design. Secondly, the concept of minimum peripheral error rectangle is proposed based on the theory of error ellipse. Then, combined with location data, road data, and scenic spot data, the improved HMM model is used to calculate the matching road. Finally, Matlab simulation experiment and comparison experiment are carried out. The results show that the accuracy of the map matching algorithm based on the improved HMM model can reach 94.5%, and the average accuracy can reach 93.1%, which is 3.6% higher than that of the traditional HMM model. The test results show that the proposed algorithm is correct and practical and has a good application prospect.

Low-Carbon Tour Route Algorithm of Urban Scenic Water Spots Based on an Improved DIANA Clustering Model

Aiming at the problems in current research into low-carbon and water scenery tourism, this paper brings forward a low-carbon tour route algorithm of urban scenic water spots based on an improved Divisive Analysis clustering model. Based on the ecological attributes of scenic water spots, the clustering model is set up to create scenic spot clusters. Via the clusters, the low-carbon tour route algorithm of urban scenic water spots based on the optimal energy conservation and emission reduction mode is proposed, and it provides the optimal scenic water spots and low-carbon tour routes for tourists. The model can thus realize the optimization of vehicle exhaust emission in urban travel and reduce exhaust emission damage to urban water bodies and natural environments. In order to verify the advantages of the proposed algorithm, this paper performs an experiment to compare the proposed algorithm with the frequently used route planning methods by tourists. The experimental results show that the proposed algorithm has great advantages in energy conservation, emission reduction and low-carbon travel and can reduce the exhaust emission and the damage to the urban water bodies and the natural environment, realizing low-carbon tourism. The main findings and contributions of the proposed work are as follows. First, an improved clustering algorithm is set up, and the urban scenic water spots are clustered according to attribute data, which could optimize the scenic spot recommendation spatial model. Second, combining with the specific characteristics of scenic water spots, the scenic spot mining and matching algorithm is set up to satisfy tourists’ needs. Third, a method that could reduce emission exhaust by optimizing self-driving tour routes is proposed, which could control and reduce the damage to urban environments and protect water ecosystems. The proposed algorithm could be used as the embedded algorithm of tour recommendation systems or the reference algorithm for planning urban tourism transportation. Especially in peak tourism season, it could be used as an effective method for tourism and traffic management departments to direct traffic flow.

Two-Dimensional Gel Electrophoresis Image Analysis.

Gel-based proteomics is still quite widespread due to its high-resolution power; the experimental approach is based on differential analysis, where groups of samples (e.g., control vs diseased) are compared to identify panels of potential biomarkers. However, the reliability of the result of the differential analysis is deeply influenced by 2D-PAGE maps image analysis procedures. The analysis of 2D-PAGE images consists of several steps, such as image preprocessing, spot detection and quantitation, image warping and alignment, spot matching. Several approaches are present in literature, and classical or last-generation commercial software packages exploit different algorithms for each step of the analysis. Here, the most widespread approaches and a comparison of the different strategiesare presented.

Hierarchical transformation-guided image registration for two-dimensional gel electrophoresis image

Many proteomics studies have been devoted to investigate the gel-based methods for separation and fractionation of complex protein mixture extracted from tissues, cells, and other biological specimens. In order to fractionate, identify, and quantify proteins when coupled with mass spectrometric identification or other immunological tests, accurate image alignment method for possible significant protein diversity under different experimental conditions is of high demand. Although lots of protein spot matching and alignment methods have been proposed for two-dimensional gel electrophoresis image, very few methods work well because of dynamic appearance changes and structure changes for gel electrophoresis images. To address these difficulties, we propose a hierarchical transformation-guided registration method to not only align the global shape changes by affine transformation but also alleviate the local structure changes between two gel electrophoresis images by no-rigid deformation registration. The non-rigid registration method is used to obtain the local displacement with shape changes. Since such initial affine transformation can alleviate the global transformation difference between two images, it becomes efficient to use non-rigid registration to refine the registration result. The visualized and quantified experimental results show that our method is more accurate and robust to identify the variability between individual proteins.

Identification of Deferentially Expressed Proteins in Milk during Experimental Bovine Mastitis using Difference Gel Electrophoresis

In order to identify and understand key changes in protein profile of milk during mastitis as a guide to detecting markers for prompt management of the disease, milk from cows in which clinical mastitis were experimentally induced were subjected to a difference gel electrophoresis (DiGE) analysis. Pooled samples from 6 udders (from 6 cows) of three selected time points; 0, 81 and 312 hours post‐challenge of S. uberis mastitis were analysed. These corresponded to samples from pre‐infection, peak and resolution phase of the mastitis challenge. After preliminary sample preparation, concentration and pooling steps, samples were labeled with CyDyes® (CyDye 2, 3 and 5) after which isoelectric focusing and gel electrophoresis were carried out respectively. DiGE gels were subsequently scanned and ImageQuant, ImageJ and DeCyder™ 2D (version 7.0) software were used to crop, obtain Jpeg images and carry out 2‐D differential analysis and processing of the images respectively. Biological Variation Analysis (BVA) software (GE Healthcare life sciences, Buckinghamshire, UK) was also used to evaluate the gels and create a gel to gel matching of spots (qualitatively and quantitatively) within the three gels produced. Overall, a total of 521 proteins spots were identified as changing significantly across the period of intramammary infection (qualitatively or quantitatively) in milk. This demonstrates the large repertoire of protein biomarker candidates available for potential employment and indicators of this disease. Some of these spots were excised for further protein identification by LC‐MS/MS analysis. Further studies are required to elucidate the merits and demerits of these changing proteins in order to identify the most suitable for clinical application in mastitis diagnosis.Support or Funding InformationZoetis, UK and TETFUND, Nigeria are acknowledged for PhD studentship fundingThis abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

Abundant proteins in platelet-rich fibrin and their potential contribution to wound healing: An explorative proteomics study and review of the literature

Background/purposeIt is well-known that diverse types of blood proteins contribute to healing process via different mechanisms. Presence and potential involvements of blood-derived abundant proteins in the platelet-rich fibrin (PRF) to its regenerative capacity have not been sufficiently emphasized in the literature. The aim of this paper was to analyze the abundant proteome content of PRF and summarize previously reported effects of identified proteins on wound healing via a literature review. Materials and methodsThe PRF samples obtained from non-smoking, systemically healthy volunteers were subjected to 2D gel electrophoresis after extracting the proteins from fibrin matrices. All matching spots were excised from the gels and identified by MALDI TOF/TOF MS/MS analysis. A literature review was conducted to reveal possible contributions of identified proteins to wound healing. ResultsTotally, thirty-five blood proteins were commonly identified among all studied samples. These proteins included serine protease inhibitors, such as alpha-1-antitrypsin, alpha-1-antichymotrypsin, alpha-1-acid glycoprotein, inter-alpha-trypsin-inhibitor, protease C1 inhibitor, and complement proteins. In addition, abundant presence of immunoglobulin G was observed. The abundance of albumin, haptoglobin, ceruloplasmin vitronectin, fetuin-A, ficolin-3 and transthyretin was also detected. ConclusionThe results of this study indicated that PRF abundantly contains blood-origin actors which were previously reported for their direct contribution to wound healing. Further studies exploring the protein content of PRF are needed to reveal its undisclosed potential roles in the healing process.

Dynamics of SiO Masers around VX Sgr

Abstract We performed Very Long Baseline Array (VLBA) observations of SiO masers ( ) toward VX Sgr from 2006 July to 2008 August. With the application of a phase reference technique, the accurate relative positions of maser spots at the two transitions can be acquired. The relative positions enable us to obtain more matched masers in the same coordinate frame to better study the dynamics of the maser shell. We adopt two different methods to investigate the global motions of the maser shell, which is found to expand in a decelerated manner. At the beginning of this process, the decelerative force can be interpreted as a force dominated by the gravitational attraction of the star. However, in the later epochs, the deceleration has a smaller magnitude, suggesting that an outward force is combating the stellar gravity. In addition, we construct a model of a rotating and expanding maser shell. The consistency of the model and observations at the first two epochs suggests approximate Keplerian rotation of the shell with a period of 46.9 years. However, other explanations, such as an axisymmetric outflow, are also possible. We also find two matched maser spots with double-peak spectra moving at a velocity of 6.8 km s−1. The special spectra provide direct observational evidence that the motion of a maser spot reflects the real gas stream, rather than changes in physical conditions. Finally, the distance to VX Sgr is calculated to be 1.10 ± 0.11 kpc using a statistical parallax method. This value is within the range reported in the literature.

What’s the Difference? 2D DIGE Image Analysis by DeCyderTM versus SameSpotsTM

The efficiency and reproducibility of two-dimensional difference gel electrophoresis (2D DIGE) depends on several crucial steps: (i) adequate number of replicate gels, (ii) accurate image acquisition, and (iii) statistically confident protein abundance analysis. The latter is inherently determined by the image analysis system. Available software solutions apply different strategies for consecutive image alignment and protein spot detection. While DeCyder^TM performs spot detection on single gels prior to the alignment of spot maps, SameSpots^TM completes image alignment in advance of spot detection. In this study, the performances of DeCyder^TM and SameSpots^TM were compared considering all protein spots detected in 2D DIGE resolved proteomes of three different environmental bacteria with minimal user interference. Proteome map-based analysis by SameSpots^TM allows for fast and reproducible abundance change determination, avoiding time-consuming, manual spot matching. The different raw spot volumes, determined by the two software solutions, did not affect calculated abundance changes. Due to a slight factorial difference, minor abundance changes were very similar, while larger differences in the case of major abundance changes did not impact biological interpretation in the studied cases. Overall, affordable fluorescent dyes in combination with fast CCD camera-based image acquisition and user-friendly image analysis still qualify 2D DIGE as a valuable tool for quantitative proteomics.

Neighborhood matrix: A new idea in matching of two dimensional gel images

Automated data analysis and pattern recognition techniques are the requirements of biological and proteomicsresearch studies. The analysis of proteins consists of some stages among which the analysis of two dimensionalelectrophoresis (2-DE) images is crucial. The aim of image capturing is to generate a Photostat that can be used infuture works such as image comparison. The researchers introduced a new method for matching two 2-DE gelimages. In this method, a neighborhood circular region is defined to obtain information about spots’ neighbors. Inthe present paper, the information obtained by this region is reordered into a matrix as a descriptor of the neighborsof each spot. The matrix is then used in matching the spots between two images. All conducted tests to evaluate themethod’s performance showed the power of the method in spot matching, even when the number of candidatematching spots in the second images increased. The proposed method provides a robust automatic comparison ideain gel images matching. Despite its low speed, its accuracy is excellent. The Novelty of the present study is the useof matrices as neighborhood descriptor. This idea is applicable in any other similar domain.

Sweet spot matching: A thin-layer chromatography-based countercurrent solvent system selection strategy

TLC-based strategies were proposed in 1979 (Hostettmann et al.) and 2005 (Friesen & Pauli; GUESS method) to minimize the number of partitioning experiments required for countercurrent separation (CCS) solvent system selection. As semi-empirical approaches, both proposed that the K values defining the sweet spot of optimal CCS corresponded to a matching Rf value range from the silica gel TLC plate developed in the organic phase of a biphasic or a corresponding monophasic solvent system. Despite their simplicity, there has been an absence of theoretical support and a deficiency of reported experimental evidence. The present study explores the theory required to develop correlations between Rf and K. All theoretical models surmise that the optimal Rf value range should be centered at 0.5. In order to validate the feasibility of the concept of matching Rf and K values, 43 natural products and six solvent system families were investigated. Out of 62 correlations, 45 resulted in matched Rf and K values. Based on this study, practical guidelines for the TLC-based prediction strategy are provided. These approaches will equip CCS users with an updated understanding of how to apply the TLC-based solvent system selection strategy to accelerate a targeted selection of CCS conditions.

The Effect of Colorants on the Content of Heavy Metals in Recycled Corrugated Board Papers

Recycled paper is an important raw material to provide sustainability of natural resources and reduce the environmental impact of the use of paper from recycled pulp in the packaging industry. Hence, recycled paper production is higher in terms of volume and utilization. Recycled paper products are used in the packaging industry partially or fully. Such usage leads to the presence of heavy metals due to recycled and chemical additive sources. The present study aims at determining the amounts and also identifying the sources of heavy metals such as Pb, Cd, Zn, Ni, and Cu contained in recycled testliner (TL) and fluting (FLT), which are main products used in production of corrugated cardboard. The metals in the structure of the paper used in packages directly or indirectly in contact with foods are heavy metals. Mean values of 2.6 mg kg-1 Pb (lead), 2.8 mg kg-1 Zn (zinc), 0.094 mg kg-1 Cd (cadmium), 1.8 mg kg-1 Ni (nickel), and 25.4 mg kg-1 Cu (copper) were detected in test liner and fluting papers using inductively coupled plasma optical emission spectrometry (ICP-OES). The main sources of heavy metals are colorants, mainly consisting of conventional paint and pigments as well as spot and Pantone Matching System (PMS) colorants.

Improved consistency in 2D gel electrophoresis: Sheep plasma as a test case.

Two-dimensional (2D) gel electrophoresis is a well-proven proteomic technique; however, sample-specific optimisation can often be necessary in order to get consistent quantitation. In particular, plasma samples are often smeared on 2D gels making spot matching difficult. A variety of different sample preparation and 2D methods were tested by using sheep plasma, and it was found that lowering sample pH prior to precipitation, using a long voltage gradient for isoelectric focusing and the inclusion of carrier ampholytes in the electrode wicks, improved both the quality and consistency of spot resolution. Analysis of the internal standards from two different DIGE experiments, one with conventional methodology and one with the improved method, showed that along with substantially improving the number of spots resolved, the average CV (coefficient of variation) of matched standards was lower with the new method. 428 matched spots were found using the improved method compared to 208 matched spots using conventional methodology. For the 174 spots that were matched between the two DIGE experiments, the average CV's of spot volumes were also significantly lower, at 0.20 for the new method compared to 0.24 for the conventional method (p < 0.001).

Physiologic changes of urinary proteome by caffeine and excessive water intake

Diurnal variations and physiologic changes of urinary proteome have been suggested in the urinary proteomics field. However, no clear evidence has been demonstrated. The present study thus aimed to define changes in urinary proteome by physiological stimuli, i.e. caffeine intake and excessive water drinking, both of which cause physiologic diuresis. Urine samples were collected from 30 healthy individuals under three different conditions: (i) morning void as the control; (ii) after drinking a cup of coffee; and (iii) after drinking 1 L of water within 20 min. Thereafter, differentially excreted proteins were analyzed by 2-DE proteomics approach and validated by Western blotting and ELISA. Spot matching, quantitative intensity analysis, and ANOVA followed by Tukey's post-hoc multiple comparisons and the Bonferroni correction revealed significant differences in levels of five protein spots among three different conditions. These proteins were identified by quadrupole time-of-flight mass spectrometry (Q-TOF MS) and/or MS/MS analyses as kininogen 1 isoform 3, β-actin, prostaglandin D synthase (PGDS), fibrinogen α-chain and immunoglobulin light chain. Among these, the decreased level of immunoglobulin was successfully validated by Western blotting and ELISA. These data indicated that caffeine intake and excessive water drinking could affect urinary excretion of some proteins and may affect urinary proteome analysis.

A proteomic approach to compare saliva from individuals with and without oral leukoplakia

BackgroundOral leukoplakia is the most common potentially malignant disorder in the oral cavity and can precede carcinoma. This study aimed to identify possible oral leukoplakia salivary biomarkers. MethodsUnstimulated saliva was collected from participants and protein concentration was determined. Proteins were then precipitated with cold acetone and separated using 2DE over a pH range of 3–10. Spot demarcation and matching were performed and protein identification was done through MS analysis. Oral leukoplakia tissues were submitted to immunohistochemistry analysis for keratin 10 (CK10). A complementary analysis of oral leukoplakias that were not included previously was performed in addition. Results226±10 spots were identified in oral leukoplakia 2DE gels, and 262±12 spots were identified in volunteers. Twenty-two spots were highly abundant in oral leukoplakias or not detected in the control group, such as apolipoprotein A1, alpha amylase, cystatins, keratin 10, and lysozyme precursor. All were identified. All oral leukoplakia cases were immunopositive for CK10, mainly in the superficial epithelial layers. ConclusionsThe 2DE salivary protein profiles of individuals with and without oral leukoplakia were observably different. CK10 appears to be an interesting protein and should be further studied in oral carcinogenesis. SignificanceMS-based proteomics enables large-scale analysis of proteins. Proteomics can provide detailed descriptions of proteomes of cells and tissues, including body fluids, and appears as a powerful tool to study human disorders. Saliva is readily accessible through non invasive collection and can mirror diverse disease states. Saliva from both diseased and healthy subjects can be analyzed through 2DE and differences between groups could be found. Routine immunohistochemistry analysis confirmed one of these findings, with CK10 being positive tissues from individuals with oral leukoplakia. Therefore, the present study allows insights into development of an important potential oral cancer precursor, named oral leukoplakia. However, the results can be extrapolated and tested in other precancer states, such as proliferative verrucous leukoplakia, patients at risk of oral cancer due to lifestyle behavior and/or cancer history in the family or even those who are under surveillance after a treated primary oral cancer.

In vitro evidence of the promoting effect of testosterone in kidney stone disease: A proteomics approach and functional validation

Incidence of kidney stone disease in males is 2- to 4-fold greater than in females. This study aimed to determine effects of testosterone on kidney stone disease using a proteomics approach. MDCK renal tubular cells were treated with or without 20nM testosterone for 7days. Cellular proteins were extracted, resolved by 2-DE, and stained with Deep Purple fluorescence dye (n=5 gels derived from 5 independent samples/group). Spot matching, quantitative intensity analysis, and statistics revealed significant changes in levels of nine protein spots after testosterone treatment. These proteins were then identified by nanoLC-ESI-Qq-TOF MS/MS. Global protein network analysis using STRING software revealed α-enolase as the central node of protein–protein interactions. The increased level of α-enolase was then confirmed by Western blotting analysis, whereas immunofluorescence study revealed the increased α-enolase on cell surface and intracellularly. Functional analysis confirmed the potential role of the increased α-enolase in enhanced calcium oxalate monohydrate (COM) crystal-cell adhesion induced by testosterone. Finally, neutralization of surface α-enolase using anti-α-enolase antibody successfully reduced the enhanced COM crystal–cell adhesion to the basal level. Our data provided in vitro evidence of promoting effect of testosterone on kidney stone disease via enhanced COM crystal–cell adhesion by the increased surface α-enolase. Biological significanceThe incidence of kidney stone disease in male is 2- to 4-fold greater than in female. One of the possible factors of the male preference is the higher testosterone hormone level. However, precise molecular mechanisms that testosterone plays in kidney stone disease remained unclear. Our present study is the first exploratory investigation on such aspect using a proteomics approach. Our data also provide a novel mechanistic aspect of how testosterone can impact the risk of kidney stone formation (i.e. the discovery that testosterone increases alpha-enolase expression on the surface of renal tubular cells that is responsible, at least in part, for crystal–cell adhesion).

Calcium oxalate crystals increased enolase-1 secretion from renal tubular cells that subsequently enhanced crystal and monocyte invasion through renal interstitium.

Calcium oxalate monohydrate (COM) crystals cause kidney stone disease by still unclear mechanisms. The present study aimed to characterize changes in secretion of proteins from basolateral compartment of renal tubular epithelial cells after exposure to COM crystals and then correlated them with the stone pathogenesis. Polarized MDCK cells were cultivated in serum-free medium with or without 100 μg/ml COM crystals for 20 h. Secreted proteins collected from the lower chamber (basolateral compartment) were then resolved in 2-D gels and visualized by Deep Purple stain (n = 5 gels/group). Spot matching and intensity analysis revealed six protein spots with significantly altered levels in COM-treated samples. These proteins were then identified by tandem mass spectrometry (Q-TOF MS/MS), including enolase-1, phosphoglycerate mutase-1, actinin, 14-3-3 protein epsilon, alpha-tubulin 2, and ubiquitin-activating enzyme E1. The increased enolase-1 level was confirmed by Western blot analysis. Functional analysis revealed that enolase-1 dramatically induced COM crystal invasion through ECM migrating chamber in a dose-dependent manner. Moreover, enolase-1 bound onto U937 monocytic cell surface markedly enhanced cell migration through the ECM migrating chamber. In summary, our data indicated that the increased secretory enolase-1 induced by COM crystals played an important role in crystal invasion and inflammatory process in renal interstitium.

Alterations of proteins in MDCK cells during acute potassium deficiency

Chronic K+ deficiency can cause hypokalemic nephropathy associated with metabolic alkalosis, polyuria, tubular dilatation, and tubulointerstitial injury. However, effects of acute K+ deficiency on the kidney remained unclear. This study aimed to explore such effects by evaluating changes in levels of proteins in renal tubular cells during acute K+ deficiency. MDCK cells were cultivated in normal K+ (NK) (K+=5.3mM), low K+ (LK) (K+=2.5mM), or K+ depleted (KD) (K+=0mM) medium for 24h and then harvested. Cellular proteins were resolved by two-dimensional gel electrophoresis (2-DE) and visualized by SYPRO Ruby staining (5 gels per group). Spot matching and quantitative intensity analysis revealed a total 48 protein spots that had significantly differential levels among the three groups. Among these, 46 and 30 protein spots had differential levels in KD group compared to NK and LK groups, respectively. Comparison between LK and NK groups revealed only 10 protein spots that were differentially expressed. All of these differentially expressed proteins were successfully identified by Q-TOF MS and/or MS/MS analyses. The altered levels of heat shock protein 90 (HSP90), ezrin, lamin A/C, tubulin, chaperonin-containing TCP1 (CCT1), and calpain 1 were confirmed by Western blot analysis. Global protein network analysis showed three main functional networks, including 1) cell growth and proliferation, 2) cell morphology, cellular assembly and organization, and 3) protein folding in which the altered proteins were involved. Further investigations on these networks may lead to better understanding of pathogenic mechanisms of low K+-induced renal injury.