Contact Matrix Research Articles

Contact formalism for coupled channels

The contact formalism, a useful tool for analyzing short-range correlations, is generalized here for systems with coupled channels, such as in nuclear physics. The relevant asymptotic form is presented and contact matrices are defined. Generally, for the case of two coupled channels, two two-body functions are included in the asymptotic form, resulting a 2 x 2 contact matrix. Nevertheless, it is shown that if the coupling terms of the potential are very weak or very strong, only a single two-body function is needed, resulting a single contact. This universal result is directly relevant to nuclear systems, and provides a theoretical explanation for the fact that proton-neutron short-range correlations can be described using the single bound-state deuteron wave function. It is achieved by applying an appropriate boundary condition on the two-body functions. This boundary condition can be interpreted as a mean field potential imposed on the correlated pair due to the residual system.

Computational tools for Hi‐C data analysis

BackgroundIn eukaryotic genome, chromatin is not randomly distributed in cell nuclei, but instead is organized into higher‐order structures. Emerging evidence indicates that these higher‐order chromatin structures play important roles in regulating genome functions such as transcription and DNA replication. With the advancement in 3C (chromosome conformation capture) based technologies, Hi‐C has been widely used to investigate genome‐wide long‐range chromatin interactions during cellular differentiation and oncogenesis. Since the first publication of Hi‐C assay in 2009, lots of bioinformatic tools have been implemented for processing Hi‐C data from mapping raw reads to normalizing contact matrix and high interpretation, either providing a whole workflow pipeline or focusing on a particular process.ResultsThis article reviews the general Hi‐C data processing workflow and the currently popular Hi‐C data processing tools. We highlight on how these tools are used for a full interpretation of Hi‐C results.ConclusionsHi‐C assay is a powerful tool to investigate the higher‐order chromatin structure. Continued development of novel methods for Hi‐C data analysis will be necessary for better understanding the regulatory function of genome organization.

Ultrasensitive binder-free glucose sensors based on the pyrolysis of in situ grown Cu MOF

A non-enzymatic glucose sensor based on carbon/Cu composite materials was developed by the in-situ growth and subsequent pyrolysis of metal-organic frameworks (MOFs) on Cu foam. After pyrolysis, SEM, HRTEM and STEM-EELS were employed to clarify the hierarchical Cu@porous carbon electrode. It is found that the Cu nanoparticles are uniformly embedded in the carbon matrix, carbon matrix in close contact with the pyrolized carbon sheets. The electrocatalytic activity of the Cu@porous carbon matrix electrode for glucose sensing was explored by cyclic voltammetry (CV) and chronoamperometry. The resulting Cu@porous carbon matrix electrode displays ultrahigh sensitivity (10.1mAcm−2mM−1), low detection limit (0.6 μM), short response time (less than 2s) and good stability, indicating that the developed electrode is a promising glucose sensor.

Contact matrix in dilute quantum systems

Contact has been well established as an important quantity to govern dilute quantum systems, in which the pairwise correlation at short distance traces a broad range of thermodynamic properties. So far, studies have been focusing on contact in individual angular momentum channels. Here, we point out that, to have a complete description of the pairwise correlation in a general dilute quantum systems, contact should be defined as a matrix. Whereas the diagonal terms of such matrix include contact of all partial wave scatterings, the off-diagonal terms, which elude previous studies in the literature, characterise the coherence of the asymptotic pairwise wavefunction in the angular momentum space and determine important thermodynamic quantities including the momentum distribution. Contact matrix allows physicists to access unexplored connections between short-range correlations and macroscopic quantum phenomena. As an example, we show the direct connection between contact matrix and order parameters of a superfluid with mixed partial waves.

Tuning ubiquinone position in biomimetic monolayer membranes.

Artificial lipid bilayers have been extensively studied as models that mimic natural membranes (biomimetic membranes). Several attempts of biomimetic membranes inserting ubiquinone (UQ) have been performed to enlighten which the position of UQ in the lipid layer is, although obtaining contradictory results. In this work, pure components (DPPC and UQ) and DPPC:UQ mixtures have been studied using surface pressure-area isotherms and Langmuir-Blodgett (LB) films of the same compounds have been transferred onto solid substrates being topographically characterized on mica using atomic force microscopy and electrochemically on indium tin oxide slides. DPPC:UQ mixtures present less solid-like physical state than pure DPPC indicating a higher-order degree for the latter. UQ influences considerably DPPC during the fluid state, but it is mainly expelled after the phase transition at [Formula: see text] 26 mN·m^-1 for the 5:1 ratio and at [Formula: see text] 21 mN·m^-1 for lower UQ content. The thermodynamic studies confirm the stability of the DPPC:UQ mixtures before that event, although presenting a non-ideal behaviour. The results indicate that UQ position can be tuned by means of the surface pressure applied to obtain LB films and the UQ initial content. The UQ positions in the biomimetic membrane are distinguished by their formal potential: UQ located in "diving" position with the UQ placed in the DPPC matrix in direct contact with the electrode surface ( -0.04±0.02 V), inserted between lipid chains without contact to the substrate ( 0.00±0.01 V) and parallel to the substrate, above the lipid chains ( 0.09±0.02 V).

Osseointegration of standard and mini dental implants: a histomorphometric comparison

BackgroundMini dental implants (MDIs) are becoming increasingly popular for rehabilitation of edentulous patients because of their several advantages. However, there is a lack of evidence on the osseointegration potential of the MDIs. The objective of the study was to histomorphometrically evaluate and compare bone apposition on the surface of MDIs and standard implants in a rabbit model.MethodsNine New Zealand white rabbits were used for the study to meet statistical criteria for adequate power. Total 18 3M™ESPE™ MDIs and 18 standard implants (Ankylos® Friadent, Dentsply) were inserted randomly into the tibia of rabbits (four implants per rabbit); animals were sacrificed after a 6-week healing period. The specimens were retrieved en bloc and preserved in 10% formaldehyde solution. Specimens were prepared for embedding in a light cure acrylic resin (Technovit 9100). The most central sagittal histological sections (30–40 μm thick) were obtained using a Leica SP 1600 saw microtome. After staining, the Leica DM2000 microscope was used, the images were captured using Olympus DP72 camera and associated software. Bone implant contact (BIC) was measured using Infinity Analyze software.ResultsAll implants were osseointegrated. Histologic measures show mineralized bone matrix in intimate contact with the implant surface in both groups. The median BIC was 58.5 % (IQR 8.0) in the MDI group and 57.0 % (IQR 5.5) in the control group (P > 0.05; Mann-Whitney test). There were no statistical differences in osseointegration at 6 weeks between MDIs and standard implants in rabbit tibias.ConclusionsBased on these results, it is concluded that osseointegration of MDIs is similar to that of standard implants.

HiC-bench: comprehensive and reproducible Hi-C data analysis designed for parameter exploration and benchmarking

BackgroundChromatin conformation capture techniques have evolved rapidly over the last few years and have provided new insights into genome organization at an unprecedented resolution. Analysis of Hi-C data is complex and computationally intensive involving multiple tasks and requiring robust quality assessment. This has led to the development of several tools and methods for processing Hi-C data. However, most of the existing tools do not cover all aspects of the analysis and only offer few quality assessment options. Additionally, availability of a multitude of tools makes scientists wonder how these tools and associated parameters can be optimally used, and how potential discrepancies can be interpreted and resolved. Most importantly, investigators need to be ensured that slight changes in parameters and/or methods do not affect the conclusions of their studies.ResultsTo address these issues (compare, explore and reproduce), we introduce HiC-bench, a configurable computational platform for comprehensive and reproducible analysis of Hi-C sequencing data. HiC-bench performs all common Hi-C analysis tasks, such as alignment, filtering, contact matrix generation and normalization, identification of topological domains, scoring and annotation of specific interactions using both published tools and our own. We have also embedded various tasks that perform quality assessment and visualization. HiC-bench is implemented as a data flow platform with an emphasis on analysis reproducibility. Additionally, the user can readily perform parameter exploration and comparison of different tools in a combinatorial manner that takes into account all desired parameter settings in each pipeline task. This unique feature facilitates the design and execution of complex benchmark studies that may involve combinations of multiple tool/parameter choices in each step of the analysis. To demonstrate the usefulness of our platform, we performed a comprehensive benchmark of existing and new TAD callers exploring different matrix correction methods, parameter settings and sequencing depths. Users can extend our pipeline by adding more tools as they become available.ConclusionsHiC-bench consists an easy-to-use and extensible platform for comprehensive analysis of Hi-C datasets. We expect that it will facilitate current analyses and help scientists formulate and test new hypotheses in the field of three-dimensional genome organization.

Development of a Dual-projected-based Automated Interference Matrix Algorithm for Industry 4.0

In order to complete the intelligent assembly operation, the cooperation between assembly robotic arm and assembly sequence planning (ASP) is necessary. This is a matter of great importance, as traditional product assembly incurs considerable manpower and time, generally accounting for 20–70% of the total manufacturing workload. In this paper, we develop a dual-projected-based automated interference matrix (DPIM) algorithm that analyzes the relations between the components of a given product. In order to reduce the number of times that collide detection is performed in comparison with the method only do collision detection, the DPIM algorithm relies on static interference detection and dual-projected detection to generate a contact matrix, a direction contact matrix, and an interference matrix. By reducing the number of times collide detection is performed, DPIM can reduce the workload of assembly, thereby reducing the total manufacturing load overall and the manufacturing time likewise.

The Capturing of Space Debris with a Spaceborne Multi-fingered Gripper

With the massive launching of spacecraft, more and more space debris are making the low Earth orbit (LEO) much more crowded which seriously affects the normal flight of other spacecrafts. Space debris removal has become a very urgent issue concerned by numerous countries. In this paper, using SwissCube as a target, the capturing of space debris with a spaceborne four-fingered gripper was studied in order to obtain the key factors that affect the capturing effect. The contact state between the gripper fingers and SwissCube was described using a defined contact matrix. The law of momentum conservation was used to model the motion variations of the gripper and SwissCube before and after the capturing process. A zero-gravity simulation environment was built using ADAMS software. Two typical kinds of capturing processes were simulated considering different stiffness of fingers and different friction conditions between fingers and SwissCube. Comparisons between results obtained with the law of momentum conservation and those from ADAMS simulation show that the theoretical calculations and simulation results are consistent. In addition, through analyzing the capturing process, a valuable finding was obtained that the contact friction and finger flexibility are two very important factors that affect the capturing result.

Incorporating social contact data in spatio-temporal models for infectious disease spread.

SummaryRoutine public health surveillance of notifiable infectious diseases gives rise to weekly counts of reported cases—possibly stratified by region and/or age group. We investigate how an age-structured social contact matrix can be incorporated into a spatio-temporal endemic–epidemic model for infectious disease counts. To illustrate the approach, we analyze the spread of norovirus gastroenteritis over six age groups within the 12 districts of Berlin, 2011–2015, using contact data from the POLYMOD study. The proposed age-structured model outperforms alternative scenarios with homogeneous or no mixing between age groups. An extended contact model suggests a power transformation of the survey-based contact matrix toward more within-group transmission.

Learning structural bioinformatics and evolution with a snake puzzle

We propose here a working unit for teaching basic concepts of structural bioinformatics and evolution through the example of a wooden snake puzzle, strikingly similar to toy models widely used in the literature of protein folding. In our experience, developed at a Master’s course at the Universidad Autónoma de Madrid (Spain), the concreteness of this example helps to overcome difficulties caused by the interdisciplinary nature of this field and its high level of abstraction, in particular for students coming from traditional disciplines. The puzzle will allow us discussing a simple algorithm for finding folded solutions, through which we will introduce the concept of the configuration space and the contact matrix representation. This is a central tool for comparing protein structures, for studying simple models of protein energetics, and even for a qualitative discussion of folding kinetics, through the concept of the Contact Order. It also allows a simple representation of misfolded conformations and their free energy. These concepts will motivate evolutionary questions, which we will address by simulating a structurally constrained model of protein evolution, again modelled on the snake puzzle. In this way, we can discuss the analogy between evolutionary concepts and statistical mechanics that facilitates the understanding of both concepts. The proposed examples and literature are accessible, and we provide supplementary material (see ‘Data Availability’) to reproduce the numerical experiments. We also suggest possible directions to expand the unit. We hope that this work will further stimulate the adoption of games in teaching practice.

Influence of social contact patterns and demographic factors on influenza simulation results.

BackgroundThe demographic composition and the frequency and nature of social contacts may affect the spread of influenza virus in a population, resulting in distinct age-dependent immunity patterns. As demography and social contact rates differ strongly between European countries, this may impact infection incidence and vaccine effectiveness and thus limit the extent to which conclusions derived from observations in one country can be generalized to others. In the current study, we aimed to decipher the impact of social contact patterns and demographic factors on simulation results and, thus, to determine to what extent vaccination results can be generalized.MethodsWe simulated the transmission of four influenza strains (A(H1N1), A(H3N2), B/Victoria, B/Yamagata) in Belgium, Finland, Germany, GB, Italy, Luxembourg, Netherlands and Poland, using the simulation tool 4Flu. Individuals were connected in a dynamically evolving age-dependent contact network based on the POLYMOD study.ResultsWhen averaged over 20 years, simulation results without vaccination ranged from annually 20,984 (Germany) to 31,322 infections (Italy) per 100,000 individuals. QIV annually prevented 1758 (Poland) to 7720 infections (Germany) per 100,000. Variability of prevented cases remained high when the country-specific vaccination was replaced by unified coverage, but was reduced considerably if the same demography was used for all countries, or even more so when the same contact matrix was used.ConclusionsContact matrix and demography strongly influence the age-dependent incidence of influenza and the success of vaccination. Projecting simulation results from one country to another can, therefore, lead to erroneous results.Electronic supplementary materialThe online version of this article (doi:10.1186/s12879-016-1981-5) contains supplementary material, which is available to authorized users.

Enhancing interacting residue prediction with integrated contact matrix prediction in protein-protein interaction.

Identifying the residues in a protein that are involved in protein-protein interaction and identifying the contact matrix for a pair of interacting proteins are two computational tasks at different levels of an in-depth analysis of protein-protein interaction. Various methods for solving these two problems have been reported in the literature. However, the interacting residue prediction and contact matrix prediction were handled by and large independently in those existing methods, though intuitively good prediction of interacting residues will help with predicting the contact matrix. In this work, we developed a novel protein interacting residue prediction system, contact matrix-interaction profile hidden Markov model (CM-ipHMM), with the integration of contact matrix prediction and the ipHMM interaction residue prediction. We propose to leverage what is learned from the contact matrix prediction and utilize the predicted contact matrix as “feedback” to enhance the interaction residue prediction. The CM-ipHMM model showed significant improvement over the previous method that uses the ipHMM for predicting interaction residues only. It indicates that the downstream contact matrix prediction could help the interaction site prediction.

Polymer models of the hierarchical folding of the Hox-B chromosomal locus.

As revealed by novel technologies, chromosomes in the nucleus of mammalian cells have a complex spatial organization that serves vital functional purposes. Here we use models from polymer physics to identify the mechanisms that control their three-dimensional spatial organization. In particular, we investigate a model of the Hox-B locus, an important genomic region involved in embryo development, to expose the principles regulating chromatin folding and its complex behaviors in mouse embryonic stem cells. We reconstruct with high accuracy the pairwise contact matrix of the Hox-B locus as derived by Hi-C experiments and investigate its hierarchical folding dynamics. We trace back the observed behaviors to general scaling properties of polymer physics.

“disassembly plan approach based on subassembly concept”

For complex products, the generation of an assembly or disassembly plan becomes a difficult task as the assembly parts’ numbers increase. To bypass this problem, the use of a subassembly concept represents an original technique. It aims to organize the multipart assembly product into some subassembly encapsulation. Each subassembly contains, relatively, a small number of parts. As a result, the assembly or disassembly plan problem becomes between the identified subassemblies and, in that case, can be generated easily. Despite the attractiveness of the subassembly concept, the identification of subassemblies from the CAD model product remains a relevant research subject to be improved. In fact, the resolution of the precedence relation problem from the CAD model data constitutes the biggest difficulty of this technique. In this work, a novel disassembly plan approach based on a subassembly concept is presented. The proposed approach starts with the investigation of the CAD assembly data to extract a contact matrix. Then, the extracted matrix is enriched by assembling conditions in order to search the set of base parts initiating subassemblies. Once the subassemblies were recognized, a new subassembly interference matrix is regenerated. The disassembly plan is carried out, between the known subassemblies, using a simplification method of subassemblies interference matrix. An example of the CAD assembly product is treated during this paper to clarify the different steps of the proposed approach. The simulated results of both subassembly identification and disassembly plan were compared to examples given by the literature in order to validate the developed approach.

Pandemic Risk Assessment Model (PRAM): a mathematical modeling approach to pandemic influenza planning.

The Pandemic Risk Assessment Model (PRAM) is a mathematical model developed to analyse two pandemic influenza control measures available to public health: antiviral treatment and immunization. PRAM is parameterized using surveillance data from Alberta, Canada during pandemic H1N1. Age structure and risk level are incorporated in the compartmental, deterministic model through a contact matrix. The model characterizes pandemic influenza scenarios by transmissibility and severity properties. Simulating a worst-case scenario similar to the 1918 pandemic with immediate stockpile release, antiviral demand is 20·3% of the population. With concurrent, effective and timely immunization strategies, antiviral demand would be significantly less. PRAM will be useful in informing policy decisions such as the size of the Alberta antiviral stockpile and can contribute to other pandemic influenza planning activities and scenario analyses.

Polymer physics of chromosome large-scale 3D organisation.

Chromosomes have a complex architecture in the cell nucleus, which serves vital functional purposes, yet its structure and folding mechanisms remain still incompletely understood. Here we show that genome-wide chromatin architecture data, as mapped by Hi-C methods across mammalian cell types and chromosomes, are well described by classical scaling concepts of polymer physics, from the sub-Mb to chromosomal scales. Chromatin is a complex mixture of different regions, folded in the conformational classes predicted by polymer thermodynamics. The contact matrix of the Sox9 locus, a region linked to severe human congenital diseases, is derived with high accuracy in mESCs and its molecular determinants identified by the theory; Sox9 self-assembles hierarchically in higher-order domains, involving abundant many-body contacts. Our approach is also applied to the Bmp7 locus. Finally, the model predictions on the effects of mutations on folding are tested against available data on a deletion in the Xist locus. Our results can help progressing new diagnostic tools for diseases linked to chromatin misfolding.

Dynamic communicability and epidemic spread: a case study on an empirical dynamic contact network

We analyse a recently proposed temporal centrality measure applied to an empirical network based on person-to-person contacts in an emergency department of a busy urban hospital. We show that temporal centrality identifies a distinct set of top-spreaders than centrality based on the time-aggregated binarized contact matrix, so that taken together, the accuracy of capturing top-spreaders improves significantly. However, with respect to predicting epidemic outcome, the temporal measure does not necessarily outperform less complex measures. Our results also show that other temporal markers such as duration observed and the time of first appearance in the network can be used in a simple predictive model to generate predictions that capture the trend of the observed data remarkably well.

Prediction of residue-residue contact matrix for protein-protein interaction with Fisher score features and deep learning

Protein-protein interactions play essential roles in many biological processes. Acquiring knowledge of the residue-residue contact information of two interacting proteins is not only helpful in annotating functions for proteins, but also critical for structure-based drug design. The prediction of the protein residue-residue contact matrix of the interfacial regions is challenging. In this work, we introduced deep learning techniques (specifically, stacked autoencoders) to build deep neural network models to tackled the residue-residue contact prediction problem. In tandem with interaction profile Hidden Markov Models, which was used first to extract Fisher score features from protein sequences, stacked autoencoders were deployed to extract and learn hidden abstract features. The deep learning model showed significant improvement over the traditional machine learning model, Support Vector Machines (SVM), with the overall accuracy increased by 15% from 65.40% to 80.82%. We showed that the stacked autoencoders could extract novel features, which can be utilized by deep neural networks and other classifiers to enhance learning, out of the Fisher score features. It is further shown that deep neural networks have significant advantages over SVM in making use of the newly extracted features.

Dispersive Solid-Phase Extraction of Rhodium from Water, Street Dust, and Catalytic Converters Using a Cellulose–Graphite Oxide Composite

ABSTRACTA cellulose–graphite oxide composite was synthesized and characterized as an adsorbent for dispersive solid-phase extraction of rhodium from various samples before atomic absorption detection. The pH, adsorbent volume, centrifugation time and rate, eluent concentration, volume and type, adsorption and elution contact time, sample volume, and matrix interferences were optimized. The developed method is simple, rapid, and inexpensive. The tolerance limits for rhodium were 10,000 mg L−1 sodium, 25,000 mg L−1 potassium, 10,000 mg L−1 magnesium, and 20,000 mg L−1 calcium. The recovery for rhodium exceeded 95%. Elution was performed with 10 mL of 2.5 mol L−1 H2SO4. The adsorption and elution contact times were 30 and 60 s, respectively. The detection limit of the method for rhodium was 5.4 µg L−1 and the precision as the relative standard deviation was 1.6%. A certified reference material 2556 (used auto catalyst pellets) and fortified samples were analyzed to evaluate the accuracy of the method. The optimized method was used for the preconcentration of rhodium from tap water, well water, wastewater, seawater, catalytic converters, and street dust.