String Interactions Research Articles

Wormholes in 2d Horǎva-Lifshitz quantum gravity

We quantize the two-dimensional projectable Horǎva-Lifshitz gravity with a bi-local as well as space-like wormhole interaction. The resulting quantum Hamiltonian coincides with the one obtained through summing over all genus in the string field theory for two-dimensional causal dynamical triangulations. This implies that our wormhole interaction can be interpreted as a splitting or joining interaction of one-dimensional strings.

Eutopic endometrium from women with endometriosis and chlamydial endometritis share immunological cell types and DNA repair imbalance: A transcriptome meta-analytical perspective

The aim of this study was to identify the key similarities between the eutopic endometrium of women with endometriosis and chlamydia-induced endometritis taking into account tissue microenvironment heterogeneity, transcript gene profile, and enriched pathways. A meta-analysis of whole transcriptome microarrays was performed using publicly available data, including samples containing both glandular and stromal endometrial components. Control samples were obtained from women without any reported pathological condition. Only samples obtained during the proliferative menstrual phase were included. Cellular tissue heterogeneity was predicted using a method that integrates gene set enrichment and deconvolution approaches. The batch effect was estimated by principal variant component analysis and removed using an empirical Bayes method. Differentially expressed genes were identified using an adjusted p-value < 0.05 and fold change = 1.5. The protein-protein interaction network was built using the STRING database and interaction score over 400. The Molecular Signatures Database was used to analyse the functional enrichment analysis. Both conditions showed similarities in cell types in the microenvironment, particularly CD4+ and CD8+ Tem cells, NKT cells, Th2 cells, basophils, and eosinophils. With regards to the regulation of cellular senescence and DNA integrity/damage checkpoint, which are commonly enriched pathways, 21 genes were down-regulated and directly related to DNA repair. Compared to the endometriosis samples, some chlamydial endometritis samples presented a lack of enriched immune pathways. Our results suggest that both conditions show similar distributions of microenvironment cell types, the downregulation of genes involved in DNA repair and cell cycle control, and pathways involved in immune response evasion.

Biological roles of the B cell receptor-associated protein 31: Functional Implication in Cancer.

BAP31 is a ubiquitously expressed integral membrane protein of the endoplasmic reticulum. BAP31 is involved in various biological and molecular processes, including protein transport, viral processing, apoptosis signaling, MHC 1 antigen processing and presentation, mitochondria and ER calcium regulation, and proteasomal protein degradation. We employed a BAP31 interaction search using STRING and inBioMap™ protein-protein interaction networks, and the Metabolic Atlas, which revealed molecular and metabolic interactors involved in various pathways essential for cell growth, cell survival, and disease development. BAP31, as a chaperone and resident protein of the ER, was reported in the development of some central nervous system disorders and metabolic diseases about AD, ALS, and Liver disease. In addition, BAP31 is overexpressed in many cancers. Furthermore, research around BAP31 involvement in cancer has taken up a shape, focusing on its roles in cancer cell survival, disease prognosis, and targeted treatment. Here, we address published data on the Biological roles of BAP31 in both health and disease. We present an analytical description of BAP31 expression and functional implication in some human cancers and the impact of its expression and regulation while it models as a potential target in cancer therapy. Besides, a profound understanding of BAP31 is insightful of the gap between cancer development and neurodegeneration, thus generating novel ideas surrounding the link between the two different cell phenomena.

Identification of dysregulated pathways through &lt;i&gt;SLC30A8&lt;/i&gt; protein interaction in type 1 diabetes mellitus

&lt;abstract&gt;&lt;sec&gt; &lt;title&gt;Objective&lt;/title&gt; &lt;p&gt;The aim of the current study was to explore the gene enrichment and dysregulated pathways on the basis of interaction network analysis of &lt;italic&gt;SLC30A8&lt;/italic&gt; in type 1 diabetes mellitus (T1DM). &lt;italic&gt;SLC30A8&lt;/italic&gt; polymorphism could be characterized as a beneficial tool to identify the interacting gene in developing T1DM.&lt;/p&gt; &lt;/sec&gt;&lt;sec&gt; &lt;title&gt;Materials and methods&lt;/title&gt; &lt;p&gt;&lt;italic&gt;SLC30A8&lt;/italic&gt; interacting protein interaction network was obtained by String Interaction network Version 11.0. Ten proteins were identified interacting with &lt;italic&gt;SLC30A8&lt;/italic&gt; and were analysed by protein-protein interaction and enrichment network analysis along with Functional Enrichment analysis tool (FunRich 3.1.3) to map the gene data sets. In entire analysis, FunRich database was used as background against all annotated gene/protein list. Protein-protein interaction (PPI) and enrichment network analysis of the selected protein: &lt;italic&gt;SLC30A8&lt;/italic&gt; gene along with gene mapping and pathway enrichment were performed using FunRich 3.1.3 and String Interaction network Version 11.0.&lt;/p&gt; &lt;/sec&gt;&lt;sec&gt; &lt;title&gt;Results&lt;/title&gt; &lt;p&gt;Biological pathway grouping displayed enriched proteins in TRAIL signalling pathway (&lt;italic&gt;p&lt;/italic&gt; &amp;lt; 0.001). &lt;italic&gt;PTPRN, GAD2&lt;/italic&gt; and &lt;italic&gt;TCF7L2&lt;/italic&gt; were enriched in TRAIL Signalling pathway when &lt;italic&gt;INS&lt;/italic&gt; was made focused gene and directly interacting with &lt;italic&gt;SLC30A8&lt;/italic&gt;.&lt;/p&gt; &lt;/sec&gt;&lt;sec&gt; &lt;title&gt;Conclusions&lt;/title&gt; &lt;p&gt;TRAIL signalling pathways were enriched in T1DM. Therefore, &lt;italic&gt;SLC30A8&lt;/italic&gt; along with &lt;italic&gt;PTPRN, GAD2&lt;/italic&gt; and &lt;italic&gt;TCF7L2&lt;/italic&gt; involved in TRAIL pathway must be further explored to understand their in vivo role in T1DM.&lt;/p&gt; &lt;/sec&gt;&lt;/abstract&gt;

Myeloid-derived suppressor cell (MDSC) key genes analysis in rat anti-CD28-induced immune tolerance kidney transplantation.

BackgroundIn the field of transplantation, inducing immune tolerance in recipients is of great importance. Blocking co-stimulatory molecule using anti-CD28 antibody could induce tolerance in a rat kidney transplantation model. Myeloid-derived suppressor cells (MDSCs) reveals strong immune suppressive abilities in kidney transplantation. Here we analyzed key genes of MDSCs leading to transplant tolerance in this model.MethodsMicroarray data of rat gene expression profiles under accession number GSE28545 in the Gene Expression Omnibus (GEO) database were analyzed. Running the LIMMA package in R language, the differentially expressed genes (DEGs) were found. Enrichment analysis of the DEGs was conducted in the Database for Annotation, Visualization and Integrated Discovery (DAVID) database to explore gene ontology (GO) annotation and their Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Their protein-protein interactions (PPIs) were provided by STRING database and was visualized in Cytoscape. Hub genes were carried out by CytoHubba.ResultsThree hundred and thirty-eight DEGs were exported, including 27 upregulated and 311 downregulated genes. The functions and KEGG pathways of the DEGs were assessed and the PPI network was constructed based on the string interactions of the DEGs. The network was visualized in Cytoscape; the entire PPI network consisted of 192 nodes and 469 edges. Zap70, Cdc42, Stat1, Stat4, Ccl5 and Cxcr3 were among the hub genes.ConclusionsThese key genes, corresponding proteins and their functions may provide valuable background for both basic and clinical research and could be the direction of future studies in immune tolerance, especially those examining immunocyte-induced tolerance.

Impact of single string structure and multiple string interaction on strangeness production in Pb+Pb collisions at sNN=2.76 TeV

We present a systematic study on the strange and multi-strange particles production in Pb+Pb collisions at $\sqrt{S_{NN}} = 2.76$ TeV based on the PACIAE model simulations. Two different mechanisms, namely the single string structure variations and multiple string interactions, are implemented in the simulations. These modifications give rise to an enhancement of the string tension value involved in the Lund string fragmentation framework and generate more strange particles in the hadronic final state. By comparing the simulation results with the ALICE experimental data, it turns out that the inclusion of the variable effective string tension in the PACIAE model is capable to reach an improved agreement between theory and experiment on the strangeness production in Pb+Pb collisions.

The interaction of glueball and heavy-light flavoured meson in holographic QCD

We construct the D4/D8 brane configuration in the Witten–Sakai–Sugimoto model by introducing a pair of heavy flavour brane with a heavy-light open string. The multiplets created by the heavy-light string acquire mass due to the finite separation of the heavy and light flavour branes thus they could be identified as the heavy-light meson fields in this model. On the other hand the glueball field is identified as the gravitational fluctuations carried by the close string in the bulk, so this model is able to describe the interaction of glueball and heavy-light meson through the open-close string interaction in gauge-gravity duality. We explicitly derive the effective action for the various glueballs and heavy-light mesons then numerically evaluate the associated lowest coupling constants. Afterwards the decay/production widths of various glueballs involving the lowest heavy-light meson, which is identified as D^{0} meson, are calculated by using our effective action which might be remarkable to theoretically study the charm oscillation e.g. D^{0}-{bar{D}}^{0}, B_{s}-{bar{B}}_{s} decay/production in hadron physics. This work extends the previous investigations of glueball in holographic QCD and it is also a further prediction of glueball-meson interaction.

Study of Forward-Backward Multiplicity Fluctuations and Correlations with Pseudorapidity

Multiplicity fluctuations in two separated pseudorapidity intervals are studied in terms of strongly intensive variables. This work presents results obtained in the MC model with quark-gluon strings as objects extended in pseudorapidity space and acting as particle emitting sources. The string interactions are implemented within the discrete model of local string fusion. Strings of fluctuating length in pseudorapidity are considered in order to estimate the non-critical background of fluctuations. The results on the dependence of strongly intensive observables on the width of acceptance windows, on the pseudorapidity separation between them and on the string density qualitatively describe the available data from the NA61/SHINE and ALICE experiments.

High Expression of TLR2 in the serum of patients with tuberculosis and lung cancer, and can promote the progression of lung cancer.

Purpose: The present paper investigated the expression of TLR2 in serum of patients with pulmonary tuberculosis and lung cancer, and verifiedthe effect of TLR2 on the biological characteristics of lung cancer cells. Methods: The common differentially expressed genes in tuberculosis and lung cancer samples were analyzed by edgeR. The intersection of genes was taken and the enrichment analysis and string interaction analysis were performed. The expression of TLR2, inflammatory factors IL6, IL17 and IL22 in serum of patients with pulmonary tuberculosis or lung cancer and lung cell were detected by ELISA. The mRNA and protein expression levels of TLR2, caspase-3, Bax and Bcl-2 were detected by qRT-PCR and Western blot. CCK-8, colony formation assay, transwell assay and flow cytometry were performed to detect the proliferation, invasion, migration and cells apoptosis of lung cancer cells. Results: Bioinformatics analysis found that high expression of TLR2 is a core regulator in lung cancer and tuberculosis. TLR2 and inflammatory factors IL6, IL17, IL22 are highly expressed in the serum of patients with tuberculosis and lung cancer by ELISA.TLR2 is also highly expressed in lung cancer cells. Silencing TLR2 inhibited the growth, invasion and migration ability of cells, and the expression of IL6, IL17 and IL22. It also promoted the expression of caspase-3 and Baxwith the decreased expression of Bcl-2. Conclusion: TLR2 and inflammatory factors IL6, IL17 and IL22 were highly expressed in the serum of patients with pulmonary tuberculosis and lung cancer. Silencing TLR2 could inhibit the growth, invasion and migration ability of lung cancer cells, and promote apoptosis.

The Itinerancy and Interactions of the Linear Strings of Holes in Copper Oxide Superconductors

Here I present a new model for the itinerancy of the strings of holes in the Cuprates HTSC. The model assumes various scenarios with respect to the order of the holes hopping and evaluates the weighting parameters for the different scenarios. The new model still results in the aggregation of holes into strings, but yields a spectral distribution for the itinerancy rates of the strings. From this distribution I infer a spectral distribution for the magnetic interaction between the strings, which suggests also a spectral distribution for the pseudogap parameter, and some relevant experimental functions. Apart from these distributions, the basic assumptions of former relevant theories remain intact. Such assumptions are the existence of the anti-ferromagnetic phases A and B, the basic structure of the pseudogap ground state, the excitation operators, and the field. The ground state and the field are basically divided into two bands, the gapless low energy band, and the high energy band. Due to the wide distributions, the bands may be partially overlapped.

Correlations between multiplicities and transverse momenta in nucleus-nucleus collisions from model with cluster of fused color strings

The long-range rapidity correlations between the multiplicities (n-n) and the transverse momentum and the multiplicity (pT-n) of charged particles are analyzed in the framework of the simple string inspired model with two types of sources. The sources of the first type correspond to the initial strings formed in a hadronic collision. The sources of the second type imitate the appearance of the emitters of a new kind resulting from interaction (fusion) of the initial strings. The model enabled to describe effectively the influence of the string fusion effects on the strength both the n-n and the pT-n correlations. Modification of the model to the analogue of the “core-corona” mechanism allows to take into account event selection criteria based on centrality and perform a comparison with existing experimental data on correlation measurements in nucleus-nucleus collisions at LHC energies. It is shown that string fusion effects in the model with the core-corona mechanism lead to the change of a sign of the pT-n correlation coefficient with a decrease of a centrality interval width.

Hypergraph-based connectivity measures for signaling pathway topologies.

Characterizing cellular responses to different extrinsic signals is an active area of research, and curated pathway databases describe these complex signaling reactions. Here, we revisit a fundamental question in signaling pathway analysis: are two molecules "connected" in a network? This question is the first step towards understanding the potential influence of molecules in a pathway, and the answer depends on the choice of modeling framework. We examined the connectivity of Reactome signaling pathways using four different pathway representations. We find that Reactome is very well connected as a graph, moderately well connected as a compound graph or bipartite graph, and poorly connected as a hypergraph (which captures many-to-many relationships in reaction networks). We present a novel relaxation of hypergraph connectivity that iteratively increases connectivity from a node while preserving the hypergraph topology. This measure, B-relaxation distance, provides a parameterized transition between hypergraph connectivity and graph connectivity. B-relaxation distance is sensitive to the presence of small molecules that participate in many functionally unrelated reactions in the network. We also define a score that quantifies one pathway's downstream influence on another, which can be calculated as B-relaxation distance gradually relaxes the connectivity constraint in hypergraphs. Computing this score across all pairs of 34 Reactome pathways reveals pairs of pathways with statistically significant influence. We present two such case studies, and we describe the specific reactions that contribute to the large influence score. Finally, we investigate the ability for connectivity measures to capture functional relationships among proteins, and use the evidence channels in the STRING database as a benchmark dataset. STRING interactions whose proteins are B-connected in Reactome have statistically significantly higher scores than interactions connected in the bipartite graph representation. Our method lays the groundwork for other generalizations of graph-theoretic concepts to hypergraphs in order to facilitate signaling pathway analysis.

Negative specific heat from non-planar interactions and small black holes in AdS/CFT

The gravity side of the gauge/gravity duality predicts the existence of small black holes with negative specific heat. A free theory of strings has a Hagedorn behavior, but it does not lead to negative specific heat. To understand such states one needs to consider a theory of interacting strings. In the dual gauge theory, the string interactions are related to non-planar diagrams. In this paper the simplest gauged matrix model of two free matrices, that has Hagedorn behavior is analyzed in detail. A simple double trace deformation of the Hamiltonian, proportional to the square of the free Hamiltonian is studied. If the interaction has a negative sign, mimicking a gravitational attraction, one produces states with negative specific heat perturbatively and one can still compute the equation of state relating the entropy and the energy. A more general argument based on non-planar interactions that are random and that grow faster in strength than the planar diagrams as a function of the planar energy suggests that states with negative specific heat appear generically.

Mapping saddles and minima on free energy surfaces using multiple climbing strings.

Locating saddle points on free energy surfaces is key in characterizing multistate transition events in complicated molecular-scale systems. Because these saddle points represent transition states, determining minimum free energy pathways to these saddles and measuring their free energies relative to their connected minima are further necessary, for instance, to estimate transition rates. In this work, we propose a new multistring version of the climbing string method in collective variables to locate all saddles and corresponding pathways on free energy surfaces. The method uses dynamic strings to locate saddles and static strings to keep a history of prior strings converged to saddles. Interaction of the dynamic strings with the static strings is used to avoid the convergence to already-identified saddles. Additionally, because the strings approximate curves in collective-variable space, and we can measure free energy along each curve, identification of any saddle's two connected minima is guaranteed. We demonstrate this method to map the network of stationary points in the 2D and 4D free energy surfaces of alanine dipeptide and alanine tripeptide, respectively.

Connectivity measures for signaling pathway topologies

Abstract Characterizing cellular responses to different extrinsic signals is an active area of research, and curated pathway databases describe these complex signaling reactions. Here, we revisit a fundamental question in signaling pathway analysis: are two molecules “connected” in a network? This question is the first step towards understanding the potential influence of molecules in a pathway, and the answer depends on the choice of modeling framework. We examined the connectivity of Reactome signaling pathways using four different pathway representations. We find that Reactome is very well connected as a graph, moderately well connected as a compound graph or bipartite graph, and poorly connected as a hypergraph (which captures many-to-many relationships in reaction networks). We present a novel relaxation of hypergraph connectivity that iteratively increases connectivity from a node while preserving the hypergraph topology. This measure, B-relaxation distance, provides a parameterized transition between hypergraph connectivity and graph connectivity. B-relaxation distance is sensitive to the presence of small molecules that participate in many functionally unrelated reactions in the network. We also define a score that quantifies one pathway’s downstream influence on another, which can be calculated as B-relaxation distance gradually relaxes the connectivity constraint in hypergraphs. Computing this score across all pairs of 34 Reactome pathways reveals pairs of pathways statistically significant influence. We present two such case studies, and we describe the specific reactions that contribute to the large influence score. Finally, we investigate the ability for connectivity measures to capture functional relationships among proteins, and use the evidence channels in the STRING database as a benchmark dataset. STRING interactions whose proteins are B-connected in Reactome have statistically significantly higher scores than interactions connected in the bipartite graph representation. Our method lays the groundwork for other generalizations of graph-theoretic concepts to hypergraphs in order to facilitate signaling pathway analysis. Author summary Signaling pathways describe how cells respond to external signals through molecular interactions. As we gain a deeper understanding of these signaling reactions, it is important to understand how molecules may influence downstream responses and how pathways may affect each other. As the amount of information in signaling pathway databases continues to grow, we have the opportunity to analyze properties about pathway structure. We pose an intuitive question about signaling pathways: when are two molecules “connected” in a pathway? This answer varies dramatically based on the assumptions we make about how reactions link molecules. Here, examine four approaches for modeling the structural topology of signaling pathways, and present methods to quantify whether two molecules are “connected” in a pathway database. We find that existing approaches are either too permissive (molecules are connected to many others) or restrictive (molecules are connected to a handful of others), and we present a new measure that offers a continuum between these two extremes. We then expand our question to ask when an entire signaling pathway is “downstream” of another pathway, and show two case studies from the Reactome pathway database that uncovers pathway influence. Finally, we show that the strict notion of connectivity can capture functional relationships among proteins using an independent benchmark dataset. Our approach to quantify connectivity in pathways considers a biologically-motivated definition of connectivity, laying the foundation for more sophisticated analyses that leverage the detailed information in pathway databases.

Multi-trace correlators from permutations as moduli space

We study the n-point functions of scalar multi-trace operators in the U(Nc) gauge theory with adjacent scalars, such as mathcal{N} = 4 super Yang-Mills, at tree-level by using finite group methods. We derive a set of formulae of the general n-point functions, valid for general n and to all orders of 1/Nc. In one formula, the sum over Feynman graphs becomes a topological partition function on Σ0,n with a discrete gauge group, which resembles closed string interactions. In another formula, a new skeleton reduction of Feynman graphs generates connected ribbon graphs, which resembles open string interaction. We define the moduli space {mathrm{mathcal{M}}}_{g,n}^{mathrm{gauge}} from the space of skeleton-reduced graphs in the connected n-point function of gauge theory. This moduli space is a proper subset of {mathrm{mathcal{M}}}_{g,n} stratified by the genus, and its top component gives a simple triangulation of Σg,n.

The shadow of dark matter as a shadow of string theory

We point out that string theory can solve the conundrum to explain the emergence of an electroweak dipole moment from electroweak singlets through induction of those dipole moments through a Kalb–Ramond dipole coupling. This can generate a U_Y(1) portal to dark matter and entails the possibility that the U_Y(1) gauge field is related to a fundamental vector field for open string interactions. The requirement to explain the observed dark matter abundance relates the coupling scale M in the corresponding low-energy effective U_Y(1) portal to the dark matter mass m_chi . The corresponding electron recoil cross sections for a single dipole coupled dark matter species are generically below the current limits from XENON, SuperCDMS and SENSEI, except in the GeV mass range if the electric dipole coupling becomes stronger than the magnetic coupling, a_e^2ge a_m^2. Furthermore, the recoil cross sections are above the neutrino floor, and the U_Y(1) portal can be tested with longer exposure or larger detectors. Discovery of electroweak dipole dark matter would therefore open an interesting window into string phenomenology.

Holographic description of heavy-flavored baryonic matter decay involving glueball

We holographically investigate the decay of heavy-flavoured baryonic hadron involving glueball by using the Witten-Sakai-Sugimoto model. Since baryon in this model is recognized as the D4-brane wrapped on $S^{4}$ and the glueball field is identified as the bulk gravitational fluctuations, the interaction of the bulk graviton and the baryon brane could be naturally interpreted as glueball-baryon interaction through the holography which is nothing but the close-open string interaction in string theory. In order to take account into the heavy flavour, an extra pair of heavy-flavoured branes separated from the other flavour branes with a heavy-light open string is embedded into the bulk. Due to the finite separation of the flavour branes, the heavy-light string creates massive multiplets which could be identified as the heavy-light meson fields in this model. As the baryon brane on the other hand could be equivalently described by the instanton configuration on the flavour brane, we solve the equations of motion for the heavy-light fields with the Belavin-Polyakov-Schwarz-Tyupkin (BPST) instanton solution for the $N_{f}=2$ flavoured gauge fields. Then with the solutions, we evaluate the soliton mass by deriving the flavoured onshell action in strongly coupling limit and heavy quark limit. After the collectivization and quantization, the quantum mechanical system for glueball and heavy-flavoured baryon is obtained in which the effective Hamiltonian is time-dependent. Finally we use the standard technique for the time-dependent quantum mechanical system to analyze the decay of heavy-flavoured baryon involving glueball and we find one of the decay process might correspond to the decay of baryonic B-meson involving the glueball candidate $f_{0}\left(1710\right)$. This work is a holographic approach to study the decay of heavy-flavoured hadron in nuclear physics.

Microscopic collectivity: The ridge and strangeness enhancement from string–string interactions

We present the microscopic model for collective effects, built on string–string interactions (string shoving and rope hadronization), recently implemented in the PYTHIA8 and DIPSY event generators. Rope hadronization is shown to give a good description of strangeness enhancement across pp, pA and AA collision systems, while string shoving qualitatively describes the ridge observed in pp collisions.

Effect of single string structure and multiple string interaction on strange particle production in pp collisions at s=7TeV

We present a systematic study on the strange particle production at the Large Hadron Collider (LHC) in proton-proton (pp) collisions at $\sqrt{s}=$ 7 TeV based on PACIAE simulations. Two different mechanisms accounting for single string structure variations and multiple string interactions are implemented in the simulations. These modifications give rise to increased effective string tension in the Lund fragmentation model and generate more strange particles in the hadronic final state. By comparing the results with a wealth of the LHC data, it is turned out that the inclusion of variable effective string tension is capable to reach an improved agreement between theory and experiment, especially on the recently observed multiplicity dependence of strangeness enhancement in pp collisions. This approach provides us a new method to understand the microscopic picture of the novel high multiplicity pp events collected at the LHC in the string fragmentation framework.