Pair Interactions Research Articles

An exposome-wide approach of organophosphate flame retardants in the Taiwanese population: Parent-child pairs interaction and potential health risk

An exposome-wide approach of organophosphate flame retardants in the Taiwanese population: Parent-child pairs interaction and potential health risk

Oxidative heterocoupling of α-carbanions of lithium acylates with 1,2-dibromoethane

The interaction of pairs of α-carbanions of lithium 2-methylpropanoate, butanoate, pentanoate, hexanoate, heptanoate and phenylacetate, generated from various CH-acids (A-H, B-H) under the action of lithium diisopropylamide in THF, with 1,2-dibromoethane leads to a mixture of products of oxidative homo[2,2,3,3-tetramethyl-, 2,3-diethyl-, 2,3-dipropyl-, 2,3-dibutyl-, 2,3-dipentyl- and 2,3 -diphenylsuccinic acids] and heterocoupling [2,2-dimethyl-3-ethyl-, 2-propyl-3-ethyl-, 2-butyl-3-ethyl-, 2-pentyl-3-ethyl-, 2-phenyl-3 -ethyl-, 2-butyl-3-propyl-, 2-pentyl-3-propyl-, 2-propyl-3-phenyl-, 2-butyl-3-pentyl-, 2-butyl-3-phenyl- and 2 -pentyl-3-phenylsuccinic acids] with a total yield of 83-99%. The selectivity of the formation of homo- and heterocoupling products depends on the structure of the coupled α-carbanions.

Inferring interactions in multispecies communities: The cryptocurrency market case.

We introduce a general framework for empirically detecting interactions in communities of entities characterized by different features. This approach is inspired by ideas and methods coming from ecology and finance and is applied to a large dataset extracted from the cryptocurrency market. The inter-species interaction network is constructed using a similarity measure based on the log-growth rate of the capitalizations of the cryptocurrency market. The detected relevant interactions are only of the cooperative type, and the network presents a well-defined clustered structure, with two practically disjointed communities. The first one is made up of highly capitalized cryptocurrencies that are tightly connected, and the second one is made up of small-cap cryptocurrencies that are loosely linked. This approach based on the log-growth rate, instead of the conventional price returns, seems to enhance the discriminative potential of the network representation, highlighting a modular structure with compact communities and a rich hierarchy that can be ascribed to different functional groups. In fact, inside the community of the more capitalized coins, we can distinguish between clusters composed of some of the more popular first-generation cryptocurrencies, and clusters made up of second-generation cryptocurrencies. Alternatively, we construct the network of directed interactions by using the partial correlations of the log-growth rate. This network displays the important centrality of Bitcoin, discloses a core cluster containing a branch with the most capitalized first-generation cryptocurrencies, and emphasizes interesting correspondences between the detected direct pair interactions and specific features of the related currencies. As risk strongly depends on the interaction structure of the cryptocurrency system, these results can be useful for assisting in hedging risks. The inferred network topology suggests fewer probable widespread contagions. Moreover, as the riskier coins do not strongly interact with the others, it is more difficult that they can drive the market to more fragile states.

Identification and characterization of CYC2-like genes related to floral symmetric development in Tagetes erecta (Asteraceae)

Marigold (Tagetes erecta) is an annual herbaceous flower belonging to Asteraceae, whose capitulum is composed of bilateral symmetry ray florets on the outer periphery and radial symmetry disk florets on the inside. The flower symmetry evolution from radial symmetry to bilateral symmetry has changed the morphology, inflorescence architecture and function of florets among several lineages in Asteraceae. Several studies have identified that CYC2 genes in TCP transcription factor family are the key genes regulating the flower morphogenesis, such as corolla symmetry and stamen development. Here, seven TeCYC2 genes were cloned and phylogenetically grouped into the CYC2 branch of TCP transcription family. TeCYC2c and TeCYC2d were found to be expressed specifically in ray florets, TeCYC2b was strongly expressed in both ray and disk florets, TeCYC2g was significantly higher expressed in ray florets than in disk florets, while TeCYC2a, TeCYC2e1 and TeCYC2e2 were significantly expressed in disk florets, according to an examination of the expression profile. Among the ectopic expression lines of seven TeCYC2 genes in Arabidopsis thaliana, the flower symmetry of all transgenic lines was changed from radial symmetry to bilateral symmetry, and only the reproductive growth of TeCYC2c lines was affected. In TeCYC2c transgenic Arabidopsis, the pollen sac was difficult to crack, and the filaments were shorter than the pistils, resulting in a significant decrease in the seed setting rate. All TeCYC2 proteins were localized in the nucleus. Eight pairs of interactions between TeCYC2 proteins were validated by Y2H and BiFC assays, indicating the possibility of TeCYC2 proteins forming homodimers or heterodimers to improve functional specificity. Our findings verified the main regulatory role of TeCYC2c on the development of corollas and stamen in marigold, and analyzed the interaction network of the formation mechanism of floral symmetry in two florets, which provided more insights into the expansion of CYC2 genes in the evolution of Asteraceae inflorescence and contributed to elucidate the complex regulatory network, as well as the molecular breeding concerning flower form diversity in marigold.

Heterologous Interactions with Galectins and Chemokines and Their Functional Consequences.

Extra- and intra-cellular activity occurs under the direction of numerous inter-molecular interactions, and in any tissue or cell, molecules are densely packed, thus promoting those molecular interactions. Galectins and chemokines, the focus of this review, are small, protein effector molecules that mediate various cellular functions-in particular, cell adhesion and migration-as well as cell signaling/activation. In the past, researchers have reported that combinations of these (and other) effector molecules act separately, yet sometimes in concert, but nevertheless physically apart and via their individual cell receptors. This view that each effector molecule functions independently of the other limits our thinking about functional versatility and cooperation, and, in turn, ignores the prospect of physiologically important inter-molecular interactions, especially when both molecules are present or co-expressed in the same cellular environment. This review is focused on such protein-protein interactions with chemokines and galectins, the homo- and hetero-oligomeric structures that they can form, and the functional consequences of those paired interactions.

Novel ceRNA network construction associated with programmed cell death in acute rejection of heart allograft in mice.

T cell-mediated acute rejection(AR) after heart transplantation(HT) ultimately results in graft failure and is a common indication for secondary transplantation. It's a serious threat to heart transplant recipients. This study aimed to explore the novel lncRNA-miRNA-mRNA networks that contributed to AR in a mouse heart transplantation model. The donor heart from Babl/C mice was transplanted to C57BL/6 mice with heterotopic implantation to the abdominal cavity. The control group was syngeneic heart transplantation with the same kind of mice donor. The whole-transcriptome sequencing was performed to obtain differentially expressed mRNAs (DEmRNAs), miRNAs (DEmiRNAs) and lncRNAs (DElncRNAs) in mouse heart allograft. The biological functions of ceRNA networks was analyzed by GO and KEGG enrichment. Differentially expressed ceRNA involved in programmed cell death were further verified with qRT-PCR testing. Lots of DEmRNAs, DEmiRNAs and DElncRNAs were identified in acute rejection and control after heart transplantation, including up-regulated 4754 DEmRNAs, 1634 DElncRNAs, 182 DEmiRNAs, and down-regulated 4365 DEmRNAs, 1761 DElncRNAs, 132 DEmiRNAs. Based on the ceRNA theory, lncRNA-miRNA-mRNA regulatory networks were constructed in allograft acute rejection response. The functional enrichment analysis indicate that the down-regulated mRNAs are mainly involved in cardiac muscle cell contraction, potassium channel activity, etc. and the up-regulated mRNAs are mainly involved in T cell differentiation and mononuclear cell migration, etc. The KEGG pathway enrichment analysis showed that the down-regulated DEmRNAs were mainly enriched in adrenergic signaling, axon guidance, calcium signaling pathway, etc. The up-regulated DEmRNAs were enriched in the adhesion function, chemokine signaling pathway, apoptosis, etc. Four lncRNA-mediated ceRNA regulatory pathways, Pvt1/miR-30c-5p/Pdgfc, 1700071M16Rik/miR-145a-3p/Pdgfc, 1700071M16Rik/miR-145a-3p/Tox, 1700071M16Rik/miR-145a-3p/Themis2, were finally validated. In addition, increased expression of PVT1, 1700071M16Rik, Tox and Themis2 may be considered as potential diagnostic gene biomarkers in AR. We speculated that Pvt1/miR-30c-5p/Pdgfc, 1700071M16Rik/miR-145a-3p/Pdgfc, 1700071M16Rik/miR-145a-3p/Tox and 1700071M16Rik/miR-145a-3p/Themis2 interaction pairs may serve as potential biomarkers in AR after HT.

Identifying the impacts of land use landscape pattern and climate changes on streamflow from past to future

Identifying the individual and combined hydrological response of land use landscape pattern and climate changes is key to effectively managing the ecohydrological balance of regions. However, their nonlinearity, effect size, and multiple causalities limit causal investigations. Therefore, this study aimed to establish a comprehensive methodological framework to quantify changes in the landscape pattern and climate, evaluate trends in streamflow response, and analyze the attribution of streamflow events in five basins in Beijing from the past to the future. Future climate projections were based on three general circulation models (GCMs) under two shared socioeconomic pathways (SSPs). Additionally, the landscape pattern in 2035 under a natural development scenario was simulated by the patch-generating land use simulation (PLUS). The Soil and Water Assessment Tool (SWAT) was applied to evaluate the streamflow spatial and temporal dynamics over the period 2005–2035 with multiple scenarios. A bootstrapping nonlinear regression analysis and boosted regression tree (BRT) model were used to analyze the individual and combined attribution of landscape pattern and climate changes on streamflow, respectively. The results indicated that in the future, the overall streamflow in the Beijing basin would decrease, with a slightly reduced peak streamflow in most basins in the summer and a significant increase in the autumn and winter. The nonlinear quadratic regression more effectively explained the impact of landscape pattern and climate changes on streamflow. The trends in the streamflow change depended on where the relationship curve was in relation to the threshold. In addition, the impacts of landscape pattern and climate changes on streamflow were not isolated but were joint. They presented a nonlinear, non-uniform, and coupled relationship. Except for the YongDing River Basin, the annual streamflow change was influenced more by the landscape pattern. The dominant factors and the critical pair interactions varied from basin to basin. Our findings have implications for city planners and managers for optimizing ecohydrological functions and promoting sustainable development.

Simple Model of Liquid Water Dynamics.

We develop an analytical statistical-mechanical model to study the dynamic properties of liquid water. In this two-dimensional model, neighboring waters can interact through a hydrogen bond, a van der Waals contact, or an ice-like cage structure or have no interaction. We calculate the diffusion coefficient, viscosity, and thermal conductivity versus temperature and pressure. The trends follow those seen in the water experiments. The model explains that in warm water, heating drives faster diffusion but less interaction, so the viscosity and conductivity decrease. Cooling cold water causes poorer energy exchange because water's ice-like cages are big and immobile and collide infrequently. The main antagonism in water dynamics is not between vdW and H bonds, but it is an interplay between both those pair interactions, multibody cages, and no interaction. The value of this simple model is that it is analytical, so calculations are immediate, and it gives interpretations based on molecular physics.

Triplet Pairing in Neutron Matter

The presence of superfluidity in neutron star interiors can affect the cooling of neutron stars in intricate ways, enhancing certain mechanisms and suppressing others. Model calculations employing realistic nuclear potentials in Bardeen–Cooper–Schrieffer theory generally suggest the development of a 3P2–3F2 pairing gap, and therefore the presence of superfluidity in dense neutron star matter. Improved models that go beyond conventional mean-field calculations by including polarization effects suggest a suppression of the triplet gap. We have evaluated the pairing interaction by summing the “parquet” Feynman diagrams, which include both ladder and ring diagrams systematically, plus a set of important nonparquet diagrams, making this the most comprehensive diagram-based approach presently available. Our results suggest a radical suppression of the 3P2–3F2 triplet pairing gap and an enhancement of 3P0 pairing.

The quantification of pairing interaction in a two-neutron transfer through the intermediary continuum

An unbound intermediate system (A+1) with the presence of a resonance, can aid in the pairing enhancement in a two-neutron transfer reaction from a bound system A to another bound system (A+2). This enhancement is a consequence of the constructive interference via the several reaction channels available in the (A+1) system. We test this feature through our study in 6He, modeled as two neutrons in the orbitals of an intermediate 5He nucleus. Weighing up the natural case of an unbound 5He with a hypothetically bound 5He, we find that the inclusion of a properly modeled continuum favours the pairing correlations leading to enhanced two-neutron transfer cross-sections.

Unique miRNome and transcriptome profiles underlie microvascular heterogeneity in mouse kidney.

Endothelial cells in blood vessels in the kidney exert different functions depending on the (micro)vascular bed they are located in. The present study aimed to investigate microRNA and mRNA transcription patterns that underlie these differences. We zoomed in on microvascular compartments in the mouse renal cortex by laser microdissecting the microvessels prior to small RNA- and RNA-sequencing analyses. By these means, we characterized microRNA and mRNA transcription profiles of arterioles, glomeruli, peritubular capillaries, and postcapillary venules. Quantitative RT-PCR, in situ hybridization, and immunohistochemistry were used to validate sequencing results. Unique microRNA and mRNA transcription profiles were found in all microvascular compartments, with dedicated marker microRNAs and mRNAs showing enriched transcription in a single microvascular compartment. In situ hybridization validated the localization of microRNAs mmu-miR-140-3p in arterioles, mmu-miR-322-3p in glomeruli, and mmu-miR-451a in postcapillary venules. Immunohistochemical staining showed that von Willebrand factor protein was mainly expressed in arterioles and postcapillary venules, whereas GABRB1 expression was enriched in glomeruli, and IGF1 was enriched in postcapillary venules. More than 550 compartment-specific microRNA-mRNA interaction pairs were identified that carry functional implications for microvascular behavior. In conclusion, our study identified unique microRNA and mRNA transcription patterns in microvascular compartments of the mouse kidney cortex that underlie microvascular heterogeneity. These patterns provide important molecular information for future studies into differential microvascular engagement in health and disease.NEW & NOTEWORTHY Renal endothelial cells display a high level of heterogeneity depending on the (micro)vascular bed they reside in. The molecular basis contributing to these differences is poorly understood yet of high importance to increase understanding of microvascular engagement in the kidney in health and disease. This report describes m(icro)RNA expression profiles of microvascular beds in the mouse renal cortex and uncovers microvascular compartment-specific m(icro)RNAs and miRNA-mRNA pairs, thereby revealing important molecular mechanisms underlying renal microvascular heterogeneity.

Pair interaction of localized topological structures in confined chiral media.

We study pairwise interactions between localized topological structures in chiral magnetic and cholesteric liquid crystal (CLC) systems confined in the planar geometry. Our calculations for magnetics are based on the lattice model that takes into account the bulk and surface anisotropies along with the exchange and the Dzyaloshinskii-Moriya interactions. In CLC cells, these anisotropies describe the energy of interaction with an external magnetic or electric field and the anchoring energy assuming that the magnetic or electric anisotropy is negative and the boundary conditions are homeotropic. We have selected the region of the phase diagram, where various localized solitonlike structures, including skyrmion tubes, torons, and leeches, embedded in the ground state of the z-cone (conical phase) coexist, and carried out numerical analysis of the distance dependencies of the effective intersoliton interaction potentials. For skyrmions and torons, the potentials are found to be attractive in the large separation region. It turned out that for these potentials, the effects of axial asymmetry are negligible. By contrast, it turned out that for the intermediate structures between the skyrmions and torons known as the leeches, the leech-leech potentials generally depend on the orientation of the intersoliton separation vector and their large distance parts may become repulsive at certain directions of the vector. All the potentials have the short distance repulsive parts and the local minima located at the equilibrium separations. It is found that the skyrmion-skyrmion potential has an additional metastable configuration shifted towards the short-distance region.

Potential Key Proteins, Molecular Networks, and Pathways in Perinatal Hypoxia.

Perinatal hypoxia is a common risk factor for CNS development. Using bioinformatics databases, a list of 129 genes involved in perinatal hypoxia was selected from the literature and analyzed with respect to proteins important for biological processes influencing the brain development. Functional enrichment analysis using the DAVID database was performed to identify relevant Gene Ontology (GO) biological processes like response to hypoxia, inflammatory response, positive and negative regulation of apoptosis, and positive and negative regulation of cell proliferation. The selected GO processes contain 17-30 proteins and show an enrichment of 6.3-14.3-fold. The STRING protein-protein interaction network and the Cytoscape data analyzer were used to identify interacting proteins playing a significant role in these processes. The two top protein pairs referring to the proteins with highest degrees and the corresponding proteins connected by high score edges exert opposite or regulatory functions and are essential for the balance between damaging, repairing, protective, or epigenetic processes. The GO response to hypoxia is characterized by the high score protein-protein interaction pairs CASP3/FAS promoting apoptosis and by the protective acting BDNF/MECP2 protein pair. Core components of the GO processes positive and negative regulation of apoptosis are the proteins CASP3/FAS/AKT/eNOS/RPS6KB1 involved in several signal pathways. The GO processes cell proliferation are characterized by the high-score protein-protein interaction pairs MYC/ MAPK1, JUN/MAPK1, IL6/IL1B, and JUN/HDAC1. The study provides new insights into the pathophysiology of perinatal hypoxia and is of importance for future investigations, diagnostics, and therapy of perinatal hypoxia.

Density functional study of atomic arrangements in CrMnFeCoNi high-entropy alloy and their impact on vacancy formation energy and segregation

Using the density functional theory-coupled Monte Carlo approach, we explored the chemical short-range order (SRO) and element segregation in equimolar CrMnFeCoNi alloy. We found that state-of-the-art approximation of random element distribution is only applicable at > 1100 K close to the melting temperature, while the Cr-Cr repulsion driving the system stabilization and accompanying the formation of cubic Cr sublattice, and mild Ni-Ni attraction are the most prominent pair interactions at lower temperatures. Chemical potential and vacancy formation energy calculations indicate that Cr is most sensitive to the local chemical environment, making Cr atoms most stabilized when the preferred SRO is introduced. While the vacancy formation is predicted equally probable among five constituting elements in the random solid solution, Cr and Ni atoms show the lowest vacancy formation energies in the structure with SRO. Furthermore, distinct element segregation was predicted in the vicinity of planar defects, including symmetric tilt grain boundary and stacking fault, which we correlated to the site- and chemistry-dependent atomic volume and bond lengths. It suggests that the local mechanical strain and bond energy induce the SRO development and element segregation: Namely, the system takes advantage of segregation of Ni atoms having large atomic volume or Cr-Cr pairs having elongated bond lengths to fill in the excess volume at defects that relaxes the mechanical strain field and optimizes bond energy distribution. The correlation between the SRO and properties of CrMnFeCoNi alloy needs further investigations, which is expected to greatly help understand and control the properties of high-entropy alloys.

Identification of immune-related lncRNA in sepsis by construction of ceRNA network and integrating bioinformatic analysis.

Sepsis is a high mortality disease which seriously threatens human life and health, for which the pathogenetic mechanism still unclear. There is increasing evidence showed that immune and inflammation responses are key players in the development of sepsis pathology. LncRNAs, which act as ceRNAs, have critical roles in various diseases. However, the regulatory roles of ceRNA in the immunopathogenesis of sepsis have not yet been elucidated. In this study, we aimed to identify immune biomarkers associated with sepsis. We first generated a global immune-associated ceRNA (IMCE) network based on data describing interactions pairs of gene-miRNA and miRNA-lncRNA. Afterward, we excavated a dysregulated sepsis immune-associated ceRNA (SPIMC) network from the global IMCE network by means of a multi-step computational approach. Functional enrichment indicated that lncRNAs in SPIMC network have pivotal roles in the immune mechanism underlying sepsis. Subsequently, we identified module and hub genes (CD4 and STAT4) via construction of a sepsis immune-related PPI network. Then, we identified hub genes based on the modular structure of PPI network and generated a ceRNA subnetwork to analyze key lncRNAs associated with sepsis. Finally, 6 lncRNAs (LINC00265, LINC00893, NDUFA6-AS1, NOP14-AS1, PRKCQ-AS1 and ZNF674-AS1) that identified as immune biomarkers of sepsis. Moreover, the CIBERSORT algorithm and the infiltration of circulating immune cells types were performed to identify the inflammatory state of sepsis. Correlation analyses between immune cells and sepsis immune biomarkers showed that the LINC00265 was strongly positive correlated with the macrophages M2 (r = 0.77). Collectively, these results may suggest that these lncRNAs (LINC00265, LINC00893, NDUFA6-AS1, NOP14-AS1, PRKCQ-AS1 and ZNF674-AS1) played important roles in the immune pathogenesis of sepsis and provide potential therapeutic targets for further researches on immune therapy treatment in patients with sepsis.

Temperature, strain rate, and point vacancy dependent anisotropic mechanical behaviors of titanium carbide (Ti3C2) MXene: A molecular dynamics study

MXenes, one of the recognizable examples of modern 2D materials, are sparking tremendous research interest because of their distinctive structural, electrical, and electrochemical properties. This study utilized classical molecular dynamics simulation to investigate temperature, strain rate, and point vacancy-dependent mechanical behaviors for both armchair and zigzag orientations of the Ti3C2 MXene using Tersoff style bond order potential. The elastic modulus of ∼155.76 GPa and fracture strain of ∼0.263 were obtained along the zigzag direction at 300 K temperature, 5.58 % and 28.29 % greater than those obtained along the armchair alignment. However, a superior tensile strength of ∼34.08 GPa was observed along the armchair orientation as opposed to ∼29.08 GPa in the zigzag direction at 300 K temperature. As the temperature rises, it was observed that fracture strength and strain both exhibit a decreasing tendency, whereas increments in strain rates cause an increasing trend. However, we observed that temperature and strain rates barely affect the elastic modulus, which agrees with the literature data. Radial distribution functions were calculated for all pair interactions to make the temperature effect more comprehensible. It was demonstrated that C, Ti, and random point vacancies have significant adverse effects on elastic modulus, fracture strength, and failure strain because of their powerful symmetry-breaking effect. With increasing concentrations of any point vacancies, rapidly declining elastic modulus, fracture strength, and failure strain were perceived. Titanium vacancies were observed to have a more significant influence on mechanical behavior, even though carbon vacancies were more likely to develop with less formation energy. The outcomes of this work deliver a clear overview of the mechanical behavior of Ti3C2 in various aspects of the environment and will shed light on the potential implementation in electrochemical sensing or energy devices.

Analysing Pine Disease Spread Using Random Point Process by Remote Sensing of a Forest Stand

The application of a process model to investigate pine tree infestation caused by bark beetles is discussed. The analysis of this disease was carried out using spatial and spatio−temporal models of random point patterns. Spatial point patterns were constructed for remote sensing images of pine trees damaged by the apical bark beetle. The method of random point processes was used for their analysis. A number of known models of point pattern processes with pairwise interaction were fitted to actual data. The best model to describe the real data was chosen using the Akaike information index. The residual K−function was used to check the fit of the model to the real data. According to values of the Akaike information criterion and the residual K−function, two models were found to correspond best to the investigated data. These are the generalized Geyer model of the point process of saturation and the pair interaction process with the piecewise constant potential of a pair of points. For the first time, a spatio−temporal model of the contagious process was used for analysis of tree damage.

Effect of substrate roughness on dynamics of wetting and decay of an ultrathin liquid film

In this study, we analyze the dynamics of wetting and decay of an ultrathin liquid film on a rough substrate. The dependence of disjoining pressure on liquid film thickness is derived by the direct numerical calculation for the Lennard-Jones pair interaction potential and 3D rough substrate with a random relief. It is shown that disjoining pressure for a rough substrate can be approximated by a similar function for a smooth one with highly fluctuating parameters over the substrate surface. The equation describing wetting and decay of 3D liquid film is modified, accounting for the calculated coordinate dependence of disjoining pressure the general form of capillary pressure depending on substrate relief. The approach is used for the simulation of drop formation from a nanosized liquid film for substrates with various roughness parameters. It is demonstrated that substrate roughness is responsible for accelerated film rupture and formation of “detectable” drops, increase in their number density, and decrease in average size. At the later stage, liquid film transformation is described by the power-law dependences of number density, average height and size with the exponents depending on substrate roughness. The blocking point of the size distribution function shifts to a larger value for a substrate with a more fine-grained structure. These changes in the growth rate and size distribution function of drops are associated with the change in conditions of liquid flow, which becomes inhomogeneous due to substrate roughness.

Ambipolar Superconductivity with Strong Pairing Interaction in Monolayer 1T'-MoTe2.

Gate tunable two-dimensional (2D) superconductors offer significant advantages in studying superconducting phase transitions. Here, we address superconductivity in exfoliated 1T'-MoTe2 monolayers with an intrinsic band gap of ∼7.3 meV using field effect doping. Despite large differences in the dispersion of the conduction and valence bands, superconductivity can be achieved easily for both electrons and holes. The onset of superconductivity occurs near 7-8 K for both charge carrier types. This temperature is much higher than that in bulk samples. Also the in-plane upper critical field is strongly enhanced and exceeds the BCS Pauli limit in both cases. Gap information is extracted using point-contact spectroscopy. The gap ratio exceeds multiple times the value expected for BCS weak-coupling. All of these observations suggest a strong enhancement of the pairing interaction.

Identification of novel immune-related biomarker and therapeutic drugs in Parkinson disease via integrated bioinformatics analysis.

The present study was designed to identify immune-related biomarker and candidate drugs for Parkinson disease (PD) by weighted gene co-expression network analysis. Differentially expressed genes were identified in PD and healthy samples in the Gene Expression Omnibus (GEO) database. Besides, immune-related genes were obtained from the immunology database. Then, a co-expression network was constructed by the weighted gene co-expression network analysis package. Diagnostic model for PD was constructed by Lasso and multivariate Cox regression. Furthermore, differentially expressed genes (DEGs) were used to establish PPI and competing endogenous RNA (ceRNA) networks. Functional enrichment and pathway analysis were performed. Drug-hub gene interaction analysis was performed via DGIdb database. PD samples and normal samples were found to have 220 upregulated genes and 216 downregulated genes in the GSE6613 dataset. The differentially expressed genes contained 50 immune-related genes, with 40 upregulated genes and 10 downregulated genes. We obtained 7 hub genes by intersecting the DEGs and candidate hub genes. As potential diagnostic markers, 2 immune-related DEGs were identified among the 7 hub genes. According to functional enrichment analysis, these DEGs were mainly enriched in immune response, inflammatory response, and cytokine-cytokine receptor interactions. Totally, we obtained 182 drug-gene interaction pairs in Drug-Gene Interaction database (DGIdb). Our results revealed crucial genes and candidate drugs for PD patients and deepen our understanding of the molecular mechanisms involved in PD.