The Network Of Interlocking Directorates And Firm Performance In Transition Economies: Evidence From China

Using a Chinese sample containing 8727 firm-years over the period from 2005 to 2010, we investigate the economic effect of interlocking directorate networks, and find that firms with central position measured by network centrality in interlocking directorate networks earn superior one- to three-year ahead performance measured by return on assets (ROA) and return on Sales (ROS). We also show that the economic effect of interlocking directorate network is more pronounced in non-state-owned enterprises (NSOEs) compared to state-owned enterprises (SOEs). Our evidence is important, because it shows that to some extent the interlocking directorate network can serve as an solution to the institutional voids which are derived from the reform in Chinese translation economy

Regulation of rat intrapulmonary arterial tone by arachidonic acid and prostaglandin E2 during hypoxia

Aims Arachidonic acid (AA) and its metabolites, prostaglandins (PG) are known to be involved in regulation of vascular homeostasis including vascular tone and vessel wall tension, but their potential role in Hypoxic pulmonary vasoconstriction (HPV) remains unclear. In this study, we examined the effects of AA and PGE2 on the hypoxic response in isolated rat intrapulmonary arteries (IPAs). Methods and Results We carried out the investigation on IPAs by vessel tension measurement. Isotetrandrine (20 µM) significantly inhibited phase I, phase IIb and phase IIc of hypoxic vasoconstriction. Both indomethacin (100 µM) and NS398 attenuated KPSS-induced vessel contraction and phase I, phase IIb and phase IIc of HPV, implying that COX-2 plays a primary role in the hypoxic response of rat IPAs. PGE2 alone caused a significant vasoconstriction in isolated rat IPAs. This constriction is mediated by EP4. Blockage of EP4 by L-161982 (1 µM) significantly inhibited phase I, phase IIb and phase IIc of hypoxic vasoconstriction. However, AH6809 (3 µM), an antagonist of EP1, EP2, EP3 and DP1 receptors, exerted no effect on KPSS or hypoxia induced vessel contraction. Increase of cellular cAMP by forskolin could significantly reduce KPSS-induced vessel contraction and abolish phase I, phase II b and phase II c of HPV. Conclusion Our results demonstrated a vasoconstrictive effect of PGE2 on rat IPAs and this effect is via activation of EP4. Furthermore, our results suggest that intracellular cAMP plays dual roles in regulation of vascular tone, depending on the spatial distribution of cAMP and its coupling with EP receptor and Ca2+ channels

Phase transitions of a double occupancy lattice gas

This article offers a detailed analysis of interacting particles in the two-dimensional square array, which is a coarse-graining model to study the multiple occupancy lattice gas system. The equilibrium properties with the maximum loading number 2 is obtained in this work. We find the large nearest neighbor interaction leads to the steeper isotherms and the large on-site interaction leads to the plateaus isotherms. The phase transitions are discussed, and the phase diagrams are obtained via the Monte Carlo simulations. By analyzing finite size effect and the hysteresis behavior, the phase boundaries and the tricritical points are located in the phase diagrams. Our results reveal the complex equilibrium phase transitions in the double occupancy lattice gas

Non-equilibrium Phase Transitions in 2D Small-World Networks: Competing Dynamics

This article offers a detailed analysis of the Ising model in 2D small-world networks with competing Glauber and Kawasaki dynamics. The non-equilibrium stationary state phase transitions are obtained in these networks. The phase transitions are discussed, and the phase diagrams are obtained via Monte Carlo simulations and finite-size analyzing. We find that as the addition of links increases the phase transition temperature increases and the transition competing probability of tricritical point decreases. For the competition of the two dynamics, ferromagnetic to anti-ferromagnetic phase transitions and the critical endpoints are found in the small-world networks

Identifying metabolic dysfunction-associated steatotic liver disease in patients with hypertension and pre-hypertension: An interpretable machine learning approach

Objective Metabolic dysfunction-associated steatotic liver disease (MASLD) is one of the most prevalent liver diseases and is associated with pre-hypertension and hypertension. Our research aims to develop interpretable machine learning (ML) models to accurately identify MASLD in hypertensive and pre-hypertensive populations. Methods The dataset for 4722 hypertensive and pre-hypertensive patients is from subjects in the NAGALA study. Six ML models, including the decision tree, K-nearest neighbor, gradient boosting, naive Bayes, support vector machine, and random forest (RF) models, were used in this study. The optimal model was constructed according to the performances of models evaluated by K-fold cross-validation ( k  = 5), the area under the receiver operating characteristic curve (AUC), average precision (AP), accuracy, sensitivity, specificity, and F1. Shapley additive explanation (SHAP) values were employed for both global and local interpretation of the model results. Results The prevalence of MASLD in hypertensive and pre-hypertensive patients was 44.3% (362 cases) and 28.3% (1107 cases), respectively. The RF model outperformed the other five models with an AUC of 0.889, AP of 0.800, accuracy of 0.819, sensitivity of 0.816, specificity of 0.821, and F1 of 0.729. According to the SHAP analysis, the top five important features were alanine aminotransferase, body mass index, waist circumference, high-density lipoprotein cholesterol, and total cholesterol. Further analysis of the feature selection in the RF model revealed that incorporating all features leads to optimal model performance. Conclusions ML algorithms, especially RF algorithm, improve the accuracy of MASLD identification, and the global and local interpretation of the RF model results enables us to intuitively understand how various features affect the chances of MASLD in patients with hypertension and pre-hypertension

Identification of hub genes based on integrated analysis of single-cell and microarray transcriptome in patients with pulmonary arterial hypertension

Abstract Background Pulmonary arterial hypertension (PAH) is a devastating chronic cardiopulmonary disease without an effective therapeutic approach. The underlying molecular mechanism of PAH remains largely unexplored at single-cell resolution. Methods Single-cell RNA sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) database (GSE210248) was included and analyzed comprehensively. Additionally, microarray transcriptome data including 15 lung tissue from PAH patients and 11 normal samples (GSE113439) was also obtained. Seurat R package was applied to process scRNA-seq data. Uniform manifold approximation and projection (UMAP) was utilized for dimensionality reduction and cluster identification, and the SingleR package was performed for cell annotation. FindAllMarkers analysis and ClusterProfiler package were applied to identify differentially expressed genes (DEGs) for each cluster in GSE210248 and GSE113439, respectively. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) were used for functional enrichment analysis of DEGs. Microenvironment Cell Populations counter (MCP counter) was applied to evaluate the immune cell infiltration. STRING was used to construct a protein-protein interaction (PPI) network of DEGs, followed by hub genes selection through Cytoscape software and Veen Diagram. Results Nineteen thousand five hundred seventy-six cells from 3 donors and 21,896 cells from 3 PAH patients remained for subsequent analysis after filtration. A total of 42 cell clusters were identified through UMAP and annotated by the SingleR package. 10 cell clusters with the top 10 cell amounts were selected for consequent analysis. Compared with the control group, the proportion of adipocytes and fibroblasts was significantly reduced, while CD8+ T cells and macrophages were notably increased in the PAH group. MCP counter revealed decreased distribution of CD8+ T cells, cytotoxic lymphocytes, and NK cells, as well as increased infiltration of monocytic lineage in PAH lung samples. Among 997 DEGs in GSE113439, module 1 with 68 critical genes was screened out through the MCODE plug-in in Cytoscape software. The top 20 DEGs in each cluster of GSE210248 were filtered out by the Cytohubba plug-in using the MCC method. Eventually, WDR43 and GNL2 were found significantly increased in PAH and identified as the hub genes after overlapping these DEGs from GSE210248 and GSE113439. Conclusion WDR43 and GNL2 might provide novel insight into revealing the new molecular mechanisms and potential therapeutic targets for PAH

An Adaptive B-Spline Neural Network and Its Application in Terminal Sliding Mode Control for a Mobile Satcom Antenna Inertially Stabilized Platform

The mobile satcom antenna (MSA) enables a moving vehicle to communicate with a geostationary Earth orbit satellite. To realize continuous communication, the MSA should be aligned with the satellite in both sight and polarization all the time. Because of coupling effects, unknown disturbances, sensor noises and unmodeled dynamics existing in the system, the control system should have a strong adaptability. The significant features of terminal sliding mode control method are robustness and finite time convergence, but the robustness is related to the large switching control gain which is determined by uncertain issues and can lead to chattering phenomena. Neural networks can reduce the chattering and approximate nonlinear issues. In this work, a novel B-spline curve-based B-spline neural network (BSNN) is developed. The improved BSNN has the capability of shape changing and self-adaption. In addition, the output of the proposed BSNN is applied to approximate the nonlinear function in the system. The results of simulations and experiments are also compared with those of PID method, non-singularity fast terminal sliding mode (NFTSM) control and radial basis function (RBF) neural network-based NFTSM. It is shown that the proposed method has the best performance, with reliable control precision

Activation of Inward Rectifier K+ Channel 2.1 by PDGF-BB in Rat Vascular Smooth Muscle Cells through Protein Kinase A

Platelet-derived growth factor-BB (PDGF-BB) can induce the proliferation, migration, and phenotypic modulation of vascular smooth muscle cells (VSMCs). We used patch clamp methods to study the effects of PDGF-BB on inward rectifier K+ channel 2.1 (Kir2.1) channels in rat thoracic aorta VSMCs (RASMCs). PDGF-BB (25 ng/mL) increased Kir2.x currents (−11.81±2.47 pA/pF, P<0.05 vs. CON, n=10). Ba2+(50 μM) decreased Kir2.x currents (−2.13±0.23 pA/pF, P<0.05 vs. CON, n=10), which were promoted by PDGF-BB (−6.98±1.03 pA/pF). PDGF-BB specifically activates Kir2.1 but not Kir2.2 and Kir2.3 channels in HEK-293 cells. The PDGF-BB-induced stimulation of Kir2.1 currents was blocked by the PDGF-BB receptor β (PDGF-BBRβ) inhibitor AG1295 and was not affected by the PDGF-BBRα inhibitor AG1296. The PDGF-BB-induced stimulation of Kir2.1 currents was blocked by the protein kinase A inhibitor Rp-8-CPT-cAMPs; however, the antagonist of protein kinase B (GSK690693) had marginal effects on current activity. The PDGF-BB-induced stimulation of Kir2.1 currents was enhanced by forskolin, an adenylyl cyclase (AC) activator, and was blocked by the AC inhibitor SQ22536. We conclude that PDGF-BB increases Kir2.1 currents via PDGF-BBRβ through activation of cAMP-PKA signaling in RASMCs