Changes in Nitric Oxide Level and Thickness Index of Synovial Fluid in Osteoarthritis Patients following Intraarticular Injection of Sodium Hyaluronate

Purpose: To monitor the changes in nitric oxide levels and synovium thickness index in synovial fluid following intra-articular injection of sodium hyaluronate.Methods: One hundred patients diagnosed with osteoarthritis of the knee from April 2014 to January 2015 in The Third Hospital of Jinan, Jinan, Shandong, China were selected and categorized into three phases; namely, mild, moderate and severe. Patients received a 20 mL sodium hyaluronate injection into the articular cavity of the knee once per week for 15 weeks, with continuous observation. The Visual Analogue Scale (VAS) and Western Ontario and McMaster University Osteoarthritis Index (WOMAC) scores were recorded after five weeks. A total of 56 patients (78 knees) remaining in serious condition after 5 weeks were divided into mild, moderate, and severe groups and treated with sodium hyaluronate once a week. Internationally reorganized VAS and WOMAC scores were adopted as clinical observation indices to indicate the curative effect of sodium hyaluronate among the 56 patients after 15 weeks of treatment. The conditions of the patients in the two phases were compared.Results: After 5 weeks of treatment, treatment effective rate in the mild, moderate and severe groups was 72.92, 66.10 and 28.57 %, respectively, with an overall effective rate of 78 %. After 15 weeks of treatment, treatment effective rate in mild, moderate, and severe groups was 96.77, 95.45 and 66.67 %, respectively, with an overall effective rate of 67.95 %.Conclusions: Clinically curative effect of sodium hyaluronate is significant for mild and moderate phase patients after intra-articular injection of sodium hyaluronate, while the effect is insignificant in severe patients. Thus, sodium hyaluronate can effectively improve nitric oxide levels in synovial fluid, reduce synovium thickness, enhances articular cavity lubrication and effectively alleviates disease severity.Keywords: Osteoarthritis, Knee, Intra-articular injection, Sodium hyaluronate, Nitric oxide, Synovium thickness, WOMA

Gossip Consensus Algorithm Based on Time-Varying Influence Factors and Weakly Connected Graph for Opinion Evolution in Social Networks

We provide a new gossip algorithm to investigate the problem of opinion consensus with the time-varying influence factors and weakly connected graph among multiple agents. What is more, we discuss not only the effect of the time-varying factors and the randomized topological structure but also the spread of misinformation and communication constrains described by probabilistic quantized communication in the social network. Under the underlying weakly connected graph, we first denote that all opinion states converge to a stochastic consensus almost surely; that is, our algorithm indeed achieves the consensus with probability one. Furthermore, our results show that the mean of all the opinion states converges to the average of the initial states when time-varying influence factors satisfy some conditions. Finally, we give a result about the square mean error between the dynamic opinion states and the benchmark without quantized communication

Singlino-dominated dark matter in general NMSSM

The general Next-to-Minimal Supersymmetric Standard Model (NMSSM) describes the singlino-dominated dark-matter (DM) property by four independent parameters: singlet-doublet Higgs coupling coefficient $\lambda$, Higgsino mass $\mu_{tot}$, DM mass $m_{\tilde{\chi}_1^0}$, and singlet Higgs self-coupling coefficient $\kappa$. The first three parameters strongly influence the DM-nucleon scattering rate, while $\kappa$ usually affects the scattering only slightly. This characteristic implies that singlet-dominated particles may form a secluded DM sector. Under such a theoretical structure, the DM achieves the correct abundance by annihilating into a pair of singlet-dominated Higgs bosons by adjusting $\kappa$'s value. Its scattering with nucleons is suppressed when $\lambda v/\mu_{tot}$ is small. This speculation is verified by sophisticated scanning of the theory's parameter space with various experiment constraints considered. In addition, the Bayesian evidence of the general NMSSM and that of $Z_3$-NMSSM is computed. It is found that, at the cost of introducing one additional parameter, the former is approximately $3.3 \times 10^3$ times the latter. This result corresponds to Jeffrey's scale of 8.05 and implies that the considered experiments strongly prefer the general NMSSM to the $Z_3$-NMSSM.Comment: 29 pages, 9 figure

The CARMA1-Bcl10 Signaling Complex Selectively Regulates JNK2 Kinase in the T Cell Receptor-Signaling Pathway

SummaryMembers of the c-Jun NH2-terminal kinase (JNK) family play crucial roles in cell activation, differentiation, and apoptosis. Although many studies have indicated that JNK1 and JNK2 have functional differences and redundancy, the upstream signaling pathway that selectively activates JNK1 or JNK2 remains unknown. In this study, we have revealed a selective mechanism of JNK activation, in which JNK2, but not JNK1, was regulated by CARMA1, a scaffold molecule, after stimulation of the T cell receptor (TCR). This CARMA1-dependent regulation of JNK2 worked through the scaffold molecule Bcl10, which was inducibly associated with JNK2 and served as a JNK-interacting protein (JIP)-like scaffold to assemble the kinases JNK2, MKK7, and TAK1. Finally, we showed that CARMA1- and Bcl10-mediated JNK2 activation had a critical role in regulating the amount of c-Jun protein. Together, our studies provide genetic evidence that JNK1 and JNK2 are differentially regulated in the TCR-signaling pathway and play different functions

Novel Proteolytic Microvesicles Released from Human Macrophages after Exposure to Tobacco Smoke

Cigarette smoking damages the extracellular matrix in a variety of locations, leading to atherosclerotic plaque instability and emphysematous lung destruction, but the underlying mechanisms remain poorly understood. Here, we sought to determine whether exposure of human macrophages, a key participant in extracellular matrix damage, to tobacco smoke extract (TSE) induces the release of microvesicles (MVs; or microparticles) with proteolytic activity; the major proteases involved; and the cellular mechanisms that might mediate their generation. We found that MVs released from TSE-exposed macrophages carry substantial gelatinolytic and collagenolytic activities that surprisingly can be predominantly attributed to a single transmembrane protease of the matrix metalloproteinase (MMP) superfamily (namely, MMP14). Flow cytometric counts revealed that exposure of human macrophages to TSE for 20 hours more than quadrupled their production of MMP14-positive MVs (control, 1112 ± 231; TSE-induced, 5823 ± 2192 MMP14-positive MVs/μL of conditioned medium; means ± SEM; n = 6; P < 0.01). Our results indicate that the production of these MVs by human macrophages relies on a series of regulated steps that include activation of two mitogen-activated protein kinases (MAPKs, i.e., the Jun N-terminal kinase and p38 MAPK), and then MAPK-dependent induction and maturation of cellular MMP14, a remarkable accumulation of MMP14 into nascent plasma membrane blebs, and finally caspase- and MAPK-dependent apoptosis and apoptotic microvesicle generation. Proteolytically active MVs induced by tobacco smoke may be novel mediators of clinical important matrix destruction in smokers

Filtering in Stochastic Systems: Analysis for the case of continuous observations with memory of arbitrary multiplicity

We consider stochastic systems with continuous time over observations with memory in the presence of an anomalous noise. The paper is devoted to analysis of some properties of an optimal unbiased in mean-square sense filter. In the case of anomalous noises action in the observation channel with memory, we have proved insensitivity of the filter to inaccurate knowledge of the matrix of anomalous noise intensity and its equivalence to a truncated filter constructed only over non-anomalous components of an observation vector

Transcriptional landscape of myasthenia gravis revealed by weighted gene coexpression network analysis

Background: As one of the most common autoimmune diseases, myasthenia gravis (MG) severely affects the quality of life of patients. Therefore, exploring the role of dysregulated genes between MG and healthy controls in the diagnosis of MG is beneficial to reveal new and promising diagnostic biomarkers and clinical therapeutic targets.Methods: The GSE85452 dataset was downloaded from the Gene Expression Omnibus (GEO) database and differential gene expression analysis was performed on MG and healthy control samples to identify differentially expressed genes (DEGs). The functions and pathways involved in DEGs were also explored by functional enrichment analysis. Significantly associated modular genes were identified by weighted gene co-expression network analysis (WGCNA), and MG dysregulated gene co-expression modular-based diagnostic models were constructed by gene set variance analysis (GSVA) and least absolute shrinkage and selection operator (LASSO). In addition, the effect of model genes on tumor immune infiltrating cells was assessed by CIBERSORT. Finally, the upstream regulators of MG dysregulated gene co-expression module were obtained by Pivot analysis.Results: The green module with high diagnostic performance was identified by GSVA and WGCNA. The LASSO model obtained NAPB, C5orf25 and ERICH1 genes had excellent diagnostic performance for MG. Immune cell infiltration results showed a significant negative correlation between green module scores and infiltration abundance of Macrophages M2 cells.Conclusion: In this study, a diagnostic model based on the co-expression module of MG dysregulated genes was constructed, which has good diagnostic performance and contributes to the diagnosis of MG

An integrated software for virus community sequencing data analysis

BACKGROUND: A virus community is the spectrum of viral strains populating an infected host, which plays a key role in pathogenesis and therapy response in viral infectious diseases. However automatic and dedicated pipeline for interpreting virus community sequencing data has not been developed yet.RESULTS: We developed Quasispecies Analysis Package (QAP), an integrated software platform to address the problems associated with making biological interpretations from massive viral population sequencing data. QAP provides quantitative insight into virus ecology by first introducing the definition "virus OTU" and supports a wide range of viral community analyses and results visualizations. Various forms of QAP were developed in consideration of broader users, including a command line, a graphical user interface and a web server. Utilities of QAP were thoroughly evaluated with high-throughput sequencing data from hepatitis B virus, hepatitis C virus, influenza virus and human immunodeficiency virus, and the results showed highly accurate viral quasispecies characteristics related to biological phenotypes.CONCLUSIONS: QAP provides a complete solution for virus community high throughput sequencing data analysis, and it would facilitate the easy analysis of virus quasispecies in clinical applications.</p