Track: Tracerouting in SDN networks with arbitrary network functions

The centralization of control plane in Software defined networking (SDN) creates a paramount challenge on troubleshooting the network as packets are ultimately forwarded by distributed data planes. Existing path tracing tools largely utilize packet tags to probe network paths among SDN-enabled switches. However, network functions (NFs) or middleboxes, whose presence is ubiquitous in today's networks, can drop packets or alter their tags - an action that can collapse the probing mechanism. In addition, sending probing packets through network functions could corrupt their internal states, risking of the correctness of servicing logic (e.g., incorrect load balancing decisions). In this paper, we present a novel troubleshooting tool, Track, for SDN-enabled network with arbitrary NFs. Track can discover the forwarding path including NFs taken by any packets, without changing the forwarding rules in switches and internal states of NFs. We have implemented Track on RYU controller. Our extensive experiment results show that Track can achieve 95.08% and 100% accuracy for discovering forwarding paths with and without NFs respectively, and can efficiently generate traces within 3 milliseconds per hop

Synthesis of Functionalized Gold Nanoparticles with Neutral, Cationic and Ionic Polymeric Ligands

Gold nanoparticles (GNPs) are playing a very important role in biological and biomedical areas in recent years. In this study, we synthesize the various types of GNPs with surface-modification ligands (such as citrate, polyphosphate (polyP), poly(ethylene glycol) (PEG), poly(acrylic acid) (PAAc), polyacrylamide (PAAm)). These particles will serve as a platform to understand the effects of particles on blood clotting kinetics. In the first part of this dissertation (chapter 1), comment applications, synthesize methods, and characterization and purification methods of GNPs were reviewed. Then in chapter 2, our studies of citrate GNPs synthesis and characterization were reported. During the particle synthesis, trisodium citrate acid was used as the reduction reagent to reduce the GNPs from chloroauric acid (HAuCl4) by the method of thermo heating. GNPs of different sizes were produced by changing the mole ratios of chloroauric acid and citrate acid. The effects of reaction temperature and pH on particles size and size distribution were studied and reported. The citrate GNPs were replaced by different polymeric ligands to study the effects of ligands on the clotting kinetics blood clotting test. In chapter 3, we use the sodium borohydride (NaBH4) as the reagent to reduce the gold nanoparticles from the chloroauric acid. Four kinds of modified polymeric ligands (polyp, PEG, PAAc, PAAm) were bound to the GNPs in water phase directly. The last part is the conclusion of this study. We proposed the possible directions for future works

Image_3_Focus on pattern recognition receptors to identify prognosis and immune microenvironment in colon cancer.tif

In 2011, J. Hoffman, and B. Beutler won the Nobel Prize of medicine for the fact that they discovered the pattern recognition receptors (PRRs) and meanwhile described their effect on cell activation from the innate and adaptive immune systems. There are more and more evidences that have proved the obvious effect of PRRs on tumorigenesis progression. Nevertheless, the overall impact of PRR genes on prognosis, tumor microenvironmental characteristics and treatment response in patients with colon adenocarcinoma (COAD) remains unclear. In this research, we systematically assessed 20 PRR genes and comprehensively identified the prognostic value and enrichment degree of PRRs. The unsupervised clustering approach was employed for dividing COAD into 4 PRR subtypes, namely cluster A, cluster B, cluster C and cluster D, which were significantly different in terms of the clinical features, the immune infiltrations, and the functions. Among them, cluster B has better immune activities and functions. Cox and LASSO regression analysis was further applied to identify a prognostic five-PRR-based risk signature. Such signature can well predict patients’ overall survival (OS), together with a good robustness. Confounding parameters were controlled, with results indicating the ability of risk score to independently predict COAD patients’ OS. Besides, a nomogram with a strong reliability was created for enhancing the viability exhibited by the risk score in clinical practice. Also, patients who were classified based on the risk score owned distinguishable immune status and tumor mutation status, response to immunotherapy, as well as sensitivity to chemotherapy. A low risk score, featuring increased tumor stemness index (TSI), human leukocyte antigen (HLA), immune checkpoints, and immune activation, demonstrated a superior immunotherapeutic response. According to the study results, the prognostic PRR-based risk signature could serve as a robust biomarker for predicting the clinical outcomes as well as evaluating therapeutic response for COAD patients.</p

Image_1_Focus on pattern recognition receptors to identify prognosis and immune microenvironment in colon cancer.tif

In 2011, J. Hoffman, and B. Beutler won the Nobel Prize of medicine for the fact that they discovered the pattern recognition receptors (PRRs) and meanwhile described their effect on cell activation from the innate and adaptive immune systems. There are more and more evidences that have proved the obvious effect of PRRs on tumorigenesis progression. Nevertheless, the overall impact of PRR genes on prognosis, tumor microenvironmental characteristics and treatment response in patients with colon adenocarcinoma (COAD) remains unclear. In this research, we systematically assessed 20 PRR genes and comprehensively identified the prognostic value and enrichment degree of PRRs. The unsupervised clustering approach was employed for dividing COAD into 4 PRR subtypes, namely cluster A, cluster B, cluster C and cluster D, which were significantly different in terms of the clinical features, the immune infiltrations, and the functions. Among them, cluster B has better immune activities and functions. Cox and LASSO regression analysis was further applied to identify a prognostic five-PRR-based risk signature. Such signature can well predict patients’ overall survival (OS), together with a good robustness. Confounding parameters were controlled, with results indicating the ability of risk score to independently predict COAD patients’ OS. Besides, a nomogram with a strong reliability was created for enhancing the viability exhibited by the risk score in clinical practice. Also, patients who were classified based on the risk score owned distinguishable immune status and tumor mutation status, response to immunotherapy, as well as sensitivity to chemotherapy. A low risk score, featuring increased tumor stemness index (TSI), human leukocyte antigen (HLA), immune checkpoints, and immune activation, demonstrated a superior immunotherapeutic response. According to the study results, the prognostic PRR-based risk signature could serve as a robust biomarker for predicting the clinical outcomes as well as evaluating therapeutic response for COAD patients.</p

Image_2_Focus on pattern recognition receptors to identify prognosis and immune microenvironment in colon cancer.tif

In 2011, J. Hoffman, and B. Beutler won the Nobel Prize of medicine for the fact that they discovered the pattern recognition receptors (PRRs) and meanwhile described their effect on cell activation from the innate and adaptive immune systems. There are more and more evidences that have proved the obvious effect of PRRs on tumorigenesis progression. Nevertheless, the overall impact of PRR genes on prognosis, tumor microenvironmental characteristics and treatment response in patients with colon adenocarcinoma (COAD) remains unclear. In this research, we systematically assessed 20 PRR genes and comprehensively identified the prognostic value and enrichment degree of PRRs. The unsupervised clustering approach was employed for dividing COAD into 4 PRR subtypes, namely cluster A, cluster B, cluster C and cluster D, which were significantly different in terms of the clinical features, the immune infiltrations, and the functions. Among them, cluster B has better immune activities and functions. Cox and LASSO regression analysis was further applied to identify a prognostic five-PRR-based risk signature. Such signature can well predict patients’ overall survival (OS), together with a good robustness. Confounding parameters were controlled, with results indicating the ability of risk score to independently predict COAD patients’ OS. Besides, a nomogram with a strong reliability was created for enhancing the viability exhibited by the risk score in clinical practice. Also, patients who were classified based on the risk score owned distinguishable immune status and tumor mutation status, response to immunotherapy, as well as sensitivity to chemotherapy. A low risk score, featuring increased tumor stemness index (TSI), human leukocyte antigen (HLA), immune checkpoints, and immune activation, demonstrated a superior immunotherapeutic response. According to the study results, the prognostic PRR-based risk signature could serve as a robust biomarker for predicting the clinical outcomes as well as evaluating therapeutic response for COAD patients.</p

sj-docx-1-sms-10.1177_20563051241229659 – Supplemental material for “It’s All About US vs THEM!”: Comparing Chinese Populist Discourses on Weibo and Twitter

Supplemental material, sj-docx-1-sms-10.1177_20563051241229659 for “It’s All About US vs THEM!”: Comparing Chinese Populist Discourses on Weibo and Twitter by Yuan Zhang and Ralph Schroeder in Social Media + Society</p

Targeting GPR133 <i>via</i> miR-106a-5p inhibits the proliferation, invasion, migration and epithelial-mesenchymal transition (EMT) of glioma cells

Background: Glioma is the most common malignant brain tumor. GPR133 is a key factor in the progression of glioma. However, the role of GPR133 in glioma invasion and EMT and the microRNAs (miRNAs) associated with this pathway are still poorly understood.Objective: This study aims to elucidate the biological function of miR-106a-5p and GPR133 in glioma as well as the molecular mechanism of their interaction.Methods: The mRNA expression of miR-106a-5p and GPR133 in glioma specimens and cells was analyzed by quantitative real-time polymerase chain reaction (qRT–PCR). The protein level of GPR133 and the levels of invasion- and EMT-related proteins were measured by western blotting. miR-106a-5p and GPR133 function in glioma cells was determined through cell counting kit-8 (CCK-8), transwell, wound healing, colony formation assays in vitro and xenograft assays in vivo. To determine the targeting relationship between miR-106a-5p and GPR133, a dual-luciferase reporter assay was conducted.Results: A marked reduction in miR-106a-5p expression was observed in glioma cells and specimens. Patients with high expression of miR-106a-5p had a good prognosis, while patients with high expression of GPR133 had a shorter OS. Additionally, overexpression of miR-106a-5p or downregulation of GPR133 inhibited the progression of glioma cells. Furthermore, miR-106a-5p negatively regulated GPR133 expression by binding to its 3′-UTR, and restrained the invasion, migration, proliferation and EMT of glioma cells by targeting GPR133.Conclusions: miR-106a-5p is a tumor suppressor that negatively regulates GPR133. The miR-106a-5p/GPR133 axis could potentially serve as a therapeutic target for glioma.</p

Latent Space Model for Higher-order Networks and Generalized Tensor Decomposition

We introduce a unified framework, formulated as general latent space models, to study complex higher-order network interactions among multiple entities. Our framework covers several popular models in recent network analysis literature, including mixture multi-layer latent space model and hypergraph latent space model. We formulate the relationship between the latent positions and the observed data via a generalized multilinear kernel as the link function. While our model enjoys decent generality, its maximum likelihood parameter estimation is also convenient via a generalized tensor decomposition procedure. We propose a novel algorithm using projected gradient descent on Grassmannians. We also develop original theoretical guarantees for our algorithm. First, we show its linear convergence under mild conditions. Second, we establish finite-sample statistical error rates of latent position estimation, determined by the signal strength, degrees of freedom and the smoothness of link function, for both general and specific latent space models. We demonstrate the effectiveness of our method on synthetic data. We also showcase the merit of our method on two real-world datasets that are conventionally described by different specific models in producing meaningful and interpretable parameter estimations and accurate link prediction.</p

Two Dimension DOA ESPRIT Algorithm Based on Parallel Coprime Arrays and Complementary Sequence in MIMO Communication System

In this paper, a novel two dimension (2-D) direction of arrival (DOA) estimation method based on complementary sequence and ESPRIT algorithm under parallel coprime Arrays is proposed for multiple input and multiple output (MIMO) system. Unlike the traditional method, the complementary sequence is used as the transmitted far-field signals. Due to the orthogonality of the complementary sequence, the DOA estimation performance can be improved. Based on the parallel coprime array, the novel ESPRIT algorithm can be used to acquire accurate DOA estimation by searching the coincide values from ambiguous estimation results. In addition, we give the experimental results and show that the proposed algorithms can obtain higher DOA estimation resolution and distinguish more targets.</div

Tafazzin (TAZ) promotes the tumorigenicity of cervical cancer cells and inhibits apoptosis

<div><p>Tafazzin (TAZ) is often aberrantly expressed in some cancers, including rectal cancer and thyroid neoplasms. However, the function of TAZ in cervical cancer cells remains unknown. This study aims to explore the expression and function of TAZ in cervical cancer cells. Here, we determined the expression of TAZ protein in normal cervical tissue (NC, n = 27), high-grade squamous intraepithelial lesions (HSIL, n = 26) and squamous cervical carcinoma (SCC, n = 41) by immunohistochemistry, the expression of TAZ protein gradually increased from NC to HSIL to SCC. TAZ was overexpressed or down-regulated in cervical cancer cells by stably transfecting a TAZ-expressing plasmid or a shRNA plasmid targeting TAZ. <i>In vitro</i>, the cell growth curves and MTT assays showed that TAZ may promote the growth and viability of cervical cancer cells. <i>In vivo</i>, xenografts experiment showed that TAZ may increase tumor-forming ability. The percentage of apoptosis cells analyzed by FACS and TUNEL assays consistently showed that TAZ inhibits apoptosis in cervical cancer cells. Furthermore, the Cleaved Caspase 9 and Cleaved Caspase 3 were down-regulated by TAZ in cervical cancer cells. Taken together, this study demonstrated that TAZ is overexpressed in cervical cancer and may promote tumorigenicity of cervical cancer cells and inhibit apoptosis.</p></div