High Degree Of Connectivity Research Articles

Analysis of crises in related economies on the example of Latin American countries

This article provides an analysis of the key macroeconomic and financial indicators of Latin American countries in 2020–2022. The objective is to periodize the behavior of economic indicators in the connected economies of developing countries. The relevance of the study lies in the need to understand the mechanisms of behavior of economic entities in crisis situations. Latin American countries were chosen as a model for the study because they are characterized by a high degree of connectivity, as they all fall into the category of developing countries and differ significantly in the behavior of regulators in crisis conditions. Based on the objective, the analyzed period for the region under consideration was conditionally divided into four stages: the initial panic of 2020, the period of the beginning of recovery at the end of 2020, the recovery of economies against the background of rising inflation in 2021, and a decrease in recovery growth due to instability in 2022. The methodology shows general trends and characteristic deviations caused by general and specific factors. General trends describe the behavior of economic indicators in the selected four stages of the crisis. The deviations show how related economies react to general external shocks in specific conditions. For example, the size of the economy and domestic economic policy have shown themselves as specific factors. The results show that Brazil’s larger economy was more affected by the inflationary shock and took tougher measures with regard to the central bank rate. Throughout the crisis and the subsequent period, Mexico demonstrated a lower unemployment rate and a lower level of government budget losses.

Comparative analysis of changes in whey proteins of goat milk throughout the lactation cycle using quantitative proteomics.

The composition and content of goat milk proteins are affected by many factors and have been extensively studied. However, variation in whey protein composition in goat milk throughout the lactation cycle has not been clarified. In the current study, 15 dairy goats were selected, and milk samples were collected at 1, 3, 30, 90, 150, and 240 d after delivery. Whey proteins were separated and digested and then identified using data-independent acquisition (DIA) and data-dependent acquisition proteomics approaches. Protein profiles identified using DIA were consistent with those of the data-dependent acquisition proteomics approach according to clustering and principal component analyses. Significant differences in the abundance of 238 proteins around the lactation cycle were identified using the DIA approach. Developmental changes of the whey proteome corresponding to lactation stage were revealed: plasminogen, α-2-macroglobulin, and fibronectin levels decreased from d 1 to 240, whereas polymeric immunoglobulin receptor, nucleobindin 2, fatty acid-binding protein 3, and lactoperoxidase increased from d 1 to 240. Protein-protein interaction analysis showed that fibronectin with a higher degree of connectivity is a central node. The findings are of great significance to better understanding the potential role of specific proteins and the mechanism of protein biosynthesis or intercellular transport in the mammary glands related to the physiological changes of dairy goats.

Weighted gene correlation network analysis identifies the critical long non-coding RNAs participate in the progression of osteosarcoma.

This study aimed to identify more biomarkers associated with osteosarcoma progression via lncRNA-mRNA co-expression network. Dataset GSE99671 was downloaded from GEO database. The mRNAs and lncRNAs that were differentially expressed between tumor and normal samples were screened out. Functional enrichment analysis of differentially expressed mRNAs was carried out, followed by weighted gene correlation network analysis (WGCNA). Based on the lncRNAs and mRNAs, a lncRNA-mRNA co-expression network was constructed. Total 703 mRNAs and 7 lncRNAs were differentially expressed between tumor and normal tissues. The mRNAs were significantly enriched in functions associated with inflammatory response as well as autoimmune thyroid disease and ribosome pathways. WGCNA revealed that ME2 module had a high correlation with tumor, and ST3GAL4, UCK2, PSAT1 etc. had higher connectivity degrees in this module. lncRNA-mRNA co-expression network showed that 12 mRNAs, such as PEMT, COL10A1 and GSTA1, were synergistically expressed with lncRNA TTTY14. Inflammatory response and ribosome synthesis may play important role in osteosarcoma progression. lncRNA TTTY14 may affect the development of osteosarcoma by cooperative expression with PEMT, COL10A1, GSTA1, etc. ST3GAL4, UCK2, PSAT1 as well as TTTY14 may serve as key biomarkers in osteosarcoma.

Establishing connectivity patterns of eastern oysters (Crassostrea virginica) on regional oceanographic scales

AbstractLocalized depletion of marine and estuarine populations often results from large‐scale natural and anthropogenic disturbances (e.g., hurricanes, oil spills) as well as overharvest of fisheries resources. Understanding how such localized depletions may affect populations at larger regional scales requires knowledge of connectivity among local populations within the larger regional landscape or metapopulation. Efforts to restore populations following such decreases require similar knowledge. During the 2010 Deepwater Horizon oil spill, dramatic declines of oysters occurred throughout estuaries west and east of the Mississippi River. We examined trajectories of particles, which were parameterized to mimic oyster larvae, using the ADvanced CIRCulation (ADCIRC; https://adcirc.org) model to evaluate potential connectivity within and among embayments from Western Louisiana to Alabama. Patterns of larval settlement, which we defined as the intersection of a larval particle with known or expected oyster habitat at any point 13–21 days post‐release, reflected much greater local contributions, with 50%–90% of settled particles originating within the same subdivision of embayments. Exchange among subdivision was much less (0%–40%) and settlement originating from outside the embayment of release was trivial under most scenarios (0%–14%). Connectivity between adjacent basins was greatest for larvae released in the southern portions of the embayment, whereas connectivity among nonadjacent basins was not predicted under the scenarios modeled. Because most local populations are relatively isolated on ecological timescales, areas suffering from extensive local depletion are likely to require extensive time to recover due to the lack of larval subsidy from the overall regional population. Restoration would require building stepping‐stone populations or reefs within and among basin to restore a high degree of connectivity.

Characterization of Multilayer Coupling Based on Square Complementary Split Ring Resonator for Multiport Device Implementation.

The advent of context-aware environments and related applications demands a high degree of connectivity, with new spectral bands and related radio resource management functionalities in the current 5G bands and foreseen in future 6G wireless communication systems. This, in turn, poses new challenges in the implementation of wireless transceivers and radiating systems, in terms of device integration, miniaturization and element isolation, among others. High-performance miniature devices are presented and studied in this work, aided by metamaterial-inspired complementary resonators. A single particle is used to build a single layer, double layer, double frequency resonators and power dividers. A complete characterization of each equivalent circuit is also analyzed, showing great agreement between analytical circuit models and full-wave electromagnetic simulations. By adding more particles, different diplexers and triplexers in the multi-layer configuration are proposed. The flexibility in the design is the key advantage, as all devices are easily tunable and the output lines can be built in different layers, enabling frequency scalability from RF to millimeter wave ranges. Nevertheless, they are only a sample of all possible combinations of devices that can be designed for integration in future wireless communication systems.

Experimental and numerical study of self-locking adaptable inter connection for modular steel structures

Compared to conventional steel construction, modular steel construction (MSC) is different. Instead of having a high degree of connectivity, the modules are connected at their corners only by inter-modular connections (IMC), which are the most vulnerable points of failure and require extra operation spaces. An adaptable connection was proposed in this study, and the working mechanism of the proposed connection was presented. Three full-scale connections consisting of square hollow section (SHS) members were tested under monotonic and cyclic loads to determine the seismic performance. The results showed that reinforced joints sustained 80% of the limit of the rigid joint at an inter-story drift ratio of 0.04 radian and satisfied the condition for strong column weak beam joint mechanism. Non-linear Finite Element Analysis (FEA) was conducted on this adaptable connection with a parametric study to study more influences of other related parameters. The findings indicated that the gap produced between connection and column under higher displacement was sensitive to the outer bolt and spring pin. This gap could be further reduced by increasing the number of outer bolts and by reducing tolerance between adapter and column walls.

A general approach to smoothing nonlinear mixed traffic via control of autonomous vehicles

Stop-and-go waves are easily caused by unstable traffic due to the collective behavior of human drivers, resulting in higher vehicle fuel consumption and emissions. In this article, we develop a general approach to synthesizing feedback controllers of autonomous vehicles (AVs) for smoothing unstable nonlinear mixed traffic flow, consisting of AVs and human-driven vehicles (HVs). In the context of traffic smoothing and stabilization, prior studies have mainly focused on analyzing string stability of specific car-following models linearized at flow equilibrium points. By contrast, we are interested to analytically synthesize appropriate feedback controllers of AVs for smoothing nonlinear mixed traffic in its general functional forms, covering a broad class of deterministic car-following models commonly seen in the literature. Specifically, by leveraging feedback control theory AVs are controlled to operate in such a way that they closely track a virtual speed profile, i.e., a subtler version of the disturbance resulting from the immediate preceding vehicle. Thus, traffic waves are reduced when propagating backward across controlled AVs. Based on the general functional form of car-following dynamics, we derive a class of effective additive AV controllers that are proven to be able to ensure convergence in tracking desired speed profiles, leading to smoother traffic. In addition, a set of sufficient conditions is devised for guaranteeing car-following safety. More importantly, head-to-tail string stability of the mixed traffic is likely to be achieved with a sufficient market penetration rate (MPR) of AVs. Notably, unlike many existing studies the feedback controllers synthesized for AVs require only local traffic information without having to rely on high degrees of vehicle connectivity, and the rate of smoothing mixed traffic is readily tunable, which is useful for practical implementations. The proposed approach is further illustrated with a theoretical intelligent driver model (IDM) and commercially available adaptive cruise control (ACC) vehicles represented by a well calibrated IDM. Extensive numerical results are presented to show the effectiveness and robustness of the feedback controllers synthesized for AVs on smoothing nonlinear mixed traffic.

Gene expression profile analysis to discover molecular signatures for early diagnosis and therapies of triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is one of the most lethal subtypes of breast cancer (BC), and it accounts for approximately 10%-20% of all invasive BCs diagnosed worldwide. The survival rate of TNBC in stages III and IV is very low, and a large number of patients are diagnosed in these stages. Therefore, the purpose of this study was to identify TNBC-causing molecular signatures and anti-TNBC drug agents for early diagnosis and therapies. Five microarray datasets that contained 304 TNBC and 109 control samples were collected from the Gene Expression Omnibus (GEO) database, and RNA-Seq data with 116 tumor and 124 normal samples were collected from TCGA database to identify differentially expressed genes (DEGs) between TNBC and control samples. A total of 64 DEGs were identified, of which 29 were upregulated and 35 were downregulated, by using the statistical limma R-package. Among them, seven key genes (KGs) were commonly selected from microarray and RNA-Seq data based on the high degree of connectivity through PPI (protein-protein interaction) and module analysis. Out of these seven KGs, sixKGs (TOP2A, BIRC5, AURKB, ACTB, ASPM, and BUB1B) were upregulated and one (EGFR) was downregulated. We also investigated their differential expression patterns with different subtypes and progression stages of BC by the independent datasets of RNA-seq profiles from UALCAN database, which indicated that they may be potential biomarkers for early diagnosis. Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses with the proposed DEGs were performed using the online Enrichr database to investigate the pathogenetic processes of TNBC highlighting KGs. Then, we performed gene regulatory network analysis and identified three transcriptional (SOX2, E2F4, and KDM5B) and three post-transcriptional (hsa-mir-1-3p, hsa-mir-124-3p, and hsa-mir-34a-5p) regulators of KGs. Finally, we proposed five KG-guided repurposable drug molecules (imatinib, regorafenib, pazopanib, teniposide, and dexrazoxane) for TNBC through network pharmacology and molecular docking analyses. These drug molecules also showed significant binding performance with some cancer-related PTM-sites (phosphorylation, succinylation, and ubiquitination) of top-ranked four key proteins (EGFR, AURKB, BIRC5, and TOP2A). Therefore, the findings of this computational study may play a vital role in early diagnosis and therapies against TNBC by wet-lab validation.

Integrative Analysis of Potential Biomarkers Involved in the Progression of Papillary Thyroid Cancer.

This study aims to explore key prognostic and diagnostic biomarkers involved in the pathogenesis of papillary thyroid cancer (PTC) which is one of the most common endocrine cancers and whose occurrence is rapidly increasing. Papillary thyroid cancer datasets containing normal and tumor samples were collected from Gene Expression Omnibus. Protein-protein interaction (PPI) network for common upregulated differentially expressed genes (DEGs) was constructed, and hub genes were studied. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis were performed to identify the vital biological behaviors and pathways involved in PTC. PPI network analysis demonstrated the interaction between 134 common upregulated DEGs, and top 15 pivotal genes with highest degree of connectivity were retrieved. Three of the hub genes (DPP4, ITGA2, FN1) were linked to the prognosis of PTC patients and considered clinically relevant core genes via survival analysis. We suggest that the identification of key genes associated with PTC development help us in understanding molecular mechanisms related to disease. These genes could also be considered the diagnostic biomarkers or as therapeutic targets in the future treatment for PTC.

Using the DEMATEL Method to Explore Influencing Factors for Video Communication and Visual Perceptions in Social Media

This study used expert interviews and the DEMATEL method to explore the influencing factors affecting the evaluation of the good and cognitive response of video communication and visual perception in social media and for the benefit of facilitation of the implementation in improving the overall video communication and visual quality in social media in the related fields of communication, advertising, and visual design. Correspondingly, it could provide educators and practitioners in the field with a foundation to maximize the effectiveness of allocating resources to these influencing factors. This study explored the influencing factors of video communication and visual perception in social media and evaluated the causality, relevance, and degree of materiality among different factors. The results of this study indicated that the six dimension factors, including like (X8), feeling satisfied (X9), feeling of attractiveness (X11), a good sense of shape contour (modeling) (X12), good visual characteristics (X13), and a good sense of color (X14), showed a high degree of connection (prominence) with other dimension factors. Improving the quality of these six factors could help solve the problem while promoting a good feeling about the other factors.

Transgenic Schwann cells overexpressing POU6F1 promote sciatic nerve regeneration within acellular nerve allografts

Objective. Acellular nerve allograft (ANA) is an effective surgical approach used to bridge the sciatic nerve gap. The molecular regulators of post-surgical recovery are not well-known. Here, we explored the effect of transgenic Schwann cells (SCs) overexpressing POU domain class 6, transcription factor 1 (POU6F1) on sciatic nerve regeneration within ANAs. We explored the functions of POU6F1 in nerve regeneration by using a cell model of H2O2-induced SCs injury and transplanting SCs overexpressing POU6F1 into ANA to repair sciatic nerve gaps. Approach. Using RNA-seq, Protein–Protein Interaction network analysis, gene ontology enrichment, and Kyoto Encyclopedia of Genes and Genomes pathway analysis, we identified a highly and differentially expressed transcription factor, POU6F1, following ANA treatment of sciatic nerve gap. Expressing a high degree of connectivity, POU6F1 was predicted to play a role in peripheral nervous system myelination. Main results. To test the role of POU6F1 in nerve regeneration after ANA, we infected SCs with adeno-associated virus—POU6F1, demonstrating that POU6F1 overexpression promotes proliferation, anti-apoptosis, and migration of SCs in vitro. We also found that POU6F1 significantly upregulated JNK1/2 and c-Jun phosphorylation and that selective JNK1/2 inhibition attenuated the effects of POU6F1 on proliferation, survival, migration, and JNK1/2 and c-Jun phosphorylation. The direct interaction of POU6F1 and activated JNK1/2 was subsequently confirmed by co-immunoprecipitation. In rat sciatic nerve injury model with a 10 mm gap, we confirmed the pattern of POU6F1 upregulation and co-localization with transplanted SCs. ANAs loaded with POU6F1-overexpressing SCs demonstrated the enhanced survival of transplanted SCs, axonal regeneration, myelination, and functional motor recovery compared to the ANA group loaded by SCs-only in line with in vitro findings. Significance. This study identifies POU6F1 as a novel regulator of post-injury sciatic nerve repair, acting through JNK/c-Jun signaling in SCs to optimize therapeutic outcomes in the ANA surgical approach.

Analysing grade retention beliefs within teachers’ psycho-pedagogic beliefs system

Teachers have a complex and multidimensional system of socially constructed beliefs that influence their professional practice. Based on self-reported beliefs of 449 Portuguese primary teachers we explored the connectivity between grade retention beliefs and other psycho-pedagogical beliefs using a structural equation model. We also studied the psychological centrality of grade retention beliefs using a latent profile analysis. The results indicated that teachers’ grade retention beliefs are maintained within their beliefs system with a high degree of connectivity and centrality, especially when shared by their community. These findings may have implications to the educational policies that aim to reduce retention rates.

Los invertebrados y la calidad del hábitat como indicadores de la condición biológica de la costa del Río de la Plata, Argentina

Estuaries are productive ecosystems that provide ecosystem goods and services, although human development causes stresses that deteriorate the quality of their waters. The Río de la Plata river presents geographic and socioeconomic relevance, besides areas of importance in the conservation of biodiversity. The objective of this study was to analyze some of the structural and functional characteristics of the meso and macroinvertebrate assemblage along 155 km of the freshwater intertidal zone, applying multivariate analysis and comparing the sampling sites subject to different types of anthropogenic disturbances. Fifty-eight taxa were identified whose total abundance ranged from 570 to 345000 individuals/m2. The highest values of richness, structural and functional diversity, and percentages of sensitive taxa were recorded in recreational areas that have vegetated coasts, a high degree of connectivity and a natural state of riparian habitats. The multivariate analysis organized the sampling sites along a turbidity-conductivity gradient and a eutrophication-contamination gradient. The cluster analysis revealed the following groups: 1) sites with little impact of protected and recreational areas, 2) sites with anthropogenic impact and domestic discharges, 3) sites highly impacted by industrial and sewage discharges, and 4) sites located close to the front of maximum turbidity. These results showed that the characteristics of the habitat and the water determine the assemblages of invertebrates. The structural and functional descriptors analyzed can act reliably in the evaluation of the ecological quality and the biotic integrity of the Argentinian intertidal sector of the river.

Brain-wide connectivity map of mouse thermosensory cortices.

In the thermal system, skin cooling is represented in the primary somatosensory cortex (S1) and the posterior insular cortex (pIC). Whether S1 and pIC are nodes in anatomically separate or overlapping thermal sensorimotor pathways is unclear, as the brain-wide connectivity of the thermal system has not been mapped. We address this using functionally targeted, dual injections of anterograde viruses or retrograde tracers into the forelimb representation of S1 (fS1) and pIC (fpIC). Our data show that inputs to fS1 and fpIC originate from separate neuronal populations, supporting the existence of parallel input pathways. Outputs from fS1 and fpIC are more widespread than their inputs, sharing a number of cortical and subcortical targets. While, axonal projections were separable, they were more overlapping than the clusters of input cells. In both fS1 and fpIC circuits, there was a high degree of reciprocal connectivity with thalamic and cortical regions, but unidirectional output to the midbrain and hindbrain. Notably, fpIC showed connectivity with regions associated with thermal processing. Together, these data indicate that cutaneous thermal information is routed to the cortex via parallel circuits and is forwarded to overlapping downstream regions for the binding of somatosensory percepts and integration with ongoing behavior.

Construction of novel lncRNA-miRNA-mRNA ceRNA networks associated with prognosis of hepatitis C virus related hepatocellular carcinoma

BackgroundHepatitis C virus (HCV) infection contribute to liver fibrosis and cirrhosis, which significantly increases the risk of hepatocellular carcinoma (HCC) development. Previous studies have demonstrated the pivotal role of competitive endogenous RNA (ceRNA) networks in tumorigenesis and cancer progression. Consequently, we herein seek to identify and evaluate the prognostic relevance of a novel ceRNA network associated with HCV-related HCC. MethodsDifferentially expressed genes (DEGs) in GSE140846 dataset from GEO were identified using Network Analyst, and GO, KEGG and Reactome analyses were performed. Furthermore, a protein-protein interaction network was generated, and hub genes were detected. Hub gene expression levels, as well as those of their upstream lncRNAs and miRNAs and associated survival analyses were conducted using appropriate bioinformatics databases. Predicted target relationships were used to establish putative ceRNA networks for HCV-related HCC. ResultsA total of 372 and 360 up- and down-regulated DE-mRNA were identified, which were associated with nuclear division, cell cycle, and ATPase activity. A PPI network containing 704 DE-mRNAs was constructed, and the 6 hub gene with the highest degree of connectivity were selected for subsequent analysis. We discovered that 22 miRNAs and 4 lncRNAs upstream of 11 hub gene were significantly associated with poor prognosis of HCV-related HCC, and used them to constructe a prognostic ceRNA network. Further experiments confirmed the ceRNA-regulatory relationship of BUB1-hsa-miR-193a-3p-MALAT1. ConclusionThis study provides novel insights into the lncRNA-miRNA-mRNA ceRNA network, and reveals potential lncRNA biomarkers in HCV related HCC.

ANALYSIS OF THE CORRELATIONAL RELATIONSHIP BETWEEN THE RESULTS OF ULTRASOUND ELASTOGRAPHY AND THE VALUES OF THE MEASURED DIFFUSION COEFFICIENT IN ASSESSING UTERINE AND ADNEXAL STRUCTURES IN REPRODUCTIVE AGE WOMEN

The purpose of the study. To study the correlational relationship between the results obtained by examining the uterus and ovaries in healthy women of reproductive age using shear wave ultrasound elastography with elastometry and magnetic resonance imaging (MRI) and assessment of the measured diffusion coefficient (MDC) of diffusion-weighted images (DWI). Materials and methods. The study group consisted of 45 healthy women of reproductive age (the average age was 32.9±3.1 years). All of them underwent ultrasound examination with the technology of two-dimensional shear wave elastography with elastometry (Aixplorer, Supersonic Imagine, France) according to the method developed and implemented by us. The MRI of uterine and ovarian structures was performed using the DWI protocol (Excelart Vantage Atlas magnetic resonance tomograph, Toshiba, Japan, 1.5 T), the myometrium and the uterine mucosa in the body and cervix, ovaries were evaluated. In the automatic mode, the MDC of unaltered structures in the uterine body and cervix and their appendages was calculated in the area of interest on ADC-maps. The degree of correlational relationship between the results of ultrasound elastography with elastometry and magnetic resonance tomography with an estimate of the measured diffusion coefficient was calculated. Results. Correlation analysis of the relationship between rigidity and the MDC of uterine and adnexal structures showed a direct inverse relationship between these values and a high degree of connection by Cheddock scale (p = 0.000000). At this, lesser MDC values (mm2 /s) of similar structures of the organs under study corresponded to large quantitative values of the Young's elasticity modulus (kPa) of all uterine and ovarian structures. Conclusion. The obtained data make it possible to optimize the diagnostic algorithm and to supplement the standard protocols for ultrasound and magnetic resonance imaging studies of gynecological organs using two-dimensional shear wave elastography with elastometry and magnetic resonance tomography with an assessment of the measured diffusion coefficient of diffusion-weighted images.

Expression and clinical significance of RAG1 in myelodysplastic syndromes

Objective To determine the expression level of RAG1 and its clinical significance in myelodysplastic syndromes (MDS). Methods To explore the candidate genes, the microarray datasets GSE19429, GSE58831, and GSE2779 were downloaded from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) in MDS were screened using RStudio, and overlapped DEGs were obtained with Venn Diagrams. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses, and protein–protein interaction network were performed. Quantitative real-time PCR (qRT-PCR) was employed to confirm the microarray results. Results This study identified 26 DEGs. Functional enrichment analyses indicated that these DEGs were significantly enriched in the immune response, and hematopoietic cell lineage. Eight core genes, for example, RAG1 and PAX5, were identified with a high degree of connectivity. The result of qRT-PCR showed that RAG1 was significantly down-regulated in MDS patients, which helped in distinguishing MDS patients from normal controls. The area under the curve of the receiver operator characteristic was 0.913 (P < 0.0001). MDS patients with low RAG1 expression level had a poor long-term survival (P = 0.031). What's more, the expression of RAG1 was significantly increased in the patients who received treatment. Conclusion The results showed that the expression of RAG1 was down-regulated in MDS patients. Lower RAG1 expression was associated with adverse clinical outcomes. RAG1 may be a potential prognostic biomarker for MDS.

Identification of core genes as potential biomarkers for predicting progression and prognosis in glioblastoma.

Background: Glioblastoma is a common malignant neuroepithelial neoplasm with poor clinical outcomes and limited treatment options. It is extremely important to search and confirm diverse hub genes that are effective in the advance and prediction of glioblastoma. Methods: We analyzed GSE50161, GSE4290, and GSE68848, the three microarray datasets retrieved from the GEO database. GO function and KEGG pathway enrichment analyses for differentially expressed genes (DEGs) were performed using DAVID. The PPI network of the DEGs was analyzed using the Search Tool for the Retrieval of Interacting Genes database and visualized by Cytoscape software. Hub genes were identified through the PPI network and a robust rank aggregation method. The Cancer Genome Atlas (TCGA) and the Oncomine database were used to validate the hub genes. In addition, a survival curve analysis was conducted to verify the correlation between the expression of hub genes and patient prognosis. Human glioblastoma cells and normal cells were collected, and then RT-PCR, Western blot, and immunofluorescence were conducted to validate the expression of the NDC80 gene. A cell proliferation assay was used to detect the proliferation of glioma cells. The effects of NDC80 expression on migration and invasion of GBM cell lines were evaluated by conducting scratch and transwell assays. Results: A total of 716 DEGs were common to all three microarray datasets, which included 188 upregulated DEGs and 528 downregulated DEGs. Furthermore, we found that among the common DEGs, 10 hub genes showed a high degree of connectivity. The expression of the 10 hub genes in TCGA and the Oncomine database was significantly overexpressed in glioblastoma compared with normal genes. Additionally, the survival analysis showed that the patients with low expression of six genes (BIR5C, CDC20, NDC80, CDK1, TOP2A, and MELK) had a significantly favorable prognosis (p < 0.01). We discovered that NDC80, which has been shown to be important in other cancers, also has an important role in malignant gliomas. The RT-PCR, Western blot, and immunofluorescence results showed that the expression level of NDC80 was significantly higher in human glioblastoma cells than in normal cells. Moreover, we identified that NDC80 increased the proliferation and invasion abilities of human glioblastoma cells. Conclusion: The six genes identified here may be utilized to form a panel of disease progression and predictive biomarkers of glioblastoma for clinical purposes. NDC80, one of the six genes, was discovered to have a potentially important role in GBM, a finding that needs to be further studied.

CASP9 As a Prognostic Biomarker and Promising Drug Target Plays a Pivotal Role in Inflammatory Breast Cancer.

Background Inflammatory breast cancer (IBC) is one of the most rare and aggressive subtypes of primary breast cancer (BC). Our study aimed to explore hub genes related to the pathogenesis of IBC, which could be considered as novel molecular biomarkers for IBC diagnosis and prognosis. Material and Methods. Two datasets from gene expression omnibus database (GEO) were selected. Enrichment analysis and protein-protein interaction (PPI) network for the DEGs were performed. We analyzed the prognostic values of hub genes in the Kaplan-Meier Plotter. Connectivity Map (CMap) and Comparative Toxicogenomics Database (CTD) was used to find candidate small molecules capable to reverse the gene status of IBC. Results 157 DEGs were selected in total. We constructed the PPI network with 154 nodes interconnected by 128 interactions. The KEGG pathway analysis indicated that the DEGs were enriched in apoptosis, pathways in cancer and insulin signaling pathway. PTEN, PSMF1, PSMC6, AURKB, FZR1, CASP9, CASP6, CASP8, BAD, AKR7A2, ZNF24, SSX2IP, SIGLEC1, MS4A4A, and VSIG4 were selected as hub genes based on the high degree of connectivity. Six hub genes (PSMC6, AURKB, CASP9, BAD, ZNF24, and SSX2IP) that were significantly associated with the prognosis of breast cancer. The expression of CASP9 protein was associated with prognosis and immune cells infiltration of breast cancer. CASP9- naringenin (NGE) is expected to be the most promising candidate gene-compound interaction for the treatment of IBC. Conclusion Taken together, CASP9 can be used as a prognostic biomarker and a novel therapeutic target in IBC.

Resilient control of double-integrator stochastic multi-agent systems under denial-of-service attacks

The resilient control problem of double-integrator stochastic multi-agent systems under denial-of-service (DoS) attack is studied in this paper. We neutralize the effects of DoS attacks by introducing a hidden layer that has no physical significance. Compared with previous works, this method requires less computation, does not require a high degree of connectivity of communication topology, and does not need to know any information about attacks, such as attack frequency and attack duration. It is proved that the introduction of hidden layer will not affect the consensus of the original system and can improve its robustness. Besides, we also verify the effectiveness of event-triggered mechanism for systems with the hidden layer.