Core Hub Research Articles

Identification of key genes in pathogenesis of placental insufficiency intrauterine growth restriction

BackgroundIntrauterine growth restriction (IUGR) is defined as a fetus that fails to achieve its genetically determined growth potential. The exact molecular mechanisms of placental insufficiency IUGR pathogenesis are a little known. Our goal was to identify key genes and gene co-expression modules related to placental insufficiency IUGR.MethodsWe used weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) network analysis to examine the IUGR dataset GSE114691 from NCBI Gene Expression Omnibus. Core modules and hub nodes of the protein-protein interaction network were identified. A gene network was constructed and genes were classified by WGCNA into different modules. The validation of potential key genes was carried out using additional datasets (GSE12216 and GSE24129).ResultsWe identified in GSE114691 539 down regulated genes and 751 up regulated genes in placental tissues characteristic of placental insufficiency IUGR compared with non-IUGR, and defined 76 genes as hub nodes in the protein-protein interaction network. Genes in the key modules of the WGCNA network were most closely associated with placental insufficiency IUGR and significantly enriched in biological process such as cellular metabolic process and macromolecule metabolic process. We identified as key genes TGFB1, LEP, ENG, ITGA5, STAT5A, LYN, GATA3, FPR1, TGFB2, CEBPB, KLF4, FLT1, and PNPLA2. The RNA expression levels of ENG and LEP, as biomarkers, were validated.ConclusionA holistic gene expression profile of placental insufficiency IUGR has been generated and the key genes ENG and LEP has potential to serve as circulating diagnosis biomarkers and therapeutic targets for placental insufficiency IUGR.

Identification and Validation of Pathogenic Genes in Sepsis and Associated Diseases by Integrated Bioinformatics Approach.

Sepsis is a clinical syndrome with high mortality and morbidity rates. In sepsis, the abrupt release of cytokines by the innate immune system may cause multiorgan failure, leading to septic shock and associated complications. In the presence of a number of systemic disorders, such as sepsis, infections, diabetes, and systemic lupus erythematosus (SLE), cardiorenal syndrome (CRS) type 5 is defined by concomitant cardiac and renal dysfunctions Thus, our study suggests that certain mRNAs and unexplored pathways may pave a way to unravel critical therapeutic targets in three debilitating and interrelated illnesses, namely, sepsis, SLE, and CRS. Sepsis, SLE, and CRS are closely interrelated complex diseases likely sharing an overlapping pathogenesis caused by erroneous gene network activities. We sought to identify the shared gene networks and the key genes for sepsis, SLE, and CRS by completing an integrative analysis. Initially, 868 DEGs were identified in 16 GSE datasets. Based on degree centrality, 27 hub genes were revealed. The gProfiler webtool was used to perform functional annotations and enriched molecular pathway analyses. Finally, core hub genes (EGR1, MMP9, and CD44) were validated using RT-PCR analysis. Our comprehensive multiplex network approach to hub gene discovery is effective, as evidenced by the findings. This work provides a novel research path for a new research direction in multi-omics biological data analysis.

Cultivated and wild pearl millet display contrasting patterns of abundance and co-occurrence in their root mycobiome

Fungal communities associated with roots play a key role in nutrient uptake and in mitigating the abiotic and biotic stress of their host. In this study, we characterized the roots mycobiome of wild and cultivated pearl millet [Pennisetum glaucum (L.) R. Br., synonym: Cenchrus americanus (L.) Morrone] in three agro-ecological areas of Senegal following a rainfall gradient. We hypothesized that wild pearl millet could serve as a reservoir of endophytes for cultivated pearl millet. We therefore analyzed the soil factors influencing fungal community structure and whether cultivated and wild millet shared the same fungal communities. The fungal communities associated with pearl millet were significantly structured according to sites and plant type (wild vs cultivated). Besides, soil pH and phosphorus were the main factors influencing the fungal community structure. We observed a higher fungal diversity in cultivated compared to wild pearl millet. Interestingly, we detected higher relative abundance of putative pathotrophs, especially plant pathogen, in cultivated than in wild millet in semi-arid and semi-humid zones, and higher relative abundance of saprotrophs in wild millet in arid and semi-humid zones. A network analysis based on taxa co-occurrence patterns in the core mycobiome revealed that cultivated millet and wild relatives had dissimilar groups of hub taxa. The identification of the core mycobiome and hub taxa of cultivated and wild pearl millet could be an important step in developing microbiome engineering approaches for more sustainable management practices in pearl millet agroecosystems.

Placental-Cadherin, a biomarker for local immune status and poor prognosis among patients with tongue squamous cell carcinoma.

The prognostic and clinicopathological value of placental-Cadherin (CDH3) in multiple cancers is controversial. The diagnostic significance and functional mechanism of CDH3 in tongue squamous cell carcinoma (TSCC) have not been thoroughly investigated. This study aims to clarify the potential of CDH3 as biomarker for TSCC. Here, meta-analysis, bioinformatics, along wet-lab techniques were employed to evaluate the diagnostic, as well as the prognostic value of CDH3 in diverse types of cancers, especially TSCC. Meta-analysis was used to determine the influence of CDH3 on prognostic and clinicopathological features in numerous cancers. Molecular biology function was used to investigate the role of CDH3 in TSCC cells. The relationship of CDH3 with tumor-infiltrating immune cells (TIICs) in TSCC was assessed using CIBERSORT. Moreover, gene set enrichment analysis (GSEA) was done based on TCGA. Besides, the hub genes and associated cascades were uncovered based on gene co-expression with CDH3. CDH3 upregulation correlated with worse overall survival and disease-free survival in various cancers. CDH3 was validated as an independent risk factor for HNSC and was linked to the onset of tumors, tumor stage, and infiltration depth. CDH3 silencing inhibited cell growth and induced apoptosis of the CAL-27 cell line. CDH3 expression level correlated with infiltration by macrophages, T cells, T cell regulatory cells (Tregs), and plasma cells in TSCC. GSEA revealed that CDH3 influences multiple cancer-associated cascades. Besides, CBX3, CCHCR1, along NFYC were identified as the core hub genes for CDH3. We identified CDH3 as a pan-cancer gene with potential prognostic and diagnostic significance in various cancers, particularly in TSCC, where it is tumorigenic.

Integrated bioinformatics analysis reveals dynamic candidate genes and signaling pathways involved in the progression and prognosis of diffuse large B-cell lymphoma.

BackgroundDiffuse large B-cell lymphoma (DLBCL) is a highly heterogeneous malignancy with varied outcomes. However, the fundamental mechanisms remain to be fully defined.AimWe aimed to identify core differentially co-expressed hub genes and perturbed pathways relevant to the pathogenesis and prognosis of DLBCL.MethodsWe retrieved the raw gene expression profile and clinical information of GSE12453 from the Gene Expression Omnibus (GEO) database. We used integrated bioinformatics analysis to identify differentially co-expressed genes. The CIBERSORT analysis was also applied to predict tumor-infiltrating immune cells (TIICs) in the GSE12453 dataset. We performed survival and ssGSEA (single-sample Gene Set Enrichment Analysis) (for TIICs) analyses and validated the hub genes using GEPIA2 and an independent GSE31312 dataset.ResultsWe identified 46 differentially co-expressed hub genes in the GSE12453 dataset. Gene expression levels and survival analysis found 15 differentially co-expressed core hub genes. The core genes prognostic values and expression levels were further validated in the GEPIA2 database and GSE31312 dataset to be reliable (p < 0.01). The core genes’ main KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichments were Ribosome and Coronavirus disease-COVID-19. High expressions of the 15 core hub genes had prognostic value in DLBCL. The core genes showed significant predictive accuracy in distinguishing DLBCL cases from non-tumor controls, with the area under the curve (AUC) ranging from 0.992 to 1.00. Finally, CIBERSORT analysis on GSE12453 revealed immune cells, including activated memory CD4+ T cells and M0, M1, and M2-macrophages as the infiltrates in the DLBCL microenvironment.ConclusionOur study found differentially co-expressed core hub genes and relevant pathways involved in ribosome and COVID-19 disease that may be potential targets for prognosis and novel therapeutic intervention in DLBCL.

Gout Is Not Just Arthritis: Abnormal Cortical Thickness and Structural Covariance Networks in Gout.

Background: Hyperuricemia is the cause of gout. The antioxidant and neuroprotective effects of uric acid seem to benefit some patients with central nervous system injury. However, changes in the brain structure have not been discovered in patients with gout.Object: Clarify the changes in cortical thickness in patients with gout and the alteration of the structural covariance networks (SCNs) based on cortical thickness.Methods: We collected structural MRIs of 23 male gout patients and 23 age-matched healthy controls. After calculating and comparing the difference in cortical thickness between the two groups, we constructed and analyzed the cortical thickness covariance networks of the two groups, and we investigated for any changes in SCNs of gout patients.Results: Gout patients have thicker cortices in the left postcentral, left supramarginal, right medial temporal, and right medial orbitofrontal regions; and thinner cortices were found in the left insula, left superior frontal, right pericalcarine, and right precentral regions. In SCN analysis, between-group differences in global network measures showed that gout patients have a higher global efficiency. In regional network measures, more nodes in gout patients have increased centrality. In network hub analysis, we found that the transfer of the core hub area, rather than the change in number, may be the characteristic of the gout's cortical thickness covariance network.Conclusion: This is the first study on changes in brain cortical thickness and SCN based on graph theory in patients with gout. The present study found that, compared with healthy controls, gout patients show regional cortical thinning or thickening, and variation in the properties of the cortical thickness covariance network also changed. These alterations may be the combined effect of disease damage and physiological compensation. More research is needed to fully understand the complex underlying mechanisms of gout brain variation.

EURECA-PRO: The European University on Responsible Consumption and Production

The European Commission (EC) called for proposals to form European University Alliances (EUA) in 2019 and 2020 to promote Europe’s universities competitiveness in the world and strengthen the European Higher Education Area (EHEA) and European Research Area (ERA). With the objective to create a global educational core hub on Sustainable Development Goal (SDG) 12 “responsible consumption and production”, a consortium of seven universities, led by Montanuniversität Leoben, received a three-year funding in 2020 for the development of a European University on REsponsible Consumption And PROduction (EURECA-PRO).

The Transcriptional Landscape and Hub Genes Associated with Physiological Responses to Drought Stress in Pinus tabuliformis.

Drought stress has an extensive impact on regulating various physiological, metabolic, and molecular responses. In the present study, the Pinus tabuliformis transcriptome was studied to evaluate the drought-responsive genes using RNA- Sequencing approache. The results depicted that photosynthetic rate and H2O conductance started to decline under drought but recovered 24 h after re-watering; however, the intercellular CO2 concentration (Ci) increased with the onset of drought. We identified 84 drought-responsive transcription factors, 62 protein kinases, 17 transcriptional regulators, and 10 network hub genes. Additionally, we observed the expression patterns of several important gene families, including 2192 genes positively expressed in all 48 samples, and 40 genes were commonly co-expressed in all drought and recovery stages compared with the control samples. The drought-responsive transcriptome was conserved mainly between P. tabuliformis and A. thaliana, as 70% (6163) genes had a homologous in arabidopsis, out of which 52% homologous (3178 genes corresponding to 2086 genes in Arabidopsis) were also drought response genes in arabidopsis. The collaborative network exhibited 10 core hub genes integrating with ABA-dependent and independent pathways closely conserved with the ABA signaling pathway in the transcription factors module. PtNCED3 from the ABA family genes had shown significantly different expression patterns under control, mild, prolonged drought, and recovery stages. We found the expression pattern was considerably increased with the prolonged drought condition. PtNCED3 highly expressed in all drought-tested samples; more interestingly, expression pattern was higher under mild and prolonged drought. PtNCED3 is reported as one of the important regulating enzymes in ABA synthesis. The continuous accumulation of ABA in leaves increased resistance against drought was due to accumulation of PtNCED3 under drought stress in the pine needles.

Elevated TYROBP expression predicts poor prognosis and high tumor immune infiltration in patients with low-grade glioma

BackgroundTyrosine protein tyrosine kinase binding protein (TYROBP) binds non-covalently to activated receptors on the surface of various immune cells, and mediates signal transduction and cellular activation. It is dysregulated in various malignancies, although little is known regarding its role in low-grade glioma. The aim of this study is to explore the clinicopathological significance, prognostic value and immune signature of TYROBP expression in low-grade glioma (LGG).MethodsThe differentially expressed genes (DEGs) between glioma samples and normal tissues were identified from two GEO microarray datasets using the limma package. The DEGs overlapping across both datasets were functionally annotated by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. STRING database was used to establish the protein-protein interaction (PPI) of the DEGs. The PPI network was visualized by Cytoscape and cytoHubba, and the core module and hub genes were identified. The expression profile of TYROBP and patient survival were validated in the Oncomine, GEPIA2 and CGGA databases. The correlation between TYROBP expression and the clinicopathologic characteristics were evaluated. Gene Set Enrichment Analysis (GSEA) and single-sample GSEA (ssGSEA) were performed by R based on the LGG data from TCGA. The TIMER2.0 database was used to determine the correlation between TYROBP expression and tumor immune infiltrating cells in the LGG patients. Univariate and multivariate Cox regression analyses were performed to determine the prognostic impact of clinicopathological factors via TCGA database.ResultsSixty-two overlapping DEGs were identified in the 2 datasets, and were mainly enriched in the response to wounding, focal adhesion, GTPase activity and Parkinson disease pathways. TYROBP was identified through the PPI network and cytoHubba. TYROBP expression levels were significantly higher in the LGG tissues compared to the normal tissues, and was associated with worse prognosis and poor clinicopathological parameters. In addition, GSEA showed that TYROBP was positively correlated to neutrophil chemotaxis, macrophage activation, chemokine signaling pathway, JAK-STAT signaling pathway, and negatively associated with gamma aminobutyric acid signaling pathway, neurotransmitter transport, neuroactive ligand receptor intersection etc. TIMER2.0 and ssGSEA showed that TYROBP expression was significantly associated with the infiltration of neutrophils, macrophages, myeloid dendritic cells and monocytes. The infiltration of the M2 phenotype macrophages, cancer-associated fibroblasts and myeloid dendritic cells correlated to worse prognosis in LGG patients. Finally, multivariate analysis showed that elevated TYROBP expression is an independent risk factor for LGG.ConclusionTYROBP is dysregulated in LGG and correlates with immune infiltration. It is a potential therapeutic target and prognostic marker for LGG.

Common abnormality of gray matter integrity in substance use disorder and obsessive-compulsive disorder: A comparative voxel-based meta-analysis.

The objective of the current study is to determine robust transdiagnostic brain structural markers for compulsivity by capitalizing on the increasing number of case‐control studies examining gray matter volume (GMV) alterations in substance use disorders (SUD) and obsessive‐compulsive disorder (OCD). Voxel‐based meta‐analysis within the individual disorders and conjunction analysis were employed to reveal common GMV alterations between SUDs and OCD. Meta‐analytic coordinates and signed brain volumetric maps determining directed (reduced/increased) GMV alterations between the disorder groups and controls served as the primary outcome. The separate meta‐analysis demonstrated that SUD and OCD patients exhibited widespread GMV reductions in frontocortical regions including prefrontal, cingulate, and insular. Conjunction analysis revealed that the left inferior frontal gyrus (IFG) consistently exhibited decreased GMV across all disorders. Functional characterization suggests that the IFG represents a core hub in the cognitive control network and exhibits bidirectional (Granger) causal interactions with the striatum. Only OCD showed increased GMV in the dorsal striatum with higher changes being associated with more severe OCD symptomatology. Together the findings demonstrate robustly decreased GMV across the disorders in the left IFG, suggesting a transdiagnostic brain structural marker. The functional characterization as a key hub in the cognitive control network and casual interactions with the striatum suggest that deficits in inhibitory control mechanisms may promote compulsivity and loss of control that characterize both disorders.

Atypical core-periphery brain dynamics in autism.

The intrinsic function of the human brain is dynamic, giving rise to numerous behavioral subtypes that fluctuate distinctively at multiple timescales. One of the key dynamical processes that takes place in the brain is the interaction between core-periphery brain regions, which undergoes constant fluctuations associated with developmental time frames. Core-periphery dynamical changes associated with macroscale brain network dynamics span multiple timescales and may lead to atypical behavior and clinical symptoms. For example, recent evidence suggests that brain regions with shorter intrinsic timescales are located at the periphery of brain networks (e.g., sensorimotor hand, face areas) and are implicated in perception and movement. On the contrary, brain regions with longer timescales are core hub regions. These hubs are important for regulating interactions between the brain and the body during self-related cognition and emotion. In this review, we summarize a large body of converging evidence derived from time-resolved fMRI studies in autism to characterize atypical core-periphery brain dynamics and how they relate to core and contextual sensory and cognitive profiles.

Fault Diagnosis Method of Power Transformer Based on Improved PNN

Power transformer is a core hub of power transmission in power grid, and its operation state will affect the effective operation of power grid. The existing power transformer fault diagnosis methods mainly use the traditional dissolved gas analysis (DGA) method combined with artificial neural network. Probabilistic neural network (PNN) has a wide range of applications in the field of power transformer fault diagnosis because of its good fault tolerance and high training efficiency. In PNN, the smoothing factor has a great influence on the output, but the parameter is lack of efficient selection method, which makes the classification efficiency of PNN not high. Aiming at this problem, a diagnosis method based on improved PNN is proposed for power transformer faults in this paper. Bat algorithm is used to optimize the smoothing factor of PNN to determine the optimal value. Based on the optimal results, the network model is trained to obtain the optimal power transformer fault diagnosis model. The experiment fully proves that the improved PNN has higher diagnosis accuracy than other methods.

Identification of Ten Core Hub Genes as Potential Biomarkers and Treatment Target for Hepatoblastoma.

BackgroundThis study aimed to systematically investigate gene signatures for hepatoblastoma (HB) and identify potential biomarkers for its diagnosis and treatment.Materials and MethodsGSE131329 and GSE81928 were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between hepatoblastoma and normal samples were identified using the Limma package in R. Then, the similarity of network traits between two sets of genes was analyzed by weighted gene correlation network analysis (WGCNA). Cytoscape was used to visualize and select hub genes. PPI network of hub genes was construed by Cytoscape. GO enrichment and KEGG pathway analyses of hub genes were carried out using ClueGO. The random forest classifier was constructed based on the hub genes using the GSE131329 dataset as the training set, and its reliability was validated using the GSE81928 dataset. The resulting core hub genes were combined with the InnateDB database to identify the innate core genes.ResultsA total of 4244 DEGs in HB were identified. WGCNA identified four modules that were significantly correlated with the disease status. A total of 114 hub genes were obtained within the top 20 genes of each node rank. 6982 relation pairs and 3700 nodes were contained in the PPI network of 114 hub genes. GO enrichment and KEGG pathway analyses of hub genes were focused on MAPK, cell cycle, p53, and other crucial pathways involved in HB. A random forest classifier was constructed using the 114 hub genes as feature genes, resulting in a 95.5% true positive rate when classifying HB and normal samples. A total of 35 core hub genes were obtained through the mean decrease in accuracy and mean decrease Gini of the random forest model. The classification efficiency of the random forest model was 81.4%. Finally, CDK1, TOP2A, ADRA1A, FANCI, XRCC1, TPX2, CCNB2, CDK4, GLYATL1, and CFHR3 were identified by cross-comparison with the InnateDB database.ConclusionOur study established a random forest classifier that identified 10 core genes in HB. These findings may be beneficial for the diagnosis, prediction, and targeted therapy of HB.

The bioinformatics analysis of quercetin in octagonal lotus for the screening of breast cancer MYC, CXCL10, CXCL11, and E2F1.

BackgroundComprehensive bioinformatics analysis of the effective molecular screening of Podophyllum octagonal in breast cancer treatment by using network pharmacology.MethodsWe collected the active ingredients and target genes of Chinese medicine octagonal lotus through the Traditional Chinese Medicine System Pharmacology Analysis Platform (TCMSP); downloaded human protein annotation information on the protein database Uniport; and collected data from five databases: GeneCards, OMIM, PharmGkb, TDD, and DrugBank. Construct the practical ingredient-target gene data intersection to obtain the target gene-disease gene and draw the Venn diagram. We use Cytoscape 3.8.0 software to construct the effective component-target gene-disease gene network. The STRING database protein interaction (PPI) networks were erected, and we used Cytoscape 3.8.0 software to screen out its core sub-networks and hub gene networks. Through survival analysis, core genes and hub genes were screened to identify several key genes. We performed key target gene ontology (GO) analysis and gene interaction (KEGG) analysis, which were followed by molecular docking of the key active ingredients in the star anise corresponding to several key genes.Results19 active ingredients, 444 drug targets, and 10,941 disease-related genes were obtained. The key active ingredient was quercetin. GO analysis revealed 2471 affected biological processes, and 167 pathways were obtained in KEGG enrichment analysis.ConclusionThis study initially screened the key active ingredients of star aniseed lotus and analyzed key genes and several essential pathways. Traditional Chinese medicine is expected to provide new evidence and research ideas to prevent and treat breast cancer.

Research on Co-authorship Network of Sports Culture in China Based on Social Network Analysis (SNA)

The co-authorship network of Chinese sports culture field is constructed while the co-authored papers published in CNKI database from 2000 to 2019. SNA methods and complex network theory are employed to analyze the structural characteristics, groups of core authors, and distribution of the network resources based on overall density, average distance, clustering coefficient, and centrality of co-authorship network. The result shows that the information liquidity is poorer, the connections are relatively loose, and there are some groups that authors are familiar with each other in the co-authorship network of sports culture. The scientists’ productivity and co-author groups’ size follow the power law distributions. The field has formed a large scale and influential groups and core authors, and mainly in small-scale cooperation. Moreover, most of the authors who published amounts of papers have limited co-authored papers, and a few core authors have high resource control. What’s more, prolific authors should expand the scope of cooperation to improve the connectivity of network. And the same time, more attention should be pay to these core authors and hub authors.

System biological investigations of hydroxychloroquine and azithromycin targets and their implications in QT interval prolongation

COVID-2019 pandemic is affecting people worldwide in the absence of an effective treatment strategy. Several suggestive therapeutic options through drug repurposing are recommended, but a complete consensus is not reached. A combination of Hydroxychloroquine (HCQ) and Azithromycin (AZM) has been widely tried and discussed but its administration has also led to potential adversities in patients. Studies are suggesting that most prominent adverse event with HCQ and AZM combination is QT interval prolongation. We studied interaction of HCQ with AZM and subsequent effect of this drug combination on QT interval prolongation. We performed system biological investigation of HCQ and AZM targets and screened important targets and pathways possibly involved in QT interval prolongation. The best core hub protein drug targets involved in QT interval prolongation were identified as HSP90AA1 exclusively associated with HCQ, while AKT1 exclusively associated with AZM on the basis of node degree value. It was found that PI3K/Akt, VEGF, ERBB2 pathways must be given consideration for understanding the role of HCQ and AZM in QT interval prolongation. Conclusion: Computational methods have certain limitations based on source database coverage and prediction algorithms and therefore this data needs experimental correlation to draw final conclusion, but current findings screen targets for QT interval prolongation associated with HCQ and AZM. These proteins and pathways may provide ways to reduce this major risk associated with this combination.

Mechanomics analysis of hESCs under combined mechanical shear, stretch, and compression.

Human embryonic stem cells (hESCs) can differentiate to three germ layers within biochemical and biomechanical niches. The complicated mechanical environments in vivo could have diverse effects on the fate decision and biological functions of hESCs. To globally screen mechanosensitive molecules, three typical types of mechanical stimuli, i.e., tensile stretch, shear flow, and mechanical compression, were applied in respective parameter sets of loading pattern, amplitude, frequency, and/or duration, and then, iTRAQ proteomics test was used for identifying and quantifying differentially expressed proteins in hESCs. Bioinformatics analysis identified 37, 41, and 23 proteins under stretch pattern, frequency, and duration, 13, 18, and 41 proteins under shear pattern, amplitude, and duration, and 4, 0, and 183 proteins under compression amplitude, frequency, and duration, respectively, where distinct parameters yielded the differentially weighted preferences under each stimulus. Ten mechanosensitive proteins were commonly shared between two of three mechanical stimuli, together with numerous proteins identified under single stimulus. More importantly, functional GSEA and WGCNA analyses elaborated the variations of the screened proteins with loading parameters. Common functions in protein synthesis and modification were identified among three stimuli, and specific functions were observed in skin development under stretch alone. In conclusion, mechanomics analysis is indispensable to map actual mechanosensitive proteins under physiologically mimicking mechanical environment, and sheds light on understanding the core hub proteins in mechanobiology.

Gene regulation network analysis reveals core genes associated with survival in glioblastoma multiforme.

Glioblastoma multiforme (GBM) is a very serious mortality of central nervous system cancer. The microarray data from GSE2223, GSE4058, GSE4290, GSE13276, GSE68848 and GSE70231 (389 GBM tumour and 67 normal tissues) and the RNA‐seq data from TCGA‐GBM dataset (169 GBM and five normal samples) were chosen to find differentially expressed genes (DEGs). RRA (Robust rank aggregation) method was used to integrate seven datasets and calculate 133 DEGs (82 up‐regulated and 51 down‐regulated genes). Subsequently, through the PPI (protein‐protein interaction) network and MCODE/ cytoHubba methods, we finally filtered out ten hub genes, including FOXM1, CDK4, TOP2A, RRM2, MYBL2, MCM2, CDC20, CCNB2, MYC and EZH2, from the whole network. Functional enrichment analyses of DEGs were conducted to show that these hub genes were enriched in various cancer‐related functions and pathways significantly. We also selected CCNB2, CDC20 and MYBL2 as core biomarkers, and further validated them in CGGA, HPA and CCLE database, suggesting that these three core hub genes may be involved in the origin of GBM. All these potential biomarkers for GBM might be helpful for illustrating the important role of molecular mechanisms of tumorigenesis in the diagnosis, prognosis and targeted therapy of GBM cancer.

Metabolomics Analysis of Ammonia Secretion during the Fermentation of Klebsiella variicola GN02 with Highly Efficient Endophytic Nitrogen-Fixing Bacteria

The ammonia-secreting performance is one of the key factors for determining nitrogen-fixing capacity of the cell. Klebsiella variicola GN02 is an endophytic nitrogen-fixing bacterium isolated from the roots of mature Pennisetum giganteum z.x.lin. In order to reveal the key factor which influences the ammonia secretion in fermentation process of K. variicola, GC-TOF-MS metabolomics was used. The changes of OD600, ammonia nitrogen content and intracellular metabolites of bacteria were measured simultaneously during fermentation, and a total of 172 intracellular metabolites were detected. Then some methods were used to analysis these high-throughput data. Principal component analysis (PCA) showed that the substances with more contribution to major component exhibited an order as mannitol, glycerol, glucose-1-phosphate, 2‑hydroxypyridine, glutamic acid, fructose-6-phosphate, aniline, lyxose and norleucine. Orthogonal projection to latent structures (OPLS) results revealed that the most important substances for the secretion of ammonia from K. variicola GN02 were mannitol, Gly-Pro, fructose-6-phosphate, and other 12 substances including glycerol, Glu and diacylglycerol having a significant impact with variable importance plot (VIP) values higher than 1, which can be used as the key metabolites for the secretion of ammonia from bacteria. Heatmap clustering analysis showed that mannitol, Gly-Pro and fructose-6-phosphate were strongly expressed at different fermentation stages as the major metabolites. Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis showed that fructose-mannose metabolism and amino acid metabolism are both metabolic pathways with the greatest impact on the secretion of ammonia in bacteria. Mannitol, fructose-6-phosphate and Glu are at the core hub of the metabolic process in bacteria, and Gly-Pro is the major nitrogen-related metabolite synthesized.

Mind-Wandering in Adolescents Predicts Worse Affect and Is Linked to Aberrant Default Mode Network–Salience Network Connectivity

Understanding the fluctuating emotional and cognitive states of adolescents with depressive symptoms requires fine-grained and naturalistic measurements. This study used ecological momentary assessment (EMA) to investigate the affective correlates and consequences of mind-wandering in adolescents with anhedonia (AH) and typically developing (TD) controls. In addition, we examined the association between mind-wandering and resting state functional connectivity between the medial prefrontal cortex (mPFC), a core hub of the default mode network (DMN) linked to internally oriented mentation, and networks linked to attentional control (dorsal attention network [DAN]) and affect/salience detection (salience network [SN]). A total of 65 adolescents, aged 12 to 18 years (TD= 36; AH= 29), completed a resting state functional magnetic resonance imaging scan and subsequently used a smartphone application for ecological momentary assessment (EMA) data collection (2-3 times/d for 5 days). Each survey (N= 678) prompted adolescents to report on their current positive and negative affect (PA and NA), cognition, and activity. The frequency of mind-wandering was higher for AH (70.0% of EMA samples) relative to TD (59.2%) participants, and the participants with AH were more likely to mind-wander to unpleasant content. Mind-wandering was associated with higher concurrent NA, even when controlling for plausible confounds (eg, current activity, social companion, rumination). Time-lagged analyses revealed a bidirectional association between mind-wandering and PA. Greater levels of mind-wandering within the AH group were associated with stronger mPFC-SN/DAN connectivity. Rates of mind-wandering were high, especially among adolescents with anhedonia, and predicted worse affect. The relation between mind-wandering and enhanced mPFC-SN coupling may reflect heightened bottom-up influence of affective and sensory salience on DMN-mediated internally oriented thought.