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To screen antigen targets for immunotherapy by analyzing over-expressed genes, and to identify significant pathways and molecular mechanisms in esophageal cancer by using bioinformatic methods such as enrichment analysis, protein-protein interaction (PPI) network, and survival analysis based on the Gene Expression Omnibus (GEO) database. By screening with highly expressed genes, we mainly analyzed proteins MUC13 and EPCAM with transmembrane domain and antigen epitope from TMHMM and IEDB websites. Significant genes and pathways associated with the pathogenesis of esophageal cancer were identified using enrichment analysis, PPI network, and survival analysis. Several software and platforms including Prism 8, R language, Cytoscape, DAVID, STRING, and GEPIA platform were used in the search and/or figure creation. Genes MUC13 and EPCAM were over-expressed with several antigen epitopes in esophageal squamous cell carcinoma (ESCC) tissue. Enrichment analysis revealed that the process of keratinization was focused and a series of genes were related with the development of esophageal cancer. Four genes including ALDH3A1, C2, SLC6A1, and ZBTB7C were screened with significant P value of survival curve. Genes MUC13 and EPCAM may be promising antigen targets or biomarkers for esophageal cancer. Keratinization may greatly impact the pathogenesis of esophageal cancer. Genes ALDH3A1, C2, SLC6A1, and ZBTB7C may play important roles in the development of esophageal cancer. [ABSTRACT FROM AUTHOR]

The integration of geosynchronous orbit (GSO) satellites in Global Navigation Satellite Systems (GNSS) is mostly discussed to enable a regional enhancement for tracking. But how do GSO satellites affect the orbit determination of the rest of the constellation? How accurately can these orbits be determined in a future GNSS tracking scenario with optical links? In this simulation study we analyze the benefit of GSO satellites as an expansion of a MEO (Medium Earth Orbit) satellite constellation – we selected the Galileo satellite constellation – for MEO Precise Orbit Determination (POD). We address not only the impact on POD of MEO satellites but also the possibility to precisely determine the GSO satellites – geostationary orbits (GEO) and inclined geosynchronous orbits (IGSO) – in such an expanded MEO constellation. In addition to GNSS microwave observations, we analyze the influence of different optical links between the participating entities: Optical two-way Inter-Satellite Links (OISL) and ground-space oriented Optical Two-Way Links (OTWL). These optical measurements together with the GNSS microwave observations give a remarkable benefit for the POD capability. In the case of GNSS and OTWL, we simulate the measurements with regard to a network of 16 ground stations. We pay great attention to the simulation of systematic effects of all measurement techniques. We discuss the influence on the systematic errors as well as the formal orbit uncertainties. A MEO constellation expanded with GSO satellites as well as the use of optical links together with GNSS observations not only improves the MEO satellite orbits but also the GSOs to a great extent. [ABSTRACT FROM AUTHOR]

While the short-term impact of collisions on missions is relatively negligible, economic models predict that in one century, space debris will be a major drag on the industry's development. However, this challenge might also become a business opportunity, with the combined effect of the New Space and renewed legal regulations. The Recycler is a project of geostationary satellite able to harvest components of cooperative satellites. By re-purposing existing hardware, the Recycler may open a second-hand market of debris-efficient On-Orbit-Servicing (OOS). This paper provides the strategic analysis of re-purposing missions, using an approach drawn from Game Theory. This enables unique guidance on which aspects of the proposal should be the focus of attention. Starting from an economic problem, the model is gradually complexified to fit future standard Recycler's contracts. A sensitivity analysis and a case study were performed to assess the viability of the project. It is concluded that the major obstacles of the Recycler are the number of clients reachable under its fuel constraints, the overall cost of the re-purposed components as well as the long-term rate of their degradation in the space environment. • Latest industry trends favor debris-efficient On-Orbit-Servicing satellites. • Supposing high chances of success, re-purposing is a viable project in GEO. • The main stress-point is the number of clients reachable by the spacecraft. • The re-purposed components' costs and their depreciation rates are also critical. [ABSTRACT FROM AUTHOR]

• Several gene sets related to chromosome segregation were enriched in LIHC. • BRIP1, NSMCE2, ANAPC7, RAD18, TTL were upregulated in LICH RNA-seq and HCC microarray. • High expression of five genes was correlated with poor prognosis in HCC. Hepatocellular carcinoma is one of the most frequent cancers with high mortality rate worldwide. TCGA LIHC HTseq counts were analyzed. GSEA was performed with GO BP gene sets. GO analysis was performed with differentially expressed genes. The subset of genes contributing most of the enrichment result of GO_BP_CHROMOSOME_SEGREGATION of GSEA were identified. Five genes have been selected in this subset of genes for further analysis. A microarray data set, GSE112790, was analyzed as a validation data set. Survival analysis was performed. According to GSEA and GO analysis several gene sets and processes related to chromosome segregation were enriched in LIHC. GO_BP_CHROMOSOME_SEGREGATION gene set from GSEA had the highest size of the genes contributing most of the enrichment. Five genes in this gene set; BRIP1, NSMCE2, ANAPC7, RAD18 and TTL , whose expressions and prognostic values have not been studied in hepatocellular carcinoma in detail, have been selected for further analyses. Expression of these five genes were identified as significantly upregulated in LIHC RNA-seq and HCC microarray data set. Survival analysis showed that high expression of the five genes was associated with poor overall survival in HCC patients. Selected genes were upregulated and had prognostic value in HCC. [ABSTRACT FROM AUTHOR]

Tuberculosis (TB) is a serious public health issue in India. Numerous molecular mechanisms and immunological responses play significant roles in the pathogenesis of tuberculosis. This study aimed to identify host immune-related biomarkers that are significantly differentially expressed in active TB and that play a vital role in disease progression. The methodology employed in this study included data collection, pre-processing, analysis, and interpretation of the results. Six microarray datasets were used to identify differentially expressed genes (DEGs), and only the common DEGs were used for further downstream analysis, such as hub gene identification, gene ontology, pathway enrichment analysis, and drug-gene interaction analysis. The study identified 1728 DEGs, including 906 upregulated and 822 downregulated genes. Five hub genes were identified that were: STAT1, GBP5, GBP1, FCGR1A, and BATF2. Gene ontology and pathway enrichment revealed that most of the genes were involved in interferon-gamma signaling. In addition, through drug-gene interactions, known drugs have been identified for STAT1, FCGR1A and GBP1. The findings of this study may contribute to early detection and treatment of active TB. [ABSTRACT FROM AUTHOR]

Persistent exposure to low-dose of cadmium is strongly linked to both the development and prognosis of non-small cell lung cancer (NSCLC), yet the precise molecular mechanism behind this relationship remains uncertain. In this study, cadmium-related pathogenic genes (CRPGs) in NSCLC were identified via differential expression analysis. NSCLC patient clusters related to CRPGs were constructed through univariate Cox and K-means clustering algorithms. Multivariate Cox and least absolute shrinkage and selection operator (LASSO) regression analyses were employed to determine the prognosis. Sixteen CRPGs showed a significant association with NSCLC. We found biological and prognostic differences between patients in clusters A and B. A predictive prognostic risk model for NSCLC revealed that FAM83H , MSMO1 , and SNAI1 are central. Hence, the 3 hub genes were named. To further elucidate the role of CRPGs in NSCLC, A549 cells were exposed to CdCl 2. The mRNA and protein expression levels of the 3 hub genes and cell invasion were detected. Moreover, 10 μM CdCl 2 may increase the protein expression of 3 hub genes and enhance the invasive ability of A549 cells. This risk model may have established a theoretical foundation for investigating the mechanisms, treatment, and prognosis of NSCLC. [Display omitted] • MAPK, Hippo, and ERBB signaling pathways may be the main pathways for CRPGs to participate in NSCLS. • 3 hub genes (Fam83h , Msmo1 , and Snai1) significantly associated with prognostic risk in NSCLC. • A risk model for predicting the prognosis of NSCLC that comprises 3 hub genes was established. [ABSTRACT FROM AUTHOR]

• It was the first time to evaluate the possible molecular mechanism of Corbrin capsules for treatment of AKI-COVID-19. • TP53, JAK2, PIK3CA, PTGS2, KEAP1, and MCL1 as the top six core protein targets. • Immune infiltration analysis revealed a notable disparity in the expression of quiescent memory CD4 T cells. • This study provided new understanding of the molecular mechanisms based on network pharmacology. of the study: This study used network pharmacology and the Gene Expression Omnibus (GEO) database to investigate the therapeutic effects of Corbrin capsules on acute kidney injury (AKI)-COVID-19 (coronavirus disease 2019). The active constituents and specific molecular targets of Corbrin capsules were obtained from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) and Swiss Target Prediction databases. The targets related to AKI and COVID-19 disease were obtained from the Online Mendelian Inheritance in Man (OMIM), GeneCards, and GEO databases. A protein–protein interaction (PPI) network was constructed by utilizing Cytoscape. To enhance the analysis of pathways associated with the pathogenesis of AKI-COVID-19, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed. Furthermore, immune infiltration analysis was performed by using single-sample gene set enrichment analysis (ssGSEA) and CIBERSORT. Molecular docking was used to assess interactions between differentially expressed genes and active ingredients. Verification was performed by utilizing GEO databases and in vivo assays. This study revealed an overlap of 18 significantly differentially expressed genes between the Corbrin capsules group and the AKI-COVID-19 target group. Analysis of the PPI network identified TP53, JAK2, PIK3CA, PTGS2, KEAP1, and MCL1 as the top six core protein targets with the highest degrees. The results obtained from GO and KEGG analyses demonstrated that the target genes were primarily enriched in the apoptosis and JAK-STAT signaling pathways. Moreover, the analysis of immune infiltration revealed a notable disparity in the percentage of quiescent memory CD4 + T cells. Western blot analyses provided compelling evidence suggesting that the dysregulation of 6 core protein targets could be effectively reversed by Corbrin capsules. This study revealed the key components, targets, and pathways involved in treating AKI-related COVID-19 using Corbrin capsules. This study also provided a new understanding of the molecular mechanisms underlying this treatment. [ABSTRACT FROM AUTHOR]

A Beidou navigation satellite system (BDS) receiver with high sensitivity is embarked in a geostationary orbit (GEO) spacecraft to demonstrate characteristics of BDS signals tracked. This receiver can be compatible with the regional (BDS-2) and global (BDS-3) systems, which have three orbit types: medium Earth orbit (MEO), inclined geostationary orbit (IGSO), and GEO. The on-orbit BDS signal characteristics, including observations quantity, availability, position dilution of precision (PDOP), and carrier-to-noise ratio (C / N 0), are presented according to in-flight data. The observations and distribution of C / N 0 with respect to nadir angles were analyzed. The average number of the BDS satellites tracked is 4.4, and the average PDOP is 12.0. PDOP improves when the BDS GEO and IGSO observations are involved. The maximum value of C / N 0 of the BDS-3 MEO satellites is approximately 49 dB-Hz, which is roughly 2 dB higher than that of the BDS-2 MEO satellites. Most of the C / N 0 of the BDS-3 MEO satellite at nadir angles beyond 26° is in the range of 27–34 dB-Hz. We reconstruct the transmit antenna gain for all observed BDS satellites using C / N 0 measurements. Moreover, we investigate the main and side lobe characteristics of the BDS satellites in terms of different orbit types and satellite manufacturers. The side lobe signals of the BDS-3 MEO generally have 20–30 dB lower gain than the peak main lobe gain. The side lobe signal performance of the BDS-2 MEO is evidently better than that of the BDS-3 MEO. We give side lobe characteristics analysis of the BDS-3 MEO satellites from two different manufacturers based on the transmit antenna gain reconstructed. [ABSTRACT FROM AUTHOR]

• The expression of JAK1, SKII, and ZBTB16 in the eye showed tissue differences. • Infiltration and dysregulation of immune cells affect the progression of Keratoconjunctivitis sicca. • After experimental verification, machine learning has certain advantages in the process of finding diagnostic markers of Keratoconjunctivitis sicca. • JAK1, SKI and ZBTB16 have potential in the diagnosis and treatment of Keratoconjunctivitis sicca. Keratoconjunctivitis sicca (KCS) is an ocular condition characterized by insufficient tear production and inflammatory irritation, with Sjögren's syndrome (SS) being a major causative factor. This study aimed to extract patient transcriptomic data from the GEO database to identify signature genes associated with the diagnosis and treatment of KCS and the expression of three key genes were experimentally verified. We performed a difference analysis on the SS patient dataset and performed a Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis on the resulting genes. Additionally, a Weighted Gene Co-expression Network Analysis (WGCNA) was constructed. Machine learning techniques were employed to analyze the most strongly correlated gene modules with SS traits. These findings were further validated using KCS immune-correlation microarrays as a validation set. The correlation of the three identified genes with 22 immune cells was assessed through immune infiltration analysis. Subsequently, a rat model of desiccated keratoconjunctivitis was established, and the modeling situation and expression of characteristic genes were analyzed at the morphological, tissue, and molecular levels. Bioinformatic prediction revealed that the expression of JAK1, SKI, ZBTB16 not only differed in the machine learning validation set, but also correlated with some immune cells in the immune infiltration analysis. The results of animal experiments showed that the transcription and expression levels of these three genes were significantly different in rat KCS tissues and normal tissues, and there were also differences in the expression of JAK1 and SKI in rat peripheral blood, as well as significant up-regulation of the expression of related inflammatory factors in KCS tissues. Through bioinformatics prediction and animal experimental validation, this study identified three differentially expressed genes in SS mediated KCS patients, which provide new potential biological targets for the diagnosis and treatment of KCS. [ABSTRACT FROM AUTHOR]

Colorectal cancer (CRC) is the third most common cancer in the world. According to several types of research, statins may impact the development and treatment of CRC. This work aimed to use bioinformatics to discover the relationship between statin targets and differentially expressed genes (DEGs) in CRC patients and determine the possible molecular effect of statins on CRC suppression. We used CRC datasets from the GEO database to select CRC-related DEGs. DGIdb and STITCH databases were used to identify gene targets of subtypes of statin. Further, we identified the statin target of CRC DEGs hub genes by using a Venn diagram of CRC DEGs and statin targets. Funrich and enrichr databases were carried out for the KEGG pathway and gene ontology (GO) enrichment analysis, respectively. GSE74604 and GSE10950 were used to identify CRC DEGs. After analyzing datasets,1370 genes were identified as CRC DEGs, and 345 targets were found for statins. We found that 35 genes are CRC DEGs statin targets. We found that statin targets in CRC were enriched in the receptor and metallopeptidase activity for molecular function, cytoplasm and plasma membrane for cellular component, signal transduction, and cell communication for biological process genes were substantially enriched based on FunRich enrichment. Analysis of the KEGG pathways revealed that the overexpressed DEGs were enriched in the IL -17, PPAR , and Toll-like receptor signaling pathways. Finally, CCNB1 , DNMT1 , AURKB , RAC1 , PPARGC1A , CDKN1A , CAV1 , IL1B , and HSPD1 were identified as hub CRC DEGs statin targets. The genetic and molecular aspects of our findings reveal that statins might have a therapeutic effect on CRC. [ABSTRACT FROM AUTHOR]

Introduction: Preeclampsia (PE) is a pregnancy specific disorder which is significantly associated with maternal and neonatal morbidity and mortality. This study aimed to explore the potential role of circRNAs in PE.Methods: The mRNA, miRNA, and circRNA expression profiles of PE were downloaded from GEO database. Bioinformatics analysis was conducted to characterize differentially expressed mRNAs (DEmRNAs), miRNAs (DEmiRNAs) and circRNAs (DEcircRNAs) in the placental tissues of women with PE versus normal pregnancies. Then, expression validation of the mRNAs, miRNAs and circRNAs were performed with RT-qPCR and GEO datasets.Results: A total of 1645 DEmRNAs, 41 DEmiRNAs and 2432 DEcircRNAs were acquired. The ceRNA network contained 4 circRNA-miRNA pairs and 64 miRNA-mRNA pairs, including 3 circRNAs, 3 miRNAs, and 63 mRNAs. Validation in RT-qPCR and GEO were generally in line with our integrated analysis results.Discussion: In conclusion, we speculated that hsa_circRNA_0001687/hsa-miR-532-3p/MMP14/AXL, hsa_circ_0001513/hsa-miR-188-5p/HMGCS1 and hsa_circ_0001513/hsa_circ_0001329/hsa-miR-760/MAP1LC3B axes may participate in the pathological process of PE. [ABSTRACT FROM AUTHOR]

Bladder cancer is the most common malignancy of the urinary system. Compound Kushen Injection (CKI) is a Chinese medicinal preparation that has been widely used in the treatment of various types of cancers in the past two decades. However, the pharmacological effect of CKI on bladder cancer is not still completely understood. In the current study, network pharmacology combined with bioinformatics was used to elucidate the therapeutic mechanism and potential targets of CKI in bladder cancer. The mechanism by which CKI was effective against bladder cancer was further verified in vitro using human bladder cancer cell line T24. Network pharmacology analysis identified 35 active compounds and 268 target genes of CKI. Bioinformatics data indicated 5500 differentially expressed genes associated with bladder cancer. Common genes of CKI and bladder cancer suggested that CKI exerted anti-bladder cancer effects by regulating genes such as MMP-9 , JUN , EGFR , and ERK1. Functional enrichment analysis indicated that CKI exerted therapeutic effects on bladder cancer by regulating certain biological processes, including cell proliferation, cell migration, and cell apoptosis. In addition, Kyoto Encyclopedia of Genes and Genomes enrichment analysis implicated pathways related to cancer, bladder cancer, and the PI3K-Akt signaling pathway. Consistently, cell experiments indicated that CKI inhibited the proliferation and migration of T24 cells, and induced their apoptosis. Moreover, RT-qPCR and Western blot results demonstrated that CKI was likely to treat bladder cancer by down-regulating the gene and protein expression of MMP-9, JUN, EGFR, and ERK1. CKI inhibited the proliferation and migration, and induced the apoptosis of T24 bladder cancer cells through multiple biological pathways and targets. CKI also exhibited significant effects on the regulation of key genes and proteins associated with bladder cancer. Overall, our findings provide solid evidence and deepen current understanding of the therapeutic effects of CKI for bladder cancer, and further support its clinical use. [ABSTRACT FROM AUTHOR]

• Using computational approaches, a total number of 7388 differentially expressed genes including 4910 downregulated and 2478 upregulated genes were screened in glioblastoma. • 12 hub genes including ARHGEF7, RAB11FIP4, PPP1R16B, OLFM1, CLDN10, BCAT1, C1QB, C1QC, IFI16, NUP37, PARP9, and PCLAF were selected. • The area under curve (AUC) in the receiver operating characteristic (ROC) curve demonstrated excellent diagnostic efficiency for the hug genes in discriminating the GBM from normal tissues. • qRT-PCR assay showed significant expression differences for the core genes in glioblastoma samples retrieved from the patients compared to the healthy controls. Glioblastoma multiforme (GBM) is the most common, most invasive, and malignant type of primary brain tumor with poor prognosis and poor survival rate. Using GSE22891 the expression and methylation status of same GBM patients was evaluated to identify key epigenetic genes in GBM. Using |log2FC| > 1 and FDR 〈 0.05 as the threshold, DEGs including 4910 downregulated and 2478 upregulated were screened and by |log2FC| 〉 0.2 and p-value < 0.05, 3223 DMCs were detected. By merging the results of DEGs and DMCs, 643 genes were selected for network analysis by WGCNA, and based on expression values three modules and by methylation values, one module was selected. Using STRING and Cytoscape databases, PPI network of genes of all modules were constructed separately. According to the PPI network, core genes were picked out. The expression status of core genes was evaluated using GSE77043, GSE42656, GSE30563, GSE22891, GSE15824, and GSE122498, and 50 genes were validated. The methylation status of 50 genes was explored using GSE50923, GSE22891, and GSE36245, and finally, 12 hub genes including ARHGEF7, RAB11FIP4, PPP1R16B, OLFM1, CLDN10, BCAT1, C1QB, C1QC, IFI16, NUP37, PARP9, and PCLAF were selected. Using GEPIA database, the expression and by cBioportal the survival plot and also scatterplot of methylation versus expression of 12 hub genes were extracted based on TCGA. To determine the diagnostic values of the hub genes, the receiver operating characteristic (ROC) curve and the area under the curve (AUC) were extracted based on GSE22891 and GSE122498. Finally, we evaluated the expression level of the genes in tissue of 83 GBM patients and also non-tumoral adjacent (as control) tissues. [Display omitted] [ABSTRACT FROM AUTHOR]

Introduction: Early-onset preeclampsia is a pregnancy complication associated with high maternal and perinatal morbidity, mortality. Intense efforts have been made to elucidate the pathogenesis, but the molecular mechanism is still elusive. This study aimed to identify potential key genes related to early-onset preeclampsia, and to obtain a better understanding of the molecular mechanisms of this disease.Methods: We performed a multi-step integrative bioinformatics analysis of microarray dataset GSE74341 downloaded from Gene Expression Omnibus (GEO) database including 7 early-onset preeclampsia and 5 gestational age matched normotensive controls. The differentially expressed genes (DEGs) were identified using the "limma" package, and their potential functions were predicted by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Furthermore, the protein-protein interaction network (PPI) was obtained from the STRING database and the PPI network was visualized by Cytoscape software. Then, hub modules and hub genes were screened out from the PPI network, and enrichment analysis was performed for them. Also, validation of hub genes expression in early-onset PE was down by using microarray dataset GSE44711.Results: A total of 628 DEGs (256 down- and 372 up-regulated) were identified in early-onset PE compared to controls. A total of 4 significant hub modules and 26 significant hub genes were identified.Conclusion: In conclusion, the DEGs related to cell-cell or cell-extracellular matrix interaction (ITGA5, SPP1, LUM, VCAN, APP), placenta metabolic or oxidative stress (CCR7, NT5E, CYBB) were predicted to be newly potential crucial genes that may play significant roles in the pathogenesis of early-onset PE. [ABSTRACT FROM AUTHOR]

• Research highlight 1 Investigation of Gut Microbiota's Role in Heart Failure: The study employed a two-sample Mendelian randomization approach to explore the potential causal link between alterations in gut microbiota and the onset and progression of heart failure. This investigation was pivotal in addressing the controversial topic of whether changes in gut microbiota directly contribute to heart failure. • Research highlight 2 Identification of Specific Bacterial Groups Associated with Heart Failure Risk: The analysis revealed seven distinct bac- terial groups within the intestines that showed associations with heart failure risk. These findings are significant as they suggest a notable correlation between these specific gut microbiota groups and heart failure,potentially offering new insights for prevention and control strategies in heart failure management. Objective: In recent years, researchers have observed a potential association between alterations in gut microbiota and the onset and progression of heart failure. Nevertheless, the causal relationship between gut microbiota and heart failure remains a topic of controversy. This study employed a two-sample Mendelian randomization approach to investigate the causal link between gut microbiota and heart failure. Method: We extracted single nucleotide polymorphism (SNPs) data for heart failure (ebi-a-gcst009541) and gut microbiota from the publicly available genome-wide association analysis (GWAS) summary database. The primary analytical method employed was inverse variance weighting (IVW), complemented by validation using MR-PRESSO, weighted median, and MR pleiotropic residual methods. Additionally, gene pleiotropy (MR-Egger), heterogeneity testing, and a "leave-one-out" analysis were conducted to assess the robustness of the findings. Utilizing the limma package, differentially expressed genes (DEGs) from the Gut Microbiota datasets (GSE3586, GSE5406) and Heart Failure datasets (GSE47908, GSE87466) sourced from the Gene Expression Omnibus (GEO) were curated. Subsequent enrichment analysis was conducted using the Cluster Profiler and GO plot packages to validate the MR analysis outcomes. Results: The results of our analysis revealed seven distinct bacterial groups in the intestines that exhibited associations.with.the.risk.of.heart.failure. These.included.class.negativicutes (P = 0.02,OR:1.11,95%CI:1.02,1.21), gene.eubacterium.eligensgroup (P = 0.02,OR:1.10,95%CI:1.01,1.20),gene.eubacteriummoxidoreducensgroup (P = 0.01,OR:1.10,95%CI:1.02,1.19),Order.selenium (P = 0.02,OR:1.11,95%CI:1.02,1.21), gene.familyxiiiucg001 (P = 0.03,OR=1.09.95%CI:1.01,1.19), gene.familyxiiiad3011group (P = 0.03,OR:0.92,95%CI:0.86,0.99), and.gene.anaerostipes (P = 0.00,OR:0.87,95%CI:0.80,0.94). Nevertheless, upon conducting reverse causal MR analysis, no evidence of a causal relationship between heart failure and the aforementioned seven gut microbiota groups was found.Bioinformatics analysis reveals shared DEGs between gut microbiota and heart failure. Conclusion: This Mendelian randomization study represents the first endeavor to explore the causal relationship between specific gut microbiota and heart failure. The findings suggest a significant correlation between these seven specific gut microbiota groups and the risk of heart failure, potentially offering valuable insights for heart failure prevention and control efforts. [Display omitted] [ABSTRACT FROM AUTHOR]

Zhimu-Huangbo (ZB) herb pair is a common prescription drug used by physicians of all dynasties, and has significant neuroprotective effect, such as the ZB can significantly promote neuronal cell regeneration, repair neuronal damage, and improve cognitive disorders. However, its ingredients are urgently needed to be identified and mechanisms is remained unclear. Using ultra performance liquid chromatography-quadrupole-time of flight-mass spectrometry (UPLC-Q-TOF-MS), the study of neuroprotective mechanism of Zhimu-Huangbo extract (ZBE) is investigated, and the network pharmacology technology and experimental validation is also performed. Firstly, UPLC-Q-TOF-MS technology was used to characterize the chemical components contained in the ZBE. After that, the TCMSP database and the Swiss Target Prediction method were used to search for potential target genes for ZBE compounds. At the same time, the OMIM and GeneCards disease databases were used to search for Alzheimer's disease (AD) targets and expanded with the GEO database. Then, GO and KEGG enrichment analysis was performed using OECloud tools. Subsequently, the potential mechanism of ZBE therapeutic AD predicted by network pharmacological analysis was experimentally studied and verified in vitro. In the UPLC-Q-TOF-MS analysis of the ZBE, a total of 39 compounds were characterized including Neomangiferin, Oxyberberine, Timosaponin D, Berberine, Timosaponin A-III, Anemarsaponin E, Timosaponin A-I, Smilagenin and so on. A total of 831 potential targets and 13995 AD-related target genes were screened. A further analysis revealed the number of common targets between ZBE and AD is 698. Through GO and KEGG enrichment analysis, we found that ZBE's anti-AD targets were significantly enriched in autophagy and mitochondrial autophagy related pathways. The results of cell experiments also confirmed that ZBE can promote mitochondrial autophagy induced by D-galactose (D-gal) HT22 cells through the PTEN-induced kinase 1/Parkin (PINK1/Parkin) pathway. ZBE can promote autophagy of mitochondria and play a protective role on damaged neurons. [Display omitted] [ABSTRACT FROM AUTHOR]

Tacrolimus is a powerful immunosuppressant and has been widely used in organ transplantation. In order to further explore the role of tacrolimus in liver transplantation, we conducted network pharmacology analysis. GSE100155 was obtained from the GEO database, and the DEGs of liver transplantation were analyzed. The 2D structure of tacrolimus was obtained from the National Library of Medicine, and the pharmacophore model of tacrolimus was predicted using the online tool pharmmapper. Then a network of tacrolimus and target genes was constructed through network pharmacology, and visualization and GO enrichment analysis was performed through Cytoscape. In addition, we also analyzed the correlation between key genes and immune infiltrating cells. The data of GSE84908 was used to verify the changes of key gene expression levels after tacrolimus treatment. The results of network pharmacological analysis showed that tacrolimus had 43 target genes, and the GO enrichment results showed many potential functions. Further analysis found that there were 5 key target genes in DEGs, and these 5 genes were significantly down-regulated in liver transplant patients. Another important finding was that 5 genes were significantly related to some immune infiltrating cells. The results of the GSE84908 data analysis showed that after tacrolimus treatment, the expression of DAAM1 was significantly increased (p = 0.015). Tacrolimus may inhibit the human immune response by affecting the expression of DAAM1 in liver transplant patients. [ABSTRACT FROM AUTHOR]

• Differentially expressed genes were analyzed and prognostic markers in LUAD were identified. • A total of 68 protein-coding differentially expressed genes were identified using TCGA dataset. • Nineteen genes were individually associated with overall survival. • A risk score was developed for stratifying prognosis in LUAD patients. • The 19-gene prognostic signature was independently validated using GEO datasets. Lung adenocarcinoma (LUAD) is the most common subtype of non-small cell lung cancer. Understanding the molecular mechanisms underlying tumor progression is of clinical significance. This study aimed to identify novel molecular markers associated with LUAD prognosis. RNA sequencing data from the Cancer Genome Atlas (TCGA) database of LUAD tumors and paired normal tissues, and microarray data from the Gene Expression Omnibus (GEO) database were obtained. In the TCGA dataset, differentially expressed (DE) genes were identified by comparing gene expression between early-stage tumors and normal tissue, as well as between advanced-stage and early-stage tumors. A risk score was developed using a weighted linear combination of individual dysregulated protein-coding genes that was associated with overall survival (OS). The prognostic value of the risk score was evaluated using Kaplan-Meier and multivariate Cox analysis. The gene signature was further validated using independent datasets from GEO. Among the 68 identified DE genes, 19 were individually associated with OS in univariate analyses. A risk score was constructed for each patient based on the coefficients in multivariate Cox model and normalized expression levels of these 19 genes. LUAD patients with a low risk score had a significantly better survival than those with a high risk score (log-rank P < 0.0001). After adjusting for age, sex, clinical stage, smoking history, and treatments, the patients with a low risk score had a 81 % decreased risk for death, compared to those with a high risk score (hazard ratio 0.19, 95 % confidence interval 0.097−0.36). The significant association of the risk score with OS in LUAD patients was further validated in three independent GEO datasets. A novel 19-gene prognostic signature based on gene expression was identified in LUAD patients. The findings further improve the understanding of LUAD prognostication and have the potential to facilitate risk-stratified disease management. [ABSTRACT FROM AUTHOR]

The rising production rate of space debris poses an increasingly severe threat of collision to satellites in the crowded Geostationary Orbit (GEO). It also presents a unique opportunity to make use of a growing supply of in-space resources for the benefit of the satellite community. "The Recycler" is a mission proposed to source replacements for failed components in GEO satellites by extracting functioning components from non-operational spacecraft in the GEO graveyard. This paper demonstrates a method of analyzing in-space re-purposing missions such as the Recycler, using real satellite data to provide a strong platform for accurate performance estimates. An inventory of 1107 satellites in the extended GEO region is presented, and a review into past GEO satellite anomalies is conducted to show that solar arrays would be in the greatest demand for re-purposing. This inventory is used as an input to a greedy selection algorithm and trajectory simulation to show that the Recycler spacecraft could harvest components for 67 client satellites with its allotted fuel budget. This capacity directly meets the levels of customer demand estimated from the GEO satellite anomaly data, placing the Recycler as a strong contender in a future second-hand satellite-component industry. Propellant mass is found to be a greater restriction on the Recycler mission than its 15-year lifetime — a problem which could be solved by on-orbit refueling. • Satellite databases are critical when designing on-orbit servicing missions. • On-orbit re-purposing missions should focus on solar arrays in Geostationary Orbit. • Multi-target trajectory optimization is used to predict the Recycler's performance. • The Recycler can visit 67 satellites using electric propulsion with its fuel budget. • On-orbit refueling is essential for sustainable satellite-servicing missions. [ABSTRACT FROM AUTHOR]

This study bioinformatically analyzed aberrant genes and pathways for associations with glioblastoma development and prognosis. The Gene Expression Omnibus (GEO) database was searched and 4 GEO datasets (GSE4290, GSE50161, GSE116520, and GSE90598) were retrieved for limma and RobustRankAggreg package analyses of differentially expressed genes (DEGs) between glioblastoma and normal brain tissues. Functional enrichment analysis was conducted for the main biological functions of these DEGs, whereas the hub genes were identified using the protein-protein interaction network and confirmed for transcriptional and translational levels using the Cancer Genome Atlas, the Genotype-Tissue Expression, and the Human Protein Atlas data. The prognostic values of these hub genes were analyzed using the Chinese Glioma Genome Atlas. Their transcriptional factor regulation network was constructed to assess the roles in glioblastoma development and progression. A total of 473 DEGs (182 upregulated and 291 downregulated) were identified and the hub genes (including CCNB1, CDC20, CCNB2, BUB1, and CCNA2) were shown in module 1 and enriched in the cell cycle or p53 signaling pathway. The highly expressed CCNB1, CDC20, BUB1, and CCNA2 in patients with glioblastoma were associated with poor overall survival, whereas TAF7 could upregulate expression of CCNB1 and CCNA2 and GTF2E2 could upregulate CDC20 expression in glioblastoma. This study showed several DEGs in glioblastoma, and aberrant expression of their hub genes was associated with glioblastoma pathogenesis and poor prognosis, especially the signaling axes of TAF7/CCNB1, TAF7/CCNA2, and GTF2E2/CDC20. [ABSTRACT FROM AUTHOR]

• Description of the space debris data acquisition with standard astronomical optical telescopes. • Astrometric reduction, data validation and orbit improvement for space debris objects. • Photometric data acquisition, light curve construction and processing, measurement error propagation. • Public catalogue of space debris light curves with electronic link. The Faculty of Mathematics, Physics and Informatics of Comenius University in Bratislava, Slovakia (FMPI) operates its own 0.7-m Newtonian telescope (AGO70) dedicated to the space surveillance tracking and research, with an emphasis on space debris. The observation planning focuses on objects on geosynchronous (GEO), eccentric (GTO and Molniya) and global navigation satellite system (GNSS) orbits. To verify the system's capabilities, we conducted an observation campaign in 2017, 2018 and 2019 focused on astrometric and photometric measurements. In last two years we have built up a light curve catalogue of space debris which is now freely available for the scientific community. We report periodic signals extracted from more than 285 light curves of 226 individual objects. We constructed phase diagrams for 153 light curves for which we obtained apparent amplitudes. [ABSTRACT FROM AUTHOR]

The manuscript authenticates the effectiveness of fusing texture and geometrical (GEO) features in magnetic resonance imaging (MRI) for tumor classification. The presented technique is evaluated on two MRI including T2 and FLAIR. The tumor region is enhanced using fast non-local mean (FNLM) method with 4 × 4 patch size. Otsu algorithm is used for tumor segmentation. Moreover, multiple features are extracted for example local binary pattern (LBP), histogram of oriented gradients (HOG) and GEO (area, circularity, filled area, and perimeter) across each segmented image. These acquired features are merged into a single dimensional vector for prediction. In the end, the fused vector is used with multiple classifiers which proved that features fusion provides good results as compared with individual features. [ABSTRACT FROM AUTHOR]

• EGR2 , GREM1 and NPY1R may be the key genes for obesity in humans. • EGR2 was discovered as a potential key gene for obesity in human adipose tissue for the first time. • EGR2 , GREM1 and NPY1R can all be regarded as a potential diagnostic biomarker for obesity in humans. Obesity is a complex condition that is affected by a variety of factors, including the environment, behavior, and genetics. However, the genetic mechanisms underlying obesity remains poorly elucidated. Therefore, our study aimed at identifying key genes for human obesity using bioinformatics analysis. The microarray datasets of adipose tissue in humans were downloaded from the Gene Expression Omnibus (GEO) database. After the selection of differentially expressed genes (DEGs), we used Lasso regression and Support Vector Machine (SVM) algorithm to further identify the feature genes. Moreover, immune cell infiltration analysis, gene set variation analysis (GSVA), GeneCards database and transcriptional regulation analysis were conducted to study the potential mechanisms by which the feature genes may impact obesity. We utilized receiver operating characteristic (ROC) curve to analysis the diagnostic efficacy of feature genes. Finally, we verified the feature genes in cell experiments and animal experiments. The statistical analyses in validation experiments were conducted using SPSS version 28.0, and the graph were generated using GraphPad Prism 9.0 software. The bioinformatics analyses were conducted using R language (version 4.2.2), with a significance threshold of p < 0.05 used. 199 DEGs were selected using Limma package, and subsequently, 5 feature genes (EGR2 , NPY1R , GREM1 , BMP3 and COL8A1) were selected through Lasso regression and SVM algorithm. Through various bioinformatics analyses, we found some signaling pathways by which feature genes influence obesity and also revealed the crucial role of these genes in the immune microenvironment, as well as their strong correlations with obesity-related genes. Additionally, ROC curve showed that all the feature genes had good predictive and diagnostic efficiency in obesity. Finally, after validation through in vitro experiments, EGR2 , NPY1R and GREM1 were identified as the key genes. This study identified EGR2 , GREM1 and NPY1R as the potential key genes and potential diagnostic biomarkers for obesity in humans. Moreover, EGR2 was discovered as a key gene for obesity in human adipose tissue for the first time, which may provide novel targets for diagnosing and treating obesity. [ABSTRACT FROM AUTHOR]

Abstract Background The current study aimed to identify potential diagnostic and prognostic gene biomarkers for colorectal cancer (CRC) based on the Gene Expression Omnibus (GEO) datasets and The Cancer Genome Atlas (TCGA) dataset. Methods Microarray data of gene expression profiles of CRC from GEO and RNA-sequencing dataset of CRC from TCGA were downloaded. After screening overlapping differentially expressed genes (DEGs) by R software, functional enrichment analyses of the DEGs were performed using the DAVID database. Then, the STRING database and Cytoscape were used to construct a protein–protein interaction (PPI) network and identify hub genes. The receiver operating characteristic (ROC) curves were conducted to assess the diagnostic values of the hub genes. Cox proportional hazards regression was performed to screen the potential prognostic genes. Kaplan-Meier curve and the time-dependent ROC curve were used to assess the prognostic values of the potential prognostic genes for CRC patients. Results Integrated analysis of GEO and TCGA databases revealed 207 common DEGs in CRC. A PPI network consisted of 70 nodes and 170 edges were constructed and top 10 hub genes were identified. The area under curve (AUC) of the ROC curves of the hub genes were 0.900, 0.927, 0.869, 0.863, 0.980, 0.682, 0.903, 0.790, 0.995, and 0.989 for CCL19, CXCL1, CXCL5, CXCL11, CXCL12, GNG4, INSL5, NMU, PYY, and SST, respectively. A prognostic gene signature consisted of 9 genes including SLC4A4, NFE2L3, GLDN, PCOLCE2, TIMP1, CCL28, SCGB2A1, AXIN2, and MMP1 was constructed with a good performance in predicting overall survivals of CRC patients. The AUC of the time-dependent ROC curve was 0.741 for 5-year survival. Conclusion The results in this study might provide some directive significance for further exploring the potential biomarkers for diagnosis and prognosis prediction of CRC patients. Highlights • Colorectal cancer related differentially expressed genes were identified based on GEO database and TCGA database. • The top 10 hub genes with relatively high diagnostic values for the patients of CRC were identified. • A 9-gene prognostic signature was identified as a potential prognostic predictor for CRC patients. [ABSTRACT FROM AUTHOR]

Abstract In order to explore the differentially expressed long non-coding RNAs (lncRNAs) in laryngeal squamous cell carcinoma (LSCC), the GSE84957 lncRNA expression profile was included in the present study through data mining in the National Center for Biotechnology Information/Gene Expression Omnibus (NCBI/GEO). Then, the differentially expressed genes (DEGs) of LSCC (1646 lncRNAs and 2713 mRNAs, fold change ≥ 2, P ≤ 0.05) were identified from the GSE84957 dataset using bioinformatics analysis. Of the 10 selected differentially expressed lncRNAs, the expression of 7 lncRNAs were verified by qRT-PCR method. Then, LINC00668 , a potential carcinogenic lncRNA, was screened out by narrowing down the screening criteria (fold change ≥ 4, P ≤ 0.01). Furthermore, correlation analysis demonstrated that expression levels of LINC00668 were associated with age, pathological differentiation degree, T stage, clinical stage and cervical lymph node metastasis. Moreover, a series of bioinformatics tools and in vitro experiments proved that knockdown of LINC00668 inhibited the proliferation, migration and invasion ability of LSCC cells. The present study identified the lncRNAs landscape of LSCC through data mining and bioinformatics analysis, and verified oncogenic LINC00668 , which may play important roles in promoting LSCC cells proliferation, migration and invasion. Highlights • This study identified the lncRNAs landscape of LSCC through data mining. • LINC00668 as an oncogene was screened out through data mining and bioinformatics. • Expression levels of LINC00668 were associated with some clinicopathological features. • Knockdown of LINC00668 could suppress proliferation, migration and invasion of cells. [ABSTRACT FROM AUTHOR]

Severe burns might be followed by severe infection associated with high mortality. In this study, we aimed to identify changes in genes and processes across time points after burn via analyzing time series gene expression profiles in burn patients and control from the Gene Expression Omnibus (GEO). Patients were classified into four groups according to time after burn and weighted gene co-expression network analysis (WGCNA) obtained three gene modules including magenta, yellow and greenyellow modules that significantly correlated positively with time after burn. We also identified four groups of differentially expressed genes (DEGs) in samples at 0-1d, 1-2d, 2-4d, and 4-7d after burn compared with controls. Functional enrichment analysis of those DEGs indicated significant enrichment of inflammatory/immune related processes throughout time points after burn, while, samples at later time points were also closely associated with cell activation regulation related processes. Short time series expression analysis of overlapping genes among the four lists of DEGs screened out two temporal gene expression profiles that exhibited decreasing and increasing expression trend across times after burn, and genes contained in those two profiles might be related to pathologic changes after severe burn. [ABSTRACT FROM AUTHOR]

Abstract Background The S100 protein family is implicated in tumor invasion and metastasis, but its prognostic roles in gastric cancer (GC) has not been elucidated. Materials and methods In the current study, Kaplan-Meier plotter (KM plotter) database integrated the expression data and survival information of 1065 GC patients were downloaded from the Gene Expression Omnibus (GEO) (GSE22377, GSE14210 and GSE51105) that published by the three major cancer centers (Berlin, Bethesda and Melbourne). Then this database was used to explore the prognostic values of mRNA expression of each individual S100 in GC patients. We further assessed the prognostic value of S100 in different Lauren classifications, clinicopathological features and clinical treatment of gastric cancer. Results Expression of 12 members of the S100 family correlated with overall survival (OS) for all GC patients. Increased expression of S100A3, S100A5, S100A7, S100A7A, S100A11, S100A13, S100Z and S100 G were found to be strongly associated with worse survival, while S100A8, S100A9, S100B and S100 P were correlated with better prognosis in all GC patients. Further assessment of prognostic values of S100 in gastric cancer with different clinical features indicated that different S100 members may interact with different signaling pathways and exerted different functions in gastric cancer development. Conclusions Although the results should be further testified in clinical studies, our findings offer new insights into the contribution of S100 members to GC progression and might promote development of S100 targeted reagents for treating GC. [ABSTRACT FROM AUTHOR]

The role of transcription factors in cancer has attracted significant attention. Although genetic models indicate MIST1 functions as a tumor suppressor in mice, its role in human pancreatic cancer is unclear. We explored the expression and function of MIST1 in pancreatic cancer. Analysis of three GEO datasets (GSE16515, GSE15471, and GSE62165) showed MIST1 mRNA was significantly downregulated in human pancreatic cancer compared to normal pancreatic tissues. Moreover, MIST1 protein and mRNA expression were downregulated in pancreatic cancer cell lines compared to normal cells. Immunohistochemistry confirmed MIST1 was downregulated in human pancreatic cancer tissues (n = 47) and associated with differentiation. In vitro, overexpression of MIST1 reduced pancreatic cancer cell growth, migration, and invasion. In vivo, overexpression of MIST1 retarded tumor xenograft growth and decreased tumor cell dissemination to the liver. Furthermore, MIST1 reversed the epithelial-mesenchymal transition by downregulating Snail and upregulating E-cadherin. Knockdown of E-cadherin promoted the migration and invasion of cancer cells overexpressing MIST1. In conclusion, this study indicates restoring the expression of MIST1 reversed the EMT and reduced the tumorigenicity of pancreatic cancer cells partly via the Snail/E-cadherin pathway. [ABSTRACT FROM AUTHOR]

Lung adenocarcinoma (LAC) is the most lethal cancer and the leading cause of cancer-related death worldwide. The identification of meaningful clusters of co-expressed genes or representative biomarkers may help improve the accuracy of LAC diagnoses. Public databases, such as the Gene Expression Omnibus (GEO), provide rich resources of valuable information for clinics, however, the integration of multiple microarray datasets from various platforms and institutes remained a challenge. To determine potential indicators of LAC, we performed genome-wide relative significance (GWRS), genome-wide global significance (GWGS) and support vector machine (SVM) analyses progressively to identify robust gene biomarker signatures from 5 different microarray datasets that included 330 samples. The top 200 genes with robust signatures were selected for integrative analysis according to "guilt-by-association" methods, including protein-protein interaction (PPI) analysis and gene co-expression analysis. Of these 200 genes, only 10 genes showed both intensive PPI network and high gene co-expression correlation (r > 0.8). IPA analysis of this regulatory networks suggested that the cell cycle process is a crucial determinant of LAC. CENPA, as well as two linked hub genes CDK1 and CDC20, are determined to be potential indicators of LAC. Immunohistochemical staining showed that CENPA, CDK1 and CDC20 were highly expressed in LAC cancer tissue with co-expression patterns. A Cox regression model indicated that LAC patients with CENPA+/CDK1+ and CENPA+/CDC20+ were high-risk groups in terms of overall survival. In conclusion, our integrated microarray analysis demonstrated that CENPA, CDK1 and CDC20 might serve as novel cluster of prognostic biomarkers for LAC, and the cooperative unit of three genes provides a technically simple approach for identification of LAC patients. [ABSTRACT FROM AUTHOR]

Aims The purpose of this study was to propose a pipeline to identify prognostic signature for HCC overall survival (OS) prediction based on HCC gene expression datasets from The Cancer Genome Atlas (TCGA). Results Differential expression analysis identified 3573 genes aberrantly expressed (DEGs) in HCC samples. Univariate cox regression analysis obtained 1605 and 1067 HCC OS and relapse free survival (RFS) related genes, which are abbreviated as OS-Gene and RFS-Gene respectively. Besides, there are 55 overlaps among DEGs, OS-Genes and RFS-Genes. Further prioritization of the 55 overlapping genes through Sure Independence Screening (SIS) resulted in 6 genes, including SRL, TTC26, CPSF2, TAF3, C16orf46 and CSN1S1, and the prognostic signature is the weighted combination of their expression values. Kaplan-Meier analysis based on the prognostic score (PS) of every sample indicates higher PS is associated with better HCC OS. Robustness of the prognostic signature was evaluated through another HCC gene expression datasets from the Gene Expression Omnibus (GEO). What's more, univariate and multivariate cox regression analysis indicate significant associations between stage/PS and HCC OS. Conclusions Our study provides a pipeline for the identification of prognostic signature for HCC OS prediction, which should also be suit for other types of cancers. [ABSTRACT FROM AUTHOR]

Through band unification and inter-calibration this paper develops and presents a method to construct virtual dual-view sensors from compatible geostationary and low-Earth-orbiting (LEO) sensors such that spectrally unified and radiometrically consistent observations from two different angles can be acquired using these virtual sensors. Results for three virtual dual-view sensors constructed from Himawari-8/AHI (one of the next generation of geostationary sensors) paired with MODIS (Aqua and Terra) and VIIRS are reported. Over 1270 representative Hyperion passes were used to reproduce, by spectral band integration, “simultaneous” observations by the three pairs of sensors, and linear relationships between AHI-MODIS and AHI-VIIRS were established, allowing the conversion of MODIS bands and VIIRS bands to AHI bands. For 95% of the sample pixels, a maximum reflectance conversion error < 0.004 was achieved. Following band conversion, inter-calibration was conducted using a ray-matching technique, involving up to 2100 matchup areas from 20 months of imagery. Overall the final calibration accuracy is high as indicated by high correlation r 2 (~0.98), small estimated parameter errors, small regression errors and negligible regression biases. The temporal drifting of the paired-sensors over a 20 month period was also analysed. It shows that all the involved sensors are very stable. Accurate inter-calibration not only provides an economical solution for the calibration and validation of remote sensors, it is also essential for synergetic multi-sensor applications. Lack of sufficient information from single-view sensors has been a common bottleneck in many remote sensing applications. Constructing virtual dual-view sensors using the presented method provides an effective way to overcome the limitations of single-view sensors, without incurring extra costs. The method can be applied to other next generation geostationary sensors leading to near global coverage and enhanced products. Inter-calibration between geostationary sensors, such as Himawari AHI – and GOES-R ABI, may be conducted using the LEO sensors as bridges. [ABSTRACT FROM AUTHOR]

Background MiR-452-5p has been reported to be down-regulated in prostate cancer, affecting the development of this type of cancer. However, the molecular mechanism of miR-452-5p in prostate cancer remains unclear. Therefore, we investigated the network of target genes of miR-452-5p in prostate cancer using bioinformatics analyses. Materials and methods We first analyzed the expression profiles and prognostic value of miR-452-5p in prostate cancer tissues from a public database. Gene Ontology (GO), the Kyoto Encyclopedia of Genes and Genomes (KEGG), PANTHER pathway analyses, and a disease ontology (DG) analysis were performed to find the molecular functions of the target genes from GSE datasets and miRWalk. Finally, we validated hub genes from the protein–protein interaction (PPI) networks of the target genes in the Human Protein Atlas (HPA) database and Gene Expression Profiling Interactive Analysis (GEPIA). Narrowing down the optimal target genes was conducted by seeking the common parts of up-regulated genes from GEPIA, down-regulated genes from GSE datasets, and predicted genes in miRWalk. Results Based on mining of GEO and ArrayExpress microarray chips and miRNA-Seq data in the TCGA database, which includes 1007 prostate cancer samples and 387 non-cancer samples, miR-452-5p is shown to be down-regulated in prostate cancer. GO, KEGG, and PANTHER pathway analyses suggested that the target genes might participate in important biological processes, such as transforming growth factor beta signaling and the positive regulation of brown fat cell differentiation and mesenchymal cell differentiation, as well as the Ras signaling pathway and pathways regulating the pluripotency of stem cells and arrhythmogenic right ventricular cardiomyopathy (ARVC). Nine genes—GABBR, PNISR, NTSR1, DOCK1, EREG, SFRP1, PTGS2, LEF1, and BMP2—were defined as hub genes in the PPI network. Three genes—FAM174B, SLC30A4, and SLIT1—were jointly shared by GEPIA, the GSE datasets, and miRWalk. Conclusions Down-regulated miR-452-5p might play an essential role in the tumorigenesis of prostate cancer. [ABSTRACT FROM AUTHOR]

Osteosarcoma (OS) is a common primary malignancy in children and adolescents with relative high survival rate after chemotherapy. While, the toxicity of chemotherapy and personalized different response to chemotherapy makes it difficult for the selection of therapeutics and improvement of diagnosis. In this study, we conducted a combined analysis of two types of microarray datasets (gene expression and DNA methylation) from the Gene Expression Omnibus (GEO). Differential methylation sites (DMS) were identified by the IMA package and differential expression genes (DEGs) were screened out via the limma package. A total of 11,242 DMS (corresponding to 3080 genes (DMGs)) and 337 DEGs, with 40 overlaps (OS genes) between DEGs and DMGs, were identified. Enriched functions of OS genes were obtained through the Database for Annotation, Visualization and Integrated Discovery (DAVID). The OS genes were mainly enriched in the biological processes related to inflammatory/immune response and Pertussis pathways and Hematopoietic cell lineage pathways. Besides, OS-specific disease network was obtained, and found that UBS and NRF1 were regulated by multiple OS genes. Kaplan Meier analysis of OS genes identified BHMT2, DOCK2, DNALI1 and RIPK3 as significant OS survival-related genes. SEMA3A and PRAME are included in the 40 OS genes and within the top 10 most up-regulated DEGs. Their expression changes were further validated in U2OS osteosarcoma cell lines and hOB normal cell lines through quantitative PCR (qPCR) and consistent result with microarray analysis was obtained. Based on this study, some novel targets were identified for OS, which would be helpful in its early diagnosis and treatment. [ABSTRACT FROM AUTHOR]

For the first time, the spin axis orientation of an inactive box-wing geosynchronous satellite has been estimated from ground-based optical photometric observations of Echostar-2’s specular reflections. Recent photometric light curves obtained of Echostar-2 over four years suggest that unusually bright and brief specular reflections were occurring twice within an observed spin period. These bright and brief specular reflections suggested two satellite surfaces with surface normals separated by approximately 180°. The geometry between the satellite, the Sun, and the observing location at the time of each of the brightest observed reflections, was used to estimate Echostar-2’s equatorial spin axis orientation coordinates. When considering prograde and retrograde rotation, Echostar-2’s spin axis orientation was estimated to have been located within 30° of either equatorial coordinate pole. Echostar-2’s spin axis was observed to have moved approximately 180° in right ascension, within a time span of six months, suggesting a roughly one year spin axis precession period about the satellite’s angular momentum vector. [ABSTRACT FROM AUTHOR]

Background Non-small cell lung cancer (NSCLC) is the major leading cause of cancer-related deaths worldwide. This study aims to explore molecular mechanism of NSCLC. Methods Microarray dataset was obtained from the Gene Expression Omnibus (GEO) database, and analyzed by using GEO2R. Functional and pathway enrichment analysis were performed based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Then, STRING, Cytoscape and MCODE were applied to construct the Protein–protein interaction (PPI) network and screen hub genes. Following, overall survival (OS) analysis of hub genes was performed by using the Kaplan–Meier plotter online tool. Moreover, miRecords was also applied to predict the targets of the differentially expressed microRNAs (DEMs). Results A total of 228 DEGs were identified, and they were mainly enriched in the terms of cell adhesion molecules, leukocyte transendothelial migration and ECM-receptor interaction. A PPI network was constructed, and 16 hub genes were identified, including TEK , ANGPT1 , MMP9 , VWF , CDH5 , EDN1 , ESAM , CCNE1 , CDC45 , PRC1 , CCNB2 , AURKA , MELK , CDC20 , TOP2A and PTTG1 . Among the genes, expressions of 14 hub genes were associated with prognosis of NSCLC patients. Additionally, a total of 11 DEMs were also identified. Conclusion Our results provide some potential underlying biomarkers for NSCLC. Further studies are required to elucidate the pathogenesis of NSCLC. [ABSTRACT FROM AUTHOR]

The Yarkovsky-O’Keefe-Radzievskii-Paddack (YORP) effect is a proposed explanation for the observed rotation behavior of inactive satellites in Earth orbit. This paper further explores the YORP effect for highly asymmetric inactive satellites. Satellite models are developed to represent the GOES 8 and GOES 10 satellites, both of which are currently inactive in geosynchronous Earth orbit (GEO). A simple satellite model for the GOES 8 satellite is used to analyze the short period variations of the angular velocity and obliquity as a result of the YORP effect. A more complex model for the rotational dynamics of the GOES 8 and GOES 10 satellites are developed to probe their sensitivity and to match observed spin periods and states of these satellites. The simulated rotation periods are compared to observations for both satellites. The comparison between YORP theory and observed rotation rates for both satellites show that the YORP effect could be the cause for the observed rotational behavior. The YORP model also predicts a novel state for the GOES 8 satellite, namely that it could periodically fall into a tumbling rotation state. Recent observations of this satellite are consistent with this prediction. [ABSTRACT FROM AUTHOR]

With a few hundred spacecraft launched to date with electric propulsion (EP), it is possible to conduct an epidemiological study of EP's on orbit reliability. The first objective of the present work was to undertake such a study and analyze EP's track record of on orbit anomalies and failures by different covariates. The second objective was to provide a comparative analysis of EP's failure rates with those of chemical propulsion. Satellite operators, manufacturers, and insurers will make reliability- and risk-informed decisions regarding the adoption and promotion of EP on board spacecraft. This work provides evidence-based support for such decisions. After a thorough data collection, 162 EP-equipped satellites launched between January 1997 and December 2015 were included in our dataset for analysis. Several statistical analyses were conducted, at the aggregate level and then with the data stratified by severity of the anomaly, by orbit type, and by EP technology. Mean Time To Anomaly (MTTA) and the distribution of the time to (minor/major) anomaly were investigated, as well as anomaly rates. The important findings in this work include the following: (1) Post-2005, EP's reliability has outperformed that of chemical propulsion; (2) Hall thrusters have robustly outperformed chemical propulsion, and they maintain a small but shrinking reliability advantage over gridded ion engines. Other results were also provided, for example the differentials in MTTA of minor and major anomalies for gridded ion engines and Hall thrusters. It was shown that: (3) Hall thrusters exhibit minor anomalies very early on orbit, which might be indicative of infant anomalies, and thus would benefit from better ground testing and acceptance procedures; (4) Strong evidence exists that EP anomalies (onset and likelihood) and orbit type are dependent, a dependence likely mediated by either the space environment or differences in thrusters duty cycles; (5) Gridded ion thrusters exhibit both infant and wear-out failures, and thus would benefit from a reliability growth program that addresses both these types of problems. [ABSTRACT FROM AUTHOR]

Glioblastoma represents one of the most aggressive malignant brain tumors with high morbidity and motility. Demethylation drugs have been developed for its treatment with little efficacy has been observed. The purpose of this study was to screen therapeutic targets of demethylation drugs or bioactive molecules for glioblastoma through systemic bioinformatics analysis. We firstly downloaded genome-wide expression profiles from the Gene Expression Omnibus (GEO) and conducted the primary analysis through R software, mainly including preprocessing of raw microarray data, transformation between probe ID and gene symbol and identification of differential expression genes (DEGs). Secondly, functional enrichment analysis was conducted via the Database for Annotation, Visualization and Integrated Discovery (DAVID) to explore biological processes involved in the development of glioblastoma. Thirdly, we constructed protein-protein interaction (PPI) network of interested genes and conducted cross analysis for multi datasets to obtain potential therapeutic targets for glioblastoma. Finally, we further confirmed the therapeutic targets through real-time RT-PCR. As a result, biological processes that related to cancer development, amino metabolism, immune response and etc. were found to be significantly enriched in genes that differential expression in glioblastoma and regulated by 5′aza-dC. Besides, network and cross analysis identified ACAT2 , UFC1 and CYB5R1 as novel therapeutic targets of demethylation drugs which also confirmed by real time RT-PCR. In conclusions, our study identified several biological processes and genes that involved in the development of glioblastoma and regulated by 5′aza-dC, which would be helpful for the treatment of glioblastoma. [ABSTRACT FROM AUTHOR]

Although significant improvements in efficiency and performance of communication satellites have been achieved in the past decades, it is expected that the demand for new platforms in Geostationary Orbit (GEO) and for the On-Orbit Servicing (OOS) on the existing ones will continue to rise. Indeed, the GEO orbit is used for many applications including direct broadcast as well as communications. At the same time, Global Navigation Satellites System (GNSS), originally designed for land, maritime and air applications, has been successfully used as navigation system in Low Earth Orbit (LEO) and its further utilization for navigation of geosynchronous satellites becomes a viable alternative offering many advantages over present ground based methods. Following our previous studies of GNSS signal characteristics in Medium Earth Orbit (MEO), GEO and beyond, in this research we specifically investigate the processing of different GNSS signals, with the goal to determine the best navigation performance they can provide in a GEO mission. Firstly, a detailed selection among different GNSS signals and different combinations of them is discussed, taking into consideration the L1 and L5 frequency bands, and the GPS and Galileo constellations. Then, the implementation of an Orbital Filter is summarized, which adaptively fuses the GN1SS observations with an accurate orbital forces model. Finally, simulation tests of the navigation performance achievable by processing the selected combination of GNSS signals are carried out. The results obtained show an achievable positioning accuracy of less than one meter. In addition, hardware-in-the-loop tests are presented using a COTS receiver connected to our GNSS Spirent simulator, in order to collect real-time hardware-in-the-loop observations and process them by the proposed navigation module. [ABSTRACT FROM AUTHOR]

Foam is of practical interest in many industrial processes, and can be used for blocking gas channeling and mobility control during the process of CO 2 storage and improved oil recovery (IOR). It is important to develop new kinds of foam agents, which can tolerate high temperature and salinity under complex reservoir conditions. It is also desirable to develop chemicals that have CO 2 -sensitivity for selective channeling blocking. CO 2 -sensitivity is referred to that injected chemical can be converted into effective foam agent in formation water with CO 2 presence. In this paper, an organic amine, octadecyl dipropylene triamine, was studied in terms of chemical mechanisms for foam generation and CO 2 -sensitivity. The chemical can be converted into a Gemini surfactant like agent to generate CO 2 foams in-situ. The effects of important influencing factors on foaming performance at reservoir conditions were evaluated, including CO 2 purity, chemical concentration, temperature, pressure and water salinity. The results indicated that the amine chemical has good CO 2 -sensitivity for generation of CO 2 foams and has exhibited extraordinary features with high temperature and salinity tolerance. CO 2 flooding assisted by this type of chemical will broaden the scope of reservoirs that can be candidates for CO 2 IOR and geo-storage. [ABSTRACT FROM AUTHOR]

In this paper, a novel semi-analytical approach is developed for solving minimum-time and minimum-fuel low-thrust transfers to geosynchronous orbit. The proposed method is mainly based on two intuitive control strategies, with one focusing on the instantaneous variation of orbit elements, and the other concerning the cumulative effect of thrust force. By optimizing the objective functions of the two strategies, analytical thrust-steering laws are derived for each case. With the use of a refined efficiency factor, thrust arc locations can also be optimized during the transfer. In addition, selection of weights and other parameters further improves the performance of the resulting trajectories. Finally, two examples of transfers are presented. The computed trajectories are very close to, or even better than the optimal results obtained from the traditional direct and indirect techniques. Due to its simplicity and good performance, the proposed method would be particularly useful for preliminary mission analysis. [ABSTRACT FROM AUTHOR]

An in-depth study, using simulations and covariance analysis, is performed to identify the optimal sequence of observations to obtain the most accurate orbit propagation. The accuracy of the results of an orbit determination/improvement process depends on: tracklet length, number of observations, type of orbit, astrometric error, time interval between tracklets and observation geometry. The latter depends on the position of the object along its orbit and the location of the observing station. This covariance analysis aims to optimize the observation strategy taking into account the influence of the orbit shape, of the relative object-observer geometry and the interval between observations. [ABSTRACT FROM AUTHOR]

The development of electrically propelled geostationary platforms, together with alternative strategies to reach geostationary orbit, increase the interest for autonomous satellite localization and particularly GNSS navigation for high altitude orbits. It is known that GNSS navigation in GTO/GEO is much more difficult than in LEO since the GNSS receiver is often or permanently at an altitude greater than the altitude of the GNSS constellations, making the GNSS signals drastically less available and weaker. This work is about GPS and Galileo navigation on GEO and GTO orbits, with revised hypotheses compared to studies sometimes more than 15 years old. Moreover, the study goes beyond GNSS geometrical visibility by dealing with operating thresholds and showing the sensitivity to key GNSS receiver thresholds and simulation hypotheses. Comprehensive simulation results and analyses come along with a discussion of the operational benefits of using GPS and Galileo navigation. These data eventually set the ground for a discussion of the key technical options (number and antenna types, GNSS function architecture, signal processing algorithms, orbital filter…). It is shown that using GNSS for GTOGEO orbits is feasible, even considering current spaceborne receivers state-of-the-art, and provides most of the acclaimed benefits of GNSS in LEO, among them more accurate spacecraft localization, precise onboard absolute time and increased autonomy. [ABSTRACT FROM AUTHOR]

Space Solar Power Station (SSPS) is a kind of space electrical power system which converts space solar energy into electrical power and transmits it to Earth ground receiving station, the energy from which is a kind of clean and renewable resource. Compared to others, the SSPS with concentrator represents the developing direction of SPSS in the future, among which, Integrated Symmetrical Concentrated system (ISC) proposed by NASA has the advantage of high collecting sunlight efficiency. However, the addition of concentrator system results in complicated mechanism and is more difficult to control in motion than before; therefore, it is particularly important to plan the effective and realizable motion trajectory when travels on its orbit in the space. For the purpose, a method of trajectory planning for this kind of system is proposed in this paper to make concentrator to realize real-time solar tracking by means of the cooperative rotation of transverse truss and concentrator on the Geostationary Orbit (GEO), and the simulation demonstrates its validation and feasibility. Finally, two improved measures especially solution 2 are presented to mitigate the overheating as the result of nonuniformity of the flux distribution on PV array caused by rotation of concentrator. [ABSTRACT FROM AUTHOR]

As the fierce battle with cancer is now expanding to companion animals, effective treatment of canine mammary carcinomas (CMT), as the most frequently diagnosed tumor in intact dogs, is becoming a crucial issue. Although many studies have been carried out concerning the clinical application of mammary tumor biomarkers, no ideal biomarker has yet been identified in CMT. Therefore, in this work, we develop EDIL3 as a CMT biomarker having significantly higher expression levels in CMT samples compared to those in controls in GSE13754, GSE22516 and GSE25586 datasets, which suggest that EDIL3 is a gene related to tumorigenesis. We also validate the significantly high expression levels of EDIL3 in CMT samples using our sequencing canine samples. ROC curves analysis showed that in comparison with HER2 reported as predictive factor for CMT patients, EDIL3 exhibits stronger power for CMT recognizing. Moreover, we also find that low expression levels of EDIL3 are associated with advanced grade status in CMT, which indicate a negative correlation between EDIL3 and CMT development. GSEA is employed to unveil the underlying mechanism of this interesting function of EDIL3 in CMT development, and it suggests that the expression level of EDIL3 is related to immunity pathway. Finally, CIBERSORT analysis is employed in this study in order to further explore the relationship between EDIL3 and immunity in CMT, and it unveils that EDIL3 has stably positive correlation with follicular helper T cells and negative correlation with NK resting cells in CMT. Our study develops EDIL3 as a biomarker for assisting CMT distinction, highlighting the relationship of EDIL3 with the infiltrations of follicular helper T cells and NK resting cells, which could be a new potential therapy target for CMT and provide bioinformatics basis for later clinical experiment validation. [ABSTRACT FROM AUTHOR]

Increasing numbers of Geostationary Earth Orbit satellites have led to the requirement of accurate station keeping and precise orbit prediction to avoid collision between satellites. In the case of ground-based optical observation, angular resolution is better than other tracking systems, such as radar systems; however, the observation time of optical observation is limited by weather or lighting conditions. To develop an effective optical observation strategy, the optical observation campaign from January to February 2014 for Communication, Ocean and Meteorological Satellite (COMS) was conducted. Because COMS is a controlled satellite with station keeping manoeuvres performed twice a week, the observation results for 1- and 2-day observations were analysed. Sparse and sporadic cases for the sequential observation of multiple satellites and a dense case for the intensive observation of specific targets were assumed for the experiments. In the 1-day arc observation experiment, the estimated orbits for dense observation cases over 10% of the orbital period showed that the maximum difference was less than 40 km (station keeping area) for 7-day propagation compared to the estimation result using the whole 1-day measurement. For the 2-day arc observation, the orbit estimation difference could be maintained within 2 km using a more frequent observation than the 1-h interval for 13 h that was used in the sparse case. Additionally, the longitudinal and latitudinal positions via the estimation result using the optical observation were compared with the Two-Line Elements (TLEs) and operator’s data. Through this study, an adequate optical tracking strategy was studied, and the possibility of cooperation with other systems was also validated. [ABSTRACT FROM AUTHOR]

Summary A major hurdle facing tuberculosis (TB) investigators who want to utilize a rapidly growing body of data from both systems biology approaches and omics technologies is the lack of a standard vocabulary for data annotation and reporting. Lacking a means to readily compare samples from different research groups, a significant quantity of potentially informative data is largely ignored by researchers. To facilitate standardizing data across studies, a simple ontology of TB terms was developed to provide a common vocabulary for annotating data sets. New terminology was developed to address animal models and experimental systems, and existing clinically focused terminology was modified and adapted. This ontology can be used to annotate host TB data in public databases and collaborations, thereby standardizing database searches and allowing researchers to more easily compare results. To demonstrate the utility of a standard TB ontology for host systems biology, a web application was developed to annotate and compare human and animal model gene expression data sets. [ABSTRACT FROM AUTHOR]

• We found that ZFC3H1 expression was connected with the prognosis of multiple malignant tumors. • Our study first reveals that ZFC3H1 could serve as a novel prognostic biomarker of pan-cancer, especially colorectal cancer. • Real-Time PCR and Western Blot were used to confirm the role of ZFC3H1 in the colorectal cancer. Zinc finger C3H1 domain-containing protein (ZFC3H1) is differentially expressed between primary tumor and the normal in most cancers. Additionally, a recent study has suggested that ZFC3H1 could serve as a novel marker for the prognosis of prostate adenocarcinoma (PRAD). However, the relationship between ZFC3H1 expression and the prognostic values in most tumors remains unclear. Our study is mainly for exploring the prognosis of ZFC3H1 in pan-cancer and for further discovering a potential therapeutics target. Based on the clinical big data, we performed a pan-cancer analysis of ZFC3H1 , including gene expression, survival prognosis, genetic alteration, protein phosphorylation, immune infiltration and enrichment analysis. In addition, Real-Time PCR and Western Blot were used to further confirm the role of ZFC3H1 in the colorectal cancer. We found that ZFC3H1 expression was connected with the prognosis of multiple malignant tumors. Furthermore, we also observed that ZFC3H1 was highly expressed in colorectal cancer through Real-Time PCR and Western Blot. The primary tumors presented higher phosphorylation level of the S655 site in lung adenocarcinoma, colon adenocarcinoma and uterine corpus endometrial carcinoma. ZFC3H1 expression was positively correlated with the immune infiltration of Cancer-associated fibroblasts (CAFs) in some tumors, such as liver hepatocellular carcinoma. And RNA surveillance pathways may be closely associated with the occurrence of tumors. Our study first reveals that ZFC3H1 could serve as a novel prognostic biomarker of pan-cancer, especially colorectal cancer. [ABSTRACT FROM AUTHOR]

Considering the limited number of studies on the biological effects on human health of cyanobacterial compounds that cause taste and odor, the present study assessed the cytotoxic and genotoxic potentials of 2-methylisoborneol (2-MIB) and geosmin (GEO) using the MTT assay and the in vitro comet and cytokinesis-block micronucleus (CBMN-Cyt) assays in human HepG2 cells. The toxicogenomics of genes responsive to DNA damage and metabolization by the exposure of cells to 2-MIB and GEO were also investigated. The results showed that concentrations of 2-MIB and GEO above 100 and 75 μg/mL, respectively, were cytotoxic to HepG2 cells. Doses of 2-MIB (12.5, 25, 50, 75 and 100 μg/mL) and GEO (12.5, 25, 50, and 75 μg/mL) were unable to induce neither DNA damage nor events associated with chromosomal instability. Similarly, no concentration of each compound induced increments in the expression of CDKN1A , GADD45α , MDM2 and TP53 DNA damage responsive genes as well as in CYP1A1 and CYP1A2 metabolizing genes. Although cytotoxicity was observed, concentrations that caused it are much higher than those expected to occur in aquatic environments. Thus, environmentally relevant concentrations of both compounds are not expected to exhibit cytotoxicity or genotoxicity to humans. [ABSTRACT FROM AUTHOR]

Abstract: Awareness of objects and events in and around the Geostationary Earth Orbit satellite belt is currently limited, and the situation is worsening as more satellites are added and the satellites trend toward smaller sizes. A potential solution is to deploy observation satellites near the geostationary altitude to improve monitoring and object characterization capabilities, but the vastness of the geostationary belt creates several unique challenges. Many of these challenges can potentially be mitigated by proper orbit and constellation designs. First, a methodology for evaluating such designs through a system simulation tool is described. Second, an analysis is performed including a variety of circular orbit, eccentric orbit, and maneuvering constellations of geostationary observer satellites. The analysis shows that non-circular orbit designs can result in improved performance for various range- and coverage-based inspection criteria. These tools are useful in mission planning and constellation design, and can be easily expanded to include additional constellation metrics or time history metrics on individual GEO objects such as illumination conditions. [Copyright &y& Elsevier]