Infection of Human Coronary Artery Endothelial Cells by Group B Streptococcus Contributes to Dysregulation of Apoptosis, Hemostasis, and Innate Immune Responses by Claudia Beyrich, Jürgen Löffler, Anna Kobsar, Christian P. Speer, Susanne Kneitz, Martin Eigenthaler

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Tissue-restricted expression of Nrf2 and its target genes in zebrafish with gene-specific variations in the induction profiles. by Hitomi Nakajima, Yaeko Nakajima-Takagi, Tadayuki Tsujita, Shin-Ichi Akiyama, Takeshi Wakasa, Katsuki Mukaigasa, Hiroshi Kaneko, Yutaka Tamaru, Masayuki Yamamoto, Makoto Kobayashi

“…Seven zebrafish genes (gstp1, mgst3b, prdx1, frrs1c, fthl, gclc and hmox1a) suitable for WISH analysis were selected from candidates for Nrf2 targets identified by microarray analysis. …”
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Inferring pathway activity toward precise disease classification. by Eunjung Lee, Han-Yu Chuang, Jong-Won Kim, Trey Ideker, Doheon Lee

“…The advent of microarray technology has made it possible to classify disease states based on gene expression profiles of patients. …”
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Prevalence and characteristics of Livestock-Associated Methicillin-Resistant Staphylococcus aureus (LA-MRSA) isolated from chicken meat in the province of Quebec, Canada. by Jocelyn Bernier-Lachance, Julie Arsenault, Valentine Usongo, Éric Parent, Josée Labrie, Mario Jacques, François Malouin, Marie Archambault

“…A total of 309 chicken drumsticks and thighs were randomly selected in 2013 from 43 retail stores in the Monteregie. …”
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The significance of long chain non-coding RNA signature genes in the diagnosis and management of sepsis patients, and the development of a prediction model by Yong Bai, Jing Gao, Yuwen Yan, Xu Zhao

“…The purpose of this study was to determine the value of Long chain non-coding RNA (LncRNA) RP3_508I15.21, RP11_295G20.2, and LDLRAD4_AS1 in the diagnosis of adult sepsis patients and to develop a Nomogram prediction model.MethodsWe screened adult sepsis microarray datasets GSE57065 and GSE95233 from the GEO database and performed differentially expressed genes (DEGs), weighted gene co-expression network analysis (WGCNA), and machine learning methods to find the genes by random forest (Random Forest), least absolute shrinkage and selection operator (LASSO), and support vector machine (SVM), respectively, with GSE95233 as the training set and GSE57065 as the validation set. …”
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Expression profiles and bioinformatic analysis of circular RNA in rheumatic heart disease: potential hsa_circ_0001490 and hsa_circ_0001296 as a diagnostic biomarker by Xiaoliang Chen, Lina Chen, Li Bi, Shunying Zhao, Xiaoyan Hu, Ni Li, Linwen Zhu, Guofeng Shao

“…The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted to predict the potential functions of the differentially expressed genes and RHD-related pathways.ResultsFour circRNAs were selected from circRNA microarray data. qRT-PCR confirmed that hsa_circ_0001490 and hsa_circ_0001296 were significantly upregulated in RHD plasma (4.28-fold, P < 0.001; 5.24-fold, P < 0.001, respectively). …”
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A Synopsis of Serum Biomarkers in Cutaneous Melanoma Patients by Pierre Vereecken, Frank Cornelis, Nicolas Van Baren, Valérie Vandersleyen, Jean-François Baurain

“…However, the poor sensitivity and specificity of those markers and many other molecules are serious limitations for their routine use in both early (AJCC stage I and II) and advanced stages of melanoma (AJCC stage III and IV). Microarray technology and proteomic research will surely provide new candidates in the near future allowing more accurate definition of the individual prognosis and prediction of the therapeutic outcome and select patients for early adjuvant strategies.…”
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Identification and validation of TSPAN13 as a novel temozolomide resistance-related gene prognostic biomarker in glioblastoma. by Haofei Wang, Zhen Liu, Zesheng Peng, Peng Lv, Peng Fu, Xiaobing Jiang

“…Using LASSO Cox analysis, we selected 12 TMZR-RDEGs to construct a risk score model, which was evaluated for performance through survival analysis, time-dependent ROC, and stratified analyses. …”
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Have maternal or paternal ages any impact on the prenatal incidence of genomic copy number variants associated with fetal structural anomalies? by Marta Larroya, Marta Tortajada, Eduard Mensión, Montse Pauta, Laia Rodriguez-Revenga, Antoni Borrell

“…We conducted a non-paired case-control study (1:2 ratio) among pregnancies undergoing chromosomal microarray analysis (CMA) because of fetal ultrasound anomalies, from December 2012 to May 2020. …”
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Cuproptosis genes in predicting the occurrence of allergic rhinitis and pharmacological treatment. by Ting Yi

“…<h4>Results</h4>Four AR signature genes (MRPS30, CLPX, MRPL13, and MRPL53) were selected by the MCC, EPC, BottleNeck, and Closeness algorithms. …”
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Bioinformatic-based differential expression gene expressions of epithelial mesenchymal transformation in diabetic kidney disease and prediction of traditional Chinese medicine by Liu Wu, Zhou Yi, Yu Fang-ning, Zhang Ning

“…ObjectiveBased upon the bioinformatic analysis of gene chip data between patients with diabetic kidney disease （DKD） and normal controls， differentially expressed genes of epithelial mesenchymal transformation of DKD were screened for elucidating its pathogenesis and predicting the potential therapeutic Chinese medicine for DKD.MethodsGSE23338 microarray data were downloaded from gene expression omnibus， related differentially expressed genes screened by R language and differentially expressed genes analyzed by Gene Ontology， Kyoto Encyclopedia of Genes and Genomes. …”
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Cellular senescence-associated genes in rheumatoid arthritis: Identification and functional analysis. by You Ao, Qing Lan, Tianhua Yu, Zhichao Wang, Jing Zhang

“…In our study, we analyzed RA microarray data from the Gene Expression Omnibus (GEO) and focused on cellular senescence genes from the CellAge database. …”
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Integrated Bioinformatics Analysis of Hub Genes and Pathways in Anaplastic Thyroid Carcinomas by Xueren Gao, Jianguo Wang, Shulong Zhang

“…The aim of the present study was to identify hub genes and pathways in ATC by microarray expression profiling. Two independent datasets (GSE27155 and GSE53072) were downloaded from GEO database. …”
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Immune-related gene characterization and biological mechanisms in major depressive disorder revealed based on transcriptomics and network pharmacology by Shasha Wu, Shasha Wu, Qing Jiang, Jinhui Wang, Jinhui Wang, Daming Wu, Yan Ren

“…Subsequently, gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Cytoscape plugin CluGO, and Gene Set Enrichment Analysis (GSEA) were utilized to identify immune-related genes. The final selection of immune-related hub genes was determined through the least absolute shrinkage and selection operator (Lasso) regression analysis and PPI analysis. …”
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Bioinformatic identification of Single Nucleotide Polymorphisms (SNPs) in keratin-associated protein genes in alpacas (Vicugna pacos) by Deyanira Figueroa, Manuel More, Gustavo Gutiérrez, F. Abel Ponce de León

“…Of these, 35 SNPs were included in the 76K alpaca SNP microarray and 32 SNPs were confirmed in a population of 936 alpacas.…”
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Pairing of competitive and topologically distinct regulatory modules enhances patterned gene expression by Itai Yanai, L Ryan Baugh, Jessica J Smith, Casey Roehrig, Shai S Shen‐Orr, Julia M Claggett, Andrew A Hill, Donna K Slonim, Craig P Hunter

“…We used RNAi and time series, whole‐genome microarray analyses to systematically perturb and characterize components of a Caenorhabditis elegans lineage‐specific transcriptional regulatory network. …”
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Evaluation of LRIG1 Expression in Larynx Pathologies by Yavuz Gündoğdu, Orhan Asya, Ayşegül Gönen, Tajaddin Muradov, Selim Yiğit Erçetin, Zeliha Leyla Cinel, Ali Cemal Yumuşakhuylu

“…Patients’ data were obtained from the medical records. The tissue microarray method was used to evaluate specimens. Results: There was a statistically significant difference between the tumor differentiation, diagnosis, and the expression of LRIG1 (respectively p=0.045, p&lt;0.001). …”
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Common gene-network signature of different neurological disorders and their potential implications to neuroAIDS. by Vidya Sagar, S Pilakka-Kanthikeel, Paola C Martinez, V S R Atluri, M Nair

“…An mRNA microarray analysis in HIV-infected monocytes showed significant changes in the expression of several genes of this in silico derived common pathway which suggests the possible physiological relevance of this gene-circuit in driving neuroAIDS condition. …”
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Investigation of Underlying Biological Association and Targets between Rejection of Renal Transplant and Renal Cancer by Yinwei Chen, Zhanpeng Liu, Qian Yu, Xu Sun, Shuai Wang, Qingyi Zhu, Jian Yang, Rongjiang Jiang

“…Finally, the PLAC8 was selected for further research, including its clinical and biological role. …”
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Bioinformatics-based analysis of autophagy-related genes and prediction of potential Chinese medicines in diabetic kidney disease by Yufeng Xing, Zining Peng, Chaoyang Ye

“…Methods: Data from sequencing microarrays GSE30528, GSE30529, and GSE1009 in the Gene Expression Omnibus (GEO) were employed. …”
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