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Showing 901 - 920 results of 1,096 for search '(( effective microarray ) OR ((( selective microarray ) OR ( detection microarray ))))', query time: 0.12s Refine Results
  1. 901

    Vitamin C Treatment Rescues Prelamin A-Induced Premature Senescence of Subchondral Bone Mesenchymal Stem Cells by Yan-Nv Qu, Li Zhang, Ting Wang, He-Yang Zhang, Ze-Ji Yang, Fang-Fang Yuan, Yan Wang, Si-Wei Li, Xiao-Xia Jiang, Xiao-Hua Xie

    Published 2020-01-01
    “…Importantly, after VC treatment, MSC/PLA showed enhanced therapy effect in the hind-limb ischemia model. In conclusion, prelamin A can accelerate SCB-MSC premature senescence by inducing DNA damage. …”
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  2. 902

    Exploration of the potential neurotransmitter or neuromodulator-like properties of harmine: evidence from synthesis to synaptic modulation by Zhejun Xie, Ning Cao, Manlin Li, Hanxue Wang, Huida Guan, Xuemei Cheng, Changhong Wang

    Published 2025-07-01
    “…Subsequently, the release, metabolism, and uptake pathways of harmine were investigated using rat brain synaptosomes and primary neural cells through mass spectrometry analysis. A human proteome microarray was employed to screen for harmine-binding receptors, followed by experimental validation.Results:Adipocyte plasma membrane-associated protein isoform X1 (APMAP-X1) could effectively catalyze the Pictet-Spengler reaction in mammals to generate tetrahydroharmine, which was subsequently oxidized by myeloperoxidase (MPO) to produce harmine. …”
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  3. 903

    Combining multi-omics analysis with machine learning to uncover novel molecular subtypes, prognostic markers, and insights into immunotherapy for melanoma by Songyun Zhao, Zihao Li, Kaibo Liu, Gaoyi Wang, Quanqiang Wang, Hua Yu, Wanying Chen, Hao Dai, Yijun Li, Jiaheng Xie, Yucang He, Liqun Li

    Published 2025-04-01
    “…Methods We obtained and processed transcriptomic data, including RNA expression profiles, methylation microarray data, gene mutation data, and clinical information, from the TCGA dataset using multi-omics analysis and machine learning techniques. …”
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    Article
  4. 904
  5. 905

    DSN1 may predict poor prognosis of lower-grade glioma patients and be a potential target for immunotherapy by Yulong Jia, Meiling Liu, Han Liu, Wenjia Liang, Qingyun Zhu, Chao Wang, Yake Chen, Yanzheng Gao, Zhendong Liu, Xingbo Cheng

    Published 2024-12-01
    “…DSN1 has been previously found to be positively correlated with various cancers. However, the effect of DSN1 or its methylation on the prognosis, molecular characteristics, and immune cell infiltration of low-grade glioma (LGG) has not yet been studied. …”
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    Article
  6. 906
  7. 907

    Bioinformatics analysis and experimental validation of potential targets and pathways in chronic kidney disease associated with renal fibrosis by Cui Huimin, Zhao Yuxin, Wang Peng, Gong Wei, Lin Hong, Li Na, Yang Jianjun

    Published 2025-04-01
    “…Conversely, when CHUK was further overexpressed, the inhibitory effect of miR-223-3p on epithelial-mesenchymal transition (EMT) was attenuated, confirming the specific interaction between miR-223-3p and CHUK. …”
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    Article
  8. 908

    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

    Published 2024-12-01
    “…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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  9. 909

    Resistome and Phylogenomics of <i>Escherichia coli</i> Strains Obtained from Diverse Sources in Jimma, Ethiopia by Mulatu Gashaw, Esayas Kebede Gudina, Guenter Froeschl, Ralph Matar, Solomon Ali, Liegl Gabriele, Amelie Hohensee, Thomas Seeholzer, Arne Kroidl, Andreas Wieser

    Published 2025-07-01
    “…Isolates exhibiting phenotypic resistance to beta-lactam antibiotics were further analyzed with a DNA microarray to confirm the presence of resistance-encoding genes. …”
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    Article
  10. 910

    Contribution of cuproptosis and immune-related genes to idiopathic pulmonary fibrosis disease by Chengji Jin, Jia Li, Qiaoyu Li, Lipeng Zhang, Shaomao Zheng, Qiong Feng, Yongjie Li, Yu Zheng, Qiuli Nie, Jin Liang, Jing Wang, Jing Wang

    Published 2025-02-01
    “…Additionally, multiple bioinformatics analyses were employed to identify immune-related biomarkers associated with the diagnosis of IPF, offering valuable insights for future treatment strategies.MethodsFour microarray datasets were selected from the Gene Expression Omnibus (GEO) collection for screening. …”
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  11. 911
  12. 912

    Large-scale genome-wide association studies and meta-analyses of longitudinal change in adult lung function. by Wenbo Tang, Matthew Kowgier, Daan W Loth, María Soler Artigas, Bonnie R Joubert, Emily Hodge, Sina A Gharib, Albert V Smith, Ingo Ruczinski, Vilmundur Gudnason, Rasika A Mathias, Tamara B Harris, Nadia N Hansel, Lenore J Launer, Kathleen C Barnes, Joyanna G Hansen, Eva Albrecht, Melinda C Aldrich, Michael Allerhand, R Graham Barr, Guy G Brusselle, David J Couper, Ivan Curjuric, Gail Davies, Ian J Deary, Josée Dupuis, Tove Fall, Millennia Foy, Nora Franceschini, Wei Gao, Sven Gläser, Xiangjun Gu, Dana B Hancock, Joachim Heinrich, Albert Hofman, Medea Imboden, Erik Ingelsson, Alan James, Stefan Karrasch, Beate Koch, Stephen B Kritchevsky, Ashish Kumar, Lies Lahousse, Guo Li, Lars Lind, Cecilia Lindgren, Yongmei Liu, Kurt Lohman, Thomas Lumley, Wendy L McArdle, Bernd Meibohm, Andrew P Morris, Alanna C Morrison, Bill Musk, Kari E North, Lyle J Palmer, Nicole M Probst-Hensch, Bruce M Psaty, Fernando Rivadeneira, Jerome I Rotter, Holger Schulz, Lewis J Smith, Akshay Sood, John M Starr, David P Strachan, Alexander Teumer, André G Uitterlinden, Henry Völzke, Arend Voorman, Louise V Wain, Martin T Wells, Jemma B Wilk, O Dale Williams, Susan R Heckbert, Bruno H Stricker, Stephanie J London, Myriam Fornage, Martin D Tobin, George T O'Connor, Ian P Hall, Patricia A Cassano

    Published 2014-01-01
    “…Publicly available microarray data confirmed differential expression of all three genes in lung samples from COPD patients compared with controls. …”
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  13. 913

    Bioinformatics-based screening and validation of PANoptosis-related biomarkers in periodontitis by Qing Sun, Qing Sun, JinYue Hu, JinYue Hu, RuYue Wang, RuYue Wang, ShuiXiang Guo, ShuiXiang Guo, GeGe Zhang, GeGe Zhang, Ao Lu, Ao Lu, Xue Yang, Xue Yang, LiNa Wang, LiNa Wang

    Published 2025-06-01
    “…Subnetworks were identified using the MCODE plugin. Key genes were selected based on integration with rank-sum test results. …”
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    Article
  14. 914

    CD226+ B cells in primary Sjögren’s syndrome: a key player in clinical manifestations and disease pathogenesis by Ping Zhao, Ping Zhao, Saizhe Song, Song Zhang, Cheng Peng, Wei Cheng, Xin Chang, Xin Chang, Changhao Xie, Zhongli Hu, Cuiping Liu

    Published 2025-07-01
    “…Multicolor immunofluorescence staining was applied to detect the co-expression of B cells and CD226 in the salivary gland of pSS patients.Microarray analysis was conducted to analyze the transcriptomic profiles of sorted CD226+ CD19+ B cells and CD226- CD19+ B cells.ResultsCD226 expression in the peripheral blood of pSS patients was significantly increased on T cells, CD19+ B cells and CD14+ monocytes, but significantly decreased on CD56+ NK cells.We identified a distinct CD226+CD19+ B cell subset that exhibited pathogenic features in pSS. …”
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  15. 915

    A novel polypeptide encoded by circSPIRE1 promotes prostate cancer proliferation and migration by restraining the ubiquitin-dependent degradation of LRP5 by Jintao Hu, Juanyi Shi, Junjie Wang, Yunfei Xiao, Degeng Kong, Mingchao Gao, Tianlong Luo, Shizhong Xu, Zhihan Yuan, Xinyi Ma, Xueseng Dong, Jingang Huang, Cheng Liu, Kewei Xu

    Published 2025-07-01
    “…This study characterizes a novel circRNA-encoded protein, rtSPIRE1, and investigates its mechanistic role in prostate cancer proliferation and migration, as well as its diagnostic and therapeutic potential. Methods RNA microarray identified circSPIRE1 in prostate cancer tissues. …”
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  16. 916

    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

    Published 2024-12-01
    “…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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    Article
  17. 917

    circKCNQ5 promotes the proliferation of DNA-methyltransferase 3A R882 mutated acute myeloid leukemia cells by elevating high-mobility group box 1 expression by Yijian Chen, Xiaodan Zhu, Chuanming Lin, Rong Xu, Pengxiang Xu, Liuyan Xin, Lin Li, Liqun Zhang

    Published 2025-12-01
    “…Background Patients with acute myeloid leukemia (AML) harboring the DNA-methyltransferase 3 A (DNMT3A) R882 mutation (DR882MUT) usually have a high recurrence rate and poor prognosis. circKCNQ5 levels were aberrantly elevated in patients with AML according to the microarray platform. Therefore, the purpose of this study is to investigate the effect and mechanism of circKCNQ5 on DR882MUT AML cell proliferation.Methods A DR882MUT cell line model was established. circKCNQ5 expression in AML cells expressing wild-type DNMT3A (DNMT3A-WT) or DR882MUT was analyzed using RT-qPCR. …”
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  18. 918

    The NR_109/FUBP1/c-Myc axis regulates TAM polarization and remodels the tumor microenvironment to promote cancer development by Baoen Shan, Cong Zhang, Guogui Sun, Hongtao Zhang, Xiaoya Li, Sisi Wei, Suli Dai, Huixia Wang, Lianmei Zhao

    Published 2023-05-01
    “…Long noncoding RNAs (lncRNAs) have been implicated in various physiological and pathological processes, yet the underlying mechanism on how lncRNAs manipulate the polarization states of TAMs is still unclear and remains to be further investigated.Methods Microarray analyses were employed to characterize the lncRNA profile involved in THP-1-induced M0, M1 and M2-like macrophage. …”
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    Article
  19. 919

    Identifying critical modules and biomarkers of intervertebral disc degeneration by using weighted gene co‐expression network by Daqian Zhou, Tao Liu, Yongliang Mei, Jiale Lv, Kang Cheng, Weiye Cai, Silong Gao, Daru Guo, Xianping Xie, Zongchao Liu

    Published 2024-12-01
    “…Additionally, we predicted miRNAs involved in hub gene co‐regulation and analyzed miRNA microarray data from GSE116726 to identify four differentially expressed miRNAs. …”
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    Article
  20. 920

    PARP9-PARP13-PARP14 axis tunes colorectal cancer response to radiotherapy by Rimvile Prokarenkaite, Karolina Kuodyte, Greta Gudoityte, Elzbieta Budginaite, Daniel Naumovas, Egle Strainiene, Kristijonas Velickevicius, Audrius Dulskas, Ernestas Sileika, Jonas Venius, Virginijus Tunaitis, Augustas Pivoriunas, Vytaute Starkuviene, Vaidotas Stankevicius, Kestutis Suziedelis

    Published 2025-07-01
    “…The transcriptomes of nonirradiated and irradiated cells were analyzed using microarrays. Gene set enrichment analysis was conducted to determine the pathways in which PARP13 is engaged. …”
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    Article