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paxgene blood mirna kit  (Qiagen)


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    Qiagen paxgene blood mirna kit
    miR-31 is correlated with disease progression during both acute and chronic HIV-1 infection. (A) Unsupervised clustering of the 251 miRNAs. After normalization and filtering of the microarray data, 251 miRNAs were retained for further analysis. Average linkage hierarchical clustering was performed using a centered correlation metric. Twenty-three samples from the FBD study were clustered into 2 groups: the left cluster was a mixture of elite controllers, viremic controllers and progressors; the right was mainly progressors with one exception. (B) Venn diagram showing the numbers of candidate miRNAs filtered with different criteria. The miRNAs in the lower left and right circles were generated by significance analysis of microarrays (SAM) of participants stratified by the CD4+ T cell count (<250 cells/μL vs. >450 cells/μL) and viral load (<2000 copies/mL vs. >10000 copies/mL), respectively. The identified 15 <t>miRNA</t> candidates were marked in red in (A) . (C) Correlation between expression levels of miR-31 and CD4+ T cell counts in HIV-1 infected individuals (FBD, former blood donor cohort). miR-31 expression was quantified by quantitative RT-PCR, and the relationship between relative level of miR-31 and CD4+ T cell count was examined by Spearman correlation (n = 50). Red dots represent patients that eventually reached the defined endpoints. (D) Kaplan-Meier survival curves of FDB patients stratified by median whole blood miR-31 level during the late phase of chronic infection. (E–G) Kaplan-Meier survival curves of another HIV patient cohort (an acute-phase prospective men who have sex with men (MSM) cohort) stratified by plasma miR-31 levels before and after infection. Absolute CD4+ T cell count below 350 cells/μL, initiation of long-term ART, progression to AIDS and death were defined as endpoints of the study. Patients were separated into two groups stratified by the median miR-31 level in plasma collected before infection (E) , during acute infection phase (F) , during early phase of chronic infection (G) .
    Paxgene Blood Mirna Kit, supplied by Qiagen, used in various techniques. Bioz Stars score: 96/100, based on 559 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/microrna+microarray+gene+expression+experiments/PAXgene+Blood+miRNA+Kit/pmc08602903-75-0-4
    Average 96 stars, based on 559 article reviews
    paxgene blood mirna kit - by Bioz Stars, 2026-09
    96/100 stars

    Images

    1) Product Images from "Hsa-miR-31 Governs T-Cell Homeostasis in HIV Protection via IFN-γ-Stat1-T-Bet Axis"

    Article Title: Hsa-miR-31 Governs T-Cell Homeostasis in HIV Protection via IFN-γ-Stat1-T-Bet Axis

    Journal: Frontiers in Immunology

    doi: 10.3389/fimmu.2021.771279

    miR-31 is correlated with disease progression during both acute and chronic HIV-1 infection. (A) Unsupervised clustering of the 251 miRNAs. After normalization and filtering of the microarray data, 251 miRNAs were retained for further analysis. Average linkage hierarchical clustering was performed using a centered correlation metric. Twenty-three samples from the FBD study were clustered into 2 groups: the left cluster was a mixture of elite controllers, viremic controllers and progressors; the right was mainly progressors with one exception. (B) Venn diagram showing the numbers of candidate miRNAs filtered with different criteria. The miRNAs in the lower left and right circles were generated by significance analysis of microarrays (SAM) of participants stratified by the CD4+ T cell count (<250 cells/μL vs. >450 cells/μL) and viral load (<2000 copies/mL vs. >10000 copies/mL), respectively. The identified 15 miRNA candidates were marked in red in (A) . (C) Correlation between expression levels of miR-31 and CD4+ T cell counts in HIV-1 infected individuals (FBD, former blood donor cohort). miR-31 expression was quantified by quantitative RT-PCR, and the relationship between relative level of miR-31 and CD4+ T cell count was examined by Spearman correlation (n = 50). Red dots represent patients that eventually reached the defined endpoints. (D) Kaplan-Meier survival curves of FDB patients stratified by median whole blood miR-31 level during the late phase of chronic infection. (E–G) Kaplan-Meier survival curves of another HIV patient cohort (an acute-phase prospective men who have sex with men (MSM) cohort) stratified by plasma miR-31 levels before and after infection. Absolute CD4+ T cell count below 350 cells/μL, initiation of long-term ART, progression to AIDS and death were defined as endpoints of the study. Patients were separated into two groups stratified by the median miR-31 level in plasma collected before infection (E) , during acute infection phase (F) , during early phase of chronic infection (G) .
    Figure Legend Snippet: miR-31 is correlated with disease progression during both acute and chronic HIV-1 infection. (A) Unsupervised clustering of the 251 miRNAs. After normalization and filtering of the microarray data, 251 miRNAs were retained for further analysis. Average linkage hierarchical clustering was performed using a centered correlation metric. Twenty-three samples from the FBD study were clustered into 2 groups: the left cluster was a mixture of elite controllers, viremic controllers and progressors; the right was mainly progressors with one exception. (B) Venn diagram showing the numbers of candidate miRNAs filtered with different criteria. The miRNAs in the lower left and right circles were generated by significance analysis of microarrays (SAM) of participants stratified by the CD4+ T cell count (<250 cells/μL vs. >450 cells/μL) and viral load (<2000 copies/mL vs. >10000 copies/mL), respectively. The identified 15 miRNA candidates were marked in red in (A) . (C) Correlation between expression levels of miR-31 and CD4+ T cell counts in HIV-1 infected individuals (FBD, former blood donor cohort). miR-31 expression was quantified by quantitative RT-PCR, and the relationship between relative level of miR-31 and CD4+ T cell count was examined by Spearman correlation (n = 50). Red dots represent patients that eventually reached the defined endpoints. (D) Kaplan-Meier survival curves of FDB patients stratified by median whole blood miR-31 level during the late phase of chronic infection. (E–G) Kaplan-Meier survival curves of another HIV patient cohort (an acute-phase prospective men who have sex with men (MSM) cohort) stratified by plasma miR-31 levels before and after infection. Absolute CD4+ T cell count below 350 cells/μL, initiation of long-term ART, progression to AIDS and death were defined as endpoints of the study. Patients were separated into two groups stratified by the median miR-31 level in plasma collected before infection (E) , during acute infection phase (F) , during early phase of chronic infection (G) .

    Techniques Used: Biomarker Discovery, Infection, Microarray, Generated, Cell Counting, Expressing, Quantitative RT-PCR, Clinical Proteomics

    Loss of miR-31 triggers CD4+ T cell activation. (A) miR-31 levels in different immune cell subtypes. Data were obtained from a miRNA RTqPCR data from Rossi et al ’s work (see the text for reference). (B) Comparison of absolute naïve CD4+ T cell counts in blood of HIV-1 infected individuals (FBD, n = 50) stratified by miR-31 expression. (C, D) Correlation between miR-31 levels and frequencies of CD38+ T cells (C) or HLA-DR+ T cells in blood of HIV infected individuals (FBD, n=44) (E) Gene set enrichment analysis (GSEA) of “naïve” signature in antagomiR-31- versus antagoNC- treated naïve CD4+ T cells. NES, normalized enrichment score. (F) Heatmap of representative genes associated with activation versus naïve state of T cells. Shown is log2 fold changes of gene expression in antagomiR-31-treated naïve CD4+ T cells relative to that in antagoNC-treated cells (n=3). (G) Effects of antagomiR-31 treatment on CD25 expression of naïve CD4+ T cells, assessed by frequency of CD25+ cells and median fluorescent intensity (MFI) of CD25. Average fold changes were 4.45 and 2.25, respectively (n = 8). Blue, antagomir-31 treated group; red, antagoNC-treated group. Representative FACS data for CD25 were shown in the left panel. (H) Schema of the in vitro assay used for examining the role of miR-31 in HIV-1 infection. CD4+ T cells were sorted, followed by transfection with antagomiR-31 or antagoNC. After 48 hours, cells were stimulated with a mix of anti-CD3 and anti-CD28 antibodies and infected with HIV-1 IIIB 5 days later. (I, J) Cells and supernatants were collected on days 5 and 11 post infection and respectively subjected to flow cytometry for determination of P24-expressing CD4+ T cells (I) and ELISA for quantification of released P24 proteins (J) (n = 3).
    Figure Legend Snippet: Loss of miR-31 triggers CD4+ T cell activation. (A) miR-31 levels in different immune cell subtypes. Data were obtained from a miRNA RTqPCR data from Rossi et al ’s work (see the text for reference). (B) Comparison of absolute naïve CD4+ T cell counts in blood of HIV-1 infected individuals (FBD, n = 50) stratified by miR-31 expression. (C, D) Correlation between miR-31 levels and frequencies of CD38+ T cells (C) or HLA-DR+ T cells in blood of HIV infected individuals (FBD, n=44) (E) Gene set enrichment analysis (GSEA) of “naïve” signature in antagomiR-31- versus antagoNC- treated naïve CD4+ T cells. NES, normalized enrichment score. (F) Heatmap of representative genes associated with activation versus naïve state of T cells. Shown is log2 fold changes of gene expression in antagomiR-31-treated naïve CD4+ T cells relative to that in antagoNC-treated cells (n=3). (G) Effects of antagomiR-31 treatment on CD25 expression of naïve CD4+ T cells, assessed by frequency of CD25+ cells and median fluorescent intensity (MFI) of CD25. Average fold changes were 4.45 and 2.25, respectively (n = 8). Blue, antagomir-31 treated group; red, antagoNC-treated group. Representative FACS data for CD25 were shown in the left panel. (H) Schema of the in vitro assay used for examining the role of miR-31 in HIV-1 infection. CD4+ T cells were sorted, followed by transfection with antagomiR-31 or antagoNC. After 48 hours, cells were stimulated with a mix of anti-CD3 and anti-CD28 antibodies and infected with HIV-1 IIIB 5 days later. (I, J) Cells and supernatants were collected on days 5 and 11 post infection and respectively subjected to flow cytometry for determination of P24-expressing CD4+ T cells (I) and ELISA for quantification of released P24 proteins (J) (n = 3).

    Techniques Used: Activation Assay, Comparison, Infection, Expressing, Gene Expression, In Vitro, Transfection, Flow Cytometry, Enzyme-linked Immunosorbent Assay

    Related Articles

    Nucleic Acid Purification:

    Article Title: Longitudinal transcriptomic profiles associated with onset and remission of adolescent depression.
    Article Snippet: 40 Peripheral venous blood samples were collected at baseline and three-year follow-up on the 41 same day as the clinical assessment in 2.5 ml PAXgene Blood RNA tubes (PreAnalitix, 42 Qiagen/BD Company). .. Nucleic acid purification from PAXgene tubes was performed by using 43 the PAXgene Blood miRNA kit (Qiagen, Hilden, Germany; Cat No./ID: 763134). .. The quality 44 of the RNA was assessed by Tapestation 2000 (Agilent, Santa Clara, United States) with RNA 45 ScreenTape system to measure the RNA integrity number (RIN).

    Isolation:

    Article Title: Blood-based RNA-Seq of 5412 individuals with rare disease identifies new candidate diagnoses in the National Genomic Research Library
    Article Snippet: .. Total RNA was isolated using the PAXgene Blood miRNA Kit (Qiagen, Germany) on the QIAcube Connect automated Nucleic Acid Extractor (Qiagen, USA) according to manufacturer’s protocol at UK Biocentre (Milton Keynes). .. The libraries were prepared from 100 ng total RNA by Illumina (Granta Park, England) with the Illumina Stranded Total RNA Prep, Ligation with Ribo-Zero Plus kit, which depletes globin and ribosomal RNAs plus additional custom deletion probes.

    Article Title: Predicting trajectories of illness using RNA velocity of whole blood.
    Article Snippet: .. Total RNA was isolated using PAXgene miRNA blood extraction kits (Qiagen), and after additional DNAse treatment (Zymo Research), was sent for ribodepletion library preparation and RNA-Seq at The Wellcome Centre for Human Genetics in Oxford, United Kingdom, using a Novaseq6000 platform at 150 bp paired-end configuration, generating a raw read count of ~30 million reads per sample. ..

    Article Title: Exogenous glucocorticoid dose impacts circulating microRNA expression in patients with adrenal insufficiency due to 21-hydroxylase deficiency
    Article Snippet: .. Total miRNA was extracted using the Qiagen PAXgene Blood miRNA Kit for microRNA isolation (QIAGEN, Germantown, MD) according to the manufacturer’s instructions. .. RNA yield, quality, and size were assessed through RNA 6000 Nano Assays using a 2100 Agilent Bioanalyzer (Agilent Technologies, Santa Clara, CA).

    Extraction:

    Article Title: Predicting trajectories of illness using RNA velocity of whole blood.
    Article Snippet: .. Total RNA was isolated using PAXgene miRNA blood extraction kits (Qiagen), and after additional DNAse treatment (Zymo Research), was sent for ribodepletion library preparation and RNA-Seq at The Wellcome Centre for Human Genetics in Oxford, United Kingdom, using a Novaseq6000 platform at 150 bp paired-end configuration, generating a raw read count of ~30 million reads per sample. ..

    RNA sequencing:

    Article Title: Predicting trajectories of illness using RNA velocity of whole blood.
    Article Snippet: .. Total RNA was isolated using PAXgene miRNA blood extraction kits (Qiagen), and after additional DNAse treatment (Zymo Research), was sent for ribodepletion library preparation and RNA-Seq at The Wellcome Centre for Human Genetics in Oxford, United Kingdom, using a Novaseq6000 platform at 150 bp paired-end configuration, generating a raw read count of ~30 million reads per sample. ..

    Reverse Transcription:

    Article Title: Predictive value of interferon regulatory factor 5 nuclear translocation in B cells for disease activity and flare in systemic lupus erythematosus: a prospective observational cohort study.
    Article Snippet: Objective: This study aimed to determine whether interferon regulatory factor 5 (IRF5) activation and its temporal dynamics in immune cells correlate with disease activity and flares in patients with systemic lupus erythematosus (SLE).. Methods: Patients with SLE were prospectively enrolled and followed up for 52 weeks.. The IRF5 nuclear translocation rate (NTR) was assessed in monocytes, dendritic cells, and B cells during baseline and follow-ups.

    Real-time Polymerase Chain Reaction:

    Article Title: Predictive value of interferon regulatory factor 5 nuclear translocation in B cells for disease activity and flare in systemic lupus erythematosus: a prospective observational cohort study.
    Article Snippet: Objective: This study aimed to determine whether interferon regulatory factor 5 (IRF5) activation and its temporal dynamics in immune cells correlate with disease activity and flares in patients with systemic lupus erythematosus (SLE).. Methods: Patients with SLE were prospectively enrolled and followed up for 52 weeks.. The IRF5 nuclear translocation rate (NTR) was assessed in monocytes, dendritic cells, and B cells during baseline and follow-ups.



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    Shanghai Biotechnology Co Ltd microrna microarray gene expression experiments
    ZEB1-AS1 sponges miR-141-3p in CRC cells. ( A ) Nuclear and cytoplasmic fractionation was analyzed for ZEB1-AS1 expression in SW480 and LOVO. ( B ) The <t>microRNA</t> array analysis in normal and tumor tissues. ( C ) The potential binding sites between ZEB1-AS1 and miR-141-3p. ( D ) The expressions of miR-141-3p in CRC tissues were detected by RT-qPCR. ( E ) Luciferase reporter assay showed ZEB1-AS1-wt activity was impaired by miR-141-3p. ( F ) The expression of miR-141-3p in SW480 and LOVO was upregulated after ZEB1-AS1 expression was downregulated identified by RT-qPCR. ( G ) The expression of miR-141-3p was negatively correlated with ZEB1-AS1 expression in CRC tissues. * P < 0.05.
    Microrna Microarray Gene Expression Experiments, supplied by Shanghai Biotechnology Co Ltd, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    ZEB1-AS1 sponges miR-141-3p in CRC cells. ( A ) Nuclear and cytoplasmic fractionation was analyzed for ZEB1-AS1 expression in SW480 and LOVO. ( B ) The microRNA array analysis in normal and tumor tissues. ( C ) The potential binding sites between ZEB1-AS1 and miR-141-3p. ( D ) The expressions of miR-141-3p in CRC tissues were detected by RT-qPCR. ( E ) Luciferase reporter assay showed ZEB1-AS1-wt activity was impaired by miR-141-3p. ( F ) The expression of miR-141-3p in SW480 and LOVO was upregulated after ZEB1-AS1 expression was downregulated identified by RT-qPCR. ( G ) The expression of miR-141-3p was negatively correlated with ZEB1-AS1 expression in CRC tissues. * P < 0.05.

    Journal: International Journal of Medical Sciences

    Article Title: Long noncoding RNA ZEB1-AS1 acts as a Sponge of miR-141-3p to Inhibit Cell Proliferation in Colorectal Cancer

    doi: 10.7150/ijms.46698

    Figure Lengend Snippet: ZEB1-AS1 sponges miR-141-3p in CRC cells. ( A ) Nuclear and cytoplasmic fractionation was analyzed for ZEB1-AS1 expression in SW480 and LOVO. ( B ) The microRNA array analysis in normal and tumor tissues. ( C ) The potential binding sites between ZEB1-AS1 and miR-141-3p. ( D ) The expressions of miR-141-3p in CRC tissues were detected by RT-qPCR. ( E ) Luciferase reporter assay showed ZEB1-AS1-wt activity was impaired by miR-141-3p. ( F ) The expression of miR-141-3p in SW480 and LOVO was upregulated after ZEB1-AS1 expression was downregulated identified by RT-qPCR. ( G ) The expression of miR-141-3p was negatively correlated with ZEB1-AS1 expression in CRC tissues. * P < 0.05.

    Article Snippet: Shanghai Biotechnology Co., Ltd conducted the microRNA microarray gene expression experiments and data analysis.

    Techniques: Fractionation, Expressing, Binding Assay, Quantitative RT-PCR, Luciferase, Reporter Assay, Activity Assay