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Image Search Results
Journal: The FASEB Journal
Article Title: Extracellular vesicles extracted from young donor serum attenuate inflammaging via partially rejuvenating aged T-cell immunotolerance
doi: 10.1096/fj.201800059R
Figure Lengend Snippet: Characteristics of serum-extracted EVs. A) Comparison of the sizes of EVs extracted from young murine serum by the ExoQuick reagent pretreated with and without using 0.2-μm filters. B) Morphology of EVs from young murine serum used in this project for rejuvenation of inflammaging, photographed by atomic force microscopy (AFM). C, D) Different miRNA expression profiles in heatmap (C) and quantified summary (D) of EVs from young vs. old murine serum, analyzed by murine miRNA microarray with Mus musculus miRBase version-21 arrays that contained 1900 unique mature miRNA probes (miRNA microarray service via LC Sciences).
Article Snippet: C , D ) Different miRNA expression profiles in heatmap ( C ) and quantified summary ( D ) of EVs from young vs. old murine serum, analyzed by
Techniques: Comparison, Microscopy, Expressing, Microarray
Journal: Toxicological Sciences
Article Title: Arsenic Induces Members of the mmu-miR-466-669 Cluster Which Reduces NeuroD1 Expression
doi: 10.1093/toxsci/kfx241
Figure Lengend Snippet: Neurogenic Transcription Factors that Are Potentially Targeted by the miR-466/669 Cluster
Article Snippet: The samples were hybridized onto
Techniques:
Journal: Toxicological Sciences
Article Title: Arsenic Induces Members of the mmu-miR-466-669 Cluster Which Reduces NeuroD1 Expression
doi: 10.1093/toxsci/kfx241
Figure Lengend Snippet: The miR-466-669 cluster share sequence similarities. Sequences of mature miRNA from the miR-466-669 cluster were aligned using Clustal Omega. All mature sequences were initially aligned together and then were subdivided into 4 major groups which have high similarity. The highlighted nucleotides were used to derive the 4 consensus sequences (as light blue). An asterisk indicates the sequence identity among all miRNAs within the group.
Article Snippet: The samples were hybridized onto
Techniques: Sequencing
Journal: Toxicological Sciences
Article Title: Arsenic Induces Members of the mmu-miR-466-669 Cluster Which Reduces NeuroD1 Expression
doi: 10.1093/toxsci/kfx241
Figure Lengend Snippet: Expression profiles of microRNAs (miRNAs) between control and arsenic exposure in differentiating P19 cells. P19 cells were induced to differentiate with or without 0.5 µM of arsenic for 9 days. MicroRNA expression was detected via a miRNA microarray and plotted as a heat map using CIM Miner (NIH). Darker shading indicates increased expression. Only statistically different miRNAs are listed in the map (Student’s t test; P value < .05).
Article Snippet: The samples were hybridized onto
Techniques: Expressing, Control, Microarray
Journal: Toxicological Sciences
Article Title: Arsenic Induces Members of the mmu-miR-466-669 Cluster Which Reduces NeuroD1 Expression
doi: 10.1093/toxsci/kfx241
Figure Lengend Snippet: Validation of miRNA transcript levels by qPCR. Day 9 differentiated P19 cells were used to confirm miRNA expression by qPCR (n = 3 per treatment). Significantly changed miRNAs with known roles in development were examined, including miR-92a (A), miR-291a (B), miR-709 (C), miR-199a (D), and miR-9 (E). Expression values were normalized with U6 snRNA and fold differences calculated from control cells using the delta Ct method. Values are expressed as mean ± SD and statistical differences were determined by Student’s t test (*P < .05).
Article Snippet: The samples were hybridized onto
Techniques: Biomarker Discovery, Expressing, Control
Journal: Toxicological Sciences
Article Title: Arsenic Induces Members of the mmu-miR-466-669 Cluster Which Reduces NeuroD1 Expression
doi: 10.1093/toxsci/kfx241
Figure Lengend Snippet: Arsenic exposure induces members of the miR-466-669 cluster along with its host gene, Sfmbt2. P19 cells were differentiated and RNA was extracted from cells exposed to 0 or 0.5 μM arsenite on days 0, 2, 5, and 9 (n = 3 per treatment per day). MicroRNA or mRNA expression was determined by qPCR. Day 9 samples were used to determine the expression of miRNA-466-669 cluster genes (A) and the host gene Sfmbt2 (B). Samples from days 0, 2, 5, to 9 were used to determine the expression of miR-467d (C), miR-669p (D), and Sfmbt2 (E). Expression values were normalized with U6 snRNA for the miRNAs, and Gapdh for Sfmbt2. Fold changes were compared with unexposed cells, and time-dependent qPCR expression fold changes were compared with day 0 unexposed cells. Data are shown as mean ± SD. Statistical differences were determined by ANOVA followed by Tukey’s test or by Student’s t test (*P < .05).
Article Snippet: The samples were hybridized onto
Techniques: Expressing
Journal: Toxicological Sciences
Article Title: Arsenic Induces Members of the mmu-miR-466-669 Cluster Which Reduces NeuroD1 Expression
doi: 10.1093/toxsci/kfx241
Figure Lengend Snippet: Inhibiting the miR-466-669 cluster during differentiation rescues the morphological loss of neurons following arsenic exposure. P19 cells were transfected with 100 nM anti-miRNA oligonucleotides which target 4 consensus sequences of the miRNA-466-467-669 cluster. Cells were coexposed to 0 or 0.5 μM arsenic for the 5 days of embryoid body formation. Only the arsenic exposure was maintained for the entire 9 days of differentiation, after which cell morphology was observed. Transfections include oligonucleotides sequences that do not target any miRNAs, designated as negative control, (N.C.), and a mixed transfection that combined all consensus anti-miRNAs. Arrows indicate neuronal cells (A). The distance of cells differentiating away from the embryoid body was quantitated using ImageJ and is expressed in mm (n = 6 replicate embryoid bodies per group) (B). mRNA levels of the neuronal cell marker NeuroD1 on day 9 was assessed by qPCR (C). mRNA expression levels were normalized with Gapdh using the comparative delta Ct method. Fold changes were compared with N.C. anti-miRNA. Data are shown as mean ± SD. Two-way ANOVA followed by Bonferroni (P < .05) was run to determine interactions and statistical differences between arsenic concentrations (*) and between the N.C. anti-miRNA and consensus anti-miRNA transfections (#).
Article Snippet: The samples were hybridized onto
Techniques: Transfection, Negative Control, Marker, Expressing
Journal: Toxicological Sciences
Article Title: Arsenic Induces Members of the mmu-miR-466-669 Cluster Which Reduces NeuroD1 Expression
doi: 10.1093/toxsci/kfx241
Figure Lengend Snippet: Consensus anti-miRNAs are active and functional and can rescue the expression of miR-466-467-669 target genes. P19 cells were transfected with all 4 miRNA inhibitors, with or without 0.5 μM arsenic (n = 3 replicates), allowed to form embryoid bodies for 5 days, and examined for mRNA expression of each of the 4 consensus sequences (A–D), 1 individual miRNA, miR-669a-3p (E), the host gene Sfmbt2 (F), and a known target gene for the consensus 1 cluster, Lats2 (G). mRNA expression levels were normalized with Gapdh, and miRNA expression levels were normalized with shRNA U6, using the comparative delta Ct method. Fold changes were compared with N.C. anti-miRNA. Data are shown as mean ± SD. Two-way ANOVA followed by Bonferroni (P < .05) was run to determine interactions and statistical differences between arsenic concentrations (*) and between the N.C. anti-miRNA and consensus anti-miRNA transfections (#) in (A–F). A 1-way ANOVA followed by Tukey’s test (P < .05) was run to determine significance (#) in (G).
Article Snippet: The samples were hybridized onto
Techniques: Functional Assay, Expressing, Transfection, shRNA
Journal: Toxicological Sciences
Article Title: Arsenic Induces Members of the mmu-miR-466-669 Cluster Which Reduces NeuroD1 Expression
doi: 10.1093/toxsci/kfx241
Figure Lengend Snippet: Mixed consensus miRNA inhibitors rescue arsenic’s inhibitory effects on NeuroD1 expression. P19 cells were transfected with a combined mixture of the 4 anti-miRNAs, with or without 0.5 μM arsenic (n = 3 replicates per anti-miRNA and per exposure group), and allowed to form embryoid bodies for 5 days. Immunohistochemistry was used to examine expression of NeuroD1 protein (red) in the embryoid bodies. Cells were counterstained with DAPI (blue) to indicate the nuclei (A). High magnification images of cells are shown in the (A) inserts. For 10 representative cells (examples are shown in the blue boxes), expression of NeuroD1 in the whole cell, cytoplasm, and nuclei were quantified using ImageJ (B). NeuroD1 transcript levels were quantified by qPCR, and normalized with Gapdh using the comparative delta Ct method with fold changes compared with N.C. (B). Data are shown as mean ± SD. Two-way ANOVA followed by Bonferroni (P < .05) was run to determine interactions and statistical differences between arsenic concentrations (*) and between the N.C. anti-miRNA and consensus anti-miRNA transfections (#).
Article Snippet: The samples were hybridized onto
Techniques: Expressing, Transfection, Immunohistochemistry
Journal: International journal of radiation oncology, biology, physics
Article Title: microRNA Alterations Driving Acute and Late Stages of Radiation-Induced Fibrosis in a Murine Skin Model
doi: 10.1016/j.ijrobp.2014.05.003
Figure Lengend Snippet: MicroRNA microarray heat map and analysis. miR arrays were performed on days 7, 14, 50, 90, and 120 after irradiation on both fibrotic and control legs. A heat map was generated to evaluate changes in miRs with a standard deviation of ≥0.5 between each time point (A); they are arranged as s from left to right: 2 day 0 controls (A and B), 7 days after irradiation (C and D), 14 days after irradiation (E), 50 days after irradiation (F and G), 90 days after irradiation (H and I), and 120 days after irradiation (J and K), and a day 120 control (L). miRs with a 2-fold change in expression (reference time-point day 0) are graphed as a function of days after irradiation (B). A significant analysis of microarrays plot was generated to help determine significantly altered miRs (C).
Article Snippet: Technical triplicates were run of 3 biological samples from each time point with use of the
Techniques: Microarray, Irradiation, Generated, Standard Deviation, Expressing