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Image Search Results
Journal: Tissue Engineering and Regenerative Medicine
Article Title: Potency of Human Urine-Derived Stem Cells for Renal Lineage Differentiation
doi: 10.1007/s13770-017-0081-y
Figure Lengend Snippet: Flow cytometric analysis of cell surface marker expression on mesenchymal stem cells. The values were normalized to the isotype IgG control. Expression of these markers was compared to the levels expressed at week 0 (in the undifferentiated phase before induction of renal-lineage differentiation). For urine-derived stem cells (USCs), 95% or more expressed the mesenchymal stem cell markers CD44 and CD73, whereas <3% expressed the hematopoietic lineage markers CD34 and CD45. Ctrl renal stem cells; ADSC adipose tissue-derived stem cells; AFSC amniotic fluid-derived stem cells; USC urine-derived stem cells
Article Snippet:
Techniques: Marker, Expressing, Derivative Assay
Journal: Tissue Engineering and Regenerative Medicine
Article Title: Potency of Human Urine-Derived Stem Cells for Renal Lineage Differentiation
doi: 10.1007/s13770-017-0081-y
Figure Lengend Snippet: Characterization of in vitro renal lineage-differentiated cells by morphological, immunocytochemical (ICC), quantitative real-time PCR, and secreted trophic factors analysis for 3 weeks. A Representative images from the morphological analysis. The original cell morphology (spindle-like) of the urine-derived stem cells (USCs) gradually changed to a large, round phenotype with a cobble stone-like appearance and cell aggregation. Representative ICC images using SSEA4, Pax2, Wt1, and Cadherin-6 antibodies. B In USCs, the stem cell marker SSEA4 was strongly expressed in undifferentiated stem cells, and then diminished in the differentiated phase. C Pax2 showed widespread nuclear expression at week 0, and then expression gradually became more localized and increased over time, and it was highly expressed in the cell aggregates at week 3. D Wt1 expression in the cytosol gradually increased over time. E Cadherin-6 was expressed in the cytoplasm of a few cells. The target proteins are shown in red, and the nucleus was stained with 4,6–diamidino-2–phenylindole (DAPI, blue). F Real-time PCR analysis. USCs showed the highest expression of LIM1, CD24, and OCLN. G Secreted trophic factor analysis by ELISA. VEGF and PDGF-bb were more strongly expressed in USCs than in ADSCs and AFSCs. The different letters on top of the bars indicate significant differences at p < 0.05. Ctrl renal stem cells, ADSC adipose tissue-derived stem cells, AFSC amniotic fluid-derived stem cells, USC urine-derived stem cells. (Color figure online)
Article Snippet:
Techniques: In Vitro, Real-time Polymerase Chain Reaction, Derivative Assay, Marker, Expressing, Staining, Enzyme-linked Immunosorbent Assay
Journal: Tissue Engineering and Regenerative Medicine
Article Title: Potency of Human Urine-Derived Stem Cells for Renal Lineage Differentiation
doi: 10.1007/s13770-017-0081-y
Figure Lengend Snippet: In vivo safety analysis of renal-differentiated cells. Renal lineage-differentiated USCs were implanted into the subcapsule of the kidney. Four weeks later, a histological analysis was performed. No abnormal morphology was observed in the implanted kidneys. Ctrl renal stem cells, ADSC adipose tissue-derived stem cells, AFSC amniotic fluid-derived stem cells, USC urine-derived stem cells
Article Snippet:
Techniques: In Vivo, Derivative Assay
Journal: Nature Communications
Article Title: Global stable-isotope tracing metabolomics reveals system-wide metabolic alternations in aging Drosophila
doi: 10.1038/s41467-022-31268-6
Figure Lengend Snippet: a Schematic illustration of MetTracer workflow. b Detailed data processing workflow in MetTracer. c Distributions of the 830 labeled metabolites in 293T cells in the metabolic network (left panel) and pathways (right panel). Red dots in the left panel represent the labeled metabolites. The circle size in the right panel represents the ratio of the number of labeled metabolites to the number of metabolites in a pathway. d Numbers of labeled metabolites and isotopologues using MetTracer and other indicated software tools. The Venn diagram shows the overlap of the labeled metabolites using MetTracer and other software. e Distribution of relative errors of labeling extent values between MetTracer and manual analysis using Skyline ( n = 830 metabolites). f Relative standard deviation (RSD) distributions of metabolites and isotopologues obtained from MetTracer and other software tools ( n = 6 technical replicates of 293T cell samples). The black dots represent median RSD. g False-positive rates of the labeled metabolites and isotopologues obtained from MetTracer and El-MAVEN. Source data are provided as a Source Data file.
Article Snippet: The
Techniques: Labeling, Software, Targeted Proteomics, Standard Deviation