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Image Search Results
Journal: Scientific Reports
Article Title: Fast and efficient isolation of murine circulating tumor cells using screencell technology for pre-clinical analyzes
doi: 10.1038/s41598-024-66032-x
Figure Lengend Snippet: Different volumes of WT mice blood collected either within ( A ) heparin tubes or ( B ) EDTA tubes were filtered with ScreenCell Cyto kits. Similar volumes of PyMT cancer mice blood were also processed with ScreenCell Cyto kits ( C ). To evaluate the correct morphology of cancer cells in EDTA tubes, MCF7, and 4T1 breast cancer cell lines were spiked into WT mice blood and processed with ScreenCell Cyto kits. The images were taken using 40X magnification ( D ). To evaluate the recovery rate of ScreenCell technology, either 0, 5, or 10 MCF7 cells were spiked into 100 µl of blood samples of healthy WT mice. Captured cancer cells were counted on Cyto ISs and recovery rate was calculated in percentage. Data are presented as mean ± SEM (n = 6) ( E ). All experiments were repeated at least 2 times.
Article Snippet:
Techniques:
Journal: Scientific Reports
Article Title: Fast and efficient isolation of murine circulating tumor cells using screencell technology for pre-clinical analyzes
doi: 10.1038/s41598-024-66032-x
Figure Lengend Snippet: This figure represents the 4T1 cancer cells isolated using ScreenCell Cyto kits either immediately after the blood draw (left image, 40X) or after 24 h of preservation at 4 °C in EDTA tubes (right image, 40X). This experiment was performed 4 times. T0: time zero.
Article Snippet:
Techniques: Isolation, Preserving
Journal: Scientific Reports
Article Title: Fast and efficient isolation of murine circulating tumor cells using screencell technology for pre-clinical analyzes
doi: 10.1038/s41598-024-66032-x
Figure Lengend Snippet: ScreenCell Cyto kits can isolate both single and cluster CTCs. ( A ) After spiking into WT mice blood, both single and cluster 4T1 cells were captured by ScreenCell Cyto kits. ( B ) Single and cluster CTCs were also efficiently captured from breast cancer mice blood. In all conditions, CTCs were distinguishable from normal epithelial cells according to their morphological features. These experiments were performed at least 3 times. All images are taken using 40X magnification, except for the CTC cluster (lower right) which is in 20X.
Article Snippet:
Techniques:
Journal: Scientific Reports
Article Title: Fast and efficient isolation of murine circulating tumor cells using screencell technology for pre-clinical analyzes
doi: 10.1038/s41598-024-66032-x
Figure Lengend Snippet: DNA concentration from WT mouse blood with or without spiked 4T1 cells isolated by ScreenCell MB device.
Article Snippet:
Techniques: Concentration Assay, Isolation
Journal: Scientific Reports
Article Title: Fast and efficient isolation of murine circulating tumor cells using screencell technology for pre-clinical analyzes
doi: 10.1038/s41598-024-66032-x
Figure Lengend Snippet: 4T1 cells were spiked into WT mice blood and filtered with ScreenCell MB kits. ISs were then directly inserted into 24 well plates and cultured for 10 days. The images of D0, D5, and D10 with RAL coloration are taken using 40X, and D10 without coloration is taken with 20X magnification. This experiment was performed 4 times. D: Day.
Article Snippet:
Techniques: Cell Culture
Journal: International Journal of Nanomedicine
Article Title: Improving the solubility and in vitro cytotoxicity (anticancer activity) of ferulic acid by loading it into cyclodextrin nanosponges
doi: 10.2147/IJN.S206350
Figure Lengend Snippet: MTT viability assay for ( A ) MCF7 and ( B ) 4T1 cell lines treated with different formulations of ferulic acid (FA)-loaded cyclodextrin nanosponges (NS) and various interval times at 570 nm.
Article Snippet: MCF7 (human breast cancer) and
Techniques: MTT Viability Assay
Journal: International Journal of Nanomedicine
Article Title: Improving the solubility and in vitro cytotoxicity (anticancer activity) of ferulic acid by loading it into cyclodextrin nanosponges
doi: 10.2147/IJN.S206350
Figure Lengend Snippet: 4T1 cell lines treated with different formulations: control cells ( A ); ferulic acid, 250 µM ( B ); nanosponges, 250 µM ( C ); ferulic acid-loaded nanosponges, 250 µM ( D ). Microscopic magnification ×10 K, after 24 hrs of incubation.
Article Snippet: MCF7 (human breast cancer) and
Techniques: Incubation
Journal: International Journal of Molecular Sciences
Article Title: Assessment of the Pharmacokinetics, Disposition, and Duration of Action of the Tumour-Targeting Peptide CEND-1
doi: 10.3390/ijms24065700
Figure Lengend Snippet: Representative images of distribution of radioactivity in perfused female BALB/c mice with 4T1 cell tumours 0.5 h ( A ) and 3 h ( B ) after intravenous administration of [ 3 H]-CEND-1 at a target dose of 5 mg/kg.
Article Snippet: The
Techniques: Radioactivity
Journal: International Journal of Molecular Sciences
Article Title: Assessment of the Pharmacokinetics, Disposition, and Duration of Action of the Tumour-Targeting Peptide CEND-1
doi: 10.3390/ijms24065700
Figure Lengend Snippet: Quantitative radioactivity analysis of perfused tissues at 0.5–8 h following intravenous administration of 5 mg/kg of [ 3 H]-CEND-1 in female BALB/c mice with 4T1 cell tumours. The data show the mean ± SD of 5 mice per timepoint.
Article Snippet: The
Techniques: Radioactivity
Journal: Molecular Pharmaceutics
Article Title: Non-Invasive Detection of Passively Targeted Poly(ethylene glycol) Nanocarriers in Tumors
doi: 10.1021/mp2003913
Figure Lengend Snippet: Passive tumor distribution of PEG nanocarriers measured non-invasively using a SkinSkan® spectrofluorometer. Nanocarriers (0.5 mM) were intravenously administered to 4T1 tumor-bearing balb/c mice and fluorescence spectra were collected from tumor and a contralateral skin (λexc.: 480 nm; λem.: 515 nm for 10–30 kDa and 520 nm for 40–60 kDa). Each column and error bar represents the mean±SD (n = 5–7). Individual comparisons between the groups were determined by Student’s t-test using the Microsoft Excel 2008. *: p<0.05, tumor vs. corresponding dermal control site.
Article Snippet: The
Techniques: Fluorescence, Control
Journal: Molecular Pharmaceutics
Article Title: Non-Invasive Detection of Passively Targeted Poly(ethylene glycol) Nanocarriers in Tumors
doi: 10.1021/mp2003913
Figure Lengend Snippet: (A) Non-invasive images showing the passive tumor distribution of PEG nanocarriers. The images were obtained on an IVIS® 100 imaging system using the excitation and emission filters corresponding to green fluorescent protein (GFP). The first two animals (balb/c mice with 4T1 tumor), starting from the left, were untreated (controls), whereas the remaining three animals were administered nanocarriers (0.5 mM) intravenously; (B) Regions of interest for tumor and control areas are shown in a mouse injected with 40 kDa nanocarrier for average efficient quantitation; and (C) Plots of average fluorescence from tumor and control site at skin’s surface against time. Each point represents the mean±SD (n = 3). Individual comparisons between groups were determined by Student’s t-test using the Microsoft Excel 2008. *: p<0.01, tumor vs. corresponding control site.
Article Snippet: The
Techniques: Imaging, Control, Injection, Quantitation Assay, Fluorescence
Journal: Molecular Pharmaceutics
Article Title: Non-Invasive Detection of Passively Targeted Poly(ethylene glycol) Nanocarriers in Tumors
doi: 10.1021/mp2003913
Figure Lengend Snippet: Ex vivo distribution studies: (A) Tissue distribution at 24 hrs; (B) Tumor distribution at 24 and 96 hrs; and (C) Plasma distribution at 24 and 96 hrs. PEG nanocarriers (0.5 mM) were intravenously administered to balb/c mice bearing 4T1 tumors and animals were euthanized to collect tissues. Each column and error bar represents the mean±SD (n = 5–7). The statistical analyses were carried out using GraphPad Prism v.4 as follows: (A) Two-way ANOVA and individual comparison between the groups were determined using Bonferroni posttests. The statistically significant groups (p<0.05, 60 kDa vs. other nanocarriers) are marked as * (10 kDa); & (20 kDa); # (30 kDa); and + (40 kDa); (B) One-way ANOVA and individual comparison between the groups were determined using Tukey posttests. The statistically significant groups (p<0.05, 60 kDa vs. other nanocarriers are marked as * (10, 20 or 30 kDa); and # (40 kDa at 96 hrs); (C) One-way ANOVA and comparison between the groups were determined using Tukey posttests. The statistically significant groups (p<0.05, 60 kDa vs. other nanocarriers) are denoted by * (10 or 20 kDa); & (30 kDa); # (40 kDa); and + (nanocarriers at 96 hrs).
Article Snippet: The
Techniques: Ex Vivo, Clinical Proteomics, Comparison
Journal: bioRxiv
Article Title: Low albumin status accompanies multi-layered immunosuppressive phenotypes in metastatic breast cancer patients
doi: 10.1101/2023.09.05.556440
Figure Lengend Snippet: a. Heatmap showing the Pearson correlation coefficients between the clinical characteristics (age and albumin levels) and the module eigengenes generated by WGCNA. In each column, the upper number indicates the Pearson correlation coefficient and the lower number in parentheses indicates a p -value calculated by WGCNA. See also Extended Data Fig. 2a, b for scale independence and mean connectivity of this analysis. b. Bar plot showing log 2 fold changes of module-3 genes between metastatic breast cancer patients (MBC) and healthy volunteers (HV). Genes showing negative correlations to albumin levels are shown in green. Genes showing positive correlations to albumin levels are shown in orange. Genes are ordered according to their correlation to albumin levels. The names of the top10 genes most strongly negatively correlating with albumin levels are indicated. c. The plasma albumin levels of sham-operated and 4T1 breast cancer-bearing mice measured 14 days after transplantation. Data are presented as the mean ± SEM. The p- value is shown (non-paired, two-tailed Student t -test). n = 11 for sham-operated mice, n = 11 for 4T1-bearing mice. d. Heatmap of module-3 genes showing the same direction of changes in the 4T1 breast cancer model compared to the human datasets. Genes are ordered according to their correlation to albumin levels in humans. The names of the top10 genes most strongly negatively correlating with albumin levels in humans are indicated. See also Extended Data Fig. 2c, d for the mouse data.
Article Snippet:
Techniques: Generated, Clinical Proteomics, Transplantation Assay, Two Tailed Test
Journal: bioRxiv
Article Title: Low albumin status accompanies multi-layered immunosuppressive phenotypes in metastatic breast cancer patients
doi: 10.1101/2023.09.05.556440
Figure Lengend Snippet: a. Heatmap of select module-2 genes showing the same direction of changes in the 4T1 breast cancer model compared to the human datasets. Genes are ordered according to their correlation to albumin levels in humans. The names of the top10 genes most strongly positively correlating with albumin levels in humans are indicated. b. Correlation of plasma albumin levels and log 2 normalized scores of CD8A in PBMC. c. Correlation of plasma albumin levels and log 2 normalized scores of KLRG1 in PBMC. d. Correlation of plasma albumin levels and log 2 normalized scores of CRTAM in PBMC. e. UMAP plot for CD8A . f. UMAP plot for KLRG1 . g. UMAP plot for CRTAM h. Estimated abundance of CD8 + T cells in PBMC calculated by ImmuCell-AI and its correlation to plasma albumin levels. i. Estimated abundance of γδ T cells in PBMC calculated by ImmuCell-AI and its correlation to plasma albumin levels. See also Extended Data Fig. 4b for the data related to natural killer cells. See also Extended Data Fig. 4a, c, d for the mouse data for CD8 + T cells, γδ T cells, and natural killer cells, respectively. j. Correlation of plasma albumin levels and log 2 normalized scores of TRDV2 in PBMC. k. UMAP plot for TRDV2 . b-d, j. Scores are normalized to the average scores of five healthy volunteers. b-d, h, i, j. The Pearson correlation coefficients and p -values obtained by simple regression analysis (GraphPad Prism) are shown. e-g, k. The data are retrieved from previously published single-cell RNA-seq (scRNA-seq) datasets from PBMC of Japanese healthy volunteers ( n = 3 (females)) . Clusters corresponding to CD8 + T cells ( e-g ) and γδ T cells ( k ) are highlighted.
Article Snippet:
Techniques: Clinical Proteomics, RNA Sequencing