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cd73 nt5e antibody  (Boster Bio)


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    Structured Review

    Boster Bio cd73 nt5e antibody
    Cd73 Nt5e Antibody, supplied by Boster Bio, used in various techniques. Bioz Stars score: 94/100, based on 3 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/cd73 nt5e antibody/product/Boster Bio
    Average 94 stars, based on 3 article reviews
    cd73 nt5e antibody - by Bioz Stars, 2026-05
    94/100 stars

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    A – A heatmap comparing reference genotyping data from the FUSION study to low-pass genotyping data generated as part of QC metrics for this study. The fraction match indicates the fraction of reads that aligned from the low pass WGS data to the reference SNP Chip. B – Histogram of FAP marker gene expression based on FACS assessment of 30 different lines. The X-axis indicates the percentage of cells per line expressing <t>NT5E.</t> The average across all cell lines was 74% of cells expressing the FAP marker gene. C – Sankey plot representing the insulin-stimulated glucose uptake assay. D – Comparison of normalized luminescence from all 30 donors (with replicates) in basal, basal with a small dose of insulin, high-insulin, and high-insulin with a small additional dose of insulin. Pink lines indicate the average luminescence value for that environmental condition. A paired Student’s t-test was used to assess statistical significance. E – An interval plot comparing donor metadata to luminescence levels in basal conditions. Red indicates a negative correlation with glucose uptake. Data represented as mean ± SEM. F – An interval plot comparing donor metadata to luminescence levels in high-insulin conditions. Red indicates a negative correlation with glucose uptake. Data represented as mean ± SEM. G – An interval plot comparing donor metadata to luminescence levels in basal conditions with an additional small dose of insulin. Data represented as mean ± SEM. H – An interval plot comparing donor metadata to luminescence levels in high-insulin conditions with an additional small dose of insulin. Red indicates a negative correlation with glucose uptake. Data represented as mean ± SEM.
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    Schematic illustration of the T-score and S-score. The tumor bed was divided into tumor and stromal compartments, and the T-score and S-score represent the quantitative measurements of <t>CD73</t> (CD3, CD8, Foxp3, and CD163) expression or lymphocyte infiltration within each compartment, respectively.
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    Schematic illustration of the T-score and S-score. The tumor bed was divided into tumor and stromal compartments, and the T-score and S-score represent the quantitative measurements of <t>CD73</t> (CD3, CD8, Foxp3, and CD163) expression or lymphocyte infiltration within each compartment, respectively.
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    Schematic illustration of the T-score and S-score. The tumor bed was divided into tumor and stromal compartments, and the T-score and S-score represent the quantitative measurements of <t>CD73</t> (CD3, CD8, Foxp3, and CD163) expression or lymphocyte infiltration within each compartment, respectively.
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    Network Construction and Analysis. (A) Venn diagram showing the overlap between MSGA and HUA targets. (B) Mapping of disease-associated targets for MSGA. (C) Core targets of MSGA and HUA: drug targets (blue), disease targets (blue), and core targets (green, right box). (D) GO enrichment analysis of core targets. (E) KEGG pathway enrichment analysis of core targets. (F) Expression levels of target genes in kidney (F-a) and liver (F-b) tissues. (G) Liver metabolic pathway profile. (H) Binding energy of <t>NT5E</t> (H-a), XDH (H-b), and HPRT1 (H-c) with five dominant active ingredients. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
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    Network Construction and Analysis. (A) Venn diagram showing the overlap between MSGA and HUA targets. (B) Mapping of disease-associated targets for MSGA. (C) Core targets of MSGA and HUA: drug targets (blue), disease targets (blue), and core targets (green, right box). (D) GO enrichment analysis of core targets. (E) KEGG pathway enrichment analysis of core targets. (F) Expression levels of target genes in kidney (F-a) and liver (F-b) tissues. (G) Liver metabolic pathway profile. (H) Binding energy of <t>NT5E</t> (H-a), XDH (H-b), and HPRT1 (H-c) with five dominant active ingredients. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
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    Image Search Results


    A – A heatmap comparing reference genotyping data from the FUSION study to low-pass genotyping data generated as part of QC metrics for this study. The fraction match indicates the fraction of reads that aligned from the low pass WGS data to the reference SNP Chip. B – Histogram of FAP marker gene expression based on FACS assessment of 30 different lines. The X-axis indicates the percentage of cells per line expressing NT5E. The average across all cell lines was 74% of cells expressing the FAP marker gene. C – Sankey plot representing the insulin-stimulated glucose uptake assay. D – Comparison of normalized luminescence from all 30 donors (with replicates) in basal, basal with a small dose of insulin, high-insulin, and high-insulin with a small additional dose of insulin. Pink lines indicate the average luminescence value for that environmental condition. A paired Student’s t-test was used to assess statistical significance. E – An interval plot comparing donor metadata to luminescence levels in basal conditions. Red indicates a negative correlation with glucose uptake. Data represented as mean ± SEM. F – An interval plot comparing donor metadata to luminescence levels in high-insulin conditions. Red indicates a negative correlation with glucose uptake. Data represented as mean ± SEM. G – An interval plot comparing donor metadata to luminescence levels in basal conditions with an additional small dose of insulin. Data represented as mean ± SEM. H – An interval plot comparing donor metadata to luminescence levels in high-insulin conditions with an additional small dose of insulin. Red indicates a negative correlation with glucose uptake. Data represented as mean ± SEM.

    Journal: bioRxiv

    Article Title: Donor-matched iPSC model reveals context-dependent T2D genetic signals in fibro-adipogenic progenitors

    doi: 10.64898/2026.02.04.702388

    Figure Lengend Snippet: A – A heatmap comparing reference genotyping data from the FUSION study to low-pass genotyping data generated as part of QC metrics for this study. The fraction match indicates the fraction of reads that aligned from the low pass WGS data to the reference SNP Chip. B – Histogram of FAP marker gene expression based on FACS assessment of 30 different lines. The X-axis indicates the percentage of cells per line expressing NT5E. The average across all cell lines was 74% of cells expressing the FAP marker gene. C – Sankey plot representing the insulin-stimulated glucose uptake assay. D – Comparison of normalized luminescence from all 30 donors (with replicates) in basal, basal with a small dose of insulin, high-insulin, and high-insulin with a small additional dose of insulin. Pink lines indicate the average luminescence value for that environmental condition. A paired Student’s t-test was used to assess statistical significance. E – An interval plot comparing donor metadata to luminescence levels in basal conditions. Red indicates a negative correlation with glucose uptake. Data represented as mean ± SEM. F – An interval plot comparing donor metadata to luminescence levels in high-insulin conditions. Red indicates a negative correlation with glucose uptake. Data represented as mean ± SEM. G – An interval plot comparing donor metadata to luminescence levels in basal conditions with an additional small dose of insulin. Data represented as mean ± SEM. H – An interval plot comparing donor metadata to luminescence levels in high-insulin conditions with an additional small dose of insulin. Red indicates a negative correlation with glucose uptake. Data represented as mean ± SEM.

    Article Snippet: Cells are then centrifuged down, media is aspirated, and the positive sample is stained with antibodies for Tra-1-60 (iPSC marker) (Miltenyi Biotec Cat# 130-122-921, RRID:AB_2801969) and NT5E (FAP marker) (Miltenyi Biotec Cat# 130-111-913, RRID:AB_2784275) for 10 minutes.

    Techniques: Generated, Marker, Gene Expression, Expressing, Comparison

    Schematic illustration of the T-score and S-score. The tumor bed was divided into tumor and stromal compartments, and the T-score and S-score represent the quantitative measurements of CD73 (CD3, CD8, Foxp3, and CD163) expression or lymphocyte infiltration within each compartment, respectively.

    Journal: Cancers

    Article Title: High CD73 Expression Is Associated with Poor Prognosis in Biliary Tract Cancer Through Reduced Stromal Tumor-Infiltrating Lymphocytes

    doi: 10.3390/cancers18060975

    Figure Lengend Snippet: Schematic illustration of the T-score and S-score. The tumor bed was divided into tumor and stromal compartments, and the T-score and S-score represent the quantitative measurements of CD73 (CD3, CD8, Foxp3, and CD163) expression or lymphocyte infiltration within each compartment, respectively.

    Article Snippet: Eligible specimens were subjected to IHC staining using a rabbit monoclonal anti-CD73 antibody (#13160, Cell Signaling Technology, Danvers, MA, USA) diluted 1:100, a rabbit polyclonal anti-CD3 antibody (Dako #IR503, Agilent, Santa Clara, CA, USA), a mouse monoclonal anti-CD8 antibody (Dako #IR623, Agilent, Santa Clara, CA, USA), a mouse monoclonal anti-CD163 antibody (#CD163-L-CE, Leica Biosystems, Nussloch, Germany) diluted 1:500, and a mouse monoclonal anti-Foxp3 antibody (#ab20034, abcam, Cambridge, UK) diluted 1:100.

    Techniques: Expressing

    Representative IHC staining images ( left ) and corresponding AI-based analysis images generated by DeepPathFinder™ ( right ) for CD73, CD3, CD8, Foxp3, and CD163 (original magnification approximately ×200). IHC-positive areas (cyan) were automatically identified and overlaid onto tumor regions (green) delineated on the corresponding H&E–stained images, enabling quantitative assessment of IHC-positive area within the tumor compartment.

    Journal: Cancers

    Article Title: High CD73 Expression Is Associated with Poor Prognosis in Biliary Tract Cancer Through Reduced Stromal Tumor-Infiltrating Lymphocytes

    doi: 10.3390/cancers18060975

    Figure Lengend Snippet: Representative IHC staining images ( left ) and corresponding AI-based analysis images generated by DeepPathFinder™ ( right ) for CD73, CD3, CD8, Foxp3, and CD163 (original magnification approximately ×200). IHC-positive areas (cyan) were automatically identified and overlaid onto tumor regions (green) delineated on the corresponding H&E–stained images, enabling quantitative assessment of IHC-positive area within the tumor compartment.

    Article Snippet: Eligible specimens were subjected to IHC staining using a rabbit monoclonal anti-CD73 antibody (#13160, Cell Signaling Technology, Danvers, MA, USA) diluted 1:100, a rabbit polyclonal anti-CD3 antibody (Dako #IR503, Agilent, Santa Clara, CA, USA), a mouse monoclonal anti-CD8 antibody (Dako #IR623, Agilent, Santa Clara, CA, USA), a mouse monoclonal anti-CD163 antibody (#CD163-L-CE, Leica Biosystems, Nussloch, Germany) diluted 1:500, and a mouse monoclonal anti-Foxp3 antibody (#ab20034, abcam, Cambridge, UK) diluted 1:100.

    Techniques: Immunohistochemistry, Generated, Staining

    Effect of the CD73 and TIL scores. Kaplan–Meier curves of the overall survival in 100 patients ( a ) 50 in the T-CD73-high group and 50 in the T-CD73-low group ( b ) 50 in the S-CD73-high group and 50 in the S-CD73-low group ( c ) 50 in the T-TIL-high group and 50 in the T-TIL-low group ( d ) 50 in the S-TIL-high group and 50 in the S-TIL-low group.

    Journal: Cancers

    Article Title: High CD73 Expression Is Associated with Poor Prognosis in Biliary Tract Cancer Through Reduced Stromal Tumor-Infiltrating Lymphocytes

    doi: 10.3390/cancers18060975

    Figure Lengend Snippet: Effect of the CD73 and TIL scores. Kaplan–Meier curves of the overall survival in 100 patients ( a ) 50 in the T-CD73-high group and 50 in the T-CD73-low group ( b ) 50 in the S-CD73-high group and 50 in the S-CD73-low group ( c ) 50 in the T-TIL-high group and 50 in the T-TIL-low group ( d ) 50 in the S-TIL-high group and 50 in the S-TIL-low group.

    Article Snippet: Eligible specimens were subjected to IHC staining using a rabbit monoclonal anti-CD73 antibody (#13160, Cell Signaling Technology, Danvers, MA, USA) diluted 1:100, a rabbit polyclonal anti-CD3 antibody (Dako #IR503, Agilent, Santa Clara, CA, USA), a mouse monoclonal anti-CD8 antibody (Dako #IR623, Agilent, Santa Clara, CA, USA), a mouse monoclonal anti-CD163 antibody (#CD163-L-CE, Leica Biosystems, Nussloch, Germany) diluted 1:500, and a mouse monoclonal anti-Foxp3 antibody (#ab20034, abcam, Cambridge, UK) diluted 1:100.

    Techniques:

    Correlations between T-CD73 and TIL scores/immune cell subsets. Spearman’s rank correlation coefficient between ( a ) T-CD73 and T-TIL scores and ( b ) T-CD73 and S-TIL scores.

    Journal: Cancers

    Article Title: High CD73 Expression Is Associated with Poor Prognosis in Biliary Tract Cancer Through Reduced Stromal Tumor-Infiltrating Lymphocytes

    doi: 10.3390/cancers18060975

    Figure Lengend Snippet: Correlations between T-CD73 and TIL scores/immune cell subsets. Spearman’s rank correlation coefficient between ( a ) T-CD73 and T-TIL scores and ( b ) T-CD73 and S-TIL scores.

    Article Snippet: Eligible specimens were subjected to IHC staining using a rabbit monoclonal anti-CD73 antibody (#13160, Cell Signaling Technology, Danvers, MA, USA) diluted 1:100, a rabbit polyclonal anti-CD3 antibody (Dako #IR503, Agilent, Santa Clara, CA, USA), a mouse monoclonal anti-CD8 antibody (Dako #IR623, Agilent, Santa Clara, CA, USA), a mouse monoclonal anti-CD163 antibody (#CD163-L-CE, Leica Biosystems, Nussloch, Germany) diluted 1:500, and a mouse monoclonal anti-Foxp3 antibody (#ab20034, abcam, Cambridge, UK) diluted 1:100.

    Techniques:

    Correlations between T-CD73 and immune cell subsets. Spearman’s rank correlation coefficient between ( a ) T-CD73 and S-CD3 scores and ( b ) T-CD73 and S-CD8 scores.

    Journal: Cancers

    Article Title: High CD73 Expression Is Associated with Poor Prognosis in Biliary Tract Cancer Through Reduced Stromal Tumor-Infiltrating Lymphocytes

    doi: 10.3390/cancers18060975

    Figure Lengend Snippet: Correlations between T-CD73 and immune cell subsets. Spearman’s rank correlation coefficient between ( a ) T-CD73 and S-CD3 scores and ( b ) T-CD73 and S-CD8 scores.

    Article Snippet: Eligible specimens were subjected to IHC staining using a rabbit monoclonal anti-CD73 antibody (#13160, Cell Signaling Technology, Danvers, MA, USA) diluted 1:100, a rabbit polyclonal anti-CD3 antibody (Dako #IR503, Agilent, Santa Clara, CA, USA), a mouse monoclonal anti-CD8 antibody (Dako #IR623, Agilent, Santa Clara, CA, USA), a mouse monoclonal anti-CD163 antibody (#CD163-L-CE, Leica Biosystems, Nussloch, Germany) diluted 1:500, and a mouse monoclonal anti-Foxp3 antibody (#ab20034, abcam, Cambridge, UK) diluted 1:100.

    Techniques:

    Network Construction and Analysis. (A) Venn diagram showing the overlap between MSGA and HUA targets. (B) Mapping of disease-associated targets for MSGA. (C) Core targets of MSGA and HUA: drug targets (blue), disease targets (blue), and core targets (green, right box). (D) GO enrichment analysis of core targets. (E) KEGG pathway enrichment analysis of core targets. (F) Expression levels of target genes in kidney (F-a) and liver (F-b) tissues. (G) Liver metabolic pathway profile. (H) Binding energy of NT5E (H-a), XDH (H-b), and HPRT1 (H-c) with five dominant active ingredients. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

    Journal: Food Chemistry: X

    Article Title: The mature stem of green Asparagus as a potential dietary supplement for hyperuricemia: Asparagus ameliorates hyperuricemia by regulating hepatic uric acid metabolism and renal uric acid excretion

    doi: 10.1016/j.fochx.2026.103482

    Figure Lengend Snippet: Network Construction and Analysis. (A) Venn diagram showing the overlap between MSGA and HUA targets. (B) Mapping of disease-associated targets for MSGA. (C) Core targets of MSGA and HUA: drug targets (blue), disease targets (blue), and core targets (green, right box). (D) GO enrichment analysis of core targets. (E) KEGG pathway enrichment analysis of core targets. (F) Expression levels of target genes in kidney (F-a) and liver (F-b) tissues. (G) Liver metabolic pathway profile. (H) Binding energy of NT5E (H-a), XDH (H-b), and HPRT1 (H-c) with five dominant active ingredients. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

    Article Snippet: Membranes were incubated overnight at 4 °C with primary antibodies against Nt5e (1:1000, Bioss, China) and Pdzk1 (1:500, GeneTex, USA), followed by standard immunoblotting procedures.

    Techniques: Expressing, Binding Assay

    MSGA mitigates HUA by regulating Nt5e. (A) Representative photomicrographs of H& E -stained liver sections (from n = 3 biologically independent mice per group) are shown. Scale bar = 200 μm. Red arrows indicate inflammatory cell infiltration. (B) Hepatic Nt5e enzyme activity (n = 3 biologically independent mice per group). (C) Western blot analysis of Nt5e protein expression: (a) representative blot images and (b) quantitative analysis (n = 3 biologically independent mice per group). (D) Relative mRNA expression level of Nt5e in liver tissue (n = 3 biologically independent mice per group). Data are presented as mean ± SD. Significant differences were determined by one-way ANOVA with Tukey's post-hoc test (* p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

    Journal: Food Chemistry: X

    Article Title: The mature stem of green Asparagus as a potential dietary supplement for hyperuricemia: Asparagus ameliorates hyperuricemia by regulating hepatic uric acid metabolism and renal uric acid excretion

    doi: 10.1016/j.fochx.2026.103482

    Figure Lengend Snippet: MSGA mitigates HUA by regulating Nt5e. (A) Representative photomicrographs of H& E -stained liver sections (from n = 3 biologically independent mice per group) are shown. Scale bar = 200 μm. Red arrows indicate inflammatory cell infiltration. (B) Hepatic Nt5e enzyme activity (n = 3 biologically independent mice per group). (C) Western blot analysis of Nt5e protein expression: (a) representative blot images and (b) quantitative analysis (n = 3 biologically independent mice per group). (D) Relative mRNA expression level of Nt5e in liver tissue (n = 3 biologically independent mice per group). Data are presented as mean ± SD. Significant differences were determined by one-way ANOVA with Tukey's post-hoc test (* p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

    Article Snippet: Membranes were incubated overnight at 4 °C with primary antibodies against Nt5e (1:1000, Bioss, China) and Pdzk1 (1:500, GeneTex, USA), followed by standard immunoblotting procedures.

    Techniques: Staining, Activity Assay, Western Blot, Expressing