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anti human cd45 antibody  (Cell Signaling Technology Inc)


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    Structured Review

    Cell Signaling Technology Inc anti human cd45 antibody
    a , Schematic illustrating the principle of QuEST for quantifying molecule numbers and surface densities. b , Isolation and detection of fluorescence-labelled single molecules by TIRFM. c , Workflow for quantifying single-molecule fluorescence intensity. d , e , Intensity distribution within a 5×5-pixel region ( d ) and corresponding mean fluorescence intensity ( e ) of single <t>CD45</t> AF405, UCHT-1 AF488, ICAM-1 AF568, and UCHT-1 AF647 molecules. f , Workflow for quantifying fluorescence intensity of multiple molecules. g , Quantification of UCHT-1 and ICAM-1 densities on supported lipid bilayers (SLBs) containing different percentages of Ni–NTA using QuEST. h , i , Schematic ( h ) and quantification results ( i ) determining the linear dynamic range of DOPE with different fluorescence levels. j , Linear density ranges of UCHT-1 and ICAM-1 under different fluorescence conditions. k , T cells clustering UCHT-1 and ICAM-1 on SLBs, with dynamic molecular densities quantified. l , Relative errors in quantifying UCHT-1 and ICAM-1 densities using QuEST. Data in g and i are presented as mean ± SD; data in e and k are presented as mean ± SEM. Statistical significance was assessed using an unpaired two-tailed Student’s t -test (**** P ≤ 0.0001; ns, not significant). In e , data were obtained from 16 single molecules. In g and i , data were obtained from three independent TIRF images. The structure of UCHT-1 was derived from PDB entry 3FZU, and the structure of ICAM-1 was generated using AlphaFold3 from the corresponding protein sequence.
    Anti Human Cd45 Antibody, supplied by Cell Signaling Technology Inc, used in various techniques. Bioz Stars score: 94/100, based on 47 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/anti human cd45 antibody/product/Cell Signaling Technology Inc
    Average 94 stars, based on 47 article reviews
    anti human cd45 antibody - by Bioz Stars, 2026-05
    94/100 stars

    Images

    1) Product Images from "Quantitative extrapolation from single-tags (QuEST) immunofluorescence microscopy to derive TCR signalosome stoichiometries in human primary T cells"

    Article Title: Quantitative extrapolation from single-tags (QuEST) immunofluorescence microscopy to derive TCR signalosome stoichiometries in human primary T cells

    Journal: bioRxiv

    doi: 10.64898/2026.03.28.715001

    a , Schematic illustrating the principle of QuEST for quantifying molecule numbers and surface densities. b , Isolation and detection of fluorescence-labelled single molecules by TIRFM. c , Workflow for quantifying single-molecule fluorescence intensity. d , e , Intensity distribution within a 5×5-pixel region ( d ) and corresponding mean fluorescence intensity ( e ) of single CD45 AF405, UCHT-1 AF488, ICAM-1 AF568, and UCHT-1 AF647 molecules. f , Workflow for quantifying fluorescence intensity of multiple molecules. g , Quantification of UCHT-1 and ICAM-1 densities on supported lipid bilayers (SLBs) containing different percentages of Ni–NTA using QuEST. h , i , Schematic ( h ) and quantification results ( i ) determining the linear dynamic range of DOPE with different fluorescence levels. j , Linear density ranges of UCHT-1 and ICAM-1 under different fluorescence conditions. k , T cells clustering UCHT-1 and ICAM-1 on SLBs, with dynamic molecular densities quantified. l , Relative errors in quantifying UCHT-1 and ICAM-1 densities using QuEST. Data in g and i are presented as mean ± SD; data in e and k are presented as mean ± SEM. Statistical significance was assessed using an unpaired two-tailed Student’s t -test (**** P ≤ 0.0001; ns, not significant). In e , data were obtained from 16 single molecules. In g and i , data were obtained from three independent TIRF images. The structure of UCHT-1 was derived from PDB entry 3FZU, and the structure of ICAM-1 was generated using AlphaFold3 from the corresponding protein sequence.
    Figure Legend Snippet: a , Schematic illustrating the principle of QuEST for quantifying molecule numbers and surface densities. b , Isolation and detection of fluorescence-labelled single molecules by TIRFM. c , Workflow for quantifying single-molecule fluorescence intensity. d , e , Intensity distribution within a 5×5-pixel region ( d ) and corresponding mean fluorescence intensity ( e ) of single CD45 AF405, UCHT-1 AF488, ICAM-1 AF568, and UCHT-1 AF647 molecules. f , Workflow for quantifying fluorescence intensity of multiple molecules. g , Quantification of UCHT-1 and ICAM-1 densities on supported lipid bilayers (SLBs) containing different percentages of Ni–NTA using QuEST. h , i , Schematic ( h ) and quantification results ( i ) determining the linear dynamic range of DOPE with different fluorescence levels. j , Linear density ranges of UCHT-1 and ICAM-1 under different fluorescence conditions. k , T cells clustering UCHT-1 and ICAM-1 on SLBs, with dynamic molecular densities quantified. l , Relative errors in quantifying UCHT-1 and ICAM-1 densities using QuEST. Data in g and i are presented as mean ± SD; data in e and k are presented as mean ± SEM. Statistical significance was assessed using an unpaired two-tailed Student’s t -test (**** P ≤ 0.0001; ns, not significant). In e , data were obtained from 16 single molecules. In g and i , data were obtained from three independent TIRF images. The structure of UCHT-1 was derived from PDB entry 3FZU, and the structure of ICAM-1 was generated using AlphaFold3 from the corresponding protein sequence.

    Techniques Used: Isolation, Fluorescence, Two Tailed Test, Derivative Assay, Generated, Sequencing



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    a , Schematic illustrating the principle of QuEST for quantifying molecule numbers and surface densities. b , Isolation and detection of fluorescence-labelled single molecules by TIRFM. c , Workflow for quantifying single-molecule fluorescence intensity. d , e , Intensity distribution within a 5×5-pixel region ( d ) and corresponding mean fluorescence intensity ( e ) of single <t>CD45</t> AF405, UCHT-1 AF488, ICAM-1 AF568, and UCHT-1 AF647 molecules. f , Workflow for quantifying fluorescence intensity of multiple molecules. g , Quantification of UCHT-1 and ICAM-1 densities on supported lipid bilayers (SLBs) containing different percentages of Ni–NTA using QuEST. h , i , Schematic ( h ) and quantification results ( i ) determining the linear dynamic range of DOPE with different fluorescence levels. j , Linear density ranges of UCHT-1 and ICAM-1 under different fluorescence conditions. k , T cells clustering UCHT-1 and ICAM-1 on SLBs, with dynamic molecular densities quantified. l , Relative errors in quantifying UCHT-1 and ICAM-1 densities using QuEST. Data in g and i are presented as mean ± SD; data in e and k are presented as mean ± SEM. Statistical significance was assessed using an unpaired two-tailed Student’s t -test (**** P ≤ 0.0001; ns, not significant). In e , data were obtained from 16 single molecules. In g and i , data were obtained from three independent TIRF images. The structure of UCHT-1 was derived from PDB entry 3FZU, and the structure of ICAM-1 was generated using AlphaFold3 from the corresponding protein sequence.
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    Image Search Results


    a , Schematic illustrating the principle of QuEST for quantifying molecule numbers and surface densities. b , Isolation and detection of fluorescence-labelled single molecules by TIRFM. c , Workflow for quantifying single-molecule fluorescence intensity. d , e , Intensity distribution within a 5×5-pixel region ( d ) and corresponding mean fluorescence intensity ( e ) of single CD45 AF405, UCHT-1 AF488, ICAM-1 AF568, and UCHT-1 AF647 molecules. f , Workflow for quantifying fluorescence intensity of multiple molecules. g , Quantification of UCHT-1 and ICAM-1 densities on supported lipid bilayers (SLBs) containing different percentages of Ni–NTA using QuEST. h , i , Schematic ( h ) and quantification results ( i ) determining the linear dynamic range of DOPE with different fluorescence levels. j , Linear density ranges of UCHT-1 and ICAM-1 under different fluorescence conditions. k , T cells clustering UCHT-1 and ICAM-1 on SLBs, with dynamic molecular densities quantified. l , Relative errors in quantifying UCHT-1 and ICAM-1 densities using QuEST. Data in g and i are presented as mean ± SD; data in e and k are presented as mean ± SEM. Statistical significance was assessed using an unpaired two-tailed Student’s t -test (**** P ≤ 0.0001; ns, not significant). In e , data were obtained from 16 single molecules. In g and i , data were obtained from three independent TIRF images. The structure of UCHT-1 was derived from PDB entry 3FZU, and the structure of ICAM-1 was generated using AlphaFold3 from the corresponding protein sequence.

    Journal: bioRxiv

    Article Title: Quantitative extrapolation from single-tags (QuEST) immunofluorescence microscopy to derive TCR signalosome stoichiometries in human primary T cells

    doi: 10.64898/2026.03.28.715001

    Figure Lengend Snippet: a , Schematic illustrating the principle of QuEST for quantifying molecule numbers and surface densities. b , Isolation and detection of fluorescence-labelled single molecules by TIRFM. c , Workflow for quantifying single-molecule fluorescence intensity. d , e , Intensity distribution within a 5×5-pixel region ( d ) and corresponding mean fluorescence intensity ( e ) of single CD45 AF405, UCHT-1 AF488, ICAM-1 AF568, and UCHT-1 AF647 molecules. f , Workflow for quantifying fluorescence intensity of multiple molecules. g , Quantification of UCHT-1 and ICAM-1 densities on supported lipid bilayers (SLBs) containing different percentages of Ni–NTA using QuEST. h , i , Schematic ( h ) and quantification results ( i ) determining the linear dynamic range of DOPE with different fluorescence levels. j , Linear density ranges of UCHT-1 and ICAM-1 under different fluorescence conditions. k , T cells clustering UCHT-1 and ICAM-1 on SLBs, with dynamic molecular densities quantified. l , Relative errors in quantifying UCHT-1 and ICAM-1 densities using QuEST. Data in g and i are presented as mean ± SD; data in e and k are presented as mean ± SEM. Statistical significance was assessed using an unpaired two-tailed Student’s t -test (**** P ≤ 0.0001; ns, not significant). In e , data were obtained from 16 single molecules. In g and i , data were obtained from three independent TIRF images. The structure of UCHT-1 was derived from PDB entry 3FZU, and the structure of ICAM-1 was generated using AlphaFold3 from the corresponding protein sequence.

    Article Snippet: Unlabelled primary antibodies : anti-human CD8α antibody (Cell Signaling Technology, Cat#85336), anti-human CD28 antibody (Cell Signaling Technology, Cat#38774S), anti-human CD45 antibody (Cell Signaling Technology, Cat#13917S), anti-human PD-1 antibody (Cell Signaling Technology, Cat#86163T), anti-human Lck antibody (Cell Signaling Technology, Cat#2787S), anti-human ZAP-70 antibody (Cell Signaling Technology, Cat#3165S), anti-human LAT antibody (Cell Signaling Technology, Cat#45533S), anti-human PLCγ1 antibody (Cell Signaling Technology, Cat#5690S), and anti-human phospho-ZAP-70 (Tyr319) antibody (Cell Signaling Technology, Cat#2701).

    Techniques: Isolation, Fluorescence, Two Tailed Test, Derivative Assay, Generated, Sequencing

    (A-C) Survival of MV4;11 cell line-derived xenograft mice treated with metronomic doses of the ziftomenib and selinexor, and in combination. (D-F) Percentage of human CD45 positive cells in the peripheral blood of MV4;11 cell line-derived xenograft mice groups two weeks post last treatment (3 mice/group) with different doses of ziftomenib and selinexor. (G) Survival of GFP/Luciferase positive OCI-AML3 cell line-derived xenograft mice treated with ziftomenib and selinexor, and with combination. (H) Bioluminescence from luciferase in different groups of GFP/Luciferase-positive OCI-AML3 cell line-derived xenograft mice.

    Journal: bioRxiv

    Article Title: Combined Menin and XPO1 inhibition drive synergistic antileukemic activity in KMT2A r and NPM1 -m AML

    doi: 10.64898/2026.03.10.710924

    Figure Lengend Snippet: (A-C) Survival of MV4;11 cell line-derived xenograft mice treated with metronomic doses of the ziftomenib and selinexor, and in combination. (D-F) Percentage of human CD45 positive cells in the peripheral blood of MV4;11 cell line-derived xenograft mice groups two weeks post last treatment (3 mice/group) with different doses of ziftomenib and selinexor. (G) Survival of GFP/Luciferase positive OCI-AML3 cell line-derived xenograft mice treated with ziftomenib and selinexor, and with combination. (H) Bioluminescence from luciferase in different groups of GFP/Luciferase-positive OCI-AML3 cell line-derived xenograft mice.

    Article Snippet: Post-necropsy immunohistochemical analysis (IHC) of mice liver and lung tissues was performed for human CD45 (Rabbit anti-human, Cell Signaling Technology, Catalog no. 13917S).

    Techniques: Derivative Assay, Luciferase

    (A-B) Survival of vehicle or inhibitor-treated KMT2A- r and NPM1 -m PDX mice. (C) Residual leukemia evaluation on treatment and post-necropsy in NPM1 -m PDX NSG mice. (D) Human (h) CD45 staining in liver biopsy (top panel) and lung biopsy (bottom panel) under the vehicle control, ziftomenib, selinexor, and combination treatment cohorts. (E) hCD45+ cell density score (IHC) in Liver and Lung tissues. (F) Residual Bone marrow hCD45% by FCM during and after treatment in control, ziftomenib, selinexor, and combination cohorts. FCM, flow cytometry. (G) Measured spleen weight post-necropsy/termination in NSG mice in all cohorts

    Journal: bioRxiv

    Article Title: Combined Menin and XPO1 inhibition drive synergistic antileukemic activity in KMT2A r and NPM1 -m AML

    doi: 10.64898/2026.03.10.710924

    Figure Lengend Snippet: (A-B) Survival of vehicle or inhibitor-treated KMT2A- r and NPM1 -m PDX mice. (C) Residual leukemia evaluation on treatment and post-necropsy in NPM1 -m PDX NSG mice. (D) Human (h) CD45 staining in liver biopsy (top panel) and lung biopsy (bottom panel) under the vehicle control, ziftomenib, selinexor, and combination treatment cohorts. (E) hCD45+ cell density score (IHC) in Liver and Lung tissues. (F) Residual Bone marrow hCD45% by FCM during and after treatment in control, ziftomenib, selinexor, and combination cohorts. FCM, flow cytometry. (G) Measured spleen weight post-necropsy/termination in NSG mice in all cohorts

    Article Snippet: Post-necropsy immunohistochemical analysis (IHC) of mice liver and lung tissues was performed for human CD45 (Rabbit anti-human, Cell Signaling Technology, Catalog no. 13917S).

    Techniques: Staining, Control, Flow Cytometry