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anti phosphorylated plcγ1  (Cell Signaling Technology Inc)


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    Structured Review

    Cell Signaling Technology Inc anti phosphorylated plcγ1
    Anti Phosphorylated Plcγ1, supplied by Cell Signaling Technology Inc, used in various techniques. Bioz Stars score: 94/100, based on 74 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/anti+plc%CE%B31/Phospho-PLCgamma1+(Ser1248)+Rabbit+mAb/pm42810528-62-20-23
    Average 94 stars, based on 74 article reviews
    anti phosphorylated plcγ1 - by Bioz Stars, 2026-10
    94/100 stars

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    Related Articles

    other:

    Article Title: Concurrence of FGFR1 mutations modulates oncogenesis in glioneuronal tumors
    Article Snippet: Anti-PLCγ1 , Cell Signaling Technology , #5690.


    Incubation:

    Article Title: Characterization of the dual ITK/JAK3 small molecule covalent inhibitor ATI-2138
    Article Snippet: Aparna Kaul, Heidi Hope, Canxin Xu, Rakesh Basavalingappa, Sara Binz, Chad Boily, Zachary Bradley, David Burt, Catherine Emanuel, Jacob Fairchild, Sarah Egan, Anne Hildebrand, Victoria Howell, Huiyan Huang, Emma Huff, Abbygail Iken, Stephanie Knapik, Melissa Lawrence, Huawen Lin, Jessea Wenjie Lu, Jonathan Mattingly, Dean McGraw, Nancy McGraw, Stephen Mnich, William Morton, Robert Ortmann, Tyler Piccinni-Ash, Rafael Saer, Cristiane Secca da Silva, Loreen Stillwell, William Taylor, Elizabeth Warner, Ann Wrightstone, E. Jon Jacobsen, David R. Anderson, Joseph Monahan

    Blocking Assay:

    Article Title: Characterization of the dual ITK/JAK3 small molecule covalent inhibitor ATI-2138
    Article Snippet: Aparna Kaul, Heidi Hope, Canxin Xu, Rakesh Basavalingappa, Sara Binz, Chad Boily, Zachary Bradley, David Burt, Catherine Emanuel, Jacob Fairchild, Sarah Egan, Anne Hildebrand, Victoria Howell, Huiyan Huang, Emma Huff, Abbygail Iken, Stephanie Knapik, Melissa Lawrence, Huawen Lin, Jessea Wenjie Lu, Jonathan Mattingly, Dean McGraw, Nancy McGraw, Stephen Mnich, William Morton, Robert Ortmann, Tyler Piccinni-Ash, Rafael Saer, Cristiane Secca da Silva, Loreen Stillwell, William Taylor, Elizabeth Warner, Ann Wrightstone, E. Jon Jacobsen, David R. Anderson, Joseph Monahan

    Gentle:

    Article Title: Characterization of the dual ITK/JAK3 small molecule covalent inhibitor ATI-2138
    Article Snippet: Aparna Kaul, Heidi Hope, Canxin Xu, Rakesh Basavalingappa, Sara Binz, Chad Boily, Zachary Bradley, David Burt, Catherine Emanuel, Jacob Fairchild, Sarah Egan, Anne Hildebrand, Victoria Howell, Huiyan Huang, Emma Huff, Abbygail Iken, Stephanie Knapik, Melissa Lawrence, Huawen Lin, Jessea Wenjie Lu, Jonathan Mattingly, Dean McGraw, Nancy McGraw, Stephen Mnich, William Morton, Robert Ortmann, Tyler Piccinni-Ash, Rafael Saer, Cristiane Secca da Silva, Loreen Stillwell, William Taylor, Elizabeth Warner, Ann Wrightstone, E. Jon Jacobsen, David R. Anderson, Joseph Monahan



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    Exploring the impact of ITK on T cell subsets. ( A ) Schematic diagram of the study design (the CD3⁺ T cells shown were primary cells isolated and sorted from the spleens of C57BL/6 mice, subsequently transduced with lentivirus and selected with puromycin to generate stable cell lines for subsequent experiments); ( B ) Quantitative detection of total CD3 + T cell proportions in BM via flow cytometry; (C) Quantitative detection of CD4 + T cell proportions in BM via flow cytometry; ( D ) Quantitative detection of CD8 + T cell proportions in BM via flow cytometry; ( E ) Quantitative detection of Th1 (CD4 + IFN-γ + ) cell proportions in BM via flow cytometry; ( F ) Quantitative detection of Th2 (CD4 + IL-4 + ) cell proportions in BM via flow cytometry; ( G ) Quantitative detection of Th17 (CD4 + IL-17 + ) cell proportions in BM via flow cytometry; ( H ) Quantitative detection of Treg (CD4 + CD25 + Foxp3 + ) cell proportions in BM via flow cytometry; ( I ) Flow cytometry analysis of the levels of ITK and <t>PLCγ1</t> phosphorylation in CD3 + T cells in BM; ( J ) Flow cytometry analysis of the mean fluorescence intensity (MFI) of ITK and <t>p-PLCγ1;</t> ( K ) IHC analysis of the levels of ITK and PLCγ1 phosphorylation in BM tissue, Bar = 50 μm; Statistical comparisons between groups were made using unpaired Student’s t-test (for normally distributed and variance-homogeneous data) or Mann–Whitney U test (for non-parametric data). * Indicates p < 0.05 between groups, ** indicates p < 0.001 between groups, *** indicates p < 0.001 between groups, with 6 mice per group
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    Exploring the impact of ITK on T cell subsets. ( A ) Schematic diagram of the study design (the CD3⁺ T cells shown were primary cells isolated and sorted from the spleens of C57BL/6 mice, subsequently transduced with lentivirus and selected with puromycin to generate stable cell lines for subsequent experiments); ( B ) Quantitative detection of total CD3 + T cell proportions in BM via flow cytometry; (C) Quantitative detection of CD4 + T cell proportions in BM via flow cytometry; ( D ) Quantitative detection of CD8 + T cell proportions in BM via flow cytometry; ( E ) Quantitative detection of Th1 (CD4 + IFN-γ + ) cell proportions in BM via flow cytometry; ( F ) Quantitative detection of Th2 (CD4 + IL-4 + ) cell proportions in BM via flow cytometry; ( G ) Quantitative detection of Th17 (CD4 + IL-17 + ) cell proportions in BM via flow cytometry; ( H ) Quantitative detection of Treg (CD4 + CD25 + Foxp3 + ) cell proportions in BM via flow cytometry; ( I ) Flow cytometry analysis of the levels of ITK and <t>PLCγ1</t> phosphorylation in CD3 + T cells in BM; ( J ) Flow cytometry analysis of the mean fluorescence intensity (MFI) of ITK and <t>p-PLCγ1;</t> ( K ) IHC analysis of the levels of ITK and PLCγ1 phosphorylation in BM tissue, Bar = 50 μm; Statistical comparisons between groups were made using unpaired Student’s t-test (for normally distributed and variance-homogeneous data) or Mann–Whitney U test (for non-parametric data). * Indicates p < 0.05 between groups, ** indicates p < 0.001 between groups, *** indicates p < 0.001 between groups, with 6 mice per group
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    Exploring the impact of ITK on T cell subsets. ( A ) Schematic diagram of the study design (the CD3⁺ T cells shown were primary cells isolated and sorted from the spleens of C57BL/6 mice, subsequently transduced with lentivirus and selected with puromycin to generate stable cell lines for subsequent experiments); ( B ) Quantitative detection of total CD3 + T cell proportions in BM via flow cytometry; (C) Quantitative detection of CD4 + T cell proportions in BM via flow cytometry; ( D ) Quantitative detection of CD8 + T cell proportions in BM via flow cytometry; ( E ) Quantitative detection of Th1 (CD4 + IFN-γ + ) cell proportions in BM via flow cytometry; ( F ) Quantitative detection of Th2 (CD4 + IL-4 + ) cell proportions in BM via flow cytometry; ( G ) Quantitative detection of Th17 (CD4 + IL-17 + ) cell proportions in BM via flow cytometry; ( H ) Quantitative detection of Treg (CD4 + CD25 + Foxp3 + ) cell proportions in BM via flow cytometry; ( I ) Flow cytometry analysis of the levels of ITK and <t>PLCγ1</t> phosphorylation in CD3 + T cells in BM; ( J ) Flow cytometry analysis of the mean fluorescence intensity (MFI) of ITK and <t>p-PLCγ1;</t> ( K ) IHC analysis of the levels of ITK and PLCγ1 phosphorylation in BM tissue, Bar = 50 μm; Statistical comparisons between groups were made using unpaired Student’s t-test (for normally distributed and variance-homogeneous data) or Mann–Whitney U test (for non-parametric data). * Indicates p < 0.05 between groups, ** indicates p < 0.001 between groups, *** indicates p < 0.001 between groups, with 6 mice per group
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    Exploring the impact of ITK on T cell subsets. ( A ) Schematic diagram of the study design (the CD3⁺ T cells shown were primary cells isolated and sorted from the spleens of C57BL/6 mice, subsequently transduced with lentivirus and selected with puromycin to generate stable cell lines for subsequent experiments); ( B ) Quantitative detection of total CD3 + T cell proportions in BM via flow cytometry; (C) Quantitative detection of CD4 + T cell proportions in BM via flow cytometry; ( D ) Quantitative detection of CD8 + T cell proportions in BM via flow cytometry; ( E ) Quantitative detection of Th1 (CD4 + IFN-γ + ) cell proportions in BM via flow cytometry; ( F ) Quantitative detection of Th2 (CD4 + IL-4 + ) cell proportions in BM via flow cytometry; ( G ) Quantitative detection of Th17 (CD4 + IL-17 + ) cell proportions in BM via flow cytometry; ( H ) Quantitative detection of Treg (CD4 + CD25 + Foxp3 + ) cell proportions in BM via flow cytometry; ( I ) Flow cytometry analysis of the levels of ITK and <t>PLCγ1</t> phosphorylation in CD3 + T cells in BM; ( J ) Flow cytometry analysis of the mean fluorescence intensity (MFI) of ITK and <t>p-PLCγ1;</t> ( K ) IHC analysis of the levels of ITK and PLCγ1 phosphorylation in BM tissue, Bar = 50 μm; Statistical comparisons between groups were made using unpaired Student’s t-test (for normally distributed and variance-homogeneous data) or Mann–Whitney U test (for non-parametric data). * Indicates p < 0.05 between groups, ** indicates p < 0.001 between groups, *** indicates p < 0.001 between groups, with 6 mice per group
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    Exploring the impact of ITK on T cell subsets. ( A ) Schematic diagram of the study design (the CD3⁺ T cells shown were primary cells isolated and sorted from the spleens of C57BL/6 mice, subsequently transduced with lentivirus and selected with puromycin to generate stable cell lines for subsequent experiments); ( B ) Quantitative detection of total CD3 + T cell proportions in BM via flow cytometry; (C) Quantitative detection of CD4 + T cell proportions in BM via flow cytometry; ( D ) Quantitative detection of CD8 + T cell proportions in BM via flow cytometry; ( E ) Quantitative detection of Th1 (CD4 + IFN-γ + ) cell proportions in BM via flow cytometry; ( F ) Quantitative detection of Th2 (CD4 + IL-4 + ) cell proportions in BM via flow cytometry; ( G ) Quantitative detection of Th17 (CD4 + IL-17 + ) cell proportions in BM via flow cytometry; ( H ) Quantitative detection of Treg (CD4 + CD25 + Foxp3 + ) cell proportions in BM via flow cytometry; ( I ) Flow cytometry analysis of the levels of ITK and <t>PLCγ1</t> phosphorylation in CD3 + T cells in BM; ( J ) Flow cytometry analysis of the mean fluorescence intensity (MFI) of ITK and <t>p-PLCγ1;</t> ( K ) IHC analysis of the levels of ITK and PLCγ1 phosphorylation in BM tissue, Bar = 50 μm; Statistical comparisons between groups were made using unpaired Student’s t-test (for normally distributed and variance-homogeneous data) or Mann–Whitney U test (for non-parametric data). * Indicates p < 0.05 between groups, ** indicates p < 0.001 between groups, *** indicates p < 0.001 between groups, with 6 mice per group
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    Cell Signaling Technology Inc rabbit anti plcγ1
    Exploring the impact of ITK on T cell subsets. ( A ) Schematic diagram of the study design (the CD3⁺ T cells shown were primary cells isolated and sorted from the spleens of C57BL/6 mice, subsequently transduced with lentivirus and selected with puromycin to generate stable cell lines for subsequent experiments); ( B ) Quantitative detection of total CD3 + T cell proportions in BM via flow cytometry; (C) Quantitative detection of CD4 + T cell proportions in BM via flow cytometry; ( D ) Quantitative detection of CD8 + T cell proportions in BM via flow cytometry; ( E ) Quantitative detection of Th1 (CD4 + IFN-γ + ) cell proportions in BM via flow cytometry; ( F ) Quantitative detection of Th2 (CD4 + IL-4 + ) cell proportions in BM via flow cytometry; ( G ) Quantitative detection of Th17 (CD4 + IL-17 + ) cell proportions in BM via flow cytometry; ( H ) Quantitative detection of Treg (CD4 + CD25 + Foxp3 + ) cell proportions in BM via flow cytometry; ( I ) Flow cytometry analysis of the levels of ITK and <t>PLCγ1</t> phosphorylation in CD3 + T cells in BM; ( J ) Flow cytometry analysis of the mean fluorescence intensity (MFI) of ITK and <t>p-PLCγ1;</t> ( K ) IHC analysis of the levels of ITK and PLCγ1 phosphorylation in BM tissue, Bar = 50 μm; Statistical comparisons between groups were made using unpaired Student’s t-test (for normally distributed and variance-homogeneous data) or Mann–Whitney U test (for non-parametric data). * Indicates p < 0.05 between groups, ** indicates p < 0.001 between groups, *** indicates p < 0.001 between groups, with 6 mice per group
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    Exploring the impact of ITK on T cell subsets. ( A ) Schematic diagram of the study design (the CD3⁺ T cells shown were primary cells isolated and sorted from the spleens of C57BL/6 mice, subsequently transduced with lentivirus and selected with puromycin to generate stable cell lines for subsequent experiments); ( B ) Quantitative detection of total CD3 + T cell proportions in BM via flow cytometry; (C) Quantitative detection of CD4 + T cell proportions in BM via flow cytometry; ( D ) Quantitative detection of CD8 + T cell proportions in BM via flow cytometry; ( E ) Quantitative detection of Th1 (CD4 + IFN-γ + ) cell proportions in BM via flow cytometry; ( F ) Quantitative detection of Th2 (CD4 + IL-4 + ) cell proportions in BM via flow cytometry; ( G ) Quantitative detection of Th17 (CD4 + IL-17 + ) cell proportions in BM via flow cytometry; ( H ) Quantitative detection of Treg (CD4 + CD25 + Foxp3 + ) cell proportions in BM via flow cytometry; ( I ) Flow cytometry analysis of the levels of ITK and <t>PLCγ1</t> phosphorylation in CD3 + T cells in BM; ( J ) Flow cytometry analysis of the mean fluorescence intensity (MFI) of ITK and <t>p-PLCγ1;</t> ( K ) IHC analysis of the levels of ITK and PLCγ1 phosphorylation in BM tissue, Bar = 50 μm; Statistical comparisons between groups were made using unpaired Student’s t-test (for normally distributed and variance-homogeneous data) or Mann–Whitney U test (for non-parametric data). * Indicates p < 0.05 between groups, ** indicates p < 0.001 between groups, *** indicates p < 0.001 between groups, with 6 mice per group
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    Exploring the impact of ITK on T cell subsets. ( A ) Schematic diagram of the study design (the CD3⁺ T cells shown were primary cells isolated and sorted from the spleens of C57BL/6 mice, subsequently transduced with lentivirus and selected with puromycin to generate stable cell lines for subsequent experiments); ( B ) Quantitative detection of total CD3 + T cell proportions in BM via flow cytometry; (C) Quantitative detection of CD4 + T cell proportions in BM via flow cytometry; ( D ) Quantitative detection of CD8 + T cell proportions in BM via flow cytometry; ( E ) Quantitative detection of Th1 (CD4 + IFN-γ + ) cell proportions in BM via flow cytometry; ( F ) Quantitative detection of Th2 (CD4 + IL-4 + ) cell proportions in BM via flow cytometry; ( G ) Quantitative detection of Th17 (CD4 + IL-17 + ) cell proportions in BM via flow cytometry; ( H ) Quantitative detection of Treg (CD4 + CD25 + Foxp3 + ) cell proportions in BM via flow cytometry; ( I ) Flow cytometry analysis of the levels of ITK and PLCγ1 phosphorylation in CD3 + T cells in BM; ( J ) Flow cytometry analysis of the mean fluorescence intensity (MFI) of ITK and p-PLCγ1; ( K ) IHC analysis of the levels of ITK and PLCγ1 phosphorylation in BM tissue, Bar = 50 μm; Statistical comparisons between groups were made using unpaired Student’s t-test (for normally distributed and variance-homogeneous data) or Mann–Whitney U test (for non-parametric data). * Indicates p < 0.05 between groups, ** indicates p < 0.001 between groups, *** indicates p < 0.001 between groups, with 6 mice per group

    Journal: Journal of Nanobiotechnology

    Article Title: Targeted inhibition of ITK activity with anti-CD3 antibody-modified calcium silicate nanoparticles loaded with novel 7H-Pyrrolo[2,3-d]pyrimidine derivatives for treating aplastic anemia

    doi: 10.1186/s12951-026-04276-7

    Figure Lengend Snippet: Exploring the impact of ITK on T cell subsets. ( A ) Schematic diagram of the study design (the CD3⁺ T cells shown were primary cells isolated and sorted from the spleens of C57BL/6 mice, subsequently transduced with lentivirus and selected with puromycin to generate stable cell lines for subsequent experiments); ( B ) Quantitative detection of total CD3 + T cell proportions in BM via flow cytometry; (C) Quantitative detection of CD4 + T cell proportions in BM via flow cytometry; ( D ) Quantitative detection of CD8 + T cell proportions in BM via flow cytometry; ( E ) Quantitative detection of Th1 (CD4 + IFN-γ + ) cell proportions in BM via flow cytometry; ( F ) Quantitative detection of Th2 (CD4 + IL-4 + ) cell proportions in BM via flow cytometry; ( G ) Quantitative detection of Th17 (CD4 + IL-17 + ) cell proportions in BM via flow cytometry; ( H ) Quantitative detection of Treg (CD4 + CD25 + Foxp3 + ) cell proportions in BM via flow cytometry; ( I ) Flow cytometry analysis of the levels of ITK and PLCγ1 phosphorylation in CD3 + T cells in BM; ( J ) Flow cytometry analysis of the mean fluorescence intensity (MFI) of ITK and p-PLCγ1; ( K ) IHC analysis of the levels of ITK and PLCγ1 phosphorylation in BM tissue, Bar = 50 μm; Statistical comparisons between groups were made using unpaired Student’s t-test (for normally distributed and variance-homogeneous data) or Mann–Whitney U test (for non-parametric data). * Indicates p < 0.05 between groups, ** indicates p < 0.001 between groups, *** indicates p < 0.001 between groups, with 6 mice per group

    Article Snippet: Primary antibodies against ITK (rabbit, 1:200, PA5-29669, Thermo Fisher, USA), CD3 (rat, 1:200, 14–0032-82, Thermo Fisher, USA), and phosphorylated PLCγ1 (rabbit, 1:200, AF3210, Affbiotech, China) were applied and incubated overnight at 4 °C.

    Techniques: Isolation, Transduction, Stable Transfection, Flow Cytometry, Phospho-proteomics, Fluorescence, MANN-WHITNEY

    Synthesis and inhibition effect evaluation of NPDP. ( A ) NPDP synthesis pathway diagram. This illustrates synthesizing NPDP from the starting material S1 through three steps, with reaction conditions and key intermediates S2 and S3 labeled for each step; ( B ) molecular docking model of NPDP with ITK. The left panel shows the overall 3D model of NPDP binding to ITK, the middle panel displays the secondary structure representation of ITK, and the right panel provides an enlarged view showing the detailed interactions of NPDP with the active site of ITK; ( C ) western blot analysis verifying the inhibitory effect of NPDP on ITK activity. The left panel shows the expression levels of p-ITK, ITK, p-PLCγ1, and PLCγ1 protein in Jurkat cells treated with NPDP, while the right panel shows the corresponding protein expression levels in CD3 + T cells overexpressing ITK after NPDP treatment; ( D ) western blot analysis of p-PLCγ1 and PLCγ1 expression in Jurkat cells following ITK knockdown and NPDP treatment; ( E ) western blot analysis of p-ITK and ITK expression in Jurkat cells treated with varying concentrations of NPDP or PRN694; ( F ) western blot analysis of p-ITK, ITK, p-PLCγ1, and PLCγ1 expression in Jurkat cells subjected to TCR stimulation and treated with NPDP or PRN694. Statistical comparisons between groups were made using unpaired Student’s t-test (for normally distributed and variance-homogeneous data) or Mann–Whitney U test (for non-parametric data). All cell experiments were conducted in triplicate

    Journal: Journal of Nanobiotechnology

    Article Title: Targeted inhibition of ITK activity with anti-CD3 antibody-modified calcium silicate nanoparticles loaded with novel 7H-Pyrrolo[2,3-d]pyrimidine derivatives for treating aplastic anemia

    doi: 10.1186/s12951-026-04276-7

    Figure Lengend Snippet: Synthesis and inhibition effect evaluation of NPDP. ( A ) NPDP synthesis pathway diagram. This illustrates synthesizing NPDP from the starting material S1 through three steps, with reaction conditions and key intermediates S2 and S3 labeled for each step; ( B ) molecular docking model of NPDP with ITK. The left panel shows the overall 3D model of NPDP binding to ITK, the middle panel displays the secondary structure representation of ITK, and the right panel provides an enlarged view showing the detailed interactions of NPDP with the active site of ITK; ( C ) western blot analysis verifying the inhibitory effect of NPDP on ITK activity. The left panel shows the expression levels of p-ITK, ITK, p-PLCγ1, and PLCγ1 protein in Jurkat cells treated with NPDP, while the right panel shows the corresponding protein expression levels in CD3 + T cells overexpressing ITK after NPDP treatment; ( D ) western blot analysis of p-PLCγ1 and PLCγ1 expression in Jurkat cells following ITK knockdown and NPDP treatment; ( E ) western blot analysis of p-ITK and ITK expression in Jurkat cells treated with varying concentrations of NPDP or PRN694; ( F ) western blot analysis of p-ITK, ITK, p-PLCγ1, and PLCγ1 expression in Jurkat cells subjected to TCR stimulation and treated with NPDP or PRN694. Statistical comparisons between groups were made using unpaired Student’s t-test (for normally distributed and variance-homogeneous data) or Mann–Whitney U test (for non-parametric data). All cell experiments were conducted in triplicate

    Article Snippet: Primary antibodies against ITK (rabbit, 1:200, PA5-29669, Thermo Fisher, USA), CD3 (rat, 1:200, 14–0032-82, Thermo Fisher, USA), and phosphorylated PLCγ1 (rabbit, 1:200, AF3210, Affbiotech, China) were applied and incubated overnight at 4 °C.

    Techniques: Inhibition, Labeling, Binding Assay, Western Blot, Activity Assay, Expressing, Knockdown, MANN-WHITNEY

    Functionalization of porous calcium silicate nanoparticles and their application in immune cell targeting. ( A ) Illustration showing the transition from basic pSiNPs to pCaSiNPs, followed by the functionalization with CD3 antibodies to create antiCD3-pCaSiNPs and the drug carrier form (antiCD3-pCaSiNP@NPDP); ( B ) ELISA detection of the presence of CD3 antibodies in different nanoparticles; ( C ) Zeta potential measurements of different nanoparticles reflecting changes in surface charge; ( D ) LC-MS analysis of the amount of NPDP released from antiCD3-pCaSiNP@NPDP nanoparticles under different pH conditions; ( E ) SEM images showing the microstructural changes from untreated pSiNPs to drug-loaded pCaSiNPs, with the boxed area indicating the magnified position; left image Bar = 100 nm, right image Bar = 50 nm; ( G ) Flow cytometry analysis of binding rates of Alexa Fluor 488-labeled antiCD3-pCaSiNP@NPDP nanoparticles to different immune cell types, highlighting high affinity for T cells; ( H ) Confocal microscopy showing intracellular localization of antiCD3-pCaSiNP@NPDP nanoparticles; ( I ) Western blot analysis of p-ITK and p-PLCγ1 expression in CD3⁺ T cells under different treatment conditions. Statistical comparisons between groups were made using unpaired Student’s t-test (for normally distributed and variance-homogeneous data) or Mann–Whitney U test (for non-parametric data). *** indicates p < 0.001 between the two groups, ns indicates no significant difference between the two groups; cell experiments were repeated three times

    Journal: Journal of Nanobiotechnology

    Article Title: Targeted inhibition of ITK activity with anti-CD3 antibody-modified calcium silicate nanoparticles loaded with novel 7H-Pyrrolo[2,3-d]pyrimidine derivatives for treating aplastic anemia

    doi: 10.1186/s12951-026-04276-7

    Figure Lengend Snippet: Functionalization of porous calcium silicate nanoparticles and their application in immune cell targeting. ( A ) Illustration showing the transition from basic pSiNPs to pCaSiNPs, followed by the functionalization with CD3 antibodies to create antiCD3-pCaSiNPs and the drug carrier form (antiCD3-pCaSiNP@NPDP); ( B ) ELISA detection of the presence of CD3 antibodies in different nanoparticles; ( C ) Zeta potential measurements of different nanoparticles reflecting changes in surface charge; ( D ) LC-MS analysis of the amount of NPDP released from antiCD3-pCaSiNP@NPDP nanoparticles under different pH conditions; ( E ) SEM images showing the microstructural changes from untreated pSiNPs to drug-loaded pCaSiNPs, with the boxed area indicating the magnified position; left image Bar = 100 nm, right image Bar = 50 nm; ( G ) Flow cytometry analysis of binding rates of Alexa Fluor 488-labeled antiCD3-pCaSiNP@NPDP nanoparticles to different immune cell types, highlighting high affinity for T cells; ( H ) Confocal microscopy showing intracellular localization of antiCD3-pCaSiNP@NPDP nanoparticles; ( I ) Western blot analysis of p-ITK and p-PLCγ1 expression in CD3⁺ T cells under different treatment conditions. Statistical comparisons between groups were made using unpaired Student’s t-test (for normally distributed and variance-homogeneous data) or Mann–Whitney U test (for non-parametric data). *** indicates p < 0.001 between the two groups, ns indicates no significant difference between the two groups; cell experiments were repeated three times

    Article Snippet: Primary antibodies against ITK (rabbit, 1:200, PA5-29669, Thermo Fisher, USA), CD3 (rat, 1:200, 14–0032-82, Thermo Fisher, USA), and phosphorylated PLCγ1 (rabbit, 1:200, AF3210, Affbiotech, China) were applied and incubated overnight at 4 °C.

    Techniques: Enzyme-linked Immunosorbent Assay, Zeta Potential Analyzer, Liquid Chromatography with Mass Spectroscopy, Flow Cytometry, Binding Assay, Labeling, Confocal Microscopy, Western Blot, Expressing, MANN-WHITNEY

    Investigating the effects of antiCD3-pCaSiNP@NPDP treatment on T cell differentiation and PLCγ1 phosphorylation. ( A ) Flow cytometry analysis of bone marrow CD3⁺ T-cell binding to antiCD3-pCaSiNP@NPDP nanoparticles; ( B ) Flow cytometry analysis of total CD3 + T cell proportion in BM; ( C ) Flow cytometry analysis of CD4 + T cell proportion in BM; ( D ) Flow cytometry analysis of CD8 + T cell proportion in BM; ( E ) Flow cytometry analysis of Th1 (CD4 + IFN-γ + ) cell proportion in BM; ( F ) Flow cytometry analysis of Th2 (CD4 + IL-4 + ) cell proportion in BM; ( G ) Flow cytometry analysis of Th17 (CD4 + IL-17 + ) cell proportion in BM; ( H ) Flow cytometry analysis of Treg (CD4 + CD25 + Foxp3 + ) cell proportion in BM; ( I ) Flow cytometry of Th1 (IFN-γ⁺) cells; ( L ) Flow cytometry analysis of PLCγ1 phosphorylation level; ( M ) IHC analysis of PLCγ1 phosphorylation in BM tissue, Bar = 50 μm; Statistical comparisons between groups were made using unpaired Student’s t-test (for normally distributed and variance-homogeneous data) or Mann–Whitney U test (for non-parametric data). * indicates p < 0.05, ** indicates p < 0.001, *** indicates p < 0.001, with 6 mice per group

    Journal: Journal of Nanobiotechnology

    Article Title: Targeted inhibition of ITK activity with anti-CD3 antibody-modified calcium silicate nanoparticles loaded with novel 7H-Pyrrolo[2,3-d]pyrimidine derivatives for treating aplastic anemia

    doi: 10.1186/s12951-026-04276-7

    Figure Lengend Snippet: Investigating the effects of antiCD3-pCaSiNP@NPDP treatment on T cell differentiation and PLCγ1 phosphorylation. ( A ) Flow cytometry analysis of bone marrow CD3⁺ T-cell binding to antiCD3-pCaSiNP@NPDP nanoparticles; ( B ) Flow cytometry analysis of total CD3 + T cell proportion in BM; ( C ) Flow cytometry analysis of CD4 + T cell proportion in BM; ( D ) Flow cytometry analysis of CD8 + T cell proportion in BM; ( E ) Flow cytometry analysis of Th1 (CD4 + IFN-γ + ) cell proportion in BM; ( F ) Flow cytometry analysis of Th2 (CD4 + IL-4 + ) cell proportion in BM; ( G ) Flow cytometry analysis of Th17 (CD4 + IL-17 + ) cell proportion in BM; ( H ) Flow cytometry analysis of Treg (CD4 + CD25 + Foxp3 + ) cell proportion in BM; ( I ) Flow cytometry of Th1 (IFN-γ⁺) cells; ( L ) Flow cytometry analysis of PLCγ1 phosphorylation level; ( M ) IHC analysis of PLCγ1 phosphorylation in BM tissue, Bar = 50 μm; Statistical comparisons between groups were made using unpaired Student’s t-test (for normally distributed and variance-homogeneous data) or Mann–Whitney U test (for non-parametric data). * indicates p < 0.05, ** indicates p < 0.001, *** indicates p < 0.001, with 6 mice per group

    Article Snippet: Primary antibodies against ITK (rabbit, 1:200, PA5-29669, Thermo Fisher, USA), CD3 (rat, 1:200, 14–0032-82, Thermo Fisher, USA), and phosphorylated PLCγ1 (rabbit, 1:200, AF3210, Affbiotech, China) were applied and incubated overnight at 4 °C.

    Techniques: Cell Differentiation, Phospho-proteomics, Flow Cytometry, Binding Assay, MANN-WHITNEY