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biotinylated uea lectin  (Vector Laboratories)


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    Structured Review

    Vector Laboratories biotinylated uea lectin
    Biotinylated Uea Lectin, supplied by Vector Laboratories, used in various techniques. Bioz Stars score: 96/100, based on 503 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    Average 96 stars, based on 503 article reviews
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    Vector Laboratories biotinylated uea1 lectin
    a , Uniform Manifold Approximation and Projection (UMAP) of 22,932 CD45 − thymic cells from 2-mo and 18-mo female C57BL/6 mice, annotated by cell type subset and outlined by cell compartment (epithelial; fibroblast; endothelial; MEC; vSMC/PC; nmSC). b , ThymoSight integration of public data for murine nonhematopoietic thymic stromal cells, including our own dataset ( n = 297,988) annotated by publication source and outlined by cell type and compartment. c , Violin plots highlighting key genes marking individual subsets within individual structural compartments (fibroblast, endothelium and epithelium). d , e , UMAPs of individual structural compartments color-coded by cell type subset ( d ) and age cohort ( e ). n EC = 1,661; n FB = 13,240; n TEC = 6,175. f , Scaled change in frequency for each individual structural cell subset with age. g , Gating strategy and quantities for cell populations within the epithelial lineage (based on previous work ) in 2-mo ( n = 10) and 18-mo ( n = 10) mice. First, based on a CD45 − EpCAM + parent gate, tuft cells were identified by expression of L1CAM, then all other TECs were assessed for expression of conventional TEC markers <t>UEA1</t> and Ly51. Within the UEA1 hi Ly51 lo mTEC population CD104 + MHCII lo cells were identified as mTEC1. Cells that were deemed as non-mTEC1 were then fractionated based on MHCII and Ly6D. h , Concatenated flow cytometry plots and graphs highlighting the frequency of Ly51 − UEA1 − (DN-TECs) across lifespan (gated on CD45 − EpCAM + MHCII + cells). i , Violin plots of aaTEC1 and aaTEC2 novel markers. j , k , Flow cytometry plots ( j ) and quantities ( k ) for aaTEC1 and aaTEC2 populations in 2-mo ( n = 15), 12-mo ( n = 10) or 18-mo ( n = 13) male and female C57BL/6 mice. Summary data represent mean ± s.e.m.; each dot represents an individual biological replicate. Statistics were generated using a two-tailed Mann–Whitney test comparing within individual subsets ( g ) or Kruskal–Wallis ( k ) test with Dunn’s correction.
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    a , Uniform Manifold Approximation and Projection (UMAP) of 22,932 CD45 − thymic cells from 2-mo and 18-mo female C57BL/6 mice, annotated by cell type subset and outlined by cell compartment (epithelial; fibroblast; endothelial; MEC; vSMC/PC; nmSC). b , ThymoSight integration of public data for murine nonhematopoietic thymic stromal cells, including our own dataset ( n = 297,988) annotated by publication source and outlined by cell type and compartment. c , Violin plots highlighting key genes marking individual subsets within individual structural compartments (fibroblast, endothelium and epithelium). d , e , UMAPs of individual structural compartments color-coded by cell type subset ( d ) and age cohort ( e ). n EC = 1,661; n FB = 13,240; n TEC = 6,175. f , Scaled change in frequency for each individual structural cell subset with age. g , Gating strategy and quantities for cell populations within the epithelial lineage (based on previous work ) in 2-mo ( n = 10) and 18-mo ( n = 10) mice. First, based on a CD45 − EpCAM + parent gate, tuft cells were identified by expression of L1CAM, then all other TECs were assessed for expression of conventional TEC markers <t>UEA1</t> and Ly51. Within the UEA1 hi Ly51 lo mTEC population CD104 + MHCII lo cells were identified as mTEC1. Cells that were deemed as non-mTEC1 were then fractionated based on MHCII and Ly6D. h , Concatenated flow cytometry plots and graphs highlighting the frequency of Ly51 − UEA1 − (DN-TECs) across lifespan (gated on CD45 − EpCAM + MHCII + cells). i , Violin plots of aaTEC1 and aaTEC2 novel markers. j , k , Flow cytometry plots ( j ) and quantities ( k ) for aaTEC1 and aaTEC2 populations in 2-mo ( n = 15), 12-mo ( n = 10) or 18-mo ( n = 13) male and female C57BL/6 mice. Summary data represent mean ± s.e.m.; each dot represents an individual biological replicate. Statistics were generated using a two-tailed Mann–Whitney test comparing within individual subsets ( g ) or Kruskal–Wallis ( k ) test with Dunn’s correction.
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    Vector Laboratories lectin
    To measure the role of EXO Ascites in cancer invasion, EXO Ascites from four patients were examined using our 3D tumor spheroid chip model with the addition of EXO Ascites and gw4869. ( A ) Schematic showing the role of EXO Ascites in cancer progression based on a tumor spheroid angiogenesis model. Cancer invasiveness and angiogenesis in the 3D models for all patients treated with EXO Ascites (at concentrations of 0, 10 2 , 10 4 , 10 6 , and 10 8 , as indicated) were measured <t>by</t> <t>immunocytochemistry</t> on day 6. Fixed samples were immunostained with antibodies against EpCAM (for cancer, red) and <t>lectin</t> (for EC, green) and counterstained with DAPI (blue). ( B ) Representative 3D tumor spheroid angiogenesis images by staining with PKH67-EXO Ascites (yellow), tumor spheroid (EpCAM, red), and vessels (lectin, green); enlarged images depict PKH67-labeled EXO Ascites into the tumor cell (left) and vessels (right). Scale bars, 1 mm and 10 μm. ( C and D ) Representative images of the coculture showing changes in cancer invasion and angiogenesis among concentrations of EXO Ascites (as indicated above) in the tumor spheroid from a MET -amplified and a MET non-amplified GC model; PKH67-labeled EXO Ascites with bright-field imaging of the chip is shown in the left, immunolabeled confocal images with EpCAM, lectin, and DAPI are shown on the top of right, and inverted microscope image of coculture shown on the bottom of right in (D). Quantification of cancer invasiveness ( E ) and angiogenesis ( F ) for the images shown in (C) and (D). n = 3 ± SEM. Scale bar, 1 mm. # P < 0.05, ## P < 0.01, and ### P < 0.001 compared with 10 μM gw4869. * P < 0.05, ** P < 0.01, and *** P < 0.001 compared with each value at 0 particles/ml EXO Ascites . Notably, the EXO Ascites of all patients ( n = 4) induced cancer invasion. Scale bar, 1 mm.
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    Vector Laboratories biotinylated ulex europaeus lectin 1
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    a , Uniform Manifold Approximation and Projection (UMAP) of 22,932 CD45 − thymic cells from 2-mo and 18-mo female C57BL/6 mice, annotated by cell type subset and outlined by cell compartment (epithelial; fibroblast; endothelial; MEC; vSMC/PC; nmSC). b , ThymoSight integration of public data for murine nonhematopoietic thymic stromal cells, including our own dataset ( n = 297,988) annotated by publication source and outlined by cell type and compartment. c , Violin plots highlighting key genes marking individual subsets within individual structural compartments (fibroblast, endothelium and epithelium). d , e , UMAPs of individual structural compartments color-coded by cell type subset ( d ) and age cohort ( e ). n EC = 1,661; n FB = 13,240; n TEC = 6,175. f , Scaled change in frequency for each individual structural cell subset with age. g , Gating strategy and quantities for cell populations within the epithelial lineage (based on previous work ) in 2-mo ( n = 10) and 18-mo ( n = 10) mice. First, based on a CD45 − EpCAM + parent gate, tuft cells were identified by expression of L1CAM, then all other TECs were assessed for expression of conventional TEC markers UEA1 and Ly51. Within the UEA1 hi Ly51 lo mTEC population CD104 + MHCII lo cells were identified as mTEC1. Cells that were deemed as non-mTEC1 were then fractionated based on MHCII and Ly6D. h , Concatenated flow cytometry plots and graphs highlighting the frequency of Ly51 − UEA1 − (DN-TECs) across lifespan (gated on CD45 − EpCAM + MHCII + cells). i , Violin plots of aaTEC1 and aaTEC2 novel markers. j , k , Flow cytometry plots ( j ) and quantities ( k ) for aaTEC1 and aaTEC2 populations in 2-mo ( n = 15), 12-mo ( n = 10) or 18-mo ( n = 13) male and female C57BL/6 mice. Summary data represent mean ± s.e.m.; each dot represents an individual biological replicate. Statistics were generated using a two-tailed Mann–Whitney test comparing within individual subsets ( g ) or Kruskal–Wallis ( k ) test with Dunn’s correction.

    Journal: Nature Immunology

    Article Title: Age-related epithelial defects limit thymic function and regeneration

    doi: 10.1038/s41590-024-01915-9

    Figure Lengend Snippet: a , Uniform Manifold Approximation and Projection (UMAP) of 22,932 CD45 − thymic cells from 2-mo and 18-mo female C57BL/6 mice, annotated by cell type subset and outlined by cell compartment (epithelial; fibroblast; endothelial; MEC; vSMC/PC; nmSC). b , ThymoSight integration of public data for murine nonhematopoietic thymic stromal cells, including our own dataset ( n = 297,988) annotated by publication source and outlined by cell type and compartment. c , Violin plots highlighting key genes marking individual subsets within individual structural compartments (fibroblast, endothelium and epithelium). d , e , UMAPs of individual structural compartments color-coded by cell type subset ( d ) and age cohort ( e ). n EC = 1,661; n FB = 13,240; n TEC = 6,175. f , Scaled change in frequency for each individual structural cell subset with age. g , Gating strategy and quantities for cell populations within the epithelial lineage (based on previous work ) in 2-mo ( n = 10) and 18-mo ( n = 10) mice. First, based on a CD45 − EpCAM + parent gate, tuft cells were identified by expression of L1CAM, then all other TECs were assessed for expression of conventional TEC markers UEA1 and Ly51. Within the UEA1 hi Ly51 lo mTEC population CD104 + MHCII lo cells were identified as mTEC1. Cells that were deemed as non-mTEC1 were then fractionated based on MHCII and Ly6D. h , Concatenated flow cytometry plots and graphs highlighting the frequency of Ly51 − UEA1 − (DN-TECs) across lifespan (gated on CD45 − EpCAM + MHCII + cells). i , Violin plots of aaTEC1 and aaTEC2 novel markers. j , k , Flow cytometry plots ( j ) and quantities ( k ) for aaTEC1 and aaTEC2 populations in 2-mo ( n = 15), 12-mo ( n = 10) or 18-mo ( n = 13) male and female C57BL/6 mice. Summary data represent mean ± s.e.m.; each dot represents an individual biological replicate. Statistics were generated using a two-tailed Mann–Whitney test comparing within individual subsets ( g ) or Kruskal–Wallis ( k ) test with Dunn’s correction.

    Article Snippet: The antibodies used were rabbit anti-pan-cytokeratin (Dako, cat. no. Z0622), anti-K5 (BioLegend, cat. no. poly19055), rat anti-mouse K8/18 (Troma-1; Developmental Studies Hybridoma Bank), rabbit anti-K14 (Abcam, cat. no. EPR17350), rat anti-mouse AIRE (WEHI, clone 5H12), rabbit anti-human/mouse DCLK1 (LSBio, cat. no. LS-C100746) and biotinylated UEA1 lectin (Vector Labs, cat. no. B-1065).

    Techniques: Expressing, Flow Cytometry, Generated, Two Tailed Test, MANN-WHITNEY

    a–c , Concatenated flow cytometry plots and quantities for cell populations within the fibroblast ( a ), endothelial ( b ), and “other” ( c ) cell lineages in 2-mo (n = 10) and 18-mo (n = 10) mice. c , Concatenated flow cytometry plots and quantities for pericytes (PC), vascular smooth muscle cells (vSMC) and mesothelial cells (MEC) (n = 10/age). d , Frequency and numbers of DN-TEC across lifespan: 2-mo (n = 14), 6-mo (n = 5), 9mo (n = 15), 12-mo (n = 5), and 18+mo (n = 18). e , Violin plots with extensive list of aaTEC1 and aaTEC2 markers. f , Gating strategy for aaTECs. aaTEC1 were first gated on CD45 − TER119 − then PDGFRα - CD31 − cells. EpCAM + MHCII + cells were gated as the whole TEC compartment, then mTECs and cTECs were excluded by taking the UEA1 − Ly51 − double negative fraction and gating on CLDN3. aaTEC2 were also first gated on CD45 − TER119 − then PDGFRα - CD31 − cells. EpCAM − MHCII + cells were then gated and PDPN + PDGFRβ - were classed at aaTEC2. Summary data represents mean ± SEM; each dot represents an individual biological replicate. Statistics for a–c were generated using two-tailed Mann–Whitney tests comparing within individual populations and for d using the Kruskal–Wallis test with Dunns correction.

    Journal: Nature Immunology

    Article Title: Age-related epithelial defects limit thymic function and regeneration

    doi: 10.1038/s41590-024-01915-9

    Figure Lengend Snippet: a–c , Concatenated flow cytometry plots and quantities for cell populations within the fibroblast ( a ), endothelial ( b ), and “other” ( c ) cell lineages in 2-mo (n = 10) and 18-mo (n = 10) mice. c , Concatenated flow cytometry plots and quantities for pericytes (PC), vascular smooth muscle cells (vSMC) and mesothelial cells (MEC) (n = 10/age). d , Frequency and numbers of DN-TEC across lifespan: 2-mo (n = 14), 6-mo (n = 5), 9mo (n = 15), 12-mo (n = 5), and 18+mo (n = 18). e , Violin plots with extensive list of aaTEC1 and aaTEC2 markers. f , Gating strategy for aaTECs. aaTEC1 were first gated on CD45 − TER119 − then PDGFRα - CD31 − cells. EpCAM + MHCII + cells were gated as the whole TEC compartment, then mTECs and cTECs were excluded by taking the UEA1 − Ly51 − double negative fraction and gating on CLDN3. aaTEC2 were also first gated on CD45 − TER119 − then PDGFRα - CD31 − cells. EpCAM − MHCII + cells were then gated and PDPN + PDGFRβ - were classed at aaTEC2. Summary data represents mean ± SEM; each dot represents an individual biological replicate. Statistics for a–c were generated using two-tailed Mann–Whitney tests comparing within individual populations and for d using the Kruskal–Wallis test with Dunns correction.

    Article Snippet: The antibodies used were rabbit anti-pan-cytokeratin (Dako, cat. no. Z0622), anti-K5 (BioLegend, cat. no. poly19055), rat anti-mouse K8/18 (Troma-1; Developmental Studies Hybridoma Bank), rabbit anti-K14 (Abcam, cat. no. EPR17350), rat anti-mouse AIRE (WEHI, clone 5H12), rabbit anti-human/mouse DCLK1 (LSBio, cat. no. LS-C100746) and biotinylated UEA1 lectin (Vector Labs, cat. no. B-1065).

    Techniques: Flow Cytometry, Generated, Two Tailed Test, MANN-WHITNEY

    a , Representative flow cytometry plots from 12–18-mo male and female Foxn1 nTnG mice at the indicated ages, gated on tdTom − GFP + cells. tdTom − GFP + EpCAM + cells were then assessed for expression of the conventional TEC markers UEA1 and Ly51. b , Claudin-3 and UEA1 expression on tdTom − GFP + EpCAM + cells in Foxn1 nTnG mice, and quantification of claudin-3 on UEA1 + mTEC and UEA1 − Ly51 − DN-TECs ( n = 4 biological replicates representing individual mice). c , Podoplanin (Pdpn) and PDGFRa expression on tdTom − GFP + EpCAM − cells ( n = 4 biological replicates representing individual mice). d , Number of GFP + EpCAM + UEA1 − Ly51 − Cldn3 + aaTEC1 and GFP + EpCAM − PDPN + PDGFRα − aaTEC2 cells in 2-mo ( n = 6) and 18-mo ( n = 4) mice. e , scRNA-seq was performed on CD45 − cells isolated from male and female 20-mo Foxn1 tdTom and age-matched WT mice, and integrated into the epithelial data described in Fig. . UMAP of 8,505 cells of the epithelial compartment in the integrated data showing the TEC annotated subsets (top) and overlaid expression of tdTomato (bottom). Scale represents log-transformed average expression of the tdTomato-WPRE element. f , RNA velocity on selected TEC populations in 2-mo (top) or 18-mo (bottom) mice. n 2mo = 1,989; n 18mo = 3,382. g , Vein plots describing the continuous transition of 18-mo early prog , mTEC1, mTEC prol and aaTEC subsets to their predicted descendants (represented by diagonal flows) and the dynamic relative frequencies (vein width on the y axis) of these TEC subsets in the thymus over the binned pseudotime. h , Expression of thymocyte markers Thy1 and Lck overlaid on the 18-mo spatial transcriptomics dataset. Outline represents thymocyte-poor area overlaid onto heatmap showing aaTEC1 or aaTEC2 signatures. i , Two representative images in 12–18-mo male and female Foxn1 nTnG mice showing tdTomato and GFP expression with HD-TEC areas highlighted, with few or no tdTomato + cells. Scale bar, 50 μm. j , Human tissue sections from a 50-year-old woman. Shown are consecutive sections with H&E, cytokeratin or CD1a staining. k , aaTEC1 and aaTEC2 gene signatures (top 20 marker genes from our mouse data converted to human orthologs; Supplementary Fig. and Supplementary Table ) were overlaid on human thymic epithelial cells ( n TEC = 40,144) from single-cell sequencing datasets generated and published elsewhere , , . Summary data represents mean ± s.e.m. and each dot represents an individual biological replicate. Statistics were generated ( b – d ) using a two-tailed Mann–Whitney test.

    Journal: Nature Immunology

    Article Title: Age-related epithelial defects limit thymic function and regeneration

    doi: 10.1038/s41590-024-01915-9

    Figure Lengend Snippet: a , Representative flow cytometry plots from 12–18-mo male and female Foxn1 nTnG mice at the indicated ages, gated on tdTom − GFP + cells. tdTom − GFP + EpCAM + cells were then assessed for expression of the conventional TEC markers UEA1 and Ly51. b , Claudin-3 and UEA1 expression on tdTom − GFP + EpCAM + cells in Foxn1 nTnG mice, and quantification of claudin-3 on UEA1 + mTEC and UEA1 − Ly51 − DN-TECs ( n = 4 biological replicates representing individual mice). c , Podoplanin (Pdpn) and PDGFRa expression on tdTom − GFP + EpCAM − cells ( n = 4 biological replicates representing individual mice). d , Number of GFP + EpCAM + UEA1 − Ly51 − Cldn3 + aaTEC1 and GFP + EpCAM − PDPN + PDGFRα − aaTEC2 cells in 2-mo ( n = 6) and 18-mo ( n = 4) mice. e , scRNA-seq was performed on CD45 − cells isolated from male and female 20-mo Foxn1 tdTom and age-matched WT mice, and integrated into the epithelial data described in Fig. . UMAP of 8,505 cells of the epithelial compartment in the integrated data showing the TEC annotated subsets (top) and overlaid expression of tdTomato (bottom). Scale represents log-transformed average expression of the tdTomato-WPRE element. f , RNA velocity on selected TEC populations in 2-mo (top) or 18-mo (bottom) mice. n 2mo = 1,989; n 18mo = 3,382. g , Vein plots describing the continuous transition of 18-mo early prog , mTEC1, mTEC prol and aaTEC subsets to their predicted descendants (represented by diagonal flows) and the dynamic relative frequencies (vein width on the y axis) of these TEC subsets in the thymus over the binned pseudotime. h , Expression of thymocyte markers Thy1 and Lck overlaid on the 18-mo spatial transcriptomics dataset. Outline represents thymocyte-poor area overlaid onto heatmap showing aaTEC1 or aaTEC2 signatures. i , Two representative images in 12–18-mo male and female Foxn1 nTnG mice showing tdTomato and GFP expression with HD-TEC areas highlighted, with few or no tdTomato + cells. Scale bar, 50 μm. j , Human tissue sections from a 50-year-old woman. Shown are consecutive sections with H&E, cytokeratin or CD1a staining. k , aaTEC1 and aaTEC2 gene signatures (top 20 marker genes from our mouse data converted to human orthologs; Supplementary Fig. and Supplementary Table ) were overlaid on human thymic epithelial cells ( n TEC = 40,144) from single-cell sequencing datasets generated and published elsewhere , , . Summary data represents mean ± s.e.m. and each dot represents an individual biological replicate. Statistics were generated ( b – d ) using a two-tailed Mann–Whitney test.

    Article Snippet: The antibodies used were rabbit anti-pan-cytokeratin (Dako, cat. no. Z0622), anti-K5 (BioLegend, cat. no. poly19055), rat anti-mouse K8/18 (Troma-1; Developmental Studies Hybridoma Bank), rabbit anti-K14 (Abcam, cat. no. EPR17350), rat anti-mouse AIRE (WEHI, clone 5H12), rabbit anti-human/mouse DCLK1 (LSBio, cat. no. LS-C100746) and biotinylated UEA1 lectin (Vector Labs, cat. no. B-1065).

    Techniques: Flow Cytometry, Expressing, Isolation, Transformation Assay, Staining, Marker, Sequencing, Generated, Two Tailed Test, MANN-WHITNEY

    a , 3D reconstruction and representative images of high-density TEC region from 12-mo Foxn1 nTnG mice stained with DCLK1 or UEA1 to highlight tuft cells and M-like cells, respectively. b , Flow cytometry plots showing proportion of selected mimetic cells (tuft, corneocyte and M-cells) in 2-mo (n = 6) and 18-mo (n = 8) Foxn1 nTnG mice. Mimetic cells were first gated on EpCAM + GFP + cells, then mTECs (UEA1 hi Ly51 lo ) were assessed for the mimetic cell markers DCLK1 (tuft cells), GP2 (microfold cells), and Ly6D (corneocytes). Bar graph shows quantification of mimetic cell numbers. c , Flow cytometry plots showing mimetic cell frequency in 18-mo Foxn1 nTnG mice (n = 8) gated on EpCAM + GFP + UEA1 − Ly51 − DN-TECs. Bar graph shows quantification of mimetic cells comparing mTECs (as in Extended Data Fig. 7b) and DN-TECs. d , Aire and Foxn1 expression in TEC subsets. e , Representative confocal images of thymic sections from 12-mo Foxn1 nTnG mice stained with anti-AIRE, with the medulla or high-density TECs highlighted. Scale bar: 50μm. Summary data represents mean ± SEM; each dot represents an individual biological replicate. Statistics for b-c were generated using two-tailed Mann–Whitney tests comparing within individual mimetic cell subsets.

    Journal: Nature Immunology

    Article Title: Age-related epithelial defects limit thymic function and regeneration

    doi: 10.1038/s41590-024-01915-9

    Figure Lengend Snippet: a , 3D reconstruction and representative images of high-density TEC region from 12-mo Foxn1 nTnG mice stained with DCLK1 or UEA1 to highlight tuft cells and M-like cells, respectively. b , Flow cytometry plots showing proportion of selected mimetic cells (tuft, corneocyte and M-cells) in 2-mo (n = 6) and 18-mo (n = 8) Foxn1 nTnG mice. Mimetic cells were first gated on EpCAM + GFP + cells, then mTECs (UEA1 hi Ly51 lo ) were assessed for the mimetic cell markers DCLK1 (tuft cells), GP2 (microfold cells), and Ly6D (corneocytes). Bar graph shows quantification of mimetic cell numbers. c , Flow cytometry plots showing mimetic cell frequency in 18-mo Foxn1 nTnG mice (n = 8) gated on EpCAM + GFP + UEA1 − Ly51 − DN-TECs. Bar graph shows quantification of mimetic cells comparing mTECs (as in Extended Data Fig. 7b) and DN-TECs. d , Aire and Foxn1 expression in TEC subsets. e , Representative confocal images of thymic sections from 12-mo Foxn1 nTnG mice stained with anti-AIRE, with the medulla or high-density TECs highlighted. Scale bar: 50μm. Summary data represents mean ± SEM; each dot represents an individual biological replicate. Statistics for b-c were generated using two-tailed Mann–Whitney tests comparing within individual mimetic cell subsets.

    Article Snippet: The antibodies used were rabbit anti-pan-cytokeratin (Dako, cat. no. Z0622), anti-K5 (BioLegend, cat. no. poly19055), rat anti-mouse K8/18 (Troma-1; Developmental Studies Hybridoma Bank), rabbit anti-K14 (Abcam, cat. no. EPR17350), rat anti-mouse AIRE (WEHI, clone 5H12), rabbit anti-human/mouse DCLK1 (LSBio, cat. no. LS-C100746) and biotinylated UEA1 lectin (Vector Labs, cat. no. B-1065).

    Techniques: Staining, Flow Cytometry, Expressing, Generated, Two Tailed Test, MANN-WHITNEY

    To measure the role of EXO Ascites in cancer invasion, EXO Ascites from four patients were examined using our 3D tumor spheroid chip model with the addition of EXO Ascites and gw4869. ( A ) Schematic showing the role of EXO Ascites in cancer progression based on a tumor spheroid angiogenesis model. Cancer invasiveness and angiogenesis in the 3D models for all patients treated with EXO Ascites (at concentrations of 0, 10 2 , 10 4 , 10 6 , and 10 8 , as indicated) were measured by immunocytochemistry on day 6. Fixed samples were immunostained with antibodies against EpCAM (for cancer, red) and lectin (for EC, green) and counterstained with DAPI (blue). ( B ) Representative 3D tumor spheroid angiogenesis images by staining with PKH67-EXO Ascites (yellow), tumor spheroid (EpCAM, red), and vessels (lectin, green); enlarged images depict PKH67-labeled EXO Ascites into the tumor cell (left) and vessels (right). Scale bars, 1 mm and 10 μm. ( C and D ) Representative images of the coculture showing changes in cancer invasion and angiogenesis among concentrations of EXO Ascites (as indicated above) in the tumor spheroid from a MET -amplified and a MET non-amplified GC model; PKH67-labeled EXO Ascites with bright-field imaging of the chip is shown in the left, immunolabeled confocal images with EpCAM, lectin, and DAPI are shown on the top of right, and inverted microscope image of coculture shown on the bottom of right in (D). Quantification of cancer invasiveness ( E ) and angiogenesis ( F ) for the images shown in (C) and (D). n = 3 ± SEM. Scale bar, 1 mm. # P < 0.05, ## P < 0.01, and ### P < 0.001 compared with 10 μM gw4869. * P < 0.05, ** P < 0.01, and *** P < 0.001 compared with each value at 0 particles/ml EXO Ascites . Notably, the EXO Ascites of all patients ( n = 4) induced cancer invasion. Scale bar, 1 mm.

    Journal: Science Advances

    Article Title: Patient-derived exosomes facilitate therapeutic targeting of oncogenic MET in advanced gastric cancer

    doi: 10.1126/sciadv.adk1098

    Figure Lengend Snippet: To measure the role of EXO Ascites in cancer invasion, EXO Ascites from four patients were examined using our 3D tumor spheroid chip model with the addition of EXO Ascites and gw4869. ( A ) Schematic showing the role of EXO Ascites in cancer progression based on a tumor spheroid angiogenesis model. Cancer invasiveness and angiogenesis in the 3D models for all patients treated with EXO Ascites (at concentrations of 0, 10 2 , 10 4 , 10 6 , and 10 8 , as indicated) were measured by immunocytochemistry on day 6. Fixed samples were immunostained with antibodies against EpCAM (for cancer, red) and lectin (for EC, green) and counterstained with DAPI (blue). ( B ) Representative 3D tumor spheroid angiogenesis images by staining with PKH67-EXO Ascites (yellow), tumor spheroid (EpCAM, red), and vessels (lectin, green); enlarged images depict PKH67-labeled EXO Ascites into the tumor cell (left) and vessels (right). Scale bars, 1 mm and 10 μm. ( C and D ) Representative images of the coculture showing changes in cancer invasion and angiogenesis among concentrations of EXO Ascites (as indicated above) in the tumor spheroid from a MET -amplified and a MET non-amplified GC model; PKH67-labeled EXO Ascites with bright-field imaging of the chip is shown in the left, immunolabeled confocal images with EpCAM, lectin, and DAPI are shown on the top of right, and inverted microscope image of coculture shown on the bottom of right in (D). Quantification of cancer invasiveness ( E ) and angiogenesis ( F ) for the images shown in (C) and (D). n = 3 ± SEM. Scale bar, 1 mm. # P < 0.05, ## P < 0.01, and ### P < 0.001 compared with 10 μM gw4869. * P < 0.05, ** P < 0.01, and *** P < 0.001 compared with each value at 0 particles/ml EXO Ascites . Notably, the EXO Ascites of all patients ( n = 4) induced cancer invasion. Scale bar, 1 mm.

    Article Snippet: Immunocytochemistry , Lectin (UEA I), biotinylated , 1:500 , B-1065-2 , Vector Laboratories.

    Techniques: Immunocytochemistry, Staining, Labeling, Amplification, Imaging, Immunolabeling, Inverted Microscopy

    Antibody lists for Western blotting,  immunocytochemistry,  IHC, imaging mass spectrometry, and exosome visualization. All antibody lists were used to characterize exosomes and verify the effects of EXOAscites on cancer progression in this study. IgG, immunoglobulin G; HRP, horseradish peroxidase.

    Journal: Science Advances

    Article Title: Patient-derived exosomes facilitate therapeutic targeting of oncogenic MET in advanced gastric cancer

    doi: 10.1126/sciadv.adk1098

    Figure Lengend Snippet: Antibody lists for Western blotting, immunocytochemistry, IHC, imaging mass spectrometry, and exosome visualization. All antibody lists were used to characterize exosomes and verify the effects of EXOAscites on cancer progression in this study. IgG, immunoglobulin G; HRP, horseradish peroxidase.

    Article Snippet: Immunocytochemistry , Lectin (UEA I), biotinylated , 1:500 , B-1065-2 , Vector Laboratories.

    Techniques: Western Blot, Immunocytochemistry, Imaging, Mass Spectrometry, Plasmid Preparation

    Lectins and their glycan-binding specificities

    Journal: iScience

    Article Title: Cancer-specific glycosylation of CD13 impacts its detection and activity in preclinical cancer tissues

    doi: 10.1016/j.isci.2023.108219

    Figure Lengend Snippet: Lectins and their glycan-binding specificities

    Article Snippet: Sambucus Nigra Lectin (SNA), Biotinylated , Vector Laboratories, UK , Cat# B-1065-2.

    Techniques: Binding Assay

    Human cancer CDX and normal tissue lysates were subjected to lectin affinity capture (A) Captured proteins were assessed by immunoblotting for CD13 using mAb 400–500 anti-CD13 antibody. Loading was assessed by Coomassie stain ( <xref ref-type=Figure S4 ). (B and C) Effect of sialo-glycan lectin binding on CD13 detection using mAb 400–500 anti-CD13 antibody and in cancer CDX and normal tissues. (D) Significance of glycosylation on the metabolic half live (min) of CD13 substrate in MCF-7 CDX homogenate. Data shown are the mean of 3 independent experiments ±SEM. ∗∗∗p > 0.001 and ∗∗∗∗p > 0.0001 (two-way ANOVA). " width="100%" height="100%">

    Journal: iScience

    Article Title: Cancer-specific glycosylation of CD13 impacts its detection and activity in preclinical cancer tissues

    doi: 10.1016/j.isci.2023.108219

    Figure Lengend Snippet: Human cancer CDX and normal tissue lysates were subjected to lectin affinity capture (A) Captured proteins were assessed by immunoblotting for CD13 using mAb 400–500 anti-CD13 antibody. Loading was assessed by Coomassie stain ( Figure S4 ). (B and C) Effect of sialo-glycan lectin binding on CD13 detection using mAb 400–500 anti-CD13 antibody and in cancer CDX and normal tissues. (D) Significance of glycosylation on the metabolic half live (min) of CD13 substrate in MCF-7 CDX homogenate. Data shown are the mean of 3 independent experiments ±SEM. ∗∗∗p > 0.001 and ∗∗∗∗p > 0.0001 (two-way ANOVA).

    Article Snippet: Sambucus Nigra Lectin (SNA), Biotinylated , Vector Laboratories, UK , Cat# B-1065-2.

    Techniques: Western Blot, Staining, Binding Assay

    CD13 detection in  lectin-affinity  captured proteins from human cancer CDX and normal tissues

    Journal: iScience

    Article Title: Cancer-specific glycosylation of CD13 impacts its detection and activity in preclinical cancer tissues

    doi: 10.1016/j.isci.2023.108219

    Figure Lengend Snippet: CD13 detection in lectin-affinity captured proteins from human cancer CDX and normal tissues

    Article Snippet: Sambucus Nigra Lectin (SNA), Biotinylated , Vector Laboratories, UK , Cat# B-1065-2.

    Techniques:

    Journal: iScience

    Article Title: Cancer-specific glycosylation of CD13 impacts its detection and activity in preclinical cancer tissues

    doi: 10.1016/j.isci.2023.108219

    Figure Lengend Snippet:

    Article Snippet: Sambucus Nigra Lectin (SNA), Biotinylated , Vector Laboratories, UK , Cat# B-1065-2.

    Techniques: Recombinant, Saline, Reverse Transcription, SYBR Green Assay, Plasmid Preparation, Western Blot, Knock-Out