Review



cd34 fraction  (Miltenyi Biotec)


Bioz Verified Symbol Miltenyi Biotec is a verified supplier
Bioz Manufacturer Symbol Miltenyi Biotec manufactures this product  
  • Logo
  • About
  • News
  • Press Release
  • Team
  • Advisors
  • Partners
  • Contact
  • Bioz Stars
  • Bioz vStars
  • 97

    Structured Review

    Miltenyi Biotec cd34 fraction
    Cd34 Fraction, supplied by Miltenyi Biotec, used in various techniques. Bioz Stars score: 97/100, based on 249 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/cd34 fraction/product/Miltenyi Biotec
    Average 97 stars, based on 249 article reviews
    cd34 fraction - by Bioz Stars, 2026-03
    97/100 stars

    Images



    Similar Products

    97
    Miltenyi Biotec cd34 fraction
    Cd34 Fraction, supplied by Miltenyi Biotec, used in various techniques. Bioz Stars score: 97/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/cd34 fraction/product/Miltenyi Biotec
    Average 97 stars, based on 1 article reviews
    cd34 fraction - by Bioz Stars, 2026-03
    97/100 stars
      Buy from Supplier

    99
    Miltenyi Biotec cd34 cell fractions
    Cd34 Cell Fractions, supplied by Miltenyi Biotec, used in various techniques. Bioz Stars score: 99/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/cd34 cell fractions/product/Miltenyi Biotec
    Average 99 stars, based on 1 article reviews
    cd34 cell fractions - by Bioz Stars, 2026-03
    99/100 stars
      Buy from Supplier

    99
    Miltenyi Biotec cd34 cell fraction
    Cd34 Cell Fraction, supplied by Miltenyi Biotec, used in various techniques. Bioz Stars score: 99/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/cd34 cell fraction/product/Miltenyi Biotec
    Average 99 stars, based on 1 article reviews
    cd34 cell fraction - by Bioz Stars, 2026-03
    99/100 stars
      Buy from Supplier

    90
    Glaxo Smith autologous cd34+-enriched cell fraction strimvelis
    FDA/EMA approved gene therapy product for rare monogenic diseases
    Autologous Cd34+ Enriched Cell Fraction Strimvelis, supplied by Glaxo Smith, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/autologous cd34+-enriched cell fraction strimvelis/product/Glaxo Smith
    Average 90 stars, based on 1 article reviews
    autologous cd34+-enriched cell fraction strimvelis - by Bioz Stars, 2026-03
    90/100 stars
      Buy from Supplier

    90
    Miltenyi Biotec cd34 + fraction
    High-throughput screening identifies VEGFR, Wee1, and MDM2 inhibitors as specific effective drugs against CML-LSPCs (A) Schematic of the high-throughput drug sensitivity and resistance testing experiments. Sixteen primary CML samples (12 CP, 1 AP, and 3 BP) and 3 healthy donor samples were screened using a library of 82 drugs in five different concentrations. In 12 CP and 1 AP-CML samples in which the blast population represented <20%, as well as in healthy donor samples, <t>CD34</t> + cells were sorted using magnetic sorting to enrich for the stem and <t>progenitor</t> <t>cell</t> (SPC) population. ∗In addition to the indicated 16 sorted samples, unsorted samples from 4 CP-CML patients were also tested. Further information about disease phase and sorting status of samples assigned to DSRT can be found in <xref ref-type=Table S1 . (B) Heatmap of the drug sensitivity of CP-LSPC ( n = 11), AP/BP ( n = 4), unsorted CP-CML ( n = 4), and healthy CD34 + ( n = 3) samples. Drug sensitivity scores (DSSs) of the most variable 20 drugs are shown. Explanatory tracks from top to bottom show disease status (CML, healthy), sorting status, phase of CML (CP, AP, or BP), and blast percentage in the initial sample prior to sorting. (+) indicates a BP patient with ABL T315I pan-TKI resistance mutation. Ward’s hierarchical clustering method was used for production of the heatmap. (C) Bar plot of the selective drug sensitivity of CML-LSPCs ( n = 16) compared to healthy CD34 + ( n = 3). Drugs are colored by their targeted functional classes. Bar height represents the specific DSS (sDSS) as calculated by the average of DSS responses in CML samples after subtraction of the average of DSS responses in healthy samples. (∗) indicates drugs that were tested only in a subset of samples. (D) Dose-response curves of TKIs (imatinib, dasatinib), VEGFR inhibitors (tivozanib, axitinib), the MDM2 inhibitor RG-7112, the BCL2 inhibitor navitoclax, the HDAC inhibitor belinostat, and the JAK2 inhibitor ruxolitinib in CP-LSPCs ( n = 11), BP ( n = 5), and healthy CD34 + ( n = 3) samples. Dots represent the median values for each group. Plots showing the individual sample’s dose-response curves for the drugs shown here are shown in Figure S2 C. See also Figures S1–S3 and Tables S1 , , and . " width="250" height="auto" />
    Cd34 + Fraction, supplied by Miltenyi Biotec, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/cd34 + fraction/product/Miltenyi Biotec
    Average 90 stars, based on 1 article reviews
    cd34 + fraction - by Bioz Stars, 2026-03
    90/100 stars
      Buy from Supplier

    Image Search Results


    FDA/EMA approved gene therapy product for rare monogenic diseases

    Journal: Clinical and Experimental Pediatrics

    Article Title: Development of orphan drugs for rare diseases

    doi: 10.3345/cep.2023.00535

    Figure Lengend Snippet: FDA/EMA approved gene therapy product for rare monogenic diseases

    Article Snippet: For instance, an autologous CD34+-enriched cell fraction, Strimvelis (GlaxoSmithKline plk, London, UK), which contains CD34+ cells transduced with a retroviral vector that encodes the human ADA cDNA sequence for ADA deficiency (introduced in 2016), and voretigene neparvovec-rzyl (Luxturna, Spark Therapeutics, Philadelphia, USA), for retinal dystrophy caused by mutations in the RPE65 gene, were approved by the FDA in 2017 at a cost of $850,000 per eye [ ].

    Techniques: Plasmid Preparation, In Vivo, Ex Vivo, Mutagenesis, Modification, Variant Assay

    High-throughput screening identifies VEGFR, Wee1, and MDM2 inhibitors as specific effective drugs against CML-LSPCs (A) Schematic of the high-throughput drug sensitivity and resistance testing experiments. Sixteen primary CML samples (12 CP, 1 AP, and 3 BP) and 3 healthy donor samples were screened using a library of 82 drugs in five different concentrations. In 12 CP and 1 AP-CML samples in which the blast population represented <20%, as well as in healthy donor samples, CD34 + cells were sorted using magnetic sorting to enrich for the stem and progenitor cell (SPC) population. ∗In addition to the indicated 16 sorted samples, unsorted samples from 4 CP-CML patients were also tested. Further information about disease phase and sorting status of samples assigned to DSRT can be found in <xref ref-type=Table S1 . (B) Heatmap of the drug sensitivity of CP-LSPC ( n = 11), AP/BP ( n = 4), unsorted CP-CML ( n = 4), and healthy CD34 + ( n = 3) samples. Drug sensitivity scores (DSSs) of the most variable 20 drugs are shown. Explanatory tracks from top to bottom show disease status (CML, healthy), sorting status, phase of CML (CP, AP, or BP), and blast percentage in the initial sample prior to sorting. (+) indicates a BP patient with ABL T315I pan-TKI resistance mutation. Ward’s hierarchical clustering method was used for production of the heatmap. (C) Bar plot of the selective drug sensitivity of CML-LSPCs ( n = 16) compared to healthy CD34 + ( n = 3). Drugs are colored by their targeted functional classes. Bar height represents the specific DSS (sDSS) as calculated by the average of DSS responses in CML samples after subtraction of the average of DSS responses in healthy samples. (∗) indicates drugs that were tested only in a subset of samples. (D) Dose-response curves of TKIs (imatinib, dasatinib), VEGFR inhibitors (tivozanib, axitinib), the MDM2 inhibitor RG-7112, the BCL2 inhibitor navitoclax, the HDAC inhibitor belinostat, and the JAK2 inhibitor ruxolitinib in CP-LSPCs ( n = 11), BP ( n = 5), and healthy CD34 + ( n = 3) samples. Dots represent the median values for each group. Plots showing the individual sample’s dose-response curves for the drugs shown here are shown in Figure S2 C. See also Figures S1–S3 and Tables S1 , , and . " width="100%" height="100%">

    Journal: Cell Reports Medicine

    Article Title: Integrated drug profiling and CRISPR screening identify BCR::ABL1-independent vulnerabilities in chronic myeloid leukemia

    doi: 10.1016/j.xcrm.2024.101521

    Figure Lengend Snippet: High-throughput screening identifies VEGFR, Wee1, and MDM2 inhibitors as specific effective drugs against CML-LSPCs (A) Schematic of the high-throughput drug sensitivity and resistance testing experiments. Sixteen primary CML samples (12 CP, 1 AP, and 3 BP) and 3 healthy donor samples were screened using a library of 82 drugs in five different concentrations. In 12 CP and 1 AP-CML samples in which the blast population represented <20%, as well as in healthy donor samples, CD34 + cells were sorted using magnetic sorting to enrich for the stem and progenitor cell (SPC) population. ∗In addition to the indicated 16 sorted samples, unsorted samples from 4 CP-CML patients were also tested. Further information about disease phase and sorting status of samples assigned to DSRT can be found in Table S1 . (B) Heatmap of the drug sensitivity of CP-LSPC ( n = 11), AP/BP ( n = 4), unsorted CP-CML ( n = 4), and healthy CD34 + ( n = 3) samples. Drug sensitivity scores (DSSs) of the most variable 20 drugs are shown. Explanatory tracks from top to bottom show disease status (CML, healthy), sorting status, phase of CML (CP, AP, or BP), and blast percentage in the initial sample prior to sorting. (+) indicates a BP patient with ABL T315I pan-TKI resistance mutation. Ward’s hierarchical clustering method was used for production of the heatmap. (C) Bar plot of the selective drug sensitivity of CML-LSPCs ( n = 16) compared to healthy CD34 + ( n = 3). Drugs are colored by their targeted functional classes. Bar height represents the specific DSS (sDSS) as calculated by the average of DSS responses in CML samples after subtraction of the average of DSS responses in healthy samples. (∗) indicates drugs that were tested only in a subset of samples. (D) Dose-response curves of TKIs (imatinib, dasatinib), VEGFR inhibitors (tivozanib, axitinib), the MDM2 inhibitor RG-7112, the BCL2 inhibitor navitoclax, the HDAC inhibitor belinostat, and the JAK2 inhibitor ruxolitinib in CP-LSPCs ( n = 11), BP ( n = 5), and healthy CD34 + ( n = 3) samples. Dots represent the median values for each group. Plots showing the individual sample’s dose-response curves for the drugs shown here are shown in Figure S2 C. See also Figures S1–S3 and Tables S1 , , and .

    Article Snippet: For samples from CML patients, where blasts constitute <20% of bone marrow mononuclear cells (BMNCs), as well as from 3 healthy donors, CD34 + fraction was enriched using magnetic cell sorting (Miltenyi Biotec, Germany), according to the manufacturer recommendations, and purity were checked using antiCD34-FITC (BDbioscience, Cat# 345801).

    Techniques: High Throughput Screening Assay, Mutagenesis, Functional Assay

    Flow-cytometry-based drug sensitivity profiling revealed selective activities of mepacrine and MDM2 and BCL2 inhibitors against CD34 + CD38 − CML cells (A) Schematic of the flow-cytometry-based drug sensitivity and resistance testing experiments (FC-DSRT). Twelve primary CML samples (6 CP, 6 AP/BP) were screened for sensitivity of 20 drugs in four different concentrations. A flow cytometry antibody panel, including stem cell and myeloid differentiation markers, as well as viability stains, was used to estimate the drug-induced differentiation and killing activity. Further information about disease phase and sorting status of samples assigned to FC-DSRT is in <xref ref-type=Table S1 . (B) Dose-response curves of selected drugs, including TKIs (imatinib, dasatinib, ponatinib), the VEGFR inhibitor tivozanib, the BCL2 inhibitor navitoclax, mepacrine, the MDM2 inhibitor RG-7112, and the HSP90 inhibitor onalespib in putative CML-LSCs (CD34 + CD38 − ) and LPCs (CD34 + CD38 + ). Dots represent the mean values from 12 CML patient samples. Plots showing the individual samples’ dose-response curves for the drugs shown here are shown in Figure S3 D. (C) Bar plot of the efficiency of the tested drugs in targeting the CD34 + CD38 − cell fraction of total CD34 + cells in the studied cohort ( n = 12). Control represents the values from DMSO-treated samples. Bar length represents median value with error bars representing the interquartile range. (D) Flow cytometry showing the expression of myeloid differentiation markers CD38 (x axis) and CD11b (y axis) on CD34 + -gated cells from control and imatinib- and mepacrine-treated CML cells over three log concentrations. (E) Volcano plot of differentially expressed genes (DEGs) in mepacrine-treated primary CML-LSPCs ( n = 4) compared to matched DMSO-treated samples. Genes with false discovery rate (FDR) values <0.001 (Bayesian statistical test) are colored in red. In addition, DEGs with >3-fold-change differences and −log10 ( p value) > 20 are labeled with gene names. See also Figures S3–S5 and Tables S1 , , , and . " width="100%" height="100%">

    Journal: Cell Reports Medicine

    Article Title: Integrated drug profiling and CRISPR screening identify BCR::ABL1-independent vulnerabilities in chronic myeloid leukemia

    doi: 10.1016/j.xcrm.2024.101521

    Figure Lengend Snippet: Flow-cytometry-based drug sensitivity profiling revealed selective activities of mepacrine and MDM2 and BCL2 inhibitors against CD34 + CD38 − CML cells (A) Schematic of the flow-cytometry-based drug sensitivity and resistance testing experiments (FC-DSRT). Twelve primary CML samples (6 CP, 6 AP/BP) were screened for sensitivity of 20 drugs in four different concentrations. A flow cytometry antibody panel, including stem cell and myeloid differentiation markers, as well as viability stains, was used to estimate the drug-induced differentiation and killing activity. Further information about disease phase and sorting status of samples assigned to FC-DSRT is in Table S1 . (B) Dose-response curves of selected drugs, including TKIs (imatinib, dasatinib, ponatinib), the VEGFR inhibitor tivozanib, the BCL2 inhibitor navitoclax, mepacrine, the MDM2 inhibitor RG-7112, and the HSP90 inhibitor onalespib in putative CML-LSCs (CD34 + CD38 − ) and LPCs (CD34 + CD38 + ). Dots represent the mean values from 12 CML patient samples. Plots showing the individual samples’ dose-response curves for the drugs shown here are shown in Figure S3 D. (C) Bar plot of the efficiency of the tested drugs in targeting the CD34 + CD38 − cell fraction of total CD34 + cells in the studied cohort ( n = 12). Control represents the values from DMSO-treated samples. Bar length represents median value with error bars representing the interquartile range. (D) Flow cytometry showing the expression of myeloid differentiation markers CD38 (x axis) and CD11b (y axis) on CD34 + -gated cells from control and imatinib- and mepacrine-treated CML cells over three log concentrations. (E) Volcano plot of differentially expressed genes (DEGs) in mepacrine-treated primary CML-LSPCs ( n = 4) compared to matched DMSO-treated samples. Genes with false discovery rate (FDR) values <0.001 (Bayesian statistical test) are colored in red. In addition, DEGs with >3-fold-change differences and −log10 ( p value) > 20 are labeled with gene names. See also Figures S3–S5 and Tables S1 , , , and .

    Article Snippet: For samples from CML patients, where blasts constitute <20% of bone marrow mononuclear cells (BMNCs), as well as from 3 healthy donors, CD34 + fraction was enriched using magnetic cell sorting (Miltenyi Biotec, Germany), according to the manufacturer recommendations, and purity were checked using antiCD34-FITC (BDbioscience, Cat# 345801).

    Techniques: Flow Cytometry, Activity Assay, Expressing, Labeling

    KCTD5 KO induces TKI resistance in CML cells through impairment of KCTD5 -mediated BCR::ABL1 ubiquitination (A) Viability of KCTD5 -KO and control K562 cells treated with imatinib (1 μmol) in long-term culture. Experiments were performed using biological triplicates of each condition. Dots represent median value and error bars indicate 95% CI. ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, ∗∗∗∗ p < 0.0001 (adjusted p value, multiple unpaired t test corrected for multiple comparisons). (B) Protein levels of KCTD5 and CUL3 proteins in complexes immunoprecipitated by ABL antibody from untreated and imatinib-treated (0.5 μmol) control and KCTD5 -KO K562 cell lysates. Densitometric analysis revealed an imatinib-induced increase in the CUL3 levels, with treated to untreated CUL3 level ratios of 1.71 in control and 1.57 in KCTD5 -KO cells. KCTD5 levels showed an 8.2-fold increase in imatinib-treated compared to untreated control samples. Data from a replicate experiment are shown in <xref ref-type=Figure S8 I. (C) Protein levels of BCR-ABL, KCTD5, and CUL3 proteins as well as ubiquitination levels in untreated and imatinib-treated (0.5 μmol) control and KCTD5 -KO K562 cell lysates. The levels of CUL3, KCTD5, and ubiquitination demonstrated 1.52-, 1.39-, and 3.12-fold increases in the imatinib-treated control sample compared to untreated control sample by densitometry analysis. Negligible changes in the quantified protein levels were found in KCTD5 -KO samples with imatinib treatment. (D) Association of HSA synergy scores between controls and KCTD5 -KO K562 cells from drug combination screening experiments (R = 0.593, Pearson correlation, p = 0.016). Combinations with enhanced synergistic activity in KCTD5 -KO K562 cells are colored in red and those with enhanced synergistic activity in control cells are colored in blue. (E) Dose-response curves of combinations of imatinib with the deubiquitinase inhibitor VLX1570 (100 nmol) and the AKT inhibitor ipatasertib (100 nmol) in control (solid curves) and KCTD5 -KO (dashed curves) K562 cells. Viability of the cells at different concentrations is presented as a percentage of the viability compared to DMSO-treated wells. A dotted line indicates 50% viability of cells. (F) Volcano plot of differentially expressed genes (DEGs) in KCTD5 -KO CML-LSPCs ( n = 2) compared to matched control LSPC samples. KCTD5 targeting CRISPR sgRNA was transduced to primary CD34 + cells with lentivirus and RNA sequencing was performed on KO and control cells. FDR < 0.05 (Bayesian statistical test) is colored in red. (G) Venn diagram showing the overlap of DEGs from RNA-sequencing experiments between KCTD5 -KO and control LSPCs ( n = 2) or K562 cells ( n = 3, biological replicates). Boxes show the main molecular pathways significantly enriched in the overlapping DEGs by pathway enrichment analysis. Genes listed are significantly differentially expressed between KCTD5 -KO and control LSPCs or K562 (FDR < 0.05, Bayesian statistical test), except for the FOS gene (marked with ∗), which showed borderline significance (FDR = 0.056) in LSPC samples. See also Figure S8 and Tables S4 and . " width="100%" height="100%">

    Journal: Cell Reports Medicine

    Article Title: Integrated drug profiling and CRISPR screening identify BCR::ABL1-independent vulnerabilities in chronic myeloid leukemia

    doi: 10.1016/j.xcrm.2024.101521

    Figure Lengend Snippet: KCTD5 KO induces TKI resistance in CML cells through impairment of KCTD5 -mediated BCR::ABL1 ubiquitination (A) Viability of KCTD5 -KO and control K562 cells treated with imatinib (1 μmol) in long-term culture. Experiments were performed using biological triplicates of each condition. Dots represent median value and error bars indicate 95% CI. ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, ∗∗∗∗ p < 0.0001 (adjusted p value, multiple unpaired t test corrected for multiple comparisons). (B) Protein levels of KCTD5 and CUL3 proteins in complexes immunoprecipitated by ABL antibody from untreated and imatinib-treated (0.5 μmol) control and KCTD5 -KO K562 cell lysates. Densitometric analysis revealed an imatinib-induced increase in the CUL3 levels, with treated to untreated CUL3 level ratios of 1.71 in control and 1.57 in KCTD5 -KO cells. KCTD5 levels showed an 8.2-fold increase in imatinib-treated compared to untreated control samples. Data from a replicate experiment are shown in Figure S8 I. (C) Protein levels of BCR-ABL, KCTD5, and CUL3 proteins as well as ubiquitination levels in untreated and imatinib-treated (0.5 μmol) control and KCTD5 -KO K562 cell lysates. The levels of CUL3, KCTD5, and ubiquitination demonstrated 1.52-, 1.39-, and 3.12-fold increases in the imatinib-treated control sample compared to untreated control sample by densitometry analysis. Negligible changes in the quantified protein levels were found in KCTD5 -KO samples with imatinib treatment. (D) Association of HSA synergy scores between controls and KCTD5 -KO K562 cells from drug combination screening experiments (R = 0.593, Pearson correlation, p = 0.016). Combinations with enhanced synergistic activity in KCTD5 -KO K562 cells are colored in red and those with enhanced synergistic activity in control cells are colored in blue. (E) Dose-response curves of combinations of imatinib with the deubiquitinase inhibitor VLX1570 (100 nmol) and the AKT inhibitor ipatasertib (100 nmol) in control (solid curves) and KCTD5 -KO (dashed curves) K562 cells. Viability of the cells at different concentrations is presented as a percentage of the viability compared to DMSO-treated wells. A dotted line indicates 50% viability of cells. (F) Volcano plot of differentially expressed genes (DEGs) in KCTD5 -KO CML-LSPCs ( n = 2) compared to matched control LSPC samples. KCTD5 targeting CRISPR sgRNA was transduced to primary CD34 + cells with lentivirus and RNA sequencing was performed on KO and control cells. FDR < 0.05 (Bayesian statistical test) is colored in red. (G) Venn diagram showing the overlap of DEGs from RNA-sequencing experiments between KCTD5 -KO and control LSPCs ( n = 2) or K562 cells ( n = 3, biological replicates). Boxes show the main molecular pathways significantly enriched in the overlapping DEGs by pathway enrichment analysis. Genes listed are significantly differentially expressed between KCTD5 -KO and control LSPCs or K562 (FDR < 0.05, Bayesian statistical test), except for the FOS gene (marked with ∗), which showed borderline significance (FDR = 0.056) in LSPC samples. See also Figure S8 and Tables S4 and .

    Article Snippet: For samples from CML patients, where blasts constitute <20% of bone marrow mononuclear cells (BMNCs), as well as from 3 healthy donors, CD34 + fraction was enriched using magnetic cell sorting (Miltenyi Biotec, Germany), according to the manufacturer recommendations, and purity were checked using antiCD34-FITC (BDbioscience, Cat# 345801).

    Techniques: Immunoprecipitation, Activity Assay, CRISPR, RNA Sequencing Assay

    Journal: Cell Reports Medicine

    Article Title: Integrated drug profiling and CRISPR screening identify BCR::ABL1-independent vulnerabilities in chronic myeloid leukemia

    doi: 10.1016/j.xcrm.2024.101521

    Figure Lengend Snippet:

    Article Snippet: For samples from CML patients, where blasts constitute <20% of bone marrow mononuclear cells (BMNCs), as well as from 3 healthy donors, CD34 + fraction was enriched using magnetic cell sorting (Miltenyi Biotec, Germany), according to the manufacturer recommendations, and purity were checked using antiCD34-FITC (BDbioscience, Cat# 345801).

    Techniques: Recombinant, Blocking Assay, Lysis, Extraction, Virus, CRISPR, Knock-Out, Plasmid Preparation, Bicinchoninic Acid Protein Assay, Magnetic Beads, RNA Sequencing Assay, Sequencing, Software