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rea266 reafinitytm h apc  (Miltenyi Biotec)


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    Structured Review

    Miltenyi Biotec rea266 reafinitytm h apc
    Rea266 Reafinitytm H Apc, supplied by Miltenyi Biotec, used in various techniques. Bioz Stars score: 94/100, based on 30 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/rea266 reafinitytm h apc/product/Miltenyi Biotec
    Average 94 stars, based on 30 article reviews
    rea266 reafinitytm h apc - by Bioz Stars, 2026-02
    94/100 stars

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    Miltenyi Biotec apc conjugated anti icam1
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    Pseudoperosin (Ps)A-D reduces the nickel sulfate (NiSO 4 ) induced upregulation of DC activation markers <t>CD54</t> and CD86 in a similar manner as dexamethasone. THP-1-derived dermal dendritic cell surrogates (DDCs) were seeded with 1 × 10 6 cells/mL into a 24-well plate. Cells were pre-treated with dexamethasone [1 µM] or PsA-D [20 µM] for 1 h, followed by NiSO 4 [380 µM] treatment for 23 h. Surface marker analysis was performed via flow cytometry and is depicted as histograms ( A ) and percentage of positive cells ( B ). Error bars indicate the standard errors of the mean ( n = 3 independent experiments with * = p ≤ 0.05 and ** = p ≤ 0.01).
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    Image Search Results


    A) Schematic of genome-wide CRISPRi screen identifying CD54 (ICAM-1) regulators. K-562 CRISPRi cells were infected with a guide RNA library at MOI 0.3 and 5, then sorted into three bins (low/high 10%, mid 20%) based on CD54 antibody staining. The screen was conducted at three different library representation levels. B) Analytic flow cytometry of sorted cell populations. C) CRISPRi screen hits showing positive regulators (CD54 low bin) and negative regulators (CD54 high bin) of CD54. MAGeCK scores across all experimental conditions are displayed for individually validated hits. D) Pearson correlation of samples with varying cell coverage, based on log 2 fold changes of normalized sgRNA abundances between low and mid CD54 populations. E) Percentage of shared hits between samples with varying cell coverage within the MOI 0.3 and MOI 5 condition. F) Hits selected across all conditions were individually validated to calculate true positive rate (TPR) and accuracy to identify hits.

    Journal: bioRxiv

    Article Title: Multiplexed Perturbation Enables Scalable Pooled Screens

    doi: 10.1101/2025.08.14.669942

    Figure Lengend Snippet: A) Schematic of genome-wide CRISPRi screen identifying CD54 (ICAM-1) regulators. K-562 CRISPRi cells were infected with a guide RNA library at MOI 0.3 and 5, then sorted into three bins (low/high 10%, mid 20%) based on CD54 antibody staining. The screen was conducted at three different library representation levels. B) Analytic flow cytometry of sorted cell populations. C) CRISPRi screen hits showing positive regulators (CD54 low bin) and negative regulators (CD54 high bin) of CD54. MAGeCK scores across all experimental conditions are displayed for individually validated hits. D) Pearson correlation of samples with varying cell coverage, based on log 2 fold changes of normalized sgRNA abundances between low and mid CD54 populations. E) Percentage of shared hits between samples with varying cell coverage within the MOI 0.3 and MOI 5 condition. F) Hits selected across all conditions were individually validated to calculate true positive rate (TPR) and accuracy to identify hits.

    Article Snippet: After lentiviral transduction and puromycin selection, live cells were stained with an APC-coupled antibody against CD54 (Miltenyi Biotec) in EasySep buffer for 30 min on ice.

    Techniques: Genome Wide, Infection, Staining, Flow Cytometry

    A) Screen results showing guide RNA enrichments based on CD54 levels comparing the bottom 10% of cells to the middle 20% (low vs. mid) or comparing the top 10% to the middle 20% (high vs. mid). False discovery rates (FDR) are shown against log10 transformed MAGeCK scores. Genes are ranked by their MAGeCK score. Results from highest cell number (250X) screens are shown here. Ranking of screen hits based on MAGeCK scores for low vs. mid (B) and high vs. mid (C) comparisons. E) Hits identified in the highest cell number sample (250x) are partitioned into quartiles based on their MAGeCK score in the low CD54 vs. mid CD54 comparison. The most enriched hits are represented in quartile 1 and the least enriched hits in quartile 4. False discovery rates (FDR) of these are shown across different conditions. (Box represents the interquartile range (IQR), spanning from the first to the third quartile, line indicates the median and whiskers extend to 1.5 times the IQR) F) Euclidean distances comparing samples with different cell coverage based on log 2 fold changes of normalized sgRNA abundances (top). Pearson correlation of the same comparison restricted to genes identified as significant hits in any of the conditions (bottom). G) Percentage of shared hits between cell number settings within the MOI 0.3 and MOI 5 condition in the high CD54 vs. mid CD54 comparison. H) As in (E) but based on the comparison high CD54 vs. mid CD54. Hits identified in the highest cell number sample (250x) are partitioned into quartiles based on their MAGeCK score. The most enriched hits are represented in quartile 1 and the least enriched hits in quartile 4. False discovery rates (FDR) of these are shown across different conditions. True-positive rate (TPR) and false-positive rate (FPR) across all conditions. Sample colors are as in (I).

    Journal: bioRxiv

    Article Title: Multiplexed Perturbation Enables Scalable Pooled Screens

    doi: 10.1101/2025.08.14.669942

    Figure Lengend Snippet: A) Screen results showing guide RNA enrichments based on CD54 levels comparing the bottom 10% of cells to the middle 20% (low vs. mid) or comparing the top 10% to the middle 20% (high vs. mid). False discovery rates (FDR) are shown against log10 transformed MAGeCK scores. Genes are ranked by their MAGeCK score. Results from highest cell number (250X) screens are shown here. Ranking of screen hits based on MAGeCK scores for low vs. mid (B) and high vs. mid (C) comparisons. E) Hits identified in the highest cell number sample (250x) are partitioned into quartiles based on their MAGeCK score in the low CD54 vs. mid CD54 comparison. The most enriched hits are represented in quartile 1 and the least enriched hits in quartile 4. False discovery rates (FDR) of these are shown across different conditions. (Box represents the interquartile range (IQR), spanning from the first to the third quartile, line indicates the median and whiskers extend to 1.5 times the IQR) F) Euclidean distances comparing samples with different cell coverage based on log 2 fold changes of normalized sgRNA abundances (top). Pearson correlation of the same comparison restricted to genes identified as significant hits in any of the conditions (bottom). G) Percentage of shared hits between cell number settings within the MOI 0.3 and MOI 5 condition in the high CD54 vs. mid CD54 comparison. H) As in (E) but based on the comparison high CD54 vs. mid CD54. Hits identified in the highest cell number sample (250x) are partitioned into quartiles based on their MAGeCK score. The most enriched hits are represented in quartile 1 and the least enriched hits in quartile 4. False discovery rates (FDR) of these are shown across different conditions. True-positive rate (TPR) and false-positive rate (FPR) across all conditions. Sample colors are as in (I).

    Article Snippet: After lentiviral transduction and puromycin selection, live cells were stained with an APC-coupled antibody against CD54 (Miltenyi Biotec) in EasySep buffer for 30 min on ice.

    Techniques: Transformation Assay, Comparison

    Pseudoperosin (Ps)A-D reduces the nickel sulfate (NiSO 4 ) induced upregulation of DC activation markers CD54 and CD86 in a similar manner as dexamethasone. THP-1-derived dermal dendritic cell surrogates (DDCs) were seeded with 1 × 10 6 cells/mL into a 24-well plate. Cells were pre-treated with dexamethasone [1 µM] or PsA-D [20 µM] for 1 h, followed by NiSO 4 [380 µM] treatment for 23 h. Surface marker analysis was performed via flow cytometry and is depicted as histograms ( A ) and percentage of positive cells ( B ). Error bars indicate the standard errors of the mean ( n = 3 independent experiments with * = p ≤ 0.05 and ** = p ≤ 0.01).

    Journal: Marine Drugs

    Article Title: Pseudopterosin A-D Modulates Dendritic Cell Activation in Skin Sensitization

    doi: 10.3390/md23060245

    Figure Lengend Snippet: Pseudoperosin (Ps)A-D reduces the nickel sulfate (NiSO 4 ) induced upregulation of DC activation markers CD54 and CD86 in a similar manner as dexamethasone. THP-1-derived dermal dendritic cell surrogates (DDCs) were seeded with 1 × 10 6 cells/mL into a 24-well plate. Cells were pre-treated with dexamethasone [1 µM] or PsA-D [20 µM] for 1 h, followed by NiSO 4 [380 µM] treatment for 23 h. Surface marker analysis was performed via flow cytometry and is depicted as histograms ( A ) and percentage of positive cells ( B ). Error bars indicate the standard errors of the mean ( n = 3 independent experiments with * = p ≤ 0.05 and ** = p ≤ 0.01).

    Article Snippet: Cells were stained with the following antibodies (diluted 1:50) for 10 min at 4 °C in the dark: REA Control (S)-APC (Miltenyi Biotec, #130-113-434), CD54-APC (Miltenyi Biotec, #130-121-342), and CD86-APC (Miltenyi Biotec, #130-116-161).

    Techniques: Activation Assay, Derivative Assay, Marker, Flow Cytometry