scholarly journals Fluorescence and Light Scatter Calibration Allow Comparisons of Small Particle Data in Standard Units across Different Flow Cytometry Platforms and Detector Settings

2020 ◽  
Vol 97 (6) ◽  
pp. 592-601 ◽  
Author(s):  
Joshua A. Welsh ◽  
Jennifer C. Jones ◽  
Vera A. Tang
Keyword(s):  
Flow Cytometry ◽  
Small Particle ◽  
Light Scatter

scholarly journals Fluorescence and light scatter calibration allow comparisons of small particle data in standard units across different flow cytometry platforms and detector settings

2019 ◽  
Author(s):  
J.A. Welsh ◽  
J.C. Jones ◽  
V.A. Tang
Keyword(s):  
Flow Cytometry ◽  
Small Particle ◽  
Scientific Progress ◽  
Extracellular Vesicle ◽  
Light Scatter ◽  
Phenotypic Analysis ◽  
Field Methods ◽  
Data Reporting ◽  
Flow Cytometry Data ◽  
Standard Configuration

AbstractFlow cytometers have been utilized for the analysis of submicron-sized particles since the late 1970s. Initially, virus analyses preceded extracellular vesicle (EV), which began in the 1990s. Despite decades of documented use, the lack of standardization in data reporting has resulted in a growing body of literature that cannot be easily interpreted, validated, or reproduced. This has made it difficult for objective assessments of both assays and instruments, in-turn leading to significant hindrances in scientific progress, specifically in the study of EVs, where the phenotypic analysis of these submicron-sized vesicles is becoming common-place in every biomedical field. Methods for fluorescence and light scatter standardization are well established and the reagents to perform these analyses are commercially available. However, fluorescence and light scatter calibration are not widely adopted by the small particle community as methods to standardize flow cytometry data. In this proof-of-concept study carried out as a resource for use at the CYTO2019 workshop, we demonstrate for the first-time simultaneous fluorescence and light scatter calibration of small particle data to show the ease and feasibility of this method for standardized flow cytometry data reporting. This data was acquired using standard configuration commercial flow cytometers, with commercially available materials, published methods, and freely available software tools. We show that application of light scatter, fluorescence, and concentration calibration can result in highly concordant data between flow cytometry platforms independent of instrument collection angle, gain/voltage settings, and flow rate; thus, providing a means of cross-comparison in standard units.

scholarly journals A Multiplexed Assay That Monitors Effects of Multiple Compound Treatment Times Reveals Candidate Immune-Enhancing Compounds

2018 ◽  
Vol 23 (7) ◽  
pp. 646-655 ◽  
Author(s):  
Ziyan Zhao ◽  
Liza Henowitz ◽  
Adam Zweifach
Keyword(s):  
Flow Cytometry ◽  
Cytotoxic T Lymphocytes ◽  
High Throughput ◽  
Treatment Time ◽  
Single Sample ◽  
Light Scatter ◽  
Flow Cytometry Assay ◽  
Multiple Treatment ◽  
Lytic Granule ◽  
Activation Status

We previously developed a flow cytometry assay that monitored lytic granule exocytosis in cytotoxic T lymphocytes stimulated by contacting beads coated with activating anti-CD3 antibodies. That assay was multiplexed in that responses of cells that did or did not receive the activating stimulus were distinguished via changes in light scatter accompanying binding of cells to beads, allowing us to discriminate compounds that activate responses on their own from compounds that enhance responses in cells that received the activating stimulus, all within a single sample. Here we add a second dimension of multiplexing by developing means to assess in a single sample the effects of treating cells with test compounds for different times. Bar-coding cells before adding them to test wells lets us determine compound treatment time while also monitoring activation status and response amplitude at the point of interrogation. This multiplexed assay is suitable for screening 96-well plates. We used it to screen compounds from the National Cancer Institute, identifying several compounds that enhance anti-LAMP1 responses. Multiple-treatment-time (MTT) screening enabled by bar-coding and read via high-throughput flow cytometry may be a generally useful method for facilitating the discovery of compounds of interest.

Adrenalectomy induces a decrease in the light scatter properties and amylase content of isolated zymogen granules from rat pancreas as analyzed by flow cytometry

1995 ◽  
Vol 147 (3) ◽  
pp. 431-440 ◽  
Author(s):  
A C Garcia-Montero ◽  
I De Dios ◽  
A I Rodriguez ◽  
A Orfao ◽  
M A Manso
Keyword(s):  
Flow Cytometry ◽  
Progressive Increase ◽  
Enzyme Concentration ◽  
Male Rats ◽  
Zymogen Granule ◽  
Light Scatter ◽  
Zymogen Granules ◽  
Mean Size ◽  
A Minor ◽  
Adrenalectomized Rats

Abstract The effect of glucocorticoid deprivation induced in male rats by adrenalectomy on the pancreatic zymogen granules was studied. Zymogen granules were purified from control, sham-operated and adrenalectomized animals studied 1, 3 and 7 days after surgery. The zymogen granules were characterized by flow cytometry, and in each granule the size (based on the forward or low angle light scatter (FSC) parameter), membrane complexity (based on side or 90° light scatter (SSC) parameter) and amylase content were evaluated. Amylase content/DNA ratio in pancreatic homogenates was also analyzed. The zymogen granules of the control rats were found to be distributed in two populations: a major one – R1 (95·45 ± 1·21%) – containing zymogen granules with a smaller mean size and complexity, and a minor population - R2 (4·45 ± 0·24%) – the granules of which had a mean size which was larger and more complex. At day +1 after adrenalectomy the zymogen granules were significantly (P<0·05) smaller than those of control animals. The R2 zymogen granules were similar to those from R1 as regards their size, but were more complex, suggesting that the immediate effect of glucocorticoid deprivation is to induce a depletion of the larger granules presumably belonging to the R2 population. The amount of amylase per granule did not vary at day +1 after adrenalectomy, although the amylase content/size ratio per granule was significantly (P<0·001) increased. This mechanism could be explained in terms of the existence of a bypass defined in the adrenalectomized animals between the granular content and cytosolic enzymes. Prolongation of the adrenalectomy period to 3 and 7 days resulted in a progressive increase in zymogen granule size and complexity, both parameters showing similar characteristics to those of the controls at day +7 after adrenalectomy. However, the percentage of zymogen granules within the R1 and R2 populations was clearly different from that of controls since the R2 population was much more numerous (11·25 ± 0·75% and 15·25 ± 1·15% (adrenalectomized rats at days +3 and +7 respectively) versus 4·45 ± 0·24% (controls)). An increase in the content of amylase per DNA was observed in adrenalectomized rats at day +1 although this transient effect cannot be related to glucocorticoid deprivation because it was also observed in sham-operated rats (day +1). However, a significant reduction, nearly 64%, in the amylase content/DNA ratio is produced by the absence of glucocorticoids 7 days after adrenalectomy and this is associated with a reduction in the content of amylase in each individual zymogen granule which reaches a minimum 3 days after adrenalectomy. It should be noted that, despite this, the enzyme concentration in each granule remains constant as there is a parallel decrease in the zymogen granule amylase content and size. Journal of Endocrinology (1995) 147, 431–440

scholarly journals Detection of silver nanoparticles in cells by flow cytometry using light scatter and far-red fluorescence

2013 ◽  
pp. n/a-n/a ◽  
Author(s):  
R. M. Zucker ◽  
K. M. Daniel ◽  
E. J. Massaro ◽  
S. J. Karafas ◽  
L. L. Degn ◽  
...  
Keyword(s):  
Flow Cytometry ◽  
Silver Nanoparticles ◽  
Light Scatter ◽  
Red Fluorescence ◽  
In Cells

Diagnostic Utility of Flow Cytometry in Myelodysplastic Syndrome: A Retrospective Validation From a Single Centre.

Blood ◽  
2009 ◽  
Vol 114 (22) ◽  
pp. 4846-4846
Author(s):  
Pervin Topcuoglu ◽  
Klara Dalva ◽  
Sule Mine Bakanay ◽  
Sinem Civriz Bozdag ◽  
Onder Arslan ◽  
...  
Keyword(s):  
Bone Marrow ◽  
Flow Cytometry ◽  
Myelodysplastic Syndrome ◽  
Antigen Expression ◽  
Pathological Examination ◽  
Light Scatter ◽  
Myeloid Lineage ◽  
Hematopoietic Stem ◽  
Altered Expression ◽  
Flow Cytometric

Abstract Abstract 4846 Myelodysplastic syndrome (MDS) is heterogeneous clonal hematopoietic stem cell disorder characterized by cytopenia(s) and dysplasia in one or more cell lineage. Though flow cytometry (FCM) is an important diagnostic tool in hematopoietic cell disorders, a prominent immunophenotyping feature in MDS may not be determined. In this study, we retrospectively evaluated flow cytometric features of bone marrow samples diagnosed as MDS with clinical and hematological findings. Patients-Method Between Feb 2004 and March 2009, flow cytometric parameters of 73 patients (M/F: 50/23) with MDS were re-analyzed. Median age was 59 years (17-89 ys). Our general principles are to evaluate quality of bone marrow samples, to determine proportion of the cells and features of their light scatter, and to give percentage of the blast. When detected a finding of dysplasia in the first analysis, the second step includes the determination of the maturation of the cells and the presence of the aberrant antigen expression. Results The samples were interpreted as MDS in % 76.7, MDS-RAEB-1 or RAEB-2 in %16.4, myeloproliferative disorder in %1.4 and non-diagnostic in %6.8 of the cases by flow cytometric examination. We detected variable degrees of hypogranulation in myeloid lineage in %82.2 of the samples by the light scatter features of the cells: 85% of severe and 15% of moderate or mild hypogranulation. The ratio of myeloid and lymphoid was changing from 0.3 to 17.5 (median 2). The decreasing of this ratio (<1) was observed in 19.4% of the samples. We detected altered expression of mature granulocyte. These included decreasing or lack of expression in CD15 45/73 (61.4%), CD13 38/70 (54.3%), CD16 53/67 (79.1%), CD11b 51/71 (71.8%), CD24 44/69 (65.2%), CD10 23/72 (31.9%) and MPO 14/72 (19.4%). Besides, bright expression of CD33 in 53.5% of the samples was observed. CD36 and CD56 in myeloid lineage were co-expressed in about 50 % of the samples. In 80.8 % of the samples dysplasia in erythroid compartment could be evaluated: Expression of CD71 according to glycophorin A (ratio <1) was decreased in 23.7 %. When we made similar analysis in the samples without RAEB-1 and -2 as pathological examination of bone marrow, 13.4 % of the samples could not be evaluated in favor of dysplasia. Of the samples with dysplasia hypogranulation, aberrant antigen expression of myeloid lineage and eryhtroid dysplasia were observed in 92.1%, 34.1% and 31.5%, respectively. In conclusion, FCM events may help to the differantial diagnosis of MDS especially when combining with clinical events. Improving of the analysis by focusing on the blast characteristics may be a standard approach to evaluate for low risk MDS. Disclosures No relevant conflicts of interest to declare.

scholarly journals Identification and Phenotyping of Leukocytes in Bovine Bronchoalveolar Lavage Fluid

2004 ◽  
Vol 11 (4) ◽  
pp. 795-798 ◽  
Author(s):  
E. C. Soethout ◽  
K. E. Müller ◽  
A. J. M. van den Belt ◽  
V. P. M. G. Rutten
Keyword(s):  
Flow Cytometry ◽  
Bronchoalveolar Lavage ◽  
Alveolar Macrophages ◽  
Bronchoalveolar Lavage Fluid ◽  
Lavage Fluid ◽  
Light Scatter ◽  
Specific Antibodies ◽  
Dual Laser

ABSTRACT A method is proposed to identify leukocyte subpopulations in bovine bronchoalveolar lavage fluid by dual-laser flow cytometry. The technique uses several parameters, i.e., exclusion of highly autofluorescent alveolar macrophages and inclusion of leukocytes on the basis of labeling by specific antibodies and light scatter characteristics.

scholarly journals The malignant cells in a Lennert's lymphoma are T lymphocytes with a mature helper surface phenotype. A multiparameter flow cytometric analysis

Blood ◽  
1986 ◽  
Vol 68 (2) ◽  
pp. 426-429 ◽  
Author(s):  
KJ Stonesifer ◽  
NA Benson ◽  
SE Ryden ◽  
DF Pawliger ◽  
RC Braylan
Keyword(s):  
Flow Cytometry ◽  
Flow Cytometric Analysis ◽  
Malignant Neoplasm ◽  
Surface Antigens ◽  
Light Scatter ◽  
Malignant Cells ◽  
T Helper ◽  
T Helper Lymphocytes ◽  
Flow Cytometric ◽  
Multiparameter Analysis

Abstract The flow cytometric analysis of DNA content in cells obtained from a case of Lennert's lymphoma demonstrated the presence of a discrete hypotetraploid cell population. Correlated multiparameter analysis of DNA, light scatter, and surface antigens by flow cytometry showed that the hypotetraploid cells were intermediate to large cells expressing T11, T3, and T4 antigens and lacking B1 and T8 antigens. These findings suggest that Lennert's lymphoma represents a malignant neoplasm of T- helper lymphocytes.

Machine Learning-Based Flow Cytometry Diagnostics in Myelodysplastic Syndromes: Validation in the HOVON89 Clinical Trial (EudraCT 2008-002195-10)

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 10-12
Author(s):  
Carolien Duetz ◽  
Sofie Van Gassen ◽  
Theresia M. Westers ◽  
Florentien in t Hout ◽  
Eline Cremers ◽  
...  
Keyword(s):  
Machine Learning ◽  
Clinical Trial ◽  
Bone Marrow ◽  
Flow Cytometry ◽  
Myelodysplastic Syndromes ◽  
Lower Risk ◽  
Validation Cohort ◽  
Cell Detection ◽  
Light Scatter ◽  
Reference Cohort

Introduction Flow cytometry is a recommended tool in the diagnostic work-up of cytopenic patients suspected for myelodysplastic syndromes. Currently used flow cytometry scores rely on human assessment of dysplastic features in the bone marrow. Although proven useful, these methods are labor intensive and require a high level of expertise. Therefore, we previously developed a machine learning-based workflow for flow cytometry diagnostics in MDS by combining computational cell detection and a machine learning-classifier. This workflow outperformed traditional diagnostic scores with respect to accuracy (sensitivity 85-97%, specificity 93-97%), time investment (&lt;30 seconds) and required materials (manuscript submitted). In the present study, we validated sensitivity of the workflow in a well-characterized clinical trial cohort (HOVON89 EudraCT 2008-002195-10) of lower risk MDS patients. Method Patient inclusion and characteristics Very low to intermediate risk MDS patients enrolled in the HOVON89 clinical trial (EudraCT 2008-002195-10) were included. 53 patients met the additional inclusion criteria, concerning written consent for add-on studies and availability of required flow cytometry data. Sample preparation Bone marrow samples were processed for flow cytometry analysis according to the European Leukemia Net guidelines. This study focused on the antibody combination optimized for assessment of myeloid progenitors and erythroid dysplasia (CD45, CD34, CD117, HLA-DR, CD71, CD36, CD105, CD33, sideward light scatter (SSC) and forward light scatter (FSC)). Machine learning-based workflow The machine learning-based workflow was developed in a prior study based on a reference cohort consisting of MDS patients without excess of blasts(n=67) and non-MDS cases (n=81) (Figure 1). MDS patients were diagnosed based on (cyto)morphology, cytogenetics and clinical follow-up. Non-MDS cases were patients with confirmed non-neoplastic cytopenias (n=69) and age-matched healthy individuals (n=12). Results In the validation cohort, the machine learning-based diagnostic workflow classified 49 out of 53 patients correctly, reaching a sensitivity of 92%. The workflow outperformed two currently used diagnostic tools for MDS flow cytometry, the Ogata score and integrated flow cytometry score (iFS). The former obtained 72% sensitivity (McNemar: p = 0.001) and the latter 83% sensitivity (McNemar: p = 0.06) in the validation cohort. Per patient, time required for automated analysis was less than 30 seconds. All four MDS patients that classified false negatively had a normal karyotype and (very) low risk disease according to the IPSS-r. In three out of four patients, no mutations or MDS-associated immunophenotypic features were detected. One patients was diagnosed as MDS-MLD and three patients as MDS-RS-SLD according to the WHO 2016 classification. The ten most relevant cellular features that discriminated between MDS and non-MDS patients in the reference data were confirmed in the current validation cohort. All ten features of MDS patients in the validation cohort were significantly different from non-MDS patients of the reference cohort (all features, p &lt; 0.00001) (Figure 2). Seven out of ten features were similar in MDS patients of the validation cohort compared to those of the MDS patients of the reference cohort (p&gt;0.05) (Figure 2). Conclusion In this validation study, we confirmed accuracy of machine learning-based flow cytometry diagnostics in lower risk MDS. The workflow obtained 92% sensitivity, which is in accordance with results from our previous study (85-97%), and outperformed currently used diagnostic flow cytometry scores for MDS (i.e. Ogata score and iFS). In our previous study specificity was 95% in both reference and test cohorts. Cellular features, most discriminative for diagnosis, were confirmed in the validation cohort, emphasizing robustness of the method. Additional benefits of this approach are the reduction in analysis time to less than thirty seconds per patient, reduction of required antibodies and increased reproducibility. Disclosures van de Loosdrecht: celgene: Honoraria; novartis: Honoraria.

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