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Despite advances in emergency care and reperfusion ther-apy, segment-elevationmyocardial infarction (STEMI) remains an important cause of morbidity and mortality.1,2 In

studies of cardiovascular cell therapy, harvested bone mar-row mononuclear cells (BMCs), including hematopoietic and nonhematopoietic cell populations (eg, mesenchymal stromal

Clinical Track

2014 American Heart Association, Inc.

Circulation Research is available at http://circres.ahajournals.org DOI: 10.1161/CIRCRESAHA.116.304710

Rationale: Despite significant interest in bone marrow mononuclear cell (BMC) therapy for ischemic heart disease, current techniques have resulted in only modest benefits. However, selected patients have shown improvements after autologous BMC therapy, but the contributing factors are unclear.

Objective: The purpose of this study was to identify BMC characteristics associated with a reduction in infarct size after ST-segment-elevationmyocardial infarction.

Methods and Results: This prospective study comprised patients consecutively enrolled in the CCTRN TIME (Cardiovascular Cell Therapy Research Network Timing in Myocardial Infarction Evaluation) trial who agreed to have their BMCs stored and analyzed at the CCTRN Biorepository. Change in infarct size between baseline (3 days after percutaneous coronary intervention) and 6-month follow-up was measured by cardiac MRI. Infarct-size measurements and BMC phenotype and function data were obtained for 101 patients (mean age, 56.5 years; mean screening ejection fraction, 37%; mean baseline cardiac MRI ejection fraction, 45%). At 6 months, 75 patients (74.3%) showed a reduction in infarct size (mean change, 21.017.6%). Multiple regression analysis indicated that infarct size reduction was greater in patients who had a larger percentage of CD31+ BMCs (P=0.046) and in those with faster BMC growth rates in colony-forming unit Hill and endothelial-colony forming cell functional assays (P=0.033 and P=0.032, respectively).

Conclusions: This study identified BMC characteristics associated with a better clinical outcome in patients with segment-elevationmyocardial infarction and highlighted the importance of endothelial precursor activity in regenerating infarcted myocardium. Furthermore, it suggests that for these patients with segment-elevationmyocardial infarction, myocardial repair was more dependent on baseline BMC characteristics than on whether the patient underwent intracoronary BMC transplantation.

Clinical Trial Registration Information: URL: http://www.clinicaltrials.gov. Unique identifier: NCT00684021. (Circ Res. 2015;116:99-107. DOI: 10.1161/CIRCRESAHA.116.304710.)

Key Words: acute myocardial infarction adult stem cell coronary circulation regeneration

Original received June 30, 2014; revision received October 6, 2014; accepted October 10, 2014. In October, 2014, the average time from submission to first decision for all original research papers submitted to Circulation Research was 16 days.

From the Houston Methodist DeBakey Heart and Vascular Center (R.C.S., B.H.T., J.P.C.) and Houston Methodist Research Institute (R.C.S., B.H.T., J.P.C.), TX; Minneapolis Heart Institute Foundation at Abbott Northwestern Hospital, MN (J.H.T.); Cedars-Sinai Heart Institute, Los Angeles, CA (T.D.H.); University of Florida College of Medicine, Gainesville (C.J.P., C.R.C.); Texas Heart Institute, CHI St. Lukes Health, Houston (J.T.W., E.C.P., M.R., A.O., D.A.T.); University of Minnesota School of Medicine, Minneapolis (C.Z.); Cleveland Clinic Foundation, OH (S.G.E.); Wake Forest, School of Medicine, Winston-Salem, NC (D.X.M.Z.); University of Louisville, School of Medicine, KY (A.B.); Indiana University School of Medicine, Indianapolis (B.H.J.); The University of Texas Health Science Center, School of Public Health, Houston (D.L., S.L.S., L.M.); National Heart, Lung, and Blood Institute, Bethesda, MD (R.F.E.); Stanford University, School of Medicine, CA (J.C.W.); and Kansas University Medical Center, School of Medicine, Kansas City (R.D.S.).

*These authors contributed equally to this article.The online-only Data Supplement is available with this article at http://circres.ahajournals.org/lookup/suppl/doi: 10.1161/CIRCRESAHA.

116.304710/-/DC1This article was sent to Steven Houser, Consulting Editor, for review by expert referees, editorial decision, and final disposition.Correspondence to Lem Moy, 1200 Pressler St E1009, Houston, TX 77030. E-mail [email protected]

Bone Marrow Characteristics Associated With Changes in Infarct Size After STEMI

A Biorepository Evaluation From the CCTRN TIME Trial

Robert C. Schutt, Barry H. Trachtenberg, John P. Cooke, Jay H. Traverse, Timothy D. Henry, Carl J. Pepine, James T. Willerson, Emerson C. Perin, Stephen G. Ellis, David X.M. Zhao,

Aruni Bhatnagar, Brian H. Johnstone, Dejian Lai, Micheline Resende, Ray F. Ebert, Joseph C. Wu, Shelly L. Sayre, Aaron Orozco, Claudia Zierold, Robert D. Simari,

Lem Moy, Christopher R. Cogle,* Doris A. Taylor,* for the Cardiovascular Cell Therapy Research Network (CCTRN)

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100 Circulation Research January 2, 2015

cells3,4 and endothelial progenitor cells),5 have been isolated and reinfused by intracoronary infusion into the heart. Clinical trials assessing the use of intracoronary transplantation of autologous BMCs to promote cardiovascular repair in pa-tients with STEMI have shown promising but mixed results.6 Therefore, a better understanding of the relationship between patients BMC characteristics and clinical outcomes is needed to determine whether the use of BMC therapy for cardiovas-cular diseases should be continued.

Editorial, see p 16Several factors may explain the mixed responses seen in

cell therapy clinical trials, including heterogeneity of BMC composition, differences in cell processing techniques, dose administered, timing and route of delivery, and patient char-acteristics. Although the study protocols were often designed to control for some of these factors, patients bone marrow characteristics were rarely assessed in relation to clinical out-comes. However, identifying the patterns in BMC character-istics associated with improved outcomes could lead to better patient selection and personalized enrichment of therapeutic cells in the product before transplantation and would enhance our understanding of the mechanisms involved in cardiovas-cular regeneration and repair.

In this study, we sought to identify BMC characteristics as-sociated with changes in infarct size after STEMI. Infarct size was chosen as the primary outcome for our analyses because it is an independent predictor of mortality in patients with coro-nary artery disease7 and measurements for this outcome are highly reproducible.

MethodsThis prospective cohort study comprised patients consecutively enrolled in the Cardiovascular Cell Therapy Research Network (CCTRN) Timing in Myocardial Infarction Evaluation (TIME) trial who participated in the 6-month follow-up and provided writ-ten consent to have their excess BMCs stored for further analyses at the CCTRN Biorepository.8,9 These analyses were prespecified in the Ancillary Functional Studies for the CCTRN protocol. The design and rationale of the CCTRN TIME trial and the CCTRN Biorepository are described elsewhere.9,10 Briefly, CCTRN TIME was a multicenter, controlled, randomized, double-blind trial con-ducted at 5 clinical centers, their satellite facilities, and a data coordinating center. The trial protocol was approved by the local institutional review boards at each center, and participants pro-vided written informed consent. Participants were randomized 2:1 to receive 150 million BMCs or placebo by intracoronary infu-sion on either day 3 or day 7 after primary percutaneous coronary intervention. With permission, the excess BMCs were sent to the

CCTRN Biorepository for phenotype and functional analyses and storage.9

Cell Processing and TransportationA detailed description of the cell processing and transportation pro-tocol used has been reported previously.11 During the CCTRN TIME clinical trial, bone marrow was obtained from each participants pos-terior iliac crest. This bone marrow was then combined with preser-vative-free heparin and transported at ambient temperature to a cell processing center at each clinical site. At the cell processing center, the bone marrow was filtered, tested for sterility, and processed to isolate the mononuclear cells by using the Sepax system (Biosafe SA, Geneva, Switzerland). After the BMC treatment product was prepared, the excess cells were shipped overnight in commercial cell-transportation packaging (EXAKT Technologies, Oklahoma City, OK) to the University of Florida and the University of Minnesota for functional and flow cytometric (FC) analyses.

Flow Cytometry Sample Preparation and Antibody LabelingFC analysis was used to immunophenotype the BMC populations. Briefly, to lyse the red blood cells, we incubated the samples in ammonium-chloride-potassium lysis buffer (0.15 mol/L NH4Cl, 10 mmol/L KHCO3, and 0.1 mmol/L EDTA; pH, 7.27.4) for 5 min-utes at room temperature. The remaining cells were then washed twice in phosphate-buffered saline+2.5% fetal calf serum (2.5% phosphate-buffered saline). Cell concentration and viability were de-termined by using the Guava ViaCount assay on a Guava PCA-96 system (Millipore Corporation, Billerica, MA). All antibodies were purchased from BD Biosciences (San Jose, CA) unless otherwise specified. Bone marrow cells were analyzed with 2 separate panels of antibodies and their respective isotype-matched controls: (1) CD45, CD34, CD133, KDR, and CD31 and (2) CD45, CD3, CD19, CD11b, CXCR4, and CD14 (Online Table I). Labeled cells were then incu-bated at room temperature for 20 minutes in the dark, washed twice in 2.5% phosphate-buffered saline, and resuspended to a final volume of 1 mL in 2.5% phosphate-buffered saline for FC analysis.

Flow Cytometry Instrument Set Up, Controls, and Fluorochrome CompensationFC data were acquired by using a BD LSR II Flow Cytometer (BD Biosciences) with 4 fixed-aligned, air-cooled lasers: 20 mW UV laser (355 nm), 25 mW violet laser (405 nm), 20 mW blue laser (488 nm), and 17 mW red laser (635 nm). The lasers, photomulti-plier tubes, dichroic long pass mirrors, band pass filters, and flu-orochromes are listed in Online Table II, and the optical pathway configuration is depicted in Online Figure I. Before immunopheno-typing was begun, instrument performance was validated by using BD Cytometer Setup and Tracking Beads (BD Biosciences). Six-peak Rainbow Calibration Particles (Spherotech Inc., Lake Forest, IL) were used to set and maintain the target median fluorescence intensity values throughout the study. Before data acquisition, hard-ware compensation was performed with cells stained with a single fluorochrome (Online Table III) by using the Compensation Setup feature of BD FACSDiva 6.0 software (BD Biosciences) and a com-pensation matrix.

Flow Cytometry Data Acquisition and Data AnalysisFC data were acquired on a BD Biosciences LSRII flow cytom-eter (BD Biosciences) at a low flow rate within the first hour af-ter sample preparation by using FACS DIVA 6.0 software. Events were triggered on the forward scatter signal. A minimum of 105 events were acquired for analysis. A trained operator blinded to the patients characteristics performed all the tests and analyzed the data throughout the study. Acquired data were analyzed using FlowJo software 7.6.5 (Tree Star Inc., Ashland, OR). Data analysis was performed by first gating around the individual lymphocyte, monocyte, and granulocyte populations, as determined on the basis of their forward scatter versus side scatter properties (Figure 1A).

Nonstandard Abbreviations and Acronyms

BMC bone marrow mononuclear cell

CCTRN Cardiovascular Cell Therapy Research Network

CFU-F colony-forming unit fibroblast

CFU-Hill colony-forming unit Hill

cMRI cardiac MRI

ECFC endothelial-colony forming cell

FC flow cytometric

STEMI ST-segmentelevation myocardial infarction



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Schutt et al Bone Marrow Traits and Infarct Size in STEMI 101

Cell debris and small particles were omitted from the analysis by excluding events with low forward scatter. All analyses were per-formed on gated lymphocytes unless otherwise specified. Online Figure II shows representative single-color histograms comparing antibodies to the isotype-matched control antibodies. CD34+ and CD34+CD133+ cells in the BMC product were measured using the International Society of Hematotherapy and Graft Engineering strategy throughout the FC analysis.9,12

Functional AnalysesTrypan blue exclusion was used to assess viability of the cells that underwent functional analysis.9 BMC function was evaluated with 3 separate assays, such as (1) the colony-forming unit Hill (CFU-Hill), (2) the endothelial-colony forming cell (ECFC), and (3) the colony-forming unit fibroblast (CFU-F) assays.9,13,14 The number of colony forming units, type of colonies, and percent confluency were recorded on days 7, 14, 21, and 28 for the ECFC and CFU-F assays and on days 4 through 9 for the CFU-Hill assay. Results from all 3 assays were assessed with the following 3 metrics, such as (1) slope of the best-fit linear curve for the percent confluency over time, (2) exponential constant of the best-fit exponential curve for the number of colonies over time, and (3) maximum number of colonies present during the entire culture period.

Measurement of Infarct SizeThe outcome measure of interest, change in infarct size, was cal-culated by subtracting the baseline measurement taken 3 days after

primary percutaneous coronary intervention from the measurement made at 6 months. Infarct size was assessed with cardiac MRI (cMRI) using delayed contrast-enhanced imaging where appropriate. To im-prove infarct size measurements for this study, we used a cMRI al-gorithm that corrected for left ventricular mass; this algorithm was not used in the original CCTRN TIME study. Infarct size and BMC measurements were made by laboratory personnel masked to all clin-ical data and treatment assignments. Further details about the trial protocol and assessment of individual outcomes can be found in a previous report.10

Statistical AnalysesWhen assessing the relationships between change in infarct size from baseline to 6 months and demographic variables, we catego-rized infarct size as a dichotomous variable (ie, either as a decrease or an increase). For this set of analyses, associations with continuous variables were determined by using an unpaired t test and associa-tions with categorical variables were determined by using the Fisher exact test. When the relationships between BMC parameters (cell phenotype and function) and infarct size were assessed, infarct size was treated as a continuous variable. These associations were deter-mined by using both univariable and multivariable linear regression analyses, in which the dependent variable was change in infarct size. Covariates for the multivariable model were selected based on previ-ous data that suggested that these factors would be relevant and bio-logically plausible to model the hypothesized relationship between bone marrow parameters and change in infarct size. Covariates for the model included age,15 baseline infarct size, diabetes mellitus,16 angiotensin-converting enzyme inhibitor use,17,18 hypertension,19 smoking status,20 and treatment received in the clinical trial.6 In this first assessment of the relationships between BMC characteristics and infarct size, we conducted multiple statistical tests. Because this was an exploratory assessment, we prioritized knowledge discovery, and we did not use statistical techniques to reduce the familywise error rate (eg, Bonferroni correction).

ResultsIn the CCTRN TIME clinical trial, 120 patients with STEMI underwent bone marrow aspiration and were ran-domized to receive either BMCs or placebo. Complete in-farct size measurements and BMC product analyses were available for 101 (84.0%) of these patients. Reasons for incomplete follow-up were reported previously.8 At the 6-month follow-up, 75 patients (74.3%) showed a reduc-tion in infarct size from baseline, with a mean infarct size of 50.425.3 g at baseline and 29.417.0 g at 6-month follow-up (mean change, 21.017.6 g). The patients who showed an increase in infarct size (n=26) had a mean infarct size of 30.919.8 g at baseline and 41.320.3 g at 6-month follow-up (mean change, 10.412.1 g). In Table 1, we present the baseline characteristics of patients when stratified according to direction of change in infarct size. With the exception of initial infarct size, there were no significant differences at baseline between patients who showed a reduction in infarct size at 6 months and those who showed an increase in infarct size. The initial infarct size measurements taken at days 3 and 7 postmyocardial infarction were found to significantly correlate with ejec-tion fraction at 6 months (day 3: r=0.376, P


results from the clinical trial, we found no significant dif-ference in the change in infarct size over time between patients who received BMC therapy and those who did not (13.320.1 g versus 12.223.9 g; P=0.802). In ad-dition, when patients were stratified by both direction of change in infarct size and treatment type, no significant differences were found between the 4 groups for any of the demographic variables assessed (Online Table IV).

The BMC phenotype and functional assay results are summarized in Table 2. When univariable analysis was performed to compare the results for patients who showed a reduction in infarct size at 6 months and those who showed an increase in infarct size, no significant dif-ferences in cell frequency were found for the phenotypes assessed. However, a significant difference was observed in the BMC functional assessments. Specifically, the ex-ponential constant for the ECFC assay was significantly higher in patients who showed a reduction in infarct size than in those who showed an increase in infarct size. In contrast, the CFU-Hill and CFU-F assays indicated no difference among patients who showed a reduction in in-farct size at 6 months and those who showed an increase in infarct size. When patients were stratified by both di-rection of change in infarct size and treatment type for the phenotype and functional comparisons, a significant difference was found in the frequency of CD19+ cells (Online Table V).

Multiple regression analysis was also used to model the relationships between either cell phenotype or functional pa-rameters and change in infarct size (results also shown in Table 2). After adjusting for age, history of diabetes mellitus, baseline infarct size, angiotensin-converting enzyme inhibi-tor use, hypertension, history of smoking, and therapy assign-ment in the clinical trial (BMC or placebo), patients with a higher percentage of CD31+ cells were shown to have a larg-er reduction in infarct size at 6 months (P=0.046). Additional gating analyses to explore this association (Figure 1) showed that a higher percentage of CD45+CD31+ cells (P=0.042), specifically CD45+CD31low cells (P=0.015), was associated with a larger reduction in infarct size. To further explore this

Table 1. Demographics and Clinical Data of Patients Stratified by Change in Infarct Size at 6 Months

Infarct Size0 (Increased)

(n=26)

P Value

Demographics

Age, y 57.010.8 55.410.7 0.512

Female 12 (16%) 3 (11.5%) 0.754

Height, m 1.760.10 1.750.08 0.666

Weight, kg 94.919.5 93.223.1 0.725

BMI, kg/m2 30.55.2 30.26.6 0.855

Previous medical history

Diabetes mellitus 14 (18.7%) 7 (26.9%) 0.406

Hypertension 46 (61.3%) 13 (50%) 0.360

Hyperlipidemia 53 (70.7%) 16 (61.5%) 0.465

History of angina 16 (21.3%) 3 (11.5%) 0.386

Smoking 44 (58.7%) 18 (69.2%) 0.484

Cardiovascular and infarction details

Baseline infarct size, g 50.425.3 30.919.8 0.001

Heart rate 80.115.7 82.211.2 0.524

Systolic BP, mm Hg 119.819.7 111.316.7 0.053

Diastolic BP, mm Hg 73.614.2 73.213.5 0.889

LV end-diastolic volume index, mL/m2

74.417.3 73.216.9 0.753

LV end-systolic volume index, mL/m2

40.512.5 42.014.9 0.439

Screening EF (echocardiography)

376% 368% 0.719

Core laboratory EF (day 3) (cMRI)

4610% 4212% 0.137

Hemoglobin, g/dL 14.12 13.41 0.142

High sensitivity CRP, mg/L

39.849.1 33.824 0.568

Peak CK, U/L 2970.82104.9 3180.02734.1 0.703

Peak CKMB, ng/mL 254.0190.1 255.8218.2 0.972

BNP, pg/mL 325.9655 214.6132.5 0.466

NT-proBNP, pg/mL 1428.21367.3 1440.61873.6 0.988

Troponin T (peak), ng/mL 9.37.6 9.26.9 0.963

Troponin I (peak), ng/mL 76.191 118.6163.7 0.478

Drug eluting stent 63 (84%) 18 (69.2%) 0.151

LAD infarction 67 (89.3%) 23 (88.5%) 1.000

Preinfarction angina 14 (18.7%) 3 (11.5%) 0.548

Transferred after MI 33 (44%) 11 (42.3%) 1.000

PCI at nonstudy center hospital

6 (8%) 2 (7.7%) 1.000

Discharge medications

ACE inhibitor 62 (82.7%) 23 (88.5%) 0.756

Aspirin 72 (96%) 26 (100%) 0.567

-blocker 73 (97.3%) 26 (100%) 1.000

Clopidogrel or prasugrel 73 (97.3%) 23 (88.5%) 0.106

Statins 71 (94.7%) 22 (84.6%) 0.199

Diuretic 16 (21.3%) 5 (19.2%) 1.000

Coumadin or enoxaparin 15 (20%) 2 (7.7%) 0.225(Continued)

Cell product information

Time from PCI to infusion, d

5.12.3 4.62 0.245

Time from aspiration to infusion, h

8.72.9 8.61.5 0.846

Final volume, mL 149.71.9 144.228.6 0.097

Cell product viability, % 98.11.6 98.51 0.284

Values shown as the meanSD or number (%). ACE indicates angiotensin-converting enzyme; BMI, body mass index; BP, blood pressure; CK, creatine kinase; CKMB, creatine kinase-MB; cMRI, cardiac MRI; CRP, C-reactive protein; EF, ejection fraction; LAD, left anterior descending; LV, left ventricular; MI, myocardial infarction; NT-proBNP, N-terminal pro-brain natriuretic peptide; and PCI, percutaneous coronary intervention.

Table 1. Continued



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association, we show the changes in infarct size between day

3 and the 6-month follow-up stratified by the percentage of

CD34+CD31low cells in the BMC product (Figure 2). In mul-

tivariable regression analysis the percentage of CD19+ cells

was not associated with change in infarct size (P=0.322).

When multivariable regression analysis was performed to

assess differences in BMC functional parameters, a higher

exponential constant for the colony growth curve was found

to be associated with a larger reduction in infarct size at 6

months in both the CFU-Hill and ECFC assays (P=0.030

and P=0.032, respectively). However, treatment assignment

(BMCs or placebo) was not associated with a reduction in in-

farct size (P=0.706) at 6 months in the multivariate analysis.

DiscussionThe purpose of this exploratory study was to identify patterns in BMC characteristics associated with either an increase or a decrease in infarct size in patients with STEMI. To accomplish this, we analyzed data from pa-tients in the CCTRN TIME trial who provided consent to have their BMC product analyzed by the CCTRN Biorepository laboratories. Multivariable regression analysis showed that an increased percentage of CD31+ cells in the bone marrow was associated with a greater reduction in infarct size at 6 months after STEMI. In addition, a greater reduction in infarct size was asso-ciated with a faster BMC growth rate in CFU-Hill and ECFC functional assays. Thus, our findings suggest that

Table 2. BMC Phenotype and Functional Characteristics of Patients Stratified by Change in Infarct Size at 6 Months

Infarct Size0* (Increased)(n=26)

Unadjusted P Value

Effect Size Adjusted P Value

Cell phenotype (% positive)

CD3+ 65.5 (58.073.9) 70.3(65.974.5) 0.871 0.03 0.456

CD11b+ 72.0 (57.579.7) 69.9 (63.776.0) 0.114 0.02 0.638

CD14+ (% monocytes) 56.2 (46.668.6) 58.2 (48.165.4) 0.363 0.12 0.177

CD19+ 11.4 (8.214.9) 9.0 (5.910.8) 0.122 0.47 0.322

CD31+ 40.5 (34.648.0) 37.6 (29.042.2) 0.154 0.36 0.046

CD45+CD31+ 39.3 (33.446.7) 36.5 (28.241.0) 0.184 0.37 0.042

CD45+CD31low 30.6 (25.536.3) 28.4 (21.133.0) 0.078 0.52 0.015

CD34+ 4.0 (2.76.3) 4.4 (3.35.4) 0.269 0.90 0.577

CD34+ (ISHAGE) 1.9 (1.42.7) 2.0 (1.52.7) 0.165 1.95 0.807

CD34+CD133+ (ISHAGE) 0.9 (0.61.5) 1.0 (0.71.3) 0.370 1.59 0.996

CD45+ 94.6 (91.796.8) 95.0 (91.896.3) 0.461 0.02 0.593

CD133+ 2.4 (1.74.3) 2.9 (2.23.7) 0.956 0.88 0.849

CXCR4+ 42.6 (34.154.1) 38.7 (27.349.1) 0.723 0.01 0.939

KDR+ 0.2 (0.10.3) 0.2 (0.10.5) 0.620 0.405 0.914

CD133+KDR+ 0.011 (0.0050.030) 0.011 (0.0040.020) 0.090 49.38 0.392

Functional analysis

CFU-Hill (No. of exponential constant of colony)

0.4 (0.00.7) 0.2 (0.00.3) 0.061 6.21 0.033

CFU-Hill (No. of maximum colony) 4.5 (0.011.5) 5.0 (2.015.0) 0.661 0.17 0.259

CFU-Hill (linear slope of confluency) 14.6 (10.619.3) 14.9 (7.216.6) 0.655 0.57 0.590

ECFC (No. of exponential constant of colony)

0.1 (0.01.5) 0.0 (0.00.1) 0.003 8.66 0.032

ECFC (No. of maximum colony) 0.0 (0.014.0) 0.0 (0.021.0) 0.828 0.03 0.626

ECFC (linear slope of confluency) 2.8 (0.73.8) 2.5 (0.95.2) 0.670 0.64 0.539

CFU-F (No. of exponential constant of colony)

1.4 (0.01.6) 0.0 (0.01.6) 0.052 8.64 0.059

CFU-F (No. of maximum colony) 4.0 (1.08.0) 6.0 (0.014.0) 0.356 0.37 0.184

CFU-F (linear slope of confluency) 2.2 (1.73.6) 2.8 (1.23.4) 0.119 2.86 0.493

All flow cytometric analyses were performed on gated lymphocytes unless otherwise specified. BMC indicates bone marrow mononuclear cell; CFU-F, colony-forming unit fibroblast; CFU-Hill, colony-forming unit Hill; ECFC, endothelial-colony forming cell; and ISHAGE, International Society of Hematotherapy and Graft Engineering.

*Values represent median and interquartile range.Value is the coefficient from multivariate regression model and represents the modeled change in infarct size (g) per unit increase in the variable. P value for the multivariable regression model that includes adjustment for age, baseline infarct size, history of hypertension, tobacco use, diabetes mellitus,

angiotensin-converting enzyme inhibitor use, and treatment received (BMCs or placebo).



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phenotype and functional assessments of bone marrow may be important for understanding individual responses to cell therapy in patients with acute STEMI. In addition, they may provide a means to prognosticate outcomes af-ter STEMI and to evaluate the mechanisms underlying responses to myocardial injury.

CD31 (platelet endothelial cell adhesion molecule-1) is a cell-surface protein present on hematopoietic progenitor cells, myelomonocytic cells, and differentiated endothelial cells. It is known to regulate leukocyte adhesion and migra-tion.21,22 In patients with STEMI, CD31 is highly expressed in the culprit plaque.23 Recently, it was demonstrated in both mice and humans that the CD31+CD45+ phenotype identifies a population of highly angiogenic and vasculo-genic cells that express cell markers associated with hema-topoietic stem/progenitor cells.24 In the same study, gene set enrichment analysis showed that the expression levels of proangiogenic genes are higher in bone marrow-derived CD31+CD45+ cells than in CD31 cells. It has also been reported that CD31+ cell therapy for myocardial infarction leads to efficient repair of ischemia in preclinical models.25 This finding in animals supports our current clinical study finding that a higher percentage of CD31+ cells in the BMC product was associated with a decrease in infarct size at 6 months after STEMI, possibly because of improved vascu-larization of the infarcted zone.

In our study, BMC function was assessed to determine whether ex vivo-derived metrics correlate with in vivo po-tential. BMC function was assessed with the CFU-Hill, ECFC, and CFU-F assays. Our results showed that the ex-ponential constant for the CFU-Hill colony growth curve was associated with a reduction in infarct size after STEMI. These findings support those from previous studies show-ing that patients with a higher number of colonies cultured by the CFU-Hill assay have lower long-term cardiovascu-lar risk.13,26 Our study also showed that rapid outgrowth of endothelial progenitor colonies, as measured by the ECFC assay, was associated with a greater reduction in infarct size at 6 months. In agreement with our findings, previous stud-ies have demonstrated that ECFC cells are mobilized after myocardial infarction and that a higher ECFC frequency is associated with a reduction in infarct size after STEMI.2729

Interestingly, for both the ECFC and the CFU-Hill assays, we found that the exponential constant of the colony growth curve (determined by recording the colony number on days 7, 14, 21, and 28), but not the maximum number of colonies, was associated with a larger reduction in infarct size after STEMI, suggesting that the capacity for rapid cell growth is important for reducing infarct size.

Although CFU-Hill colonies were initially thought to be composed of endothelial progenitor cells, recent stud-ies have shown that these colonies actually comprise a mixture of lymphocytes, monocytes, macrophages, and various subpopulations of endothelial cells.14,30 This agrees with our findings that patients whose BMCs pro-duced higher numbers of CFU-Hill colonies also had a higher percentage of CD45+CD31+ cells (myelomonocyt-ic cells, macrophages) in the bone marrow. Furthermore, the fact that we found these cell phenotypes and func-tions to be associated with a larger reductions in infarct size at 6 months is consistent with emerging data show-ing that monocytes play a key role in cardiac angiogen-esis and collateral vessel formation, thereby contributing to cardiac repair after myocardial infarction.3133 In fact, when a myocardial injury occurs, monocytes/macro-phages show a biphasic response.31 Shortly after an in-jury, monocytes and type-1 (inflammatory) macrophages are recruited to the site via monocyte chemoattractant protein-1. However, within several days, type-2 (repara-tive) macrophages arrive to participate in injury resolu-tion and contribute to cardiac angiogenesis and collateral vessel formation.

The CFU-F assay is a functional assessment of bone marrow-derived multipotent mesenchymal stromal cells, which are fibroblast-like cells capable of dif-ferentiating into bone, cartilage, adipose tissue, and fibrous tissue.34,35 There is increasing evidence that these cells may have a significant role in the response to injury in patients with ischemic cardiac disease.3638 In this study, none of the metrics measured with the CFU-F assay were found to be significant (ie, P


Therefore, we recommend that future studies evaluate the role of this assay in assessing response to myocar-dial injury.

Although BMC therapy was not shown to have a thera-peutic effect in the original CCTRN TIME trial,8 there is still much information that can be gained by analyzing the BMC product from these patients with STEMI. First, our findings may provide new insight about the cellular subsets responsible for repair in patients with cardio-vascular disease. Furthermore, our findings suggest that bone marrow composition may be a predictor of clini-cal outcomes. For the patients in this study, transplan-tation of autologous BMCs into the heart did not affect the clinical outcomes assessed, whereas the endogenous BMC characteristics at baseline were found to be associ-ated with a reduction in infarct size. Both BMCs and pro-genitor cells are known to home to ischemic myocardium after an injury.3941 Given that endogenous mechanisms for progenitor cell recruitment already exist, it may be more important to promote favorable bone marrow activ-ity than to artificially translocate regenerative cells into the injured tissue. Therefore, our study may suggest im-portant therapeutic targets for cardiovascular regenera-tive therapies.

When interpreting the results of this study, several fac-tors should be taken into consideration. First, this study was limited to analyses of BMCs obtained at a single time point after myocardial infarction. However, information from 1 point in time is not likely to completely capture the dynamic nature of the injury response. Second, although the injury response may include BMCs, cells in the pe-ripheral circulation, and local inflammatory responses, we only assessed BMC characteristics in this study. Despite this limitation, we were able to identify multiple asso-ciations with the outcome of interest. Third, although the analyses performed in this study were prespecified, this was a biologically guided exploratory study. In an attempt to balance this and focus on the characteristics with the potential to influence the future direction of cell therapy, we limited our discussion to the associations for which there is a strong biological rationale for the relationship and compelling preclinical data to support our findings. Fourth, some patients in our study cohort received cell therapy as part of the clinical trial, whereas others re-ceived placebo. This was unlikely to have affected our results because change in infarct size was not found to be significantly different for patients who received the stem cell product and those who received placebo in the CCTRN TIME trial. However, we adjusted for this treat-ment difference in the statistical model to limit its poten-tial for being a confounding factor. Fifth, in patients with an acute infarction, quantifying infarct size by using cMRI can be problematic because these measurements may in-clude areas of myocardial necrosis, as well as areas of edema and inflammation.42 Therefore, changes in infarct size may reflect changes in inflammation in addition to changes in the pattern of necrosis. Characterizing patients on the basis of infarct size could generate a regression to

the mean scenario in which patients with a small infarct size at baseline are unlikely to show much change, where-as those with a large infarct size at baseline may show a smaller infarct size at the 6-month follow-up. To help determine whether the observed changes in infarct size were in fact related to changes in myocardial necrosis, we explored correlations between the infarct size calculated by using cMRI and both creatine kinase-MB level and ejection fraction, 2 variables known to be associated with infarct size. In this analysis, the correlation between cre-atine kinase-MB level and day 3 infarct size was relatively weak (R2=0.35), whereas the correlation between creatine kinase-MB level and day 7 infarct size was much stron-ger (R2=0.66). The correlations between day 3 infarct size and day 3 ejection fraction (R2=0.27) and day 7 ejection fraction (R2=0.45) were both low to moderate. Overall, the correlations between the cMRI measurement of infarct size and the surrogate markers were moderate. Finally, because this was an exploratory study, any relationships found to be significant will have to be reassessed in a con-firmatory study.

ConclusionsTo our knowledge, this is the first comprehensive report of the correlation between BMC phenotype and functional assay re-sults and infarct size in patients with STEMI. This type of analysis may be useful for generating hypotheses on the role of cellular subsets in cardiovascular repair. Furthermore, although the response to cell therapy with unselected BMCs was limited in the CCTRN TIME trial, this study may provide a means to significantly improve cell product composition, optimize patient selection for clinical trials, and personalize medical therapies for patients with heart disease.

AcknowledgmentsWe thank Heather Leibrecht, MS at the Texas Heart Institute for her assistance in preparation of this article.

Sources of FundingThis study was funded by UM1 HL087318 (Cardiovascular Cell Therapy Research Network) and R01 HL091005 (Ancillary Studies), University of Florida.

DisclosuresNone.

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What Is Known?

In cardiovascular cell therapy, harvested bone marrow mononuclear cells (BMCs) are isolated and reinfused into the heart by using intra-coronary infusion, with the goal of repairing injured myocardium after segment-elevationmyocardial infarction (STEMI).

Clinical trials of intracoronary autologous BMC transplantation in pa-tients with STEMI have shown varied results

What New Information Does This Article Contribute?

Specific populations of BMCs were found to be associated with re-duced infarct size after STEMI.

Patients who had BMCs that showed faster growth of endothelial pre-cursor cells in in vitro assays had larger reductions in infarct size after STEMI.

Transplantation of autologous BMCs into the heart did not affect clinical outcomes; rather, endogenous BMC characteristics at baseline were found to be associated with reduced infarct size.

Because STEMI is a significant cause of cardiovascular morbid-ity and mortality, an important area of ongoing investigation is

the identification of specific BMC subsets that are involved in myocardial repair. In this study, we evaluated the baseline BMC characteristics of participants in the Cardiovascular Cell Therapy Research Network Timing in Myocardial Infarction Evaluation tri-al, a randomized, controlled trial assessing the use of autologous BMC transplantation in patients with STEMI. Although infusion of autologous BMCs into the heart did not affect clinical outcomes, some endogenous BMC characteristics at baseline were found to be associated with a reduction in infarct size at 6 months after STEMI. Specifically, this study showed that patients with bone marrow containing a higher percentage of CD45+CD31low cells had larger reductions in infarct size. Additionally, patients with bone marrow containing cells that grew more rapidly in the CFU-Hill and the endothelial-colony forming cell assays had larger reductions in infarct size. Thus, it may be more beneficial for patients to have favorable bone marrow activity than to artifi-cially translocate regenerative cells into the injured myocardial tissue. These findings suggest that optimizing patient selection and improving cell product composition are important directions for future investigation.

Novelty and Significance



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for the Cardiovascular Cell Therapy Research Network (CCTRN)R. Cogle and Doris A. Taylor

ChristopherWu, Shelly L. Sayre, Aaron Orozco, Claudia Zierold, Robert D. Simari, Lem Moy, Aruni Bhatnagar, Brian H. Johnstone, Dejian Lai, Micheline Resende, Ray F. Ebert, Joseph C.

Carl J. Pepine, James T. Willerson, Emerson C. Perin, Stephen G. Ellis, David X.M. Zhao, Robert C. Schutt, Barry H. Trachtenberg, John P. Cooke, Jay H. Traverse, Timothy D. Henry,

Biorepository Evaluation From the CCTRN TIME TrialBone Marrow Characteristics Associated With Changes in Infarct Size After STEMI: A

Print ISSN: 0009-7330. Online ISSN: 1524-4571 Copyright 2014 American Heart Association, Inc. All rights reserved.is published by the American Heart Association, 7272 Greenville Avenue, Dallas, TX 75231Circulation Research

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Supplemental Material

Online Table I. Staining Reagents Used for the Phenotype Analysis

Antibody Antigen Manufacturer Clone Catalog# Anti-hCD45 CD45 BD Pharmingen 2D1 340953 Anti-hCD34 CD34 BD Pharmingen 8G12 348791 Anti-hCD133 CD133 Miltenyi Biotec AC133 130-080-801 Anti-hCD31 CD31 BD Pharmingen WM59 555445 Anti-hKDR KDR* R&D Systems 89106 FAB357A Anti-hCD3 CD3 BD Pharmingen SK7 557851 Anti-hCXCR4 CXCR4 BD Pharmingen 12G5 555974 Anti-hCD14 CD14 BD Pharmingen M5E2 555397 Anti-hCD19 CD19 BD Pharmingen SJ25C1 560177 Anti-hCD11b CD11b BD Pharmingen ICRF44 550019 CD45-Iso Unknown BD Pharmingen MOPC-21 552834 CD34-Iso Unknown BD Pharmingen MOPC-21 557872 CD133-Iso Unknown BD Pharmingen MOPC-21 555749 CD31-Iso Unknown BD Pharmingen MOPC-21 555748 KDR-Iso Unknown R&D Systems 11711 IC002A CD3-Iso Unknown BD Pharmingen MOPC-21 557872 CD184-Iso Unknown BD Pharmingen MOPC-21 555749 CD14-Iso Unknown BD Pharmingen MOPC-21 555748 CD19-Iso Unknown BD Pharmingen MOPC-21 560167 CD11b-Iso Unknown BD Pharmingen MOPC-21 555751 *KDR refers to kinase insert domain-containing receptor, also known VEGFR-2 (vascular endothelial growth factor receptor-2) and CD309. CXCR4 refers to C-X-C chemokine receptor type 4, also known as fusin and CD184.

Online Table II. Flow Cytometer Set-up

Detector array (laser)

PMT (detector)

Long pass dichroic mirror

Band pass filter

Fluorochrome

Octagon (488-nm blue laser)

A 735 LP 780/60 PE-Cy7

B 685 LP 695/40 PerCP-Cy5.5 C 550 LP 575/26 PE, PI D 505 LP 530/30 FITC, GFP E blank 488/10 SSC F blank blank none G blank blank none H - blank none Trigon (633-nm red laser)

A 735 LP 780/60 APC-Cy7

B 685 LP 660/20 APC C - blank none Trigon (405-nm violet laser)

A 505 LP 525/50 AmCyan

B blank 440/40 Pacific Blue C - blank none Trigon (355-nm UV laser)

A 505 LP 530/30 Indo-1 (blue)

B blank 440/40 Indo-1 (Violet), DAPI C - blank N/A PMT, photo multiplier tube. LP, longpass filter, nm nanometer

Online Table III. Compensation Tubes Used for Creating a Compensation Matrix

Laser (PMT-Detector)

488-nm D

488-nm C

488-nm B

488-nm A

633-nm B

633-nm A

Tube #1 CD45 - - - - - Tube #2 - CXCR4 - - - - Tube #3 - - CD45 - - - Tube #4 - - - CD3 - - Tube #5 - - - - CD11b - Tube #6 - - - - - CD19 Tube #7 - - - - - -

Online Table IV. Demographics and Clinical Data of Patients Stratified by Change in Infarct Size at 6 Months and Treatment Received (BMCs or Placebo)

Received BMCs Received placebo

Infarct size decreased

Infarct size increased


Infarct size increased P value

(n=51) (n=15) (n=24) (n=11) Age 57.5 11.2 53.0 8.2 56.0 10.1 58.7 13.1 0.462 Female 8 (15.7%) 2 (13.3%) 4 (16.7%) 1 (9.1%) 0.938 Height (meters) 1.77 0.10 1.76 0.10 1.75 0.11 173 0.06 0.895 Weight (kg) 94.5 19.8 97.7 23.4 95.7 19.2 87.1 22.2 0.601 BMI (kg/m2) 30.2 5.2 31.5 6.9 31.0 5.3 28.5 6.1 0.547 Prior medical history Diabetes 10 (19.6%) 3 (20%) 4 (16.7%) 4 (36.4%) 0.589 Hypertension 28 (54.9%) 6 (40%) 18 (75%) 7 (63.6%) 0.158 Hyperlipidemia 36 (70.6%) 9 (60%) 17 (70.8%) 7 (63.6%) 0.853 History of angina 11 (21.6%) 2 (13.3%) 5 (20.8%) 1 (9.1%) 0.730 Smoking 30 (58.8%) 10 (66.7%) 14 (58.3%) 8 (72.7%) 0.799 Cardiovascular and infarction details Baseline infarct size (grams) 47.4 24.5 36.9 26.4 43.6 26.9 33.3 17.3 0.251 Heart rate 79.9 14.2 82.6 10.2 80.5 18.8 81.7 12.9 0.929 Systolic BP (mmHg) 119.3 20.8 112.3 18.4 121.0 17.4 110.0 14.7 0.268 Diastolic BP (mmHg) 73.3 15.5 75.6 13.6 74.4 11.2 69.9 13.4 0.763 Screening EF (echocardiography) 36.2 5.9 36.0 8.1 38.3 4.3 36.8 7.8 0.564 Core lab EF (day 3) (cMRI) 45.4 9.9 44.9 13.9 46.8 9.3 38.7 8.5 0.190 Hemoglobin (g/dL) 14.3 1.8 13.6 1.1 13.4 2.2 13.1 0.9 0.089 High sensitivity CRP (mg/L) 41.0 54.8 26.5 21.7 37.5 35.8 46.0 23.7 0.679 Peak CK (U/L) 3215.2 2029.9 3593.6 3006.1 2493.2 2213.8 2600.9 2326.3 0.442 Peak CKMB (ng/mL) 274.3 174.8 262.6 253.7 213.4 216.6 245.8 168.2 0.731 BNP (pg/mL) 335.2 779.7 191.0 89.2 308.9 341.9 247.0 178 0.897 NT-proBNP (pg/mL) 1691.4 1414.8 550.3 281.6 375.5 207.2 2627.7 2591 0.239

Troponin T (peak) (ng/mL) 10.9 8.3 8.5 7 6.9 5.9 10.8 7.6 0.349 Troponin I (peak) (ng/mL) 76.3 96.2 214.1 270.7 74.3 77.2 54.9 41.9 0.417 Drug eluting stent 42 (82.4%) 10 (66.7%) 21 (87.5%) 8 (72.7%) 0.380 LAD infarction 45 (88.2%) 12 (80%) 22 (91.7%) 11 (100%) 0.418 Preinfarction angina 10 (19.6%) 1 (6.7%) 4 (16.7%) 2 (18.2%) 0.704 Transferred after MI 20 (39.2%) 6 (40%) 13 (54.2%) 5 (45.5%) 0.663 PCI at non-study center hospital 6 (11.8%) 0 (0%) 0 (0%) 2 (18.2%) 0.112 Discharge medications ACE inhibitor 44 (86.3%) 14 (93.3%) 18 (75%) 9 (81.8%) 0.444 Aspirin 48 (94.1%) 15 (100%) 24 (100%) 11 (100%) 0.386 Beta blocker 49 (96.1%) 15 (100%) 24 (100%) 11 (100%) 0.572 Clopidogrel or prasugrel 49 (96.1%) 13 (86.7%) 24 (100%) 10 (90.9%) 0.260 Statins 47 (92.2%) 13 (86.7%) 24 (100%) 9 (81.8%) 0.235 Diuretic 14 (27.5%) 1 (6.7%) 2 (8.3%) 4 (36.4%) 0.069 Coumadin or enoxaparin 12 (23.5%) 1 (6.7%) 3 (12.5%) 1 (9.1%) 0.316 Cell product information Time from PCI to infusion (days) 5.1 2.2 5.0 2.4 5.3 2.5 3.9 1.3 0.399 Time from aspiration to infusion (hours) 8.9 3.5 8.6 1.6 8.4 1.1 8.6 1.4 0.887 Final volume (mL) 150.0 0 140.3 37.7 149.0 3.3 149.5 1.8 0.146 Cell product viability (%) 98.1 1.7 98.4 1.2 98.2 1.5 98.6 0.8 0.710

Values represent mean SD or number (%). BMI, body mass index; BNP, brain natriuretic peptide BP, blood pressure; CK, creatine kinase; CKMB, creatine kinase-MB; CRP, C-reactive protein; EF, ejection fraction; LAD, left anterior descending; LV, left ventricular; MI, myocardial infarction; PCI, percutaneous coronary intervention.

Online Table V. BMC Phenotype and Functional Characteristics of Patients Stratified by Change in Infarct Size and Treatment Received (BMCs or Placebo)

Received BMCs Received placebo Infarct size decreased




P value (n=51) (n=15) (n=24) (n=11) Cell phenotype CD3+ 64.7 (56.9-74.6) 70.4 (65.9-74.5) 68.5 (60.6-73.0) 70.2 (62.2-74.8) 0.149 CD11b+ 72.5 (57.5-80.3) 72.4 (65.1-76.4) 71.2 (59.9-79.4) 68.1 (62.2-71.5) 0.978 CD14+ (% monocytes) 56.7 (44.8-69.3) 61.0 (55.9-67.8) 55.2 (48.8-66.7) 53.8 (44.0-62.3) 0.573 CD19+ 9.3 (6.0-12.3) 7.9 (6.5-11.2) 8.9 (7.5-12.5) 5.9 (3.2-8.4) 0.038 CD133+ 2.6 (1.8-4.4) 2.5 (1.5-3.4) 2.3 (1.6-3.8) 3.0 (2.8-4.6) 0.415 CD31+ 40.3 (34.6-44.7) 39.4 (29.0-42.2) 41.1 (33.9-50.8) 37.4 (29.0-44.5) 0.592 CD34+ 4.7 (2.7-7.2) 4.3 (3.0-5.4) 3.4 (2.6-5.4) 4.4 (4.1-6.0) 0.332 CD34+ (ISHAGE) 1.8 (1.2-2.8) 1.8 (1.4-2.2) 2.1 (1.7-2.5) 2.4 (1.7-2.9) 0.561 CD34+CD133+ (ISHAGE) 0.9 (0.5-1.5) 0.7 (0.7-1.2) 1.0 (0.8-1.4) 1.3 (0.8-1.6) 0.252 CD45+ 94.4 (91.1-96.8) 93.9 (90.5-96.3) 94.9 (93.5-97.0) 95.1 (92.8-96.9) 0.784 CD45+CD31+ 39.0 (33.4-43.4) 38.0 (28.0-41.0) 39.4 (32.5-49.8) 36.1 (28.5-42.6) 0.625 CD45+CD31low 30.6 (25.5-34.8) 28.4 (20.0-37.1) 30.3 (25.4-41.4) 26.5 (21.4-32.6) 0.541 Functional analysis CFU-Hill (exponential constant of colony #) 0.4 (0.0-0.7) 0.2 (0.0-0.3) 0.3 (0.0-0.6) 0.2 (0.0-0.5) 0.654 CFU-Hill (maximum colony #) 4.0 (0.0-11.0) 9.0 (4.0-17.0) 6.0 (0.0-14.0) 4.5 (1.0-8.0) 0.559 CFU-Hill (linear slope of confluency) 12.2 (8.8-14.9) 11.0 (3.6-16.4) 19.3 (16.1-24.8) 15.7 (14.9-16.6) 0.056 ECFC (exponential constant of colony #) 0.2 (0.0-1.6) 0.0 (0.0-0.0) 0.0 (0.0-0.2) 0.1 (0.0-1.4) 0.127 ECFC (maximum colony #) 3.5 (0.0-15.0) 0.0 (0.0-22.0) 0.0 (0.0-4.0) 5.5 (0.0-16.0) 0.676 ECFC (linear slope of confluency) 2.9 (2.3-4.6) 3.3 (1.8-7.1) 0.7 (0.0-3.8) 2.4 (0.0-2.7) 0.638 CFU-F (exponential constant of colony #) 1.4 (0.1-1.6) 0.1 (0.0-1.6) 0.1 (0.0-1.6) 0.0 (0.0-0.0) 0.140 CFU-F (maximum colony #) 4.0 (2.0-8.0) 6.0 (0.0-17.0) 2.0 (0.0-6.0) 6.0 (2.5-11.5) 0.301 CFU-F (linear slope of confluency) 2.5 (2.0-3.4) 3.1 (2.8-3.5) 2.0 (1.0-4.6) 1.0 (0.7-1.2) 0.678

All FC analyses were performed on gated lymphocytes unless otherwise specified. Values represent median and interquartile range.

Online Figure I. Flow cytometer optical pathway configuration

A. Blue Laser

B. Red Laser

C. Violet Laser

D. UV Laser

Online Figure 2. Flow cytometry histograms of BMC populations and isotype controls. A, Gated lymphocytes were evaluated for the presence of CD45, CD31, CD133, CD34, KDR (CD309), CD11b, CD3, CXCR4 (CD184), and CD19. B, Gated monocytes were evaluated for the presence of CD14. Flow cytometric gates are outlined in black for each dot plot. Antigen-specific signals are shown in blue, and signals for the respective fluorescent isotype IgG are shown in red.

clinical track - circulation...

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