Acute inflammatory stimuli rapidly mobilize neutrophils from the bone marrow by shortening postmitotic maturation time and releasing younger neutrophils; however, the kinetics of this change in maturation time remains unknown. We propose a kinetic model that examines the rate of change in neutrophil average age at exit from the bone marrow during active mobilization to quantify this response and use this model to examine the temporal profile of late neutrophil phenotypic maturation. Total and CD10−/CD16low circulating neutrophils were quantified in cardiac surgery patients during extracorporeal circulation (ECC). Net growth in the circulating neutrophil pool occurred during the procedural (0.04 ± 0.02 × 109·l−1·min−1), warming (0.14 ± 0.02 × 109·l−1·min−1), and weaning (0.12 ± 0.06 × 109·l−1·min−1) phases of ECC. When applied to our differential equation mathematical model, these results predict that neutrophil average age at exit from the bone marrow decreased continually during ECC, resulting in average neutrophil release 8.44 ± 2.20 h earlier during the weaning phase than at the beginning of ECC sampling. Modeling of concurrent changes in CD10−/CD16low neutrophil numbers indicates that CD10 expression is directly related to neutrophil mean age and predicts that the proportion of mobilizable postmitotic neutrophils that are CD10+ increases from 64 to 81% during these sampled 8.4 h of maturation.
- bone marrow
- postmitotic maturation
- neutrophil recruitment
- mathematical modeling
the increased peripheral demand for neutrophils typical of acute inflammatory states is supplied predominantly by increased bone marrow neutrophil production, a response mediated acutely by increased release of preformed neutrophils. During steady-state production, mature neutrophils are released from the bone marrow at a mean age of ∼12 days after precursors become neutrophil lineage-committed (9, 11). Postmitotic maturation time, which accounts for 6–8 days under basal conditions (14), is reduced by 3–4 days during active neutrophil recruitment (13, 19, 37), thereby increasing neutrophil availability for release in the circulation. Circulating neutrophil numbers can increase within 1–2 h of exposure to a leukocytosis-inducing stimulus (21), indicating a rapid onset of this abbreviation in postmitotic transit time. Although total transit time is reduced, the acceleration of neutrophil postmitotic transit, particularly the acute response during exposure to a neutrophil-mobilizing stimulus, has not been quantified. The reduction in neutrophil average age at exit from the bone marrow during active neutrophil recruitment can provide an estimate of this acute acceleration of postmitotic transit, which may afford a measure of bone marrow integrity and response to stimulation.
We (35) and others (24, 32) have demonstrated that an increased proportion of circulating neutrophils exhibit a CD10− phenotype, in association with low CD16 expression (CD10−/CD16low) (35) during active bone marrow neutrophil recruitment. Neutrophil CD10 expression is functionally significant, since this zinc metalloprotease (neutral endopeptidase 184.108.40.206) cleaves and inactivates multiple proinflammatory, vasoactive, and neuropeptides (6, 18, 39). Whereas CD16 expression is acquired during the metamyelocyte stage and levels gradually increase with continuing morphological maturation (40), CD10 is expressed only by segmented neutrophils (17), and an estimated 25% of maturing bone marrow neutrophils are CD10− (32). The CD10−/CD16low subpopulation is thus morphologically heterogeneous, consisting of maturing segmented neutrophils, all band forms and some metamyelocytes. Although previous studies have established the rate at which morphological maturation occurs in the neutrophil lineage relative to time spent within the bone marrow (9–11, 28), the age-related acquisition of functionally relevant markers such as CD10 remains unreported.
Transit of neutrophil lineage-committed cells through maturation within the bone marrow, followed by their release in the circulation, is predicted to be sequential, conforming to first in-first out kinetics based on cellular age (4, 11, 29, 34). The increase in cellular mean age during transit can be described by a “pipeline” model of neutrophil production that is limited by a release point that defines neutrophil age at exit in the circulation (Fig. 1). During the acute phase of neutrophil recruitment, rates of cell proliferation and maturation within the bone marrow should not change, and the only means to rapidly increase circulating neutrophil numbers is to release cells at a younger average age (from a progressively earlier point in the pipeline). Changes in circulating neutrophil numbers during stimulated bone marrow release, when applied to this model of neutrophil production, can be used to predict the change in average age at which neutrophils are released in the circulation. However, this approach requires that neutrophil release from the bone marrow is the only contributor to expansion of the circulating neutrophil pool during active neutrophil recruitment. Neutrophils can also be recruited from the extramedullary marginal pool; however, these demarginated neutrophils have no distinguishing morphological or phenotypic characteristics, preventing their quantification.
Extracorporeal circulation (ECC) during cardiac surgery provides a unique intravascular environment wherein the pulmonary vascular bed, a significant reservoir of marginal neutrophils (1), is excluded from the circulation for a substantial duration. Cardiac surgery also incorporates inhibitors and stimulants of bone marrow neutrophil release; systemic hypothermia suppresses active neutrophil recruitment from the bone marrow (3), whereas rewarming (38, 41) and reperfusion of the ischemic myocardium (25) promote recruitment. Intraoperative sampling during ECC thereby provides a useful in vivo model to evaluate acute changes in the kinetics of bone marrow neutrophil release under conditions of limited demargination. Serial sampling over a short time interval also ensures that changes in neutrophil intravascular half-life [t1/2, usually 6–8 h under resting conditions (14)] and time to onset of apoptosis [usually 24–48 h (27)] will not contribute to observed changes in circulating neutrophil numbers.
By investigating acute changes in the composition and size of the circulating neutrophil pool in cardiac surgery patients during ECC, we identify net expansion of the circulating neutrophil pool accompanied by an increasing proportion of neutrophils that exhibited the CD10−/CD16low phenotype. Mathematical modeling of changes in total neutrophil numbers revealed a progressive decrease in the average age at which neutrophils exit the bone marrow during ECC. Concurrent changes in numbers of CD10−/CD16low circulating neutrophils were used to predict the acquisition of CD10 expression throughout late neutrophil maturation as cellular mean age increases.
MATERIALS AND METHODS
Fluorochrome conjugated monoclonal antibodies.
CD10 (HI10a, mouse IgG1Ê)-phycoerythrin (PE) was from BD Biosciences Immunocytometry Systems (BDIS; San Jose, CA); CD16 (3G8, mouse IgG1Ê)-PE-Cy5 and IgG1Ê isotypes (MOPC-21)-PE and -PE-Cy5 were from BD PharMingen (BD Biosciences Pharmingen, San Diego, CA).
Buffers, anticoagulants, and other reagents.
Anticoagulants used were EDTA and citrate-theophylline-adenosine-dipyradimole (CTAD) in vacutainers (Becton-Dickinson, Franklin Lakes, NJ). The fluorescent nuclear dye Hoechst 33342 (Molecular Probes, Eugene OR), 50 μM in 0.9% NaCl (Baxter Healthcare, Sydney, Australia), was used to label leukocytes in whole blood. Hanks' balanced salt solution (HBSS) contained 10 mM HEPES, 0.5% BSA, and 1 mM sodium azide (NaN3; all from Sigma, St. Louis, MO). NaN3, 1 mM in 0.9% NaCl (Baxter Healthcare) was used during antibody incubation. All buffers, media, and reagents were Zetapore (Cuno Filter Systems, Meriden, CT) filtered for sterilization and to minimize lipopolysaccharide contamination.
Patients aged 35–80 yr undergoing elective, first-time cardiac surgery (n = 10; Table 1) were prospectively recruited from the Cardiothoracic Surgical Unit of Royal Prince Alfred Hospital, Sydney. Exclusion criteria were evidence of bacterial infection within the preceding 2 wk, immunosuppressive diseases, acute coronary syndromes within the preceding 4 wk, severely impaired left ventricular function (ejection fraction <30%), use of any immunomodulatory medications (e.g., steroids, immunosuppressive agents), and chronic renal failure (serum creatinine >200 μmol/l). Written informed consent was obtained from all patients, and the study was approved by the institutional ethics committee.
Cardiac surgery with hypothermic ECC was performed through a median sternotomy under general anesthesia as previously described (35). After administration of 400 U/kg unfractionated porcine heparin (Pharmacia), ECC was established. In brief, a dual-stage cannula inserted in the right atrium provided venous drainage to the ECC circuit, whereas oxygenated blood was returned to the patient through an arterial cannula placed in the ascending aorta, bypassing the cardiac and pulmonary vascular beds. A vascular clamp was applied across the ascending aorta, cardioplegia was administered to arrest the heart, and patients were systemically cooled to 30–32°C. At the completion of the surgical procedure, patients were rewarmed to 37°C, and the aortic cross-clamp was removed, reestablishing myocardial blood flow. Patients were weaned from ECC after return of mechanical cardiac activity, at which stage normal pulmonary blood flow was gradually reestablished.
Samples (1.5 ml) were collected from the systemic circulation via the radial arterial line of patients immediately before anesthetic induction (baseline) and sequentially at 3- to 4-min intervals during the procedural, warming, and weaning phases of ECC (Table 2 and Fig. 2); four samples were collected within each intraoperative stage. Blood was immediately anticoagulated with EDTA-CTAD, and leukocytes were labeled with 50 μM Hoechst 33342 at 30°C for 10 min. Samples were then placed on ice in the dark, and cells were labeled for flow cytometry.
Antibody labeling of whole blood, performed within 2 h of sample collection, was a modification of a previously published method (26). Aliquots (5 μl) of Hoechst-labeled blood were incubated with 1 μl each of CD10-PE and CD16-PE-Cy5 in combination or isotype control monoclonal antibodies (MAbs; saturating concentrations) in 1 mM NaN3 on ice in the dark for 20 min, diluted to 0.75–1.0 ml with HBSS-BSA-NaN3, and stored at 4°C in the dark for up to 4 h.
Flow cytometry was performed using an LSR bench-top flow cytometer (BDIS) within 4 h of sample collection, and Cell Quest Pro software (version 4.0.2; BDIS) was used to acquire and store data files. The validity of data over time was confirmed by daily calibration of the flow cytometer using Calibrite Rainbow beads (BDIS). A total of 1.5 × 106 events were acquired per sample; leukocytes identified by positive Hoechst 33342 fluorescence and granulocyte events within the leukocyte gate, identified on the basis of their characteristic forward and side angle light scatter, were analyzed for MAb-related fluorescence. Contaminating eosinophils were excluded from the granulocyte population on the basis of absent CD10 and CD16 expression (CD10−/CD16− events); neutrophil events were identified by positive CD16 expression. The proportion of neutrophil events with positive CD10 MAb fluorescence was then determined for each sample.
Full blood counts.
Differential full blood counts on EDTA-CTAD anti-coagulated blood were performed with a Sysmex SF-3000 (Roche Diagnostics, Sydney, Australia) automatic full blood count analyzer. Neutrophil counts after baseline were corrected for hemodilution using the formula: (baseline hematocrit/observed hematocrit) × observed neutrophil count = corrected count.
Data are represented as means ± SE for n = 10 cardiac surgery patients unless otherwise stated. Results were analyzed using Prism statistical software (GraphPad Prism version 4.00 for Windows; GraphPad Software, San Diego, CA). Changes in neutrophil numbers were compared using paired t-tests (baseline vs. first intraoperative sample) and one-way repeated-measures ANOVA (comparisons within each phase of ECC). Statistical significance was defined as P < 0.05.
The basic conceptual model of neutrophil production is that of a pipeline of neutrophils of different ages maturing in the bone marrow that enter the circulation at a certain “release point” along the pipeline. Under basal conditions, neutrophil production is constant, and neutrophils are released in a fully mature state. However, during inflammation, this baseline neutrophil production may be increased by the release of less mature neutrophils in the circulation. This equates to a left shift in the release point (Fig. 1), leading to a temporary increase in production and the emergence of less mature neutrophils in the circulation.
We denote the number of neutrophil precursor cells produced per hour from the bone marrow in the lineage toward mature neutrophils at time t by N(t) and the age of their release in circulation by s. The maturation time for newly committed neutrophil precursors in the bone marrow to enter circulation is of the order of days [typically 12 days (9, 11) in the absence of inflammation]; however, the duration of time covering the three phases of ECC is of the order of hours (typically 1–2 h). Thus, over the time frame of our investigation, the number of neutrophils at any maturation stage along the pipeline that could enter the circulation would not be influenced by any rise in the production of early stage neutrophils. The baseline entry rate of neutrophils from the bone marrow in the circulation is taken to be constant, N0 (since we assume that at baseline, before surgery, the number of neutrophils in the bone marrow is in equilibrium).
We would like to model the total neutrophil level in circulation, which we define as NC. We denote this number, at time t by NC(t). If 1/δ is the average number of hours neutrophils will survive in circulation, established as ∼6–8 h (2, 14) (we use an estimate of 7 h for 1/δ), then the rate of change in the total number of these neutrophils is given by (1) Here, the left-hand side of this equation (dNC/dt) is the rate of change in the number of circulating neutrophils (NC) with time. The right hand side of the equation specifies what influences the change in the number of circulating neutrophils, namely the total production of circulating neutrophils, N0(1 − ds/dt), incorporating baseline bone marrow neutrophil production (N0), adjusted for any release of less mature neutrophils because of a left shift of the release point (1 − ds/dt), and natural death or extravascular loss (δNC). The ds/dt term (the time derivative of the release age s) in Eq. 1 specifies the rate at which the release point in the pipeline (age at neutrophil release) is changing. Thus 1) if the release point for entry to circulation is not moving (ds/dt = 0) then neutrophils are being released at the baseline rate (N0); 2) if the release point is moving left (ds/dt < 0) then neutrophils are being released in the circulation faster than usual (the release rate is >N0), and at progressively younger ages; and 3) if the release point is moving right (ds/dt > 0) then the rate of neutrophil release is less than usual (N0; this is not considered in our study). The baseline neutrophil entry rate in the circulation, N0, is calculated from Eq. 1 assuming that the measured pre-ECC neutrophil levels (N̄C) are in equilibrium, that is, dNC/dt = 0 and ds/dt = 0, leading to N0 = δN̄C.
It is reasonable to fit the measured data to (and consider that the population of neutrophils is changing according to) a linear expression in each phase of sampling during ECC. By estimating the growth in neutrophil numbers during each sampling phase, we can then estimate the neutrophil production required to generate the observed growth rates. If the growth in circulating neutrophil numbers is linear during each phase, then NC = α + tβ (α and β are calculated from linear regression) and the “velocity” of the release point for the pipeline describing neutrophil age at release (i.e., the rate at which a left shift of the release point is occurring) ds/dt = 1 − 1/N0 [β + δ(α + tβ)]. The best-fitting straight line through the data points for each phase of ECC sampling is calculated (see Fig. 4A) determining the line's slope (β) and y-intercept (α); given that the number of neutrophils can then be interpolated at any time, using Eq. 1 and rearranging for ds/dt, we have a mathematical expression for the velocity of the neutrophil release point (entry age in the circulation) at any time. Finally, the age of release, “s,” at any time is calculated by mathematical integration of its velocity ds/dt.
To estimate the age profile of acquiring CD10 expression in the bone marrow, we extended our mathematical model. The proportion of neutrophils of age s in the bone marrow that are CD10− is denoted as p(s). Hence, initially, at baseline, the proportion of neutrophils released that are CD10− is p(0) ≈ 0.02, and it can be assumed that this proportion, p, increases toward a value of one with decreasing neutrophil age (that is, all newly produced postmitotic neutrophils are CD10− at the commencement of maturation in the bone marrow). Next, the change in the number of CD10− neutrophils measured in the circulating pool [N(t)] can be modeled similarly to the total number of neutrophils, namely, Accordingly, we estimate the proportion of CD10− neutrophils, p(s), at any given point s in the pipeline by which is calculated from the best-fitting straight lines through the data points for total and CD10− neutrophil counts during each phase of ECC. Here, dNC/dt + δNC refers to the overall production rate of neutrophils as determined by the rate of production required to result in the observed increase in the slope of the data plus the production required to account for the death rate of neutrophils, so that p(s) is the ratio of the overall production rate of CD10− neutrophils to the overall production rate of total neutrophils.
Although bone marrow neutrophil release is stimulated during ECC (5, 20), an early, transient neutropenia is frequently observed upon its commencement (20, 22). Consequently, intraoperative sampling was commenced 32.9 ± 6.2 min after ECC was established to ensure that any acute neutrophil sequestration was complete and flux between circulating and marginal neutrophil pools had reached equilibrium. There were 3.90 ± 0.28 × 109/l neutrophils within the circulating pool at the pre-ECC baseline, of which 2.2 ± 0.4% were CD10−/CD16low (Figs. 3A and 4A). Total circulating neutrophil numbers were slightly reduced to 3.08 ± 0.26 × 109/l in the first intraoperative sample (P = 0.03; Fig. 4A); however, the CD10−/CD16low subpopulation increased from 0.08 ± 0.02 × 109/l at baseline to 0.50 ± 0.10 × 109/L (P = 0.003) to represent 16.4 ± 2.7% of the circulating pool at this stage (Figs. 3B and 4A).
During ECC, active bone marrow neutrophil release is reportedly suppressed by hypothermia but stimulated by systemic rewarming (38, 41) and may be further augmented with myocardial reperfusion (25, 35). Total circulating neutrophil numbers increased during procedural (P = 0.03), warming (P < 0.0001), and weaning (P = 0.06) phases of ECC (Fig. 4A) relative to numbers present at the start of each phase. The rate of increase in circulating neutrophils appeared to be linear and was similar between operative stages (Table 3 and Fig. 4A), indicating steady growth in the circulating neutrophil pool throughout ECC. At the completion of sampling, circulating neutrophil numbers had increased to 9.39 ± 1.54 × 109/l (Fig. 4A), an increment of 2.46 ± 0.42-fold relative to baseline. The number of circulating CD10−/CD16low neutrophils increased progressively and similarly during procedural (P < 0.0001), warming (P < 0.0001), and weaning (P = 0.0008) phases of ECC (Table 3 and Figs. 3, B-D, and 4A). The increase in the CD10−/CD16low subpopulation also appeared to be linear throughout ECC (Fig. 4A). The rates of change in total and CD10−/CD16low neutrophil numbers (Fig. 4A) were not significantly altered after reestablishment of normal pulmonary blood flow upon weaning from ECC (Fig. 2), indicating a negligible contribution to circulating neutrophil numbers from pulmonary demargination.
Basal bone marrow neutrophil production, based on an intravascular t1/2 of 7 h (2, 14), was calculated to be 0.009 ± 0.001 × 109·l−1·min−1 [3.90 ± 0.28 × 109/l × δ(=1/7/h) ÷ 60 min/h; this is equivalent to a production rate of 0.95 ± 0.07 × 109·kg−1·day−1, based on a blood volume of 71 ml/kg, and is consistent with prior reports (14, 42) (Table 3)]. There was net growth in the circulating neutrophil pool during procedural ECC, which increased further with warming and remained similar throughout the weaning phase (Table 3). Assuming that flux between circulating and marginal neutrophil pools, intravascular t1/2, and time to onset of apoptosis all remained constant during the brief intraoperative sampling interval, net growth in the circulating neutrophil pool during ECC could be attributed to increased bone marrow neutrophil production. We calculated that neutrophil production by the bone marrow increased during procedural ECC and was further augmented with warming but remained relatively constant during the weaning phase (Table 3). The CD10−/CD16low subpopulation contributed a progressively increasing proportion of bone marrow neutrophil production during each stage of ECC (Table 3).
The short intraoperative sampling interval necessitates that the calculated increase in bone marrow neutrophil production was produced by augmented release of preformed neutrophils (and band forms) and not by increased proliferation of neutrophil precursors. Neutrophils must exit the bone marrow at a progressively earlier maturational age to generate such an increase in production. The total number of neutrophils within the circulating pool at any given time can be used to predict the average age of neutrophils upon their release from the bone marrow based on our mathematical model. We predict that the release point defining neutrophil mean age at release (Fig. 1) moved with a negative velocity (underwent a “left shift” in the pipeline), defined as the rate of change of the average age (in hours) of released neutrophils as a function of time (in hours), to a progressively earlier point in the pipeline during ECC (Fig. 4B). Based on our model fit to the data, the release point had a negative acceleration that was similar and approximately constant for each stage. Consequently, the average age at which neutrophils were released from the bone marrow during the weaning phase of ECC was reduced by ∼8.44 ± 2.20 h relative to the release age at the beginning of ECC sampling (Fig. 5).
The age-related profile of CD10 expression during late neutrophil maturation in the bone marrow is uncertain. Concurrent changes in total and CD10−/CD16low circulating neutrophil numbers obtained during ECC sampling were incorporated in our mathematical model to estimate the relationship between the proportion of mobilizable postmitotic neutrophils that are CD10− and cellular mean age. Under basal conditions, the estimated proportion of mobilizable postmitotic neutrophils that were CD10− was 2.2% (Fig. 4B). We predict that this proportion increases as the average age of neutrophils within the bone marrow postmitotic compartment declines (Fig. 4B). Our model predicts that CD10 expression is directly related to cellular mean age and is acquired at an approximately constant rate during the final hours of neutrophil maturation (Fig. 6). At baseline, under steady-state conditions, we estimate that 97.8 ± 0.4% of neutrophils released from the bone marrow are CD10+. By the weaning phase of ECC, we estimate that only 64.5 ± 1.8% of neutrophils leaving the bone marrow are CD10+, suggesting a rapid acquisition of CD10 expression in the final hours of neutrophil maturation.
The bone marrow postmitotic compartment contains a large reserve of functional, although not necessarily mature, neutrophils available for release in the circulation when demand is acutely increased (7, 8). Mobilization of neutrophils from the bone marrow is known to abbreviate total postmitotic transit time by 3–4 days (13, 19, 37); however, expansion of the circulating pool occurs within 1–2 h of exposure to a leukocytosis-inducing stimulus (21), indicating that more acute reductions in transit time may occur. We anticipated that such an acute reduction in transit time may be quantifiable by determining the previously unknown rate of change in postmitotic maturation time during active neutrophil recruitment. Neutrophil postmitotic transit time was evaluated in terms of mean cellular age by modeling circulating neutrophil numbers during ECC, a stimulus that induces bone marrow neutrophil recruitment (38, 41) in association with limited demargination (15, 16) and which permits repeated and frequent sampling. Our model predicts the rate of change in the average age at which neutrophils exit the bone marrow during active neutrophil recruitment. It thereby quantifies the acute acceleration and consequent abbreviation of postmitotic transit time by examining exit from the end of a temporal pipeline of bone marrow neutrophil production rather than quantifying the entire duration of this phase.
The narrow sampling interval of our study limits the potential for alterations in neutrophil intravascular survival to contribute significantly to growth in the circulating neutrophil pool. Because the sampling period is relatively short compared with the average lifespan of a neutrophil (i.e., ∼1.7 vs. 7 h, respectively), even if neutrophil death was reduced to zero during the sampling period, this should only increase the observed number of circulating neutrophils by <30% (vs. the ∼2.5-fold increase observed). This permits the assumption that increased bone marrow neutrophil production is the only significant source for the expanded circulating neutrophil pool during ECC. Morphologically mature neutrophils remain in the bone marrow for ∼2–3 days before their release (11), and there are sufficient postmitotic reserves to supply basal neutrophil production for at least 4–5 days (36, 43). The observed rapid increase in bone marrow neutrophil production can only be explained by an increased rate of release of these preformed neutrophils, given an anticipated delay of 3–4 days before increased proliferation within the mitotic pool would be expected to contribute (43). The overall 2.46 ± 0.42-fold increment in circulating neutrophil numbers observed was consistent with other studies investigating acute mobilization of neutrophils from the bone marrow reserve (12, 23, 33), suggesting that the response to such leukocytosis-inducing stimuli is of a relatively uniform magnitude. The progressive increase in relative size of the younger CD10−/CD16low subpopulation during net circulating neutrophil pool growth was consistent with age-dependent first in-first out kinetics for neutrophil release from the bone marrow.
Changes in phenotype during neutrophil lineage maturation have traditionally been evaluated relative to cell morphology as an indicator of maturity. However, as exemplified in previous studies (35), the CD10−/CD16low phenotype identifies greater numbers of phenotypically immature neutrophils than does cellular morphology alone. The temporal profile of phenotypic maturation may therefore provide a more detailed and accurate indicator of the rate at which mature phenotypic characteristics are acquired. By analyzing concurrent changes in total and CD10−/CD16low neutrophils in the circulating pool, our model predicts an age-related profile of CD10 expression during late neutrophil maturation that is independent of cell morphology. Assuming that CD10 expression is acquired at the same rate during steady-state neutrophil turnover and abbreviated bone marrow transit, we demonstrate that CD10 is acquired at an approximately constant rate with increasing neutrophil mean age. Moreover, phenotypic maturation appears to continue for the entire duration of postmitotic transit, since only a small proportion of circulating neutrophils are CD10− under basal conditions in this study and others (24, 30, 35). In contrast to morphological maturational changes that occur on a time scale of days, our results suggest that phenotypic changes occur at a more rapid rate, since acquisition of CD10 expression was evident on an hourly basis. Whether prematurely released CD10−/CD16low neutrophils can subsequently complete their maturation and acquire CD10 expression within the vascular space is unknown. However, mature neutrophils require at least 8 h for CD10 synthesis (31), a time frame outside the range of intraoperative sampling duration used here, and should not significantly affect our analysis.
The significant increase in CD10−/CD16low neutrophils during ECC is consistent with a substantial contribution from bone marrow neutrophil release to the observed growth in circulating neutrophil numbers. However, we cannot exclude a contribution from other sources. Although the pulmonary marginal neutrophil reserve is excluded from the circulation during ECC, demargination of neutrophils from other organ-specific vascular beds can contribute to expansion of the circulating neutrophil pool. Because ECC is associated with limited demargination (15, 16), it is likely that contributions from the marginal neutrophil pool are not likely to significantly confound our conclusions.
In conclusion, the results reported here comply with an age-related pipeline model of bone marrow neutrophil production through which cellular transit follows first in-first out kinetics and is acutely accelerated during active neutrophil recruitment. The proportion of CD10− neutrophils within the maturing bone marrow pool was directly related to the mean age of cells. This mathematical model may be applicable to in vivo analysis of acute changes in postmitotic transit time induced by other stimuli that can selectively mobilize the bone marrow neutrophil reserve.
This work was supported by the National Heart Foundation of Australia, The National Health and Medical Research Council of Australia, The Royal Australasian College of Surgeons, The Australasian Society of Cardiothoracic Surgeons Research Foundation, the James S. McDonnell Foundation 21st Century Research Awards/Studying Complex Systems, and a New South Wales Ministry for Science and Medical Research Infrastructure grant. M. P. Davenport is a Sylvia and Charles Viertel Senior Medical Research Fellow. D. P. Wilson is a University of New South Wales Vice Chancellor's Postdoctoral Fellow.
We thank flow cytometrist Leonie Gaudry for excellent technical assistance, Deborah Cromer for detailed assistance with scrutiny of our mathematical model and calculations, and Colin Chesterman and the Departments of Haematology and Flow Cytometry, Prince of Wales Hospital, Sydney, Australia, for use of equipment and resources invaluable to this project.
↵* Y. Orr and D. P. Wilson contributed equally to the experimental work.
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- Copyright © 2007 the American Physiological Society