Method of Assessing Infection Status

Abstract

The present invention relates to a method for assessing the infection status of a subject and in particular to a method for assessing the infection status of a subject by analysing the cellular and/or humoral composition of breastmilk from said subject. The invention has been developed primarily for use as a method for detecting infection in a breastfeeding mother and/or infant.

Claims

1-8. (canceled)

9. A method of treatment comprising: (a) measuring at least one immunological marker in a breastmilk sample from a breastfeeding mother, wherein the at least one immunological marker comprises a cellular and/or a humoral immunological marker; (b) detecting an elevated measure of the at least one immunological marker by comparing the measurement of the at least one marker to a reference measure of the marker in breastmilk of a healthy subject; (c) diagnosing an infection in the mother and/or an infant breastfed by the breastfeeding mother from the elevated measure of the at least one immunological marker; (d) treating the infection with an antibiotic; (e) measuring the at least one immunological marker in a breastmilk sample after the treating.

10. The method of claim 9 that further comprises: (f) detecting an elevated measure of the at least one immunological marker in step (e) by comparing the measurement of the at least one marker to a reference measure of the marker in breastmilk of a healthy subject; and (g) treating the infection with a different antibiotic from the antibiotic of step (d).

11. The method according to claim 10, wherein the cellular and/or humoral immunological marker comprises interleukin-2 (IL-2), interleukin-4 (IL-4), interleukin-6 (IL-6), interleukin-10 (IL-10), interleukin-17a (IL-17a), or interferon-gamma (IFN).

12. The method according to claim 10, wherein the cellular and/or humoral immunological marker comprises immunoglobulin M (IgM).

13. The method according to claim 10, wherein the cellular and/or humoral immunological marker comprises live CD45-positive immune cells.

14. The method according to claim 13, wherein the CD45-positive cells comprise one or more populations of T-cells.

15. The method according to claim 9, that comprises performing at least the measuring and detecting steps with a breastmilk sample from each breast.

16. A method of evaluating donated samples of breastmilk comprising: (a) measuring at least one immunological marker in breastmilk samples from at least one lactating mother, wherein the at least one immunological marker is selected from an immune cell (IC), a cytokine, and an immunoglobulin; (b) comparing the measurement of the at least one marker to a reference measure of the marker in breastmilk of a healthy subject; (c) (1) discarding, as unsuitable for heterologous consumption, breastmilk samples with an elevated measurement of the last least one immunological marker, and (2) selecting for banking or feeding to an infant that is not the child of the lactating mother (heterologous recipient), breastmilk samples free of the elevated measurement of the immunological marker.

17. The method according to claim 16, wherein the immunological marker comprises a cytokine.

18. The method according to claim 17, wherein the cytokine comprises interleukin-2 (IL-2), interleukin-4 (IL-4), interleukin-6 (IL-6), interleukin-10 (IL-10), interleukin-17a (IL-17a), or interferon-gamma (IFN).

19. The method according to claim 16, wherein the immunological marker comprises a live CD45-positive immune cell.

20. The method according to claim 19, wherein the CD45-positive cell comprises one or more populations of T-cells.

21. The method according to claim 16, wherein the immunological marker comprises an immunoglobulin.

22. The method according to claim 21, wherein the immunoglobulin comprises immunoglobulin M (IgM).

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Embodiments of the invention will now be described, by way of example only, with reference to the accompanying drawings in which:

[0064] FIG. 1 schematically illustrates the different cell types present in breastmilk.

[0065] FIG. 2 schematically illustrates the different processing steps employed to analyse the composition of breastmilk.

[0066] FIG. 3 shows the change in the proportion of immune cells (ICs) in response to infection; in this case the amount of ICs in breastmilk obtained during infection (mastitis) is compared to the amount of ICs in breastmilk obtained from the same woman before the infection.

[0067] FIG. 4 illustrates that the ICs identified respond to Antigen and phytohaemaglutinin (PHA) exposure in cell proliferation assays.

[0068] FIG. 5 shows, in a similar fashion to FIG. 3, the change in the proportion of immune cells (ICs) in response to infection; in this case the infection is a cold from which both the mother and the infant suffer. This figure also shows the IC profiles for breastmilk obtained from mothers before, during and after a cold which affected both the mother and the infant.

[0069] FIG. 6 and FIG. 7 show the IC profiles for breastmilk obtained from mothers before, during and after a cold which affected both the mother and the infant.

[0070] FIG. 8 shows the effect of an infant-only cold on the IC composition of the mother.

[0071] FIG. 9 illustrates the IC profiles of breastmilk from three mothers during late stages of lactation showing that no or only few ICs are detectable during late lactation in healthy subjects.

[0072] FIG. 10 compares the IC composition of a mother's colostrum with the IC composition of breastmilk obtained during week 2 of lactation.

[0073] FIG. 11 shows a further example of the comparison of the IC composition of a mother's colostrum with the IC composition of breastmilk obtained at a later stage illustrating the decline of ICs during the maturation of breastmilk.

[0074] FIG. 12 shows a further example similar to the example illustrated in FIG. 11.

[0075] FIG. 13 shows the proportion of ICs (in %) in relation to total cell numbers in breastmilk obtained from infected and healthy mothers as well as the proportion of ICs in colostrum obtained from a healthy mother.

[0076] FIG. 14 illustrates the IC composition of breastmilk obtained from infected as well as healthy subjects during early and late stages of lactation (healthy=bottom; infection=top).

[0077] FIG. 15 illustrates the IC composition of breastmilk by infection status.

[0078] FIG. 16 illustrates the proportion of viable immune cells obtained from infected as well as healthy subjects during early and late stages of lactation (healthy=red/bottom; infection=blue/top).

[0079] FIG. 17 illustrates total cell count in breastmilk by infection status.

[0080] FIG. 18 illustrates total cell count in breastmilk obtained from infected as well as healthy subjects during early and late stages of lactation (healthy=red/the curve moving upward around week 100; infection=blue/the curve moving downward around week 100).

[0081] FIG. 19 shows the total cell counts in breastmilk obtained from each participant when infected as well as when healthy.

[0082] FIG. 20 illustrates the amount of IgA detected in breastmilk from healthy as well as from infected subjects and in colostrum.

[0083] FIG. 21 shows the amounts of IgA detected in breastmilk obtained from infected as well as healthy subjects during early and late stages of lactation (healthy=red/bottom; infection=blue/top).

[0084] FIG. 22 illustrates the amount of IgG detected in breastmilk from healthy as well as from infected subjects and in colostrum.

[0085] FIG. 23 illustrates the amount of IgG detected in breastmilk from healthy as well as from infected subjects and in colostrum (healthy=red/the bottom curve at week 50; infection=blue/the top curve at week 50).

[0086] FIG. 24 illustrates the amount of IgM detected in breastmilk from healthy as well as from infected subjects and in colostrum.

[0087] FIG. 25 illustrates the amount of IgM detected in breastmilk from healthy as well as from infected subjects and in colostrum.

[0088] FIG. 26 shows the amount of IgM detected in breastmilk obtained from each participant when infected as well as when healthy.

[0089] FIG. 27 shows the Lactoferrin concentrations in breastmilk from healthy as well as from infected subjects and in colostrum.

[0090] FIG. 28 shows the Lactoferrin concentrations in breastmilk obtained from infected as well as healthy subjects during early and late stages of lactation (healthy=red/bottom; infection=blue/top).

[0091] FIG. 29 shows the Lactoferrin concentrations in breastmilk obtained from each participant when infected as well as when healthy.

[0092] FIG. 30 shows the cytokine levels in breastmilk in response to infection.

[0093] FIG. 31 illustrates different IC populations present in breastmilk in response to infection.

DETAILED DESCRIPTION OF THE INVENTION

[0094] The prior art indicates that colostrum has a high content of immune cells even when obtained from a healthy lactating subject. Further, it has been shown that colostrum contains high levels of secretory immunoglobulin A (IgA) and lactoferrin.

[0095] However, it has unexpectedly been found that the composition of mature breastmilk, especially with respect to the proportion of immune cells and immune factors, is not as variable as long thought. Rather than having a high variability, it has been found that mature human breastmilk contains no or very few immune cells under normal conditions. Specifically, it has been found that typically less than 2% of all cells contained in breastmilk from a healthy lactating subject are immune cells.

[0096] Further, it has been established that a change in infection status triggered by, for example a maternal infection, leads to a rapid increase in the immune cell content of mature breastmilk, which, in turn, returns close to baseline levels upon recovery. However, a residual elevation above baseline levels may be indicative of a previous infection.

[0097] In addition, it has surprisingly been found that the immune cell content of mature breastmilk remains at baseline levels throughout the entire lactation period in healthy individuals.

[0098] Similarly, it has been found that cytokine levels as well as the levels of other immune factors such as immunoglobulins change in response to infection.

[0099] The baseline ranges of immune cell levels and other immune factor levels in breastmilk have been examined in healthy mother/infant dyads. It has also been examined how these levels are influenced by infections of the mother/infant dyad.

[0100] As indicated above, the present invention relates to the surprising finding that the composition of mature breastmilk, especially with respect to the proportion of immunological markers such as immune cells, cytokines and immunoglobulins, is not as variable as long thought. Rather than having a high variability, it has been found that mature human breastmilk contains no or very few immune cells under normal conditions. Specifically, it has been found that typically less than 2% of all cells contained in breastmilk from a healthy lactating subject are immune cells.

[0101] Similarly, it has been found that cytokine levels as well as the levels of other immune factors such as immunoglobulins increase in response to infection.

[0102] While it has been confirmed that colostrum has a high content of immune cells even when obtained from a healthy lactating subject, it has also been established that infection triggers a rapid increase in the immune cell content of mature breastmilk. However, this rapid increase returns to near pre-infection baseline levels upon recovery. Specifically, it has been found that colostrum contains considerable numbers of immune cells (leukocytes13-70% out of total cells) and high levels of immunoglobulins and lactoferrin. Within the first 1-2 weeks postpartum, leukocyte numbers decreased significantly to the above-mentioned low baseline level in mature breastmilk of 0-2% (P<0.001).

[0103] Further, it has been surprisingly found that the immune cell content of mature breastmilk remains at near baseline levels throughout the entire lactation period in healthy individuals. Specifically, this baseline level was maintained throughout lactation unless the mother and/or her infant became infected. In the case of infection leukocyte levels significantly increased up to 94% out of total cells (P<0.001). Upon recovery from the infection, baseline values were restored.

[0104] As indicated above, the methods of the present invention allow for the assessment of a subject's infection status based on the immune cell (IC) composition of the subject's breastmilk. This will allow early diagnosis of infections of the breast but also of an infection that is systemic or that affects distal organs and/or tissues remote from the breast. Especially mastitis, either a fungal of bacterial infection, is a serious complication during breastfeeding and, if advanced, is severely debilitating condition. The early symptoms of mastitis, however, are very similar to the symptoms of the common flu and, as a result, mastitis is often only appropriately diagnosed once advanced. This often compromises continuous breastfeeding and can in instances lead to early termination of breastfeeding.

[0105] Referring to FIGS. 3, 4, 14 and Table 1 below, it is noteworthy that the IC content of mature breastmilk increases drastically in response to a mastitis. Interestingly, whereas the increase and overall amount of ICs in mature breastmilk is less pronounced in response to maternal cold (also see FIGS. 5 to 7). Again some cytokines are drastically increased in response to mastitis. Specifically, and as for example shown in FIG. 30, the levels of Interleukin-2 (IL2); Interleukin-4 (IL4); Interleukin-6 (IL6); Interleukin-10 (IL10); and Interleukin-17A (IL17A) as well as of Interferon-gamma (IFN-) and Tumor Necrosis Factor (TNF) increase in response to mastitis. While some of these cytokines are also increased in response to a maternal cold, the difference in cytokine levels when compared to the reference, baseline levels are again greater in response to mastitis.

[0106] Similarly, as can be seen in FIGS. 20 to 26, the concentrations of immunoglobulins such as for example IgA, IgG and IgM in breastmilk also change in response to infection.

[0107] As such, analysing the composition of breastmilk not only allows a general assessment of a change in the infection status, but it also allows for the differentiation between different infection types due to characteristic IC, cytokine and immunoglobulin amounts, as well as characteristic distribution of IC-types within the total IC population (see FIG. 31), cytokine or immunoglobulin profiles.

[0108] In practice the methods of the present invention cannot only assist in the diagnosis but can also serve as a further tool to assess the effectiveness of a treatment. For example, if a lactating mother is receiving treatment, relatively simple analysis of her breastmilk in accordance with the present invention will reveal whether the treatment is effective, i.e. whether a decline in ICs in the breastmilk and/or an appropriate change in the cytokine and/or immunoglobulin profiles can be observed. This is particularly important for infections, which can be caused by either bacterial of fungal pathogens. Fungal mastitis for example does not respond to antibiotic treatment which can easily be assessed by a method of the present invention.

[0109] Furthermore, an increasing number of bacterial strains display resistance to commonly used antibiotics. An early indication as to whether a chosen antibiotic is in fact effective to treat the particular bacterial pathogen can be obtained by analysing the composition of breastmilk in accordance with the present invention. Such analysis will allow the treating physician to change the antibiotic at an earlier stage than currently possible and without the need for the patient to go through an entire treatment regime with an ineffective antibiotic before switching to a more effective antibiotic.

[0110] Also as indicated above, the methods of the present invention can be utilised to assess a change in the infection status of a lactating subject in response to infection. Without limitation, a change in infection status in response to infections such as influenza, fungal or bacterial mastitis, urinary tract infection, vaginal infection, ear infection or gastrointestinal infection can be assessed by the methods of the present invention.

[0111] In addition to the above, it is common that breastmilk donated from lactating mothers is banked as a resource for families where breastmilk from the own mother is not available. However, even with the careful assessment of the donor and her infection status latent and/or asymptomatic infections may not become apparent. However, as has been shown by the present studies, even latent and/or asymptomatic infections can severely alter the IC composition and/or the cytokine and/or immunoglobulin profiles of breastmilk.

[0112] In particular, it has been shown (FIGS. 13, 20, 22, 24 and 30) that the amount of ICs, as well as of cytokines and/or immunoglobulins increases in response to infection. However, as the recipients of the donated and banked breastmilk are generally not closely related to the donor, the immunological load of breastmilk obtained from an infected donor may lead to an undesirable immune response by the recipient. The methods of the present invention provide for convenient screening of breastmilk donations for their suitability for banking and future heterologous consumption.

Materials & Methods

Breastmilk Sample Collection

[0113] A longitudinal study was designed and approved by the Human Research Ethics Committee of The University of Western Australia. Written informed consent was obtained from all participants who included volunteering breastfeeding mothers of a broad lactation spectrum of 1 to 21 months, recruited prior or during an infection. The study included collection of a breastmilk sample of 10-50 ml principally on 2-3 different time points per participant: prior, during and after an infection, with the first time point missing in five of the participants. Three of the participants underwent infection incidents on two occasions during the study period, for both of which breastmilk samples were acquired. In these cases, the sampling sequence was: prior, during and after infection 1, during and after infection 2. One of the participants suffered repeated infections during the study period (cold, mastitis, urinary tract infection and cold) during all of which breastmilk samples were acquired. Finally, one of the participants never experienced an infection during the study period and in this case one control sample was obtained from this individual.

[0114] The mothers provided detailed description of the symptoms of the infections, which were general or respiratory viral or bacterial infections of the mother and/or the breastfed infant, such as influenza (sore throat, fever, blocked/runny nose, coughing, sneezing), mastitis, nipple thrush, gastrointestinal tract infection (nausea, diarrhoea, vomiting, headache), and urinary tract infection (frequent feeling and/or need to urinate, dysuria, hematuria, malaise).

[0115] Breastmilk samples were aseptically collected in the morning within 30 min of a feed using a Medela Symphony or Swing electric breast pump (Medela AG, Switzerland) and kept in sterile polypropylene vials at approximately 20 C. during transportation to the laboratory. Cellular analyses were conducted in the freshly expressed samples within 1-2 hours of breastmilk expression, while all other analyses were done in frozen (80 C.) sample aliquots within five months of sample collection as described below.

Subjects

[0116] All participants completed the study's questionnaire. Socioeconomic stratum, maternal age range, mean maternal age, ethnic background, employment before delivery, infant delivery, mean and range of infant birth weight, mean and range of gestational age, number of male and female infants, Apgar scores, first- or second-born.

Cellular Analyses

[0117] Freshly expressed breastmilk samples were transported to the laboratory at 20 C. and aliquoted appropriately within 1-2 hours of expression. A 1-5 ml aliquot was stored at 80 C. for biochemical analyses, while the bulk of the sample was diluted with equal volume of sterile phosphate-buffered saline (PBS, pH 7.4, Gibco, USA) and centrifuged at 2,000 rpm 20 min at 20 C. The fat layer was removed with a pipette and the liquid part was stored separately at 80 C. for biochemical analyses. The cell pellet was washed three times in PBS and was finally resuspended in 7% Fetal Bovine Serum (FBS, Certified, Invitrogen, USA) in PBS.

[0118] First, the total cellular content and cell viability of each sample was determined with a Neubauer hemocytometer by Trypan Blue exclusion. For FACS analyses, the cell suspension was distributed in vials and the cells were incubated for 1 hour at 4 C. with mouse anti-human CD45 conjugated to fluorescein isothiocyanate (FITC) (1:11, Miltenyi Biotec, Germany; 1:50, Becton Dickinson, San Diego, USA) or phycoerythrin (PE) (1:11, Miltenyi Biotec, Germany). Negative control samples were incubated with the respective isotype control conjugate obtained from the same suppliers. Subsequently, the cells were washed twice in 7% FBS in PBS and incubated for 30 min at 4 C. with live/dead fixable far-red dead cell stain (Invitrogen, USA) as per manufacturer's instructions. This step enabled differentiation between dead and live cells, of which only the latter were taken into account in the analyses. After incubation, the cells were washed twice in 7% FBS in PBS, resuspended in 1% paraformaldehyde/0.7% sucrose solution in PBS and were either immediately analysed or stored at 4 C. for up to 12 hours prior to analysis. FACS analysis was done with a FACS Calibur Flow Cytometer (Becton Dickinson, N.J., USA) and further data analyses were done using the FlowJo software. A completely unstained sample was always prepared in which propidium iodide (Sigma-Aldrich) was added at 1 g/ml after fixation and immediately prior to FACS analysis to check for the cellular uniformity of each cell suspension. In cases where this sample contained non-cell particles (such as cellular fragments or fat globules), propidium iodide was added in all other samples (stained and controls) of the same cell suspension and only the cellular component was taken into account in the analyses.

[0119] Part of the cell suspension obtained after centrifugation was immediately fixed in 1% paraformaldehyde/0.7% sucrose solution in PBS for immunofluorescence staining. Cytospins of the cell suspensions on glass slides were generated by centrifuging at 600 rpm for 4 min. The same antibodies used for flow cytometry were also used for immunofluorescence staining and were applied on the cytospins for 1 hour at room temperature under humid conditions. Appropriate controls were also used. The cytospins were then washed in PBS, incubated with DAPI (1:100, Dako) for 15 min, and after a final wash they were mounted in fluorescence mounting medium (Dako) and observed using an Olympus TH4-200 inverted microscope.

Biochemical Analyses

[0120] For all biochemical analyses, defatted acellular breastmilk sample aliquots stored at 80 C. were used. Cytokines were determined using a multiplex kit (Millipore) for 20 different cytokines, chemokines and growth factors, following the manufacturer's instructions. In short, the stored breastmilk samples were thawed to room temperature and 50 l of sample per well was added in a 96-well filter-bottomed plate. Each sample was assayed in duplicate. After addition of the beads and incubation on a plate shaker overnight at 4 C., the wells were vacuum-washed with buffer and antibody conjugate was added for a 1-hour incubation on a plate shaker. An additional incubation with streptavidin-phycoerythrin was done on the plate shaker, which was followed by a vacuum-wash and addition of 100 l of sheath fluid. The plate was read in a Luminex 200 Multiplex Analyser (Invitrogen). A five-parameter logistic model was used to convert the bead fluorescence intensities to analyte concentrations.

[0121] Secretory IgA (sIgA), IgG and IgM were analysed by enzyme-linked sandwich immunoassay. The 96-well filter-bottomed plates were coated with 250 l/well of rabbit anti-human sIgA (1:2000 in PBS, Gibco, USA) or mouse anti-human IgG (1:2000 in PBS, Gibco, USA) or mouse anti-human IgM (1:2000 in PBS, Gibco, USA) overnight at 4 C. Subsequently, the antibody solution was carefully discarded and 300 l of blocking solution (5% w/v carnation soy powder in 0.05% Tween-20 in PBS) was added to each well for a 30-min incubation at room temperature. The stored breastmilk samples were thawed to room temperature and diluted in 0.05% Tween-20 in PBS 2000 times. The microtitre plate was then washed three times with washing buffer (0.05% Tween-20 in PBS) and 200 l/well of the standards, samples or controls were added to the plate, which was then covered with a plate sealer for a 60-minute incubation at 37 C. The plate was then washed three times with washing buffer before addition of 200 l/well of secondary antibody and incubation for 30 min at room temperature (1:1000 rabbit anti-human sIgA conjugated to horseradish peroxidase; or 1:1000 mouse anti-human IgG conjugated to biotin; or 1:1000 mouse anti-human IgM conjugated to biotin). All secondary antibodies were diluted in 0.05% Tween-20 in PBS containing 1 mg/ml BSA to prevent non-specific absorption. In the IgG and IgM assays, incubation with the secondary antibody was followed by three washes and subsequent incubation with 200 l/well of an anti-biotin-horseradish peroxidise antibody (1:1000) for 30 min at room temperature. After incubation with the secondary antibody in the sIgA assay and with the tertiary antibody in the IgG and IgM assays, the plate was washed six times with washing buffer and then rinsed with deionised water before addition of 200 l/well of the colour reagent (6% hydrogen peroxide, 1% ABTS). The colour reaction was stopped after 30 min by addition of 100 l/well of 3M sulfuric acid. The plated was read at 405 nm using a plate reader.

Statistical Analyses

[0122] Statistical analyses were performed in R 2.9.0 1 (R Foundation for Statistical Computing, Vienna, Austria, 2009) using the base packages and libraries lattice (Sarkar D., In. R package version 0.17-22 ed, 2009), nlme Pinheiro J. et al. In. R package version 3.1-89 ed, 2008) and multcomp (Hothorn T. et al. 2008). Results are presented as meanSEM unless otherwise specified, and P<0.05 was considered significant. Linear mixed effects models were used to determine which of the response variables [leukocyte levels (% of total cells), leukocyte levels (per mL of breastmilk), total and viable cell levels (per mL breastmilk), cell viability (% viable cells of total cells), sIgA, IgG, IgM and lactoferrin] were affected by breastmilk type, lactation stage, infection status of the mother/infant dyad, and breastfeeding status (exclusive versus non-exclusive). All models included a grouping factor of dyad and a random effect of different baseline levels for each dyad. Where infection status was included in a model, healthy was considered to be the reference level. To determine whether data transformation was required, comparisons were made between raw data, square root-transformed data and natural log-transformed data models. After fitting the univariate model for each predictor, diagnostic plots (fitted values versus standardised residuals; qq-plot of residuals) were examined. In cases where a transformation was obviously superior, this was used for all covariate models. Due to the measured zeroes obtained for leukocyte levels (% and per mL breastmilk) of some samples, these variables were transformed using the additive constant 0.5 for both the square root and the log transformations (Yamamura K. 1999). Differences between colostrum, healthy and infection samples were tested for with a three-level categorical predictor of breastmilk type. Differences between healthy samples and each of the infection types were tested using a five-level factor (healthy, breast, baby, cold, and other), with the colostrum samples omitted. Differences between pre- and post-infection healthy samples were tested where data was available (n=7) by classifying healthy as a two level factor (pre and post). To determine whether there were interactions between the infection status of the dyad and either lactation stage (age in weeks) or exclusive breastfeeding (yes/no) in mature breastmilk, interaction models were considered for each of these covariates separately. Infection status was considered as a two level factor (heathy and infection). Models were selected using backwards stepwise methods, starting with the main effects+interaction model. Where the interaction was significant, all main effects were retained in the model.

[0123] For the lactation stage model, analysis was restricted to records where the baby was under 60 weeks of age (N=46 records, for 15 participants. The effect of viral antigens and PHA on proliferation rate in leukocyte cultures generated from two samples of mastitic breastmilk was also assessed using linear mixed effects models. Separate models were used for each response variable, with replicate as the grouping variable and a random effect of different baseline effects per replicate. Tukey's HSD (honestly significant difference) test was used to test all pairwise comparisons between the three treatments (control, viral antigen, PHA). Multivariate patterns in the immune markers (sIgA, IgG, IgM, lactoferrin) and three cellular measures (total cell, leukocyte number and percentage of leukocytes) were investigated analytically using singular value decomposition principal components analysis on scaled and centred data and graphically using biplots. This enabled comparisons between the conditions that were seen infrequently.

Results

[0124] Healthy Mother/Infant Dyads have a Low Baseline Level of Leukocytes in Breastmilk

[0125] FACS quantification of CD45 protein expression was done by an analytic gating strategy that excluded interference by dead/dying cells and/or fat globules. Although colostrum always contained considerable levels of leukocytes (13.2-70.4% leukocytes of total breastmilk cells; 32,175-784,080 viable leukocytes/mL colostrum), these rapidly decreased towards the end of the first week postpartum to reach a baseline level in transitional breastmilk (0-1.7% leukocytes of total breastmilk cells; 0-3,450 viable leukocytes/mL breastmilk) and mature breastmilk (0-1.5% leukocytes of total breastmilk cells; 0-1,151 viable leukocytes/mL breastmilk) when both the breastfeeding mother and infant were healthy (Tables 2 and 3). The low baseline level of mature breastmilk leukocytes under healthy conditions was maintained even at late lactation stages (year 2-4 postpartum) (Table 2) and was found to fluctuate within certain limits (0-2% leukocytes of total breastmilk cells) both between and within individuals.

Infections of the Mother/Infant Dyad Stimulate a Leukocyte Response in Breastmilk

[0126] Infections of the breast, other organs or general maternal infections all stimulated a leukocyte response in breastmilk that ranged from 0.7% (sore breast) to 93.6% (mastitis) leukocytes of total breastmilk cells (P<0.001) (Tables 2 and 3). Severe breast infections such as mastitis stimulated a greater leukocyte response (P<0.001). The effect of systemic and other organ infections on breastmilk leukocyte levels was in agreement with the observed effect of mastitis of one breast on breastmilk leukocyte levels of the other (mastitis-free) breast. A small increase in breastmilk leukocyte levels was also observed when only the infant had an infection, while the mother was asymptomatic (P=0.046). No difference was seen between pre- and post-infection baseline leukocyte levels (P=0.48). Importantly, the leukocyte response to infection and recovery, as well as transition from colostrum to transitional breastmilk was rapid. In contrast to leukocytes, breastmilk total cell and viable cell levels did not significantly vary by infection status or breastmilk type (Table 3). However, the number of total cells significantly increased (P=0.002) with lactation stage (Table 2). The latter did not significantly influence % cell viability (P=0.09) (Table 2). Breastmilk leukocyte levels did not significantly change after week 1 postpartum as long as the dyad was healthy (P=0.36). Leukocytes in breastmilk from women with mastitis contained a number of different immune cells such as monocytes, macrophages, dendritic cells, T helper cells, cytotoxic T cells, natural killer cells, and a small population of B lymphocytes. Infection-stimulated leukocytes contained activated cell subsets that responded to viral antigens and PHA in culture with increased proliferation rate and altered expression of IL-6, IL-17A, IFN- and TNF-.

Infections of the Mother/Infant Dyad Stimulate a Humoral Immune Response in Breastmilk

[0127] In addition to breastmilk the above-described leukocyte response to maternal/infant infection, a often significant humoral immune response was also observed. sIgA was higher in colostrum compared to mature breastmilk from healthy dyads (P<0.001) (FIGS. 20 to 29; Tables 2 and 3). In mature breastmilk, sIgA concentration increased only during infection of the mother and/or the infant (P=0.034) (FIGS. 20 to 29; Tables 2 and 3), and this increase was stronger in organ-specific infections (Table 4). IgG concentration was generally low (2.8-22.9 g/mL) (Table 2), with no marked difference between colostrum and mature breastmilk from healthy dyads (P=0.71), and marginally increased with maternal or infant infection (P=0.048) (FIGS. 20 to 29; Tables 2 and 3). No difference was seen between pre- and post-infection baseline sIgA and IgG levels (P=0.37 and P=0.66, respectively). In few subjects, sIgA/IgG concentration was higher in the post-recovery sample, suggesting a potentially delayed response to infection. Infant age had a profound effect on breastmilk sIgA (P<0.001), IgG (P=0.045) and lactoferrin (P=0.008) concentrations (Table 2). In the dataset of healthy dyads, an initial sIgA decrease from colostrum to mature breastmilk up to around week 25 and a plateau until week 50 was followed by an increase in later lactation. IgG concentration was constant for the first 60 weeks postpartum, but increased in later lactation (Table 2). Lactoferrin concentration initially decreased up to around week 25 and then increased as lactation progressed (Table 2). Involution seemed to influence the biochemical and total cellular, but not the leukocyte levels of breastmilk, with marked increases in these components (Table 2).

Breastmilk Immune Response Differs Between Infection Types

[0128] Breastmilk leukocyte levels were significantly higher for all infection types compared to the healthy baseline, with the weakest response seen for infant infections (P=0.046), and the strongest response for breast infections (P<0.001), particularly mastitis (Table 4). A decrease in % cell viability with infection was observed only for maternal colds (P=0.025). Total breastmilk cell levels increased during breast-related infections, being associated with a stronger leukocyte response in mastitis compared to less severe breast infections (Table 4). Principal component analysis (PCA) demonstrated distinctive response patterns for specific sample types. Mastitis (N=5) clustered separately from other infections, being strongly associated with breastmilk leukocyte levels. Weaning (N=1) and menstruation (N=1) were separate from the rest of the healthy dataset. Colostrum also tended to cluster differently from the healthy dataset.

Non-Exclusive Breastfeeding is Associated with Lower Baseline Breastmilk Leukocyte Levels

[0129] Breastfeeding status significantly related to breastmilk leukocyte levels. Under healthy conditions, the baseline breastmilk leukocyte levels was lower in non-exclusively breastfed infants (P=0.024), the majority of whom received breastmilk with no detectable leukocytes. The infection response in both exclusive and non-exclusive breastfeeding dyads was such that similar leukocyte levels were seen during infection.

[0130] In addition to the description of the results provided above and in the Figures, the results obtained by way of the above-described cellular and biochemical analysis are summarised in Tables 1 to 5 below.

TABLE-US-00001 TABLE 1 Total viable Lactation stage Exclusive IgA* IgG* IgM* Lact* ICs cells/ml Cell viability Viable ICs/ml Dyad Date (weeks) Infection status Milk status breast feeding (g/ml) (g/ml) (g/ml) (g/l) (%) of milk# (%) of milk D 1 17 Sep. 2010 Colostrum Colostrum Colostrum yes 1428 7.3 16.2 7.5 NA 2,250,000 96.6 NA 1 Oct. 2010 3 healthy transition milk yes 131 2.8 8.3 2.9 0 113,492 97.3 0 13 Oct. 2011 15 baby mild cold mature milk yes 652 4.8 12.4 2.0 1.11 265,000 96.4 2,942 11 Feb. 2011 19 healthy mature milk yes 257 4.6 6.5 1.9 0 229,729 100.0 0 D 2 15/10 Colostrum Colostrum Colostrum yes 2178 6.9 19.1 7.7 13.2 243,750 100.0 32,175 25 Oct. 2010 2 healthy transition milk yes 670 9.7 14.1 4.2 0.12 883,333 97.2 1,060 6 Dec. 2010 7 sore breast mature milk yes 36 10.0 8.3 3.1 0.72 333,333 96.8 2,400 27 Dec. 2010 10 healthy mature milk yes 534 6.4 10.6 2.5 0.07 228,395 100.0 160 D 3 5 Nov. 2010 Colostrum Colostrum Colostrum yes 2136 12.2 24.8 7.7 39.6 1,980,000 94.3 784,080 9 Nov. 2011 1 (day 7) healthy transition milk yes 1096 6.6 15.4 4.5 1.65 200,758 97.2 3,313 9 Dec. 2010 6 Cold, sore mature milk yes 848 6.6 9.3 3.4 22.1 50,000 93.3 11,050 throat 13 Jan. 2011 11 blocked duct mature milk yes 594 9.0 4.5 2.9 12.5 265,000 100.0 33,125 18 Jan. 2011 12 mastitis mature milk yes 696 11.7 7.8 3.2 64.9 696,070 91.0 451,749 D 4 1 Oct. 2010 4 cold mature milk yes 417 13.0 30.0 3.2 82.3 194,545 87.7 160,111 29 Nov. 2010 13 healthy mature milk yes 313 7.4 11.6 3.7 1.52 40,000 96.3 608 D 5 5 Oct. 2010 15 cold mature milk yes 1711 10.1 11.1 3.6 33.9 321,918 96.9 109,130 22 Oct. 2010 17 mother gastro mature milk yes 1312 9.8 15.4 3.7 1.36 159,091 99 2,164 17 Nov. 2010 21 minor cold mature milk yes 1049 8.7 10.1 3.5 3.19 115,278 97.6 3,677 18 Nov. 2010 21 healthy mature milk yes 446 6.7 9.5 3.1 0.41 250,000 96.8 1,025 10 Jan. 2011 28 cold mature milk no 1509 14.4 13.2 2.9 15.1 140,000 93.3 21,140 D 6 11 Sep. 2010 10 healthy mature milk yes 1276 12.4 14.9 2.9 0.45 255,769 96.3 1,151 17 Sep. 2010 11 cold mature milk yes 1401 10.7 19.8 3.7 28.8 676,191 94.0 194,743 1 Oct. 2010 13 healthy mature milk yes 960 10.8 9.8 2.3 0.06 588,542 100.0 353 D 7 17 Sep. 2010 26 healthy mature milk yes 496 4.0 11.1 1.3 0 433,333 98.1 0 27 Oct. 2010 32 baby fever mature milk yes 611 7.4 14.4 2.1 1.08 98,633 97.1 1,065 17 Nov. 2010 35 healthy mature milk yes 638 7.4 4.2 2.0 0.07 252,500 98.1 177 27 Dec. 2010 40 sore breast mature milk yes 714 8.8 19.3 1.2 shift 437,500 100.0 NA 18 Jan. 2011 43 healthy mature milk no 401 5.0 8.8 1.2 0.1 706,667 98.1 707 21 Mar.2011 52 mastitis mature milk no 946 25.9 18.2 2.4 71.7 1,059,740 96.2 759,834 D 8 17 Sep. 2010 28 healthy mature milk no 1350 16.4 23.7 4.0 0 183,871 93.4 0 25 Nov. 2010 38 cold mature milk no 789 7.6 14.4 3.6 3 1,000,000 98.8 30,000 18 Jan. 2011 45 healthy mature milk no 1044 16.1 23.3 3.9 0.08 1,066,667 98.5 853 D 9 14 Oct. 2010 27 healthy mature milk no 638 6.2 14.7 2.0 1.09 97,500 99.2 1,063 2 Nov. 2010 30 cold mature milk no 696 5.6 12.6 1.6 32.9 56,190 100.0 18,487 23 Nov. 2010 33 mastitis mature milk no 1230 14.2 21.8 3.3 93.6 504,951 96.2 472,634 left 23 Nov. 2010 33 ok mature milk no 831 6.6 16.0 2.1 12.9 37,000 94.9 4,773 right 8 Dec. 2010 35 recovering mature milk no 1312 8.8 20.6 3.1 43.5 58,696 90.0 25,533 left mastitis D 10 9 Nov. 2010 49 healthy mature milk no 137 7.0 5.2 3.5 0 358,974 100.0 0 16 Dec. 2010 54 measles mature milk no 173 6.9 5.9 2.9 2.13 60,714 97.1 1,293 18 Jan. 2011 59 healthy mature milk no 244 6.0 4.9 3.1 0 102,778 97.4 0 D 11 11 Jan. 2011 64 recovering mature milk no 1179 8.2 6.8 3.1 2.61 174,603 99.1 4,557 vaginal thrush 13 Jan. 2011 64 healthy mature milk no 743 4.0 2.9 2.2 0 1,075,000 97.8 0 D 12 4 Nov. 2010 88 healthy mature milk no 1243 7.4 8.1 4.5 0.06 480,769 97.1 288 10 Jan. 2011 98 gastro mature milk no 1657 9.4 10.5 4.7 4.27 1,166,667 98.6 49,817 18 Jan. 2011 99 healthy mature milk no 1240 12.7 13.0 3.7 0 3,357,143 98.3 0 D 13 6 Dec. 2010 Colostrum Colostrum Colostrum yes 2008 7.1 56.1 7.4 70.4 110,000 88.7 77,440 9 Dec. 2010 1 (day 6) healthy transition milk yes 1044 7.0 24.8 5.2 0.59 406,667 95.3 2,399 16 Dec. 2010 2 (day 13) cold transition milk yes 922 13.0 10.2 4.3 18.8 183,333 94.3 34,467 27 Jan. 2011 8 mastitis mature milk yes 1418 17.1 10.7 3.7 90.5 2,867,383 98.0 2,594,982 D 14 13 Jan. 2011 Colostrum Colostrum Colostrum yes 1883 5.3 37.0 6.3 38.4 577,778 96.3 221,867 20 Jan. 2011 2 healthy transition milk yes 812 6.8 29.8 4.2 0.96 359,375 100.0 3,450 D 15 13 Jan. 2011 97 healthy mature milk no 976 4.6 7.1 3.3 0 633,333 100.0 0 D 16 20 Oct. 2010 52 cold mature milk no 506 2.3 10.8 2.1 2.87 102,326 97.8 2,937 9 Nov. 2010 55 healthy mature milk no 621 4.0 13.0 2.3 0 75,926 100 0 D 17 10 Jan. 2011 74 cold mature milk no 2002 8.5 31.1 4.0 4.74 420,000 97.7 19,908 11 Feb. 2011 78 eye infection mature milk no 2184 11.0 48.8 4.6 12.5 1,708,333 97.6 213,542 D 18 10 Jan. 2011 146 cold mature milk no 1906 13.4 23.5 5.6 6.36 49,166 96.7 3,127 19 Jan. 2011 147 ear infection mature milk no 1888 11.4 22.1 4.6 10.8 126,786 95.9 13,693 14 Feb. 2011 152 healthy - weaning milk no 1761 22.9 100.4 6.2 0 2,600,000 96.3 0 WEANING D 19F 19 Jan. 2011 189 healthy - mature milk no 1991 17.8 23.1 5.8 0.55 2,500,000 100.0 13,750 PERIODS D 20 27 Jan. 2011 57 mastitis mature milk no 722 12.7 5.9 3.2 58.9 400,000 96.3 235,600 9 Sep. 2011 59 healthy mature milk no 485 10.4 4.3 3.1 0 177,778 96.9 0 D 21 15 Mar. 2011 3 healthy transition milk yes 275 5.3 8.2 2.1 0.67 203,704 91.7 1,365 *Average

TABLE-US-00002 TABLE 2 Total cell, leukocyte, immunoglobulin (sIgA, IgG, IgM) and lactoferrin contents of human breastmilk at different stages of lactation, and responses to infections of the mother/infant dyad. Transitional Months Months Months Months Late Involution Breastmilk Health Colostrum.sup.a milk.sup.b 1-3 4-6 7-9 10-12 Year 2 lactation.sup.c milk.sup.d component status n = 5h n = 6h, 1i n = 2h, 7i n = 4h, 4i n = 4h, 6i n = 2h, 2i n = 6h, 7i n = 3h, 3i n = 1 Total cells.sup.e/ Healthy 110,000- 113,492- 228,395- 40,000- 97,500- 706,667- 75,926- 633,333- 2,600,000 mL milk 2,250,000 883,333 255,769 588,542 433,333 1,066,667 1,075,000 3,357,143 Infection 183,333 50,000- 115,278- 37,000- 437,500- 60,714- 49,166- 2,867,383 321,918 504,951 1,000,000 1,708,333 1,166,667 % Leukocytes Healthy 13.2-70.4 0.0-1.65 0.07-0.45 0.0-1.52 0.0-1.09 0.08-0.1 0.0-0.06 0.0-0.55 0.0 Infection 18.8 0.72-90.5 1.1-33.9 1.08-93.6 >3 2.13-71.7 4.27-10.8 Leukocytes.sup.e/ Healthy 32,175- 0-3,450 160- 0-1,025 0-1,063 707-853 0-288 0-13,750 0 mL milk 784,080 1,151 Infection 34,467 2,400- 2,164- 1,065- >30,000 1,293- 3,127- 2,594,982 109,130 472,634 59,834 49,817 sIgA (g/mL) Healthy 1428-2178 131-1096 534-1276 257-960 496-1350 401-1044 137-1243 976-1991 1761 Infection 922 36-1418 652-1711 611-1509 714-789 173-2002 1657-1906 IgG (g/mL) Healthy 5.3-12.2 2.8-9.7 6.4-12.4 4.6-10.8 4.0-16.4 5.0-16.1 4.0-10.4 4.6-17.8 22.9 Infection 13.0 6.6-17.1 4.8-10.1 5.6-14.4 7.6-8.8 2.3-25.9 9.4-13.4 IgM (g/mL) Healthy 16.2-56.1 8.2-29.8 10.6-14.9 6.5-11.6 4.2-23.7 8.8-23.3 2.9-13.0 7.1-23.1 100.4 Infection 10.2 4.5-19.8 10.1-15.4 12.6-21.8 14.4-19.3 5.9-31.1 10.5-23.5 Lactoferrin Healthy 6.3-7.7 2.1-5.2 2.5-2.9 1.9-3.7 1.3-4.0 1.2-3.9 2.3-4.5 3.3-5.8 6.2 (g/L) Infection 4.3 2.9-3.7 2.0-3.7 1.6-3.3 1.2-3.6 2.1-4.6 4.6-5.6 .sup.aColostrum was defined as breastmilk collected between days 0-4 postpartum; .sup.bTransitional milk was defined as breastmilk collected between day 5 and week 3 postpartum; .sup.cLate lactation was defined as the period between months 25 and 48 postpartum; .sup.dInvolution milk was collected 5 days after baby weaned off breastmilk (month 38 postpartum); .sup.eTotal cells/mL and leukocytes/mL refer to total viable cells/mL and viable leukocytes/mL, respectively. (h = healthy and i = infection)

TABLE-US-00003 TABLE 3 Statistical comparison of the levels of measured variables between milk samples grouped by type (colostrum versus mature breastmilk from healthy mother/infant dyads) or health status of the mother/infant dyad (healthy versus under infection), taking into account individual differences. Healthy Under infection (mature milk) (mature milk) Colostrum Response Transform Value Diff P value Diff P value total cell content log.sub.e 12.8 0.3 0.271 0.5 0.326 (/mL milk) viable cell content log.sub.e 12.8 0.3 0.253 0.5 0.353 (/mL milk) leukocyte content.sup.a log.sub.e(x + 0.5) 3.8 5.9 <0.001 7.2 <0.001 (/mL milk) % total cell viability none 97.8 1.5 0.043 2.6 0.056 (of total cells) % leukocytes.sup.a log.sub.e(x + 0.5) 0.25 2.5 <0.001 3.6 <0.001 (of total cells) sIgA (g/mL) none 860.7 169.9 0.034 1288.5 <0.001 IgG (g/mL) log.sub.e 2.01 0.22 0.048 0.07 0.710 IgM (g/mL) log.sub.e 2.49 0.064 0.606 0.864 <0.001 Lactoferrin (g/L) none 3.41 0.08 0.658 3.88 <0.001 .sup.aFor leukocyte content and percentage, the data was transformed using the additive constant 0.5 for both the square root and the log transformations due to the zeroes in the data (Yamamura K. 1999) P values compare each group with the Healthy (mature milk) group.

TABLE-US-00004 TABLE 4 Effects of different types of infection on breastmilk cellular and biochemical composition. Other Healthy Infant only Breast-related Cold infections Response Value Diff P value Diff P value Diff P value Diff P value total cell content 12.8 0.9 0.127 0.6 0.133 0.6 0.094 0.4 0.348 (/mL milk) (log.sub.e) viable cell 12.8 0.9 0.123 0.6 0.143 0.6 0.085 0.4 0.345 content (/mL milk) (log.sub.e) leukocyte 3.7 4.3 0.046 6.7 <0.001 6.1 <0.001 5.9 0.0004 content.sup.a (/mL milk) (log.sub.e(x + 0.5)) % total cell 97.8 0.9 0.571 1.7 0.093 2.1 0.025 0.2 0.834 viability (of total cells) % leukocytes.sup.a 0.3 1.1 0.064 3.2 <0.001 2.8 <0.001 2.1 <0.001 (of total cells) (log.sub.e(x + 0.5)) sIgA 858 88 0.632 174 0.155 144 0.197 302 0.042 IgG (log.sub.e) 2.02 0.07 0.738 0.58 0.0003 0.04 0.758 0.12 0.481 IgM (log.sub.e) 2.49 0.21 0.474 0.05 0.796 0.02 0.913 0.16 0.493 lactoferrin 3.4 0.2 0.638 0.1 0.787 0.1 0.654 0.1 0.766 Groups include: infant only infection (N = 3), breast-related infection (N = 9), cold (N = 12), other organ-specific infections (eye, ear, vaginal, urinary tract and gastrointestinal infections; N = 6), and no infection/healthy (N = 28). .sup.aFor leukocyte content and percentage, the data was transformed using the additive constant 0.5 for both the square root and the log transformations due to the zeroes obtained (Yamamura K. 1999) P values compare infection groups with the Healthy group.

TABLE-US-00005 TABLE 5 Dyad D 22 D 23 D 24 D 25 D 26 D 27 D 28 D 29 Infection status mother-mastitis- mother recurring recovering infant-only nipple/vaginal mother/baby infant-only from mother/baby mother mother/baby fever thrush healthy cold mastitis healthy cold healthy CD45+ [%] 9.78 44.2 1.82 2.27 30.86 1.84 3.18 0.3 CD45+/CD45RO+ [%] 8.93 0.28 CD45+/CD45RO [%] 0.85 0.02 CD45+/CD14+ [%] 4.17 20.06 0.15 CD45+/CD14 [%] 5.57 10.8 0.15 CD45/CD14+high [%] 18.7 60.8 89.3 CD45/CD14+low [%] 70.2 total CD14+ [%] 93.07 80.86 89.45 CD45+/CD15+high[%] 1.01 0.37 0.75 6.06 CD45+/CD15 [%] 8.72 1.45 1.52 24.8 CD45/CD15+high [%] 1.75 1.99 2.97 CD45/CD15+low [%] 8.79 CD15+high total [%] 2.76 CD15+total [%] 11.55 3.32 2.73 9.03 CD45+/HLADR+ [%] 5.88 CD45+/HLADRlow [%] 3.86 CD45/HLADR+ [%] 67.3 HLA+ total [%] 73.18 CD45+/CD3+/CD4+ 2.014 14.01 0.41 0.203619 5.9444 0.34 0.8 0.0486 (t-helper) [%] CD45+/CD3+ [%] 2.61 18.1 0.79 0.35 8.96 0.61 1.61 0.094 total CD3+ 2.61 18.1 0.79 0.35 8.96 0.61 1.61 0.0936 (total T-cells) [%] CD45+/CD3 [%] 7.17 26.1 1.03 1.92 21.84 1.23 1.57 0.2064 CD45+/CD4+ [%] 4.14 22.8 0.45 1.05 7.71 0.47 0.84 0.064 total CD4+ [%] 4.14 22.8 0.45 1.048 7.71 0.75 1.03 0.064 CD45+/CD4 [%] 5.64 21.4 1.37 1.22 23.09 1.37 2.34 0.236 CD45+/CD3+/CD8+ 0.908 4.95 0.195 0.088757 2.68 0.25 0.86178 0.0405 (t-cytotoxic) [%] CD45+/CD8+ [%] 0.85 6.1 0.24 0.79 4.34 0.27 0.98 0.091 total CD8+ [%] 0.85 15.3 0.24 0.79 4.33664 0.27 1.07 0.0906 CD45+/CD8 [%] 8.93 38.1 1.58 1.48 26.52 1.57 2.2 0.209 CD45+/CD3+/CD56+ 0.091 0.703 0.034 0.066511 0.1848 0.018 0.167 0.02211 (NK-T-cells) [%] CD45+/CD3/CD56+ 0.3 0.87 0.047 0.71051 1.16732 0.065 0.789 0.00633 (other NK-cells) [%] CD45+/CD56+ 0.391 1.573 0.081 0.777021 1.35212 0.083 0.956 0.02844 (total NK-cells) [%] total CD56+ [%] 0.391 16.9 0.081 0.777021 1.35212 0.083 0.956 0.02844 CD45+/CD56 [%] 9.389 42.1 1.739 1.492979 29.50788 1.757 2.224 0.27156 CD45+/CD3+/CD16+ 0.17 (NK-T-cells) [%] CD45+/CD3/CD16+ [%] 3.11 CD45+/CD16+ [%] 4.05 CD45+/CD16 [%] 5.87 CD45/CD16+ [%] 5.86 CD45+/CD19+ [%] 5.11 CD45+/CD19 [%] 4.79 0.019 total CD19+ [%] 5.11 0.019 CD45+/CD25+ [%] 8.1 CD45+/CD25 [%] 1.76 CD45/CD25+ [%] 0.13 total CD25+ [%] 8.23

[0131] Thus, while there has been described what are believed to be the embodiments of the invention, those skilled in the art will recognize that other and further modifications may be made thereto without departing from the spirit of the invention, and it is intended to claim all such changes and modifications as falling within the scope of the invention.