Monocyte Responses in the Context of Q Fever: From a Static Polarized Model to a Kinetic Model of Activation
Monocyte Responses in the Context of Q Fever: From a Static Polarized Model to a Kinetic Model of Activation
Vikram Mehraj 0
Julien Textoris ) 0
Amira Ben Amara 0
Eric Ghigo 0
Didier Raoult 0
Christian Capo 0
Jean-Louis Mege 0
0 Aix-Marseille University , URMITE, CNRS UMR 7278, IRD 198, INSERM 1095, Marseille , France
Background. Q fever is caused by Coxiella burnetii, a bacterium that persists in M2-polarized macrophages. We wondered whether the concept of M1/M2 polarization is applicable to Q fever patients. Methods. Monocytes from healthy controls were cultured with IFN-γ and IL-4, agonists of M1 and M2 macrophages, respectively, and their gene expression was assessed using whole-genome microarrays. Selected biomarkers were assessed in blood from Q fever patients by real-time reverse transcription polymerase chain reaction (RTPCR). Results. Monocytes exhibited early (6-hour) patterns of activation specific to IFN-γ or IL-4 and a late (18-hour) pattern of common activation. Because these responses were not reducible to M1/M2 polarization, we selected biomarkers and tested their relevance in Q fever patients. The early genes NLRC5, RTP4, and RHOH, which were modulated in response to IFN-γ, were up-regulated in patients with acute Q fever, and the expression levels of the late genes ALOX15, CLECSF1, CCL13, and CCL23 were specifically increased in patients with Q fever endocarditis. The RHOH and ALOX15 genes were associated with the activity of acute Q fever and Q fever endocarditis, respectively. Conclusions. Our results show that the kinetic model of monocyte activation enables a dynamic approach for the evaluation of Q fever patients.
Q fever is caused by Coxiella burnetii, an intracellular
bacterium known for its myeloid tropism. This disease
is characterized by a primary infection that may become
chronic in patients with valvulopathy, pregnant women,
and immunocompromised patients [
]. Although the
primary infection is characterized by a Th1-type
protective immune response, the chronic form of the
disease is due to impaired cell-mediated immunity [
The analysis of C. burnetii-macrophage interaction has
shown that macrophage polarization is critical for
bacterial elimination or persistence [
The concept of macrophage polarization is
instrumental in analyzing the activation of murine macrophages
and, to a lesser degree, human macrophages [
macrophages that are stimulated by interferon (IFN)-γ
in the presence or absence of lipopolysaccharide (LPS)
are considered inflammatory, microbicidal, and
tumoricidal. M2 macrophages, which are induced by
interleukin (IL)-4/IL-13, IL-10/transforming growth factor
(TGF)-β1, immune complexes, apoptotic cells, and
corticosteroids, are poorly inflammatory and exhibit
immunoregulatory functions [
]. Polarized macrophages
are involved in innate immune response to pathogens [
autoimmune diseases [
], and local immune
suppression associated with tumors [
]. We previously showed
that C. burnetii induces an atypical M2 program in
macrophages that combined M2 markers, including
TGFβ1, IL-10, CCL18, mannose receptor, and arginase, and
some M1 markers, including IL-6 and CCL8 [
uptake of apoptotic lymphocytes by macrophages
stimulates an M2 program and the replication of C. burnetii.
Both events are prevented in the presence of IFN-γ [
In vivo, the overexpression of IL-10 in transgenic mice enables
bacterial persistence and mimics features of chronic Q fever,
including the M2 polarization of macrophages [
]. These reports
suggest that the chronic evolution of Q fever is related to the M2
polarization of macrophages, but direct evidence of such a
relationship in infected patients is lacking. The concept of the M1/
M2 polarization of macrophages seems pertinent only in few
clinical situations, and in vivo and in vitro data are often
]. In addition, only monocytes, not tissue
macrophages, are easily accessible in clinical investigations, and it is
not known if the concept of macrophage polarization is
applicable to monocytes.
In this study, using a high-throughput microarray approach,
we analyzed the transcriptional responses of circulating
monocytes to IFN-γ and IL-4, canonical agonists of M1 and M2
macrophages, respectively. When monocytes were stimulated for 6
hours, they exhibited early responses to IFN-γ and IL-4 that
were not reducible to M1/M2 polarization. After 18 hours, the
monocyte response was no longer polarized, and a late response
signature was identified. By selecting early- and late-related
genes from each monocyte signature, we showed that specific
biomarkers could be used to distinguish acute Q fever and Q
This study was approved by the Ethics Committee of the
Aix-Marseille University, and written informed consent was
obtained from each subject. Q fever diagnosis was based on
epidemiological, clinical, and serological criteria [
]. We included
14 patients with acute Q fever with a mean age of 47 years
(range, 28–69 years), 13 patients with chronic Q fever and
endocarditis with a mean age of 52 years (range, 39–64 years). Six
patients with acute Q fever and 9 patients with Q fever
endocarditis were investigated twice: at the inclusion, after 5 (3–6)
months for acute Q fever and after 16 (8–25) months for Q
fever endocarditis. The control group consisted of 10 healthy
controls with a mean age of 48 years (range, 32–59 years), 8
patients with classical Whipple’s disease (mean age of 64 years,
range: 53–69 years), 7 trauma patients with a mean age of 34
years (range, 24–37 years) and 5 trauma patients with
pneumonia (mean age of 36 years, range, 29–43 years) [
were handled anonymously without knowledge of disease state
until statistical analysis. Peripheral blood was drawn in
PAXgene tubes (Qiagen), and RNA was extracted after DNase
treatment (see below).
Monocytes and Macrophages
Blood donor buffy coats were provided by the Etablissement
Français du Sang (Marseille). Peripheral blood mononuclear
cells were subjected to CD14+ magnetic cell sorting (Miltenyi
Biotec), which yielded monocytes with a purity higher than
95%, as assessed by flow cytometry. Monocytes (106 cells/
assay) were differentiated into macrophages as described
], and after differentiation, more than 95% of cells
were macrophages as assessed by CD68 expression and CD14
down-regulation. Monocytes and monocyte-derived
macrophages were stimulated with 20 ng/mL recombinant human
IFN-γ (PeproTech) or IL-4 (AbCys) for 6 or 18 hours.
RNA was extracted with an RNeasy Mini kit (Qiagen) and
analyzed with microarray chips (4×44K Whole Human Genome,
Agilent Technologies, Massy, France) as recently described [
MIAME-compliant data were submitted to the Gene
Expression Omnibus (GEO) of the National Center for
Biotechnology Information (http://www.ncbi.nlm.nih.gov/geo/) and
can be assessed with the GEO series accession number
The data were analyzed with R and the Bioconductor
software suites with Significance Analysis of Microarray and a
multiclass model integrating the experimental design. Functional
enrichment analysis was performed with DAVID as described
]. To assess the M1/M2 polarization status of
monocytes, 28 M1 genes and 17 M2 genes (Supplementary
Table 1) were manually selected from the literature [
were found to be modulated in IFN-γ- or IL-4-stimulated
macrophages. These genes were plotted above a virtual cell
according to their cellular localization. The modulation of gene
expression was explored by color coding. The ratio of gene
expression in stimulated cells to gene expression in unstimulated
cells is coded from red to blue, whereas the ratio of gene
expression in IFN-γ-stimulated cells to gene expression in
IL-4-stimulated cells is coded from pink to green. Cytoscape [
Inkscape were used to design the figures. These 45 genes were
also analyzed by quantitative real-time reverse transcription
polymerase chain reaction (qRT-PCR) to confirm microarray
results. The overall correlation coefficient for the 2 techniques
was high (R² = 0.64; P = .01).
qRT-PCR experiments were performed with the MMLV RT
Kit (Life Technologies) and the 7900HT Fast Real Time
PCR System (Applied Biosystems) as recently described [
Gene-specific primers were designed with Primer3 [
results were normalized to the result for the housekeeping
gene β-actin and are expressed as ΔCt values (ΔCt = CtTarget–
CtActin), where Ct is the number of PCR cycles. Correlation
analysis for the microarray and qRT-PCR data was performed
with the Spearman correlation coefficient. The significance of
the differential expression in patients observed by qRT-PCR
was assessed by the Wilcoxon rank sum test with a P-value
cutoff of .05.
Kinetics of Transcriptional Responses of Monocytes to IFN-γ
The transcriptional responses of monocytes and macrophages
to IFN-γ or IL-4 were investigated using whole-genome
microarrays. The overall transcriptional response showed a
completely different activation pattern in monocytes and macrophages.
Principal component analysis confirmed that the cell type
(monocytes or macrophages), time (6 or 18 hours), and type of
stimulation (IFN-γ or IL-4) influenced transcriptional
modulation (Figure 1A and 1B). Based on a multiclass model that
integrates the cell type (macrophages or monocytes), length of
stimulation (6 or 18 hours) and type of stimulation (IFN-γ
or IL-4), 15 619 probes were modulated with an absolute FC
of at least 2.0 and a false discovery rate (FDR) < 1% (assessed
with significance analysis of microarray). When filtering the
dataset for an absolute FC ≥ 4.0 and a FDR < 1% 4807
modulated probes (3406 genes) were identified. These 4807 modulated
probes are represented as a heatmap (Figure 1C). Modulated
genes were then filtered to retain those genes specifically
modulated in monocytes (Figure 1D). We identified 587 probes
whose targets were modulated in IFN-γ- or IL-4-stimulated
monocytes compared with unstimulated monocytes. The early
genes (6-hour stimulation) that were specifically up-regulated in
response to IFN-γ or IL-4 included the targets of 59 probes
(46 annotated genes) and the targets of 61 probes (39 annotated
genes), respectively. In contrast to the early responses of
monocytes to IFN-γ and IL-4, the patterns of the late response
(18-hour stimulation) of monocytes to IFN-γ and IL-4 were
indistinguishable and were characterized by a specific cluster of
up-regulated genes that corresponded to 74 probes and 57
annotated genes (Figure 1D). Taken together, these results revealed
a biphasic response of monocytes to IFN-γ and IL-4.
Polarization of Early and Late Monocyte Responses
We wondered whether the polarization observed in
macrophages is applicable to the early and late responses of
monocytes. We studied the expression in monocytes of 28 and 17
genes considered to be markers of M1 and M2 polarization in
]. In the early response of monocytes to
IFNγ, 16 M1 genes were up-regulated, but only one M2 gene was
up-regulated (Figure 2A). In the early response of monocytes to
IL-4, 10 M2 genes, but only 3 M1 genes, were up-regulated
(Figure 2C). Hence, the early responses of monocytes to IFN-γ
and IL-4 showed a clear dichotomy in the expression of M1
and M2 genes (Figure 2E). We then investigated whether the
specific signatures of monocytes induced by IFN-γ and IL-4
included M1/M2 genes. In the early signature induced by IFN-γ
(which included 46 genes), only 11 genes were M1 genes.
Similarly, the early signature induced by IL-4, composed of 39 genes,
included only 2 M2 genes, demonstrating that the early
responses of monocytes are not reducible to M1/M2 polarization.
In the late response of monocytes to IFN-γ, most M1 genes
that were up-regulated in the early response to IFN-γ returned
to their basal levels or were down-regulated. Only one M1 gene
remained up-regulated. In addition, 8 M2 genes were
up-regulated in the late response to IFN-γ (compare Figure 2A and 2B).
The late response of monocytes to IL-4 was characterized by
the up-regulation of one M1 gene, the down-regulation of 14
M1 genes, and the up-regulation of 10 M2 genes (compare
Figure 2C and 2D). The modulation of M1 and M2 genes was
remarkably similar in the late responses of monocytes to IFN-γ
and IL-4 (Figure 2F), demonstrating that the late responses of
monocytes were not polarized as the responses of macrophages.
As a consequence, we hypothesized that the M1/M2
transcriptional program of macrophages may be insufficient to
account for the clinical manifestation of Q fever. To test this
hypothesis, we selected 6 M1-related genes (IL15, CXCL9,
IL2RA, IDO1 [NDO], TNF, TNFSF10 [TRAIL]) and 6
M2related genes (CHN2, CTSC, CD209 [DC-SIGN], FN1, HRH1,
SLC4A7), and we assessed their expression levels in Q fever
patients. The expression levels of M1 and M2 genes (with the
exception of CD209) were similar in healthy controls and patients
with acute Q fever. In patients with Q fever endocarditis, the
expression levels of 4 M1 genes were up-regulated, and the
expression level of one M2 gene was down-regulated relative
to the expression levels in healthy controls (Supplementary
Figure 1). These results show that the expression of the M1/M2
genes does not characterize the evolution of Q fever.
Functional Classification of Early and Late Monocyte
Because the majority of the genes up-regulated in the early and
late signatures of monocytes were not M1/M2 genes, we
wondered if these genes belonged to distinct functional groups.
Among the early genes specifically up-regulated in response to
IFN-γ, we identified 6 different clusters including “apoptosis,”
“complement,” “defense response,” “IFN-related genes,” “Jak/
Stat pathway,” and lipid metabolism.” Six other functional
clusters were identified among the early genes that were
specifically up-regulated in response to IL-4. They included “cell
adhesion,” “C-type lectin,” “cytoskeleton,” “endocytosis and
vesicular transport,” “response to wounding,” and “RNA
binding.” The late response of monocytes was organized in 5
different clusters including “Ig domain,” “immune response,”
“Golgi apparatus,” “signal transduction,” and “Wnt pathway”
(Table 1). These results demonstrated that the early and the late
responses of monocytes to IFN-γ and IL-4 were characterized
by specific functional signatures that may be useful to define
new biomarkers of Q fever.
Specific Biomarkers of Q Fever
Among the early annotated genes, we selected 4 genes
representative of the early IFN-γ response (NLRC5, RTP4, C1S, GCH1)
and 4 genes representative of the early IL-4 response (ITGB3,
TREM1, NEDD4L, RHOH), which are not described as M1 or
M2 markers. The expression levels of these genes were
compared between healthy controls and Q fever patients using
qRTPCR. In acute Q fever, 2 early genes associated with the IFN-γ
response, NLRC5 and RTP4, were significantly up-regulated.
This up-regulation was specific of acute Q fever. Indeed, the
expression of NLRC5 and RTP4 genes was not modulated in
patients with Q fever endocarditis relative to healthy controls
(Figure 3). In patients with Whipple’s disease, an infectious
disease due to an intracellular bacterium with macrophage
tropism, NLRC5, RTP4, and RHOH genes were not modulated
(Supplementary Figure 2). In trauma patients with or without
pneumonia, who exhibited an intense inflammatory response,
NLRC5 and RTP4 genes were down-regulated, suggesting that
the modulation of early genes in acute Q fever was not a
consequence of inflammatory response. Interestingly, the ITGB3 and
TREM1 genes, which were associated with the early response to
IL-4, were significantly down-regulated in patients with acute
Q fever compared with controls. Only one early gene associated
with the IL-4-response, RHOH, was significantly up-regulated
in patients with acute Q fever (Figure 3B). Therefore, the
upregulation of NLRC5, RTP4, and RHOH genes may be
considered biomarkers of acute Q fever.
A similar procedure was used to define biomarkers from the
late signature of monocytes using eight genes belonging to
different clusters. In acute Q fever patients, 5 genes (ALOX15,
CLEC4F, CCL23, BACE1, RAMP1) were not differentially
regulated relative to the expression levels in healthy controls
(Figure 4), demonstrating that late biomarkers were unable to
distinguish acute Q fever. By contrast, the ALOX15, CLEC4F,
CCL13, CCL23, and RAMP1 genes were significantly
upregulated in patients with Q fever endocarditis relative to
healthy controls. Interestingly, the expression levels of ALOX15,
CLEC4F, CCL13, and CCL23 were significantly higher in
patients with Q fever endocarditis than in patients with acute Q
fever (Figure 4), suggesting that these genes may serve as
specific biomarkers of Q fever endocarditis. We also found that 2 late
genes, GALNTL18 and WNT5B, which were not modulated in
Response to wounding CCL5, CD93, HLA-DQA1, TREM1,
THBD, FCGR2A, SLAMF1, RHOH
Early IFN-γ signature
Early IL-4 signature
JAK2, IL7, STAT1, IL15, PML, IL15RA
IL7, IL15, IL15RA, HLA-DRB6, JAK2,
STAT1, PML, C1S, GCH1, APOL1,
APOL2, APOL3, RSAD2
CASP1, CASP5, CARD16, CARD17,
APOL1, APOL2, APOL3
IRF1, IRF5, NLRC5, IFI35, ETV7, HIVEP2,
DDX3Y, DDX43, EIF1AY, RAVER2,
RPS4Y1, RPS4Y2, TEP1, RNASE6
CD93, EHD2, CCL5, STAB1, RAB15,
FRMD4A, PDLIM2, ARHGAP26, ITGB3,
CD93, STAB1, THBD
CD93, ITGB3, STAB1, THBD, MSN
F13A1, MAL, MAF, CD1D, FCERA1,
ALOX15, CACNB4, CCL23, CD36,
TREM2, CXCL14, CCL3
CCL23, CXCL14, FCER1A, CACNB4,
DACT1, FZD7, RAMP1, GFRA2,
CD36, GALNTL4, BACE1, CXCL14,
GGTA1, PCSK5, TMEM130
DACT1, FDZ7, WNT5B
CD1D, FCER1A, AMICA1, PDGFRL,
The genes included in the early and late signatures of monocytes were
analyzed with the functional analysis tools of DAVID. Major functional clusters
are listed with corresponding genes.
Abbreviations: IFN, interferon; IL, interleukin.
Q fever endocarditis patients, were down-regulated in acute Q
fever patients, providing indirect evidence that late genes may
be biomarkers of Q fever endocarditis. Again, late genes were
not modulated in patients with patients with Whipple’s disease.
In trauma patients with or without pneumonia, these genes
were down-modulated compared with healthy controls
(Supplementary Figure 2). These results demonstrate that ALOX15,
CCL13, and CCL23 genes were specifically up-regulated in Q
Finally, we assessed the modulation of putative biomarkers
during the follow-up of patients with Q fever. In patients with
acute Q fever, the expression of NLRC5 and RTP4 genes remained
up-regulated 5 months after the initial inclusion whereas the
expression of RHOH gene was similar to controls after 5 months
(Figure 5A). The modulation of CCL23, CLECF4, ALOX15, and
CCL13 genes was assessed in patients with Q fever endocarditis
16 months after the inclusion. The expression of CCL13 and
CCL23 genes remained unchanged. By contrast, the expression of
ALOX15 and CLECF4 genes decreased with time, but only the
expression of ALOX15 gene returned to control levels (Figure 5B).
Taken together, our results support the hypothesis that the
kinetics model of monocyte activation is useful to assess the clinical
manifestation of Q fever.
The M2 polarization of macrophages has been considered
critical for the persistence of C. burnetii [
6, 9, 11
]. Nevertheless, this
concept needs to be confirmed in circulating monocytes.
Different constraints impair the evaluation of patients with Q fever
based on the concept of macrophage polarization. The isolation
of macrophages is adapted for pathophysiological studies but is
not convenient for routine use in clinical practice. As a
consequence, the use of whole blood may be a practical alternative
but requires the validation of monocyte biomarkers. In this
study, we investigated the responses of monocytes to IFN-γ and
IL-4, and we used these data to guide our analysis of whole
blood from patients with Q fever.
The responses of monocytes to IFN-γ and IL-4 consisted of
early and late phases of activation, a pattern that did not fit
with the M1/M2 polarization model at the transcriptional level.
The hallmarks of M1/M2 polarization were found in the early
phases of monocyte activation, but the second phase of
monocyte activation was common to the different modes of
stimulation. Our results were consistent with the modulation of early
and late genes in macrophages stimulated with LPS [
the transient polarization observed in murine monocytes
stimulated with Listeria monocytogenes [
In the early phase of the monocyte response to IFN-γ, we
identified one set of up-regulated genes that included M1
genes, interferon-response genes, and genes related to
inflammatory signaling, complement, and apoptosis. A second set of
genes that were specifically up-regulated in IL-4-stimulated
monocytes included M2-related genes, and a series of genes
partitioned into different clusters associated with lectins, cell
adhesion, endocytosis, and the cytoskeleton. By contrast, the
late response of monocytes was characterized by the
up-regulation of numerous genes independent of the agonist, IFN-γ or
IL-4. This late response was also distinct from the LPS tolerance
that appears late in the inflammatory response and is associated
with an M2 program [
]. The late response of monocytes may
be considered a termination program with only some features
of the M2 program. Our results were consistent with data
obtained in a murine model of resolving and nonresolving
peritonitis. In this model, peritoneal macrophages from mice with
sustained inflammation may be referred to as M1 macrophages,
and macrophages from mice with resolving inflammation
produce high levels of immunoregulatory cytokines but also
present hallmarks of M1 macrophages [
]. A recent
transcriptional analysis confirmed that the peritoneal macrophages
collected from mice with resolving inflammation exhibit a unique
phenotype that is inconsistent with the conventional M1/M2
macrophage classification [
]. These results suggest a high
level of plasticity in macrophages. The existence of a unique
termination program in monocytes stimulated with IFN-γ and
IL-4 may represent a parsimonious way to control the
monocyte activation induced by a great variety of cytokines and
We showed that the model of M1/M2 polarization was not
applicable to monocyte responses in the context of Q fever. We
selected M1-related and M2-related genes and tested these
genes in whole blood. The expression levels of these genes were
similar in patients with acute Q fever and healthy controls.
Only a minority of these genes were up-regulated in patients
with Q fever endocarditis. Such findings demonstrate that Q
fever patients exhibited an activation program that cannot be
classified as an M1 or M2 pattern, in contrast to the result of in
vitro and in vivo studies using macrophages [
9, 10, 24
differences in the transcriptional programs of monocytes and
macrophages may explain why attempts to use markers
defined as M1/M2 for macrophages are unsuccessful in clinical
]. Only rare reports suggest that monocytes are
polarized in infectious diseases. In addition, even though
monocytes from patients with Whipple’s disease overexpress
CD163, other markers of M2 cells are lacking . In patients
with active tuberculosis [
] or in children vaccinated with
], a transient M1 profile is identified, whereas in vitro
studies with macrophages suggest M2 polarization [
contrast, monocytes stimulated with Orientia tsutsugamushi
and patients with scrub typhus both exhibit an M1-type
Interestingly, the identification of early and late signatures of
in vitro-stimulated monocytes allowed the identification of Q
fever biomarkers. Some early genes specifically associated with
acute Q fever, such as NLRC5 and RTP4, were up-regulated by
IFN-γ, suggesting that acute Q fever is controlled at least in
part by an IFN-γ-mediated immune response. That these genes
were not modulated in patients with Q fever endocarditis
confirmed the defective Th1-response reported for Q fever
]. We also found that genes associated with IL-4
response, such as ITGB3 and TREM1, were down-regulated in
patients with acute Q fever, reinforcing our hypothesis that
acute Q fever is associated with an efficient immune response.
Moreover, we found that some late genes, including ALOX15,
CLEC4F, CCL13, and CCL23, were specifically associated with
Q fever endocarditis. Note that a few late genes were also
related to the M2 program, a result that might lead to incorrect
conclusions about monocyte activation in the context of Q
fever endocarditis. The modulation of early genes in acute Q
fever and late genes in Q fever endocarditis seemed to be
specific of Q fever because these genes were not modulated in
patients with another infectious disease, the Whipple’s disease,
and patients with acute pathologies such as trauma or
pneumonia. The follow-up of patients with Q fever revealed that the
expression of RHOH and ALOX15 genes was normalized after
several months of disease’s evolution, suggesting that these
genes may be considered as biomarkers of the activity of acute
Q fever and Q fever endocarditis, respectively.
In conclusion, we demonstrated that the concept of
macrophage polarization is not useful to describe monocyte activation
and is irrelevant to explore patients at the bedside. The kinetic
approach of monocyte activation we developed allowed the
identification of new biomarkers of acute Q fever and Q fever
endocarditis, respectively. Additionally, 2 biomarkers were
associated with the activity of the disease.
Supplementary materials are available at The Journal of Infectious Diseases
online (http://jid.oxfordjournals.org/). Supplementary materials consist of
data provided by the author that are published to benefit the reader. The
posted materials are not copyedited. The contents of all supplementary data
are the sole responsibility of the authors. Questions or messages regarding
errors should be addressed to the author.
Financial support. This work was supported by funds from the
Assistance Publique—Hôpitaux de Marseille, Marseille, France (contract
2009A00945-52). V. M. was supported by a grant from the Higher Education
Commission (Pakistan) and the Assistance Publique—Hôpitaux de
Marseille. This work was also supported by ANR project MigreFlame
The information in this article has never been presented elsewhere.
Potential conflicts of interest. All other authors report no potential
All authors have submitted the ICMJE Form for Disclosure of Potential
Conflicts of Interest. Conflicts that the editors consider relevant to the
content of the manuscript have been disclosed.
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