Single-cell analysis reveals immune cell abnormalities underlying the clinical heterogeneity of systemic sclerosis

Single-cell analysis reveals immune cell abnormalities underlying the clinical heterogeneity of systemic sclerosis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Single-cell analysis reveals immune cell abnormalities underlying the clinical heterogeneity of systemic sclerosis Masayuki Nishide, Hiroshi Shimagami, Kei Nishimura, Hiroaki Matsushita, and 20 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4728677/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 17 Jun, 2025 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Abstract Autoimmune rheumatic diseases present with diverse clinical manifestations that often complicate management strategies. Systemic sclerosis (SSc) is a representative disease with multiple organ manifestations affecting patients worldwide, and exploring the variation of immune abnormalities in this disease is of great interest. However, previous studies have focused on diseased tissues, and it remains largely unknown how cellular diversity links to clinical heterogeneity. Here, we perform single-cell transcriptome and surface proteome analyses of peripheral blood mononuclear cells (PBMCs) from 21 SSc patients who are not receiving immunomodulatory therapy and show that different clinical manifestations are associated with distinct immune abnormalities. Enrichment of a specific CD14 + monocyte subset characterized by EGR1 expression is observed in patients with scleroderma renal crisis (SRC). Integrated analysis of PBMCs and kidney biopsy cells indicates that this monocyte subset directly differentiates into tissue-damaging macrophages under activation of NF-κB signaling. Clinically, EGR1 expression in monocytes is significantly upregulated at the onset of SRC and decreases after treatment, suggesting its potential as a biomarker for SRC. In patients with interstitial lung disease (ILD), a CD8 + T cell subset with type II interferon signature is highly enriched in both peripheral blood and lung tissue of patients with progressive disease, suggesting that chemokine-driven migration of these cells is involved in ILD progression. Thus, distinct immune cell profiles at the single cell level reveal different directions of immune dysregulation between organ manifestations and provide insights for tailored treatment strategies. Health sciences/Diseases/Rheumatic diseases/Connective tissue diseases/Systemic sclerosis Biological sciences/Immunology/Autoimmunity Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction The clinical heterogeneity in systemic autoimmune diseases often complicates the management of individual patients 1 . Systemic sclerosis (SSc) is primarily characterized by Raynaud's phenomenon and skin sclerosis, with an estimated global prevalence of approximately one million individuals. Patients with SSc present with a particularly diverse range of organ manifestations 2 . These complications directly impact the daily activities of SSc patients and are associated with a poor prognosis 3 . The specific organs affected vary between patients; 50–65% develop interstitial lung disease (ILD), approximately 50% develop digital ulcers, and 1–14% develop scleroderma renal crisis (SRC), which is the most severe acute organ complication leading to end-stage renal disease and even death 2 , 4 . While vascular damage and tissue fibrosis due to immune dysregulation play a central role in the pathogenesis of SSc 2 , the immunological abnormalities underlying the clinical heterogeneity of the disease and the diversity of organ involvement have not been sufficiently investigated. Therefore, it is of great interest to explore the variation of immune abnormalities underlying the diversity of organ involvement in SSc. Single-cell RNA sequencing (scRNA-seq) is a technique that comprehensively captures the diversity of individual cells. Since 2018, scRNA-seq studies of SSc patient samples have provided important insights into the pathology of the disease. Skin vascular endothelial cells from SSc patients show significant increases in gene expression related to extracellular matrix formation and angiogenesis inhibition 5 . Looking further into the diseased skin, functional alterations of LRG5 + fibroblasts 6 , enrichment of SFRP2 high fibroblasts 7 , the presence of FCN1 + dendritic cells 8 and CXCL13 + T cells 9 have also been demonstrated. Thus, while studies of the pathological mechanisms at the lesion sites in SSc are rapidly advancing 10 , it is still largely unknown how cellular diversity relates to symptom diversity from a single-cell transcriptomic perspective. To elucidate the immune abnormalities underlying different patterns of organ involvement, we hypothesized that peripheral blood, which has not been widely analyzed in scRNA-seq studies in SSc, may serve as a reservoir of information that can distinguish different endotypes among patients and is as important as information from organ tissues. In this study, we recruit SSc patients without infections, malignancies, or other systemic autoimmune diseases. In addition, patients not receiving immunosuppressive therapy are selected for scRNA-seq. Peripheral blood mononuclear cells (PBMCs) are collected from 21 patients and age- and sex- matched healthy donors. Kidney tissue is collected from one patient with new-onset SRC. SSc patients with SRC and ILD show distinct immune abnormalities characterized by the enrichment of different cell populations. Detailed analyses of CD14 + monocytes in the SRC group and CD8 + T cells in the ILD group allow for the identification of specific cells associated with each type of organ involvement. Classification of patients based on the diversity of peripheral blood single-cell profiles identifies pathological subsets of SRC and ILD, which hold potential as biomarkers and therapeutic targets. Result Single-cell profiling of PBMCs reveals distinct immune landscapes in SSc patients with different organ complications PBMCs were obtained from 21 patients with SSc and six age- and sex-matched healthy donors. All recruited patients with SSc fulfilled the 2013 American College of Rheumatology (ACR)/European League Against Rheumatism (EULAR) classification criteria 11 . The clinical characteristics of patients with SSc are summarized in Table 1 . Detailed information on individual patients with SSc is provided in Supplementary Tables 1, 2, and 3. Isolated PBMCs were analyzed on a 10x chromium® platform, and the transcriptome and expression of 43 surface proteins were simultaneously obtained using Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq); the experimental overview is shown in Fig. 1 a. A total of 238,924 cells were processed, and each cell was annotated with supervised analysis using existing datasets 12 . Uniform Manifold Approximation and Projection (UMAP) plots of PBMCs from SSc patients and healthy donors are shown in Fig. 1 b. UMAP plots of PBMCs from each SSc patient or healthy donor are provided in Extended Data Fig. 1 . The ratio of the number of cells in each subset to the total number of PBMCs was calculated. There were no significant differences in the proportion of each cell population relative to the total number of PBMCs between SSc patients and healthy donors (Fig. 1 c,d). Table 1. Clinical characteristics of systemic sclerosis patients and healthy donors. To analyze in-depth profiles of each cell population using single-cell transcriptomes, we further subdivided each cell population using previously reported marker genes 13 – 16 . UMAP plots of monocyte subsets and profiles of highly expressed genes are provided in Extended Data Fig. 2 a and Extended Data Fig. 2 b, respectively. UMAP plots of monocyte subsets from individual SSc patients or healthy donors are provided in Extended Data Fig. 2 c. Similarly, single-cell level gene expression profiles were determined for CD4 + T cell subsets (Extended Data Fig. 3 a-c), CD8 + T cell subsets (Extended Data Fig. 4 a-c), B cell subsets (Extended Data Fig. 5 a-c), natural killer (NK) cell subsets (Extended Data Fig. 6 a-c), and plasmacytoid dendritic cell (pDC) subsets (Extended Data Fig. 7a-c). Next, principal component analysis (PCA) was performed to visualize the variability in immune abnormalities among the SSc patients. The PCA was conducted on the relative proportion of each cell subpopulation to the total PBMCs. Each vector representing a specific cell subpopulation is plotted on a two-dimensional graph according to its principal component 1 (PC1) and principal component 2 (PC2) (Fig. 1 e). Individual SSc patients and healthy donors were then plotted based on their respective PC1 and PC2 values (Fig. 1 f, left). The mean of the vectors representing individual SSc patients and those representing healthy donors pointed in distinct directions. Patients with SSc were further categorized by concomitant organ complications: SRC, ILD without SRC, and neither SRC nor ILD (Fig. 1 f, right). The direction of the mean vector of the SRC group was aligned with the vectors representing monocyte and dendritic cell subpopulations, whereas the mean vector of the ILD without SRC group was closely associated with the vectors for T cell subpopulations and plasmablasts. The mean vector of cases with neither SRC nor ILD showed an orientation similar to that of healthy donors. To further elucidate the compositional changes in PBMCs from SSc patients with SRC or ILD, we performed differential abundance analysis using milo 17 , which is a cluster-free and age-adjusted approach designed to detect changes in cell composition between conditions. Differential abundance analysis revealed that CD14 + monocytes, CD16 + monocytes, and NK cells were particularly enriched in patients with SRC compared to those without SRC (Fig. 2 a,b). In contrast, memory T cell subsets such as CD8 + effector memory T cells were notably enriched in ILD patients (Fig. 2 c,d). These data suggest that a skew in the gene expression profiles within the peripheral blood of SSc patients is associated with their organ complications. Specifically, SRC was linked to myeloid cell subsets, whereas ILD was linked to lymphoid cell subsets. Differential abundance analysis further highlighted the distinct immune abnormalities underlying each complication; enrichment of monocytes in SRC and memory T cells in ILD. EGR1-expressing CD14 + monocytes were specifically enriched in SRC. PCA and differential abundance analysis identified the monocyte subsets as interesting targets in terms of elucidating the pathogenesis of SRC. UMAP plots of monocytes from SSc patients with SRC or without SRC are shown in Fig. 3 a. Five cellular clusters of CD14 + monocytes were identified by their distinct gene expression profiles: CD14 + monocytes with high expression of EGR1 (CD14_EGR1), interferon signature genes (ISGs) (CD14_ISG), PLBD1 (CD14_PLBD1), VCAN (CD14_VCAN), or HLA (CD14_HLA). Other clusters include intermediate monocytes (Intermediate), CD16 + monocytes characterized by high expression of ISGs (CD16_ISG), other CD16 + monocytes (CD16), conventional type 1 dendritic cells (cDC1), and conventional type 2 dendritic cells (cDC2). Quantitative analysis of the relative distribution of each cellular subpopulation showed that the CD14_EGR1, CD14_ISG, Intermediate, and CD16_ISG subsets were abundant in patients with SRC (Fig. 3 b). Differential abundance analysis further identified significant enrichment of CD14_EGR1 (median log 2 -fold change: +1.9), CD14_ISG (median log 2 -fold change: +1.3), and CD16_ISG (median log 2 -fold change: +1.6) subsets in patients with SRC, with the interquartile range of neighbors shifting entirely toward SRC, relative to the baseline where the fold change equals 1 (Fig. 3 c,d). Similar results were observed when conducting differential abundance analysis comparing SRC patients with healthy donors (Extended Data Fig. 8a,b). To determine whether the increases in the CD14_EGR1, CD14_ISG, and CD16_ISG subsets were specific to SRC patients, we recruited patients with lupus nephritis (LN) and compared the proportion of each subset among patients with SRC, patients with LN, and healthy donors using CITE-seq. The clinical profiles of LN patients are presented in Supplementary Table 4. UMAP plots derived from the subset analysis of monocytes are displayed in Extended Data Fig. 9a. Highly expressed genes in each cell subpopulation are detailed in Extended Data Fig. 9b. UMAP plots of monocytes from individual patients and healthy donors are provided in Extended Data Fig. 9c. The proportion of the CD14_EGR1 subset was significantly increased in patients with SRC compared to patients with LN or healthy donors, whereas the proportions of the CD14_ISG and CD16_ISG subsets were higher in patients with LN (Fig. 3 e). The expression of EGR1 in total monocytes was increased only in patients with SRC, while the expression of ISG15 , a representative ISG, was highly elevated in patients with LN (Fig. 3 f). Pathological role of CD14_EGR1 monocytes in tissue damage mediated by NF-κB pathway activation To further explore the characteristics of this specific CD14_EGR1 subset, we identified differentially expressed genes (DEGs) in this subset compared to other monocyte subpopulations (Supplementary Table 5). Pathway analysis of the DEGs (log 2 -fold change > 0.5) showed predominant activation of the "TNF-alpha signaling via NF-κB” pathway in the CD14_EGR1 subset (Fig. 4 a). The expression levels of representative NF-κB–targeted genes such as EGR1 , IL1B , CCR1 , and SGK1 are shown in Fig. 4 b. The results indicate that the expression of each gene was increased in the SRC group, with a similar distribution to EGR1 . The expression profiles of cell surface antigens based on CITE-seq indicated that the CD14_EGR1 subset highly expressed CD11b, CD38, and CD4 (Extended Data Fig. 10), suggesting that the subset has enhanced capacity for tissue migration and differentiation 18 – 20 . On the basis of these gene expression profiles and surface antigen data, we hypothesized that the CD14_EGR1 subset possesses enhanced migratory capacity in tissues and contributes to renal damage. A sample of kidney tissue was obtained from a patient at the onset of SRC (patient ID: SSc-19). Pathological findings showed intimal thickening and luminal narrowing within arteries, fibrinoid necrosis of arterioles, red blood cell fragmentations, and focal tubular necrosis, which support the diagnosis of SRC (Extended Data Fig. 11a-d). Renal cells and total peripheral white blood cells from the same patient were independently analyzed on the BD Rhapsody® platform. The UMAP plots of the peripheral white blood cells and renal cells are shown in Extended Data Fig. 12a. Profiles of highly expressed genes (Extended Data Fig. 12b) and surface antigens (Extended Data Fig. 12c) for each cell population are also provided. We then subset monocytes, conventional dendritic cells (cDCs) and macrophages. The RNA expression profile of known gene markers 21 was used to divide these cells into five groups: CD14 + monocytes (CD14_Mo), CD16 + monocytes (CD16_Mo), cDCs, macrophages characterized by high expression of THBS1 (THBS1_Mac), and macrophages characterized by high expression of C1QC (C1QC_Mac). The C1QC_Mac subset was considered as kidney resident macrophages characterized by high expression of genes such as C1QC , CD81 , and CD74 22 . UMAP plots derived from this subset analysis are presented in Fig. 4 c, divided by blood and renal cells. Profiles of highly expressed genes in myeloid subsets are provided in Fig. 4 d. In the THBS1_Mac subset, genes linked to vascular injury and fibrosis, such as THBS1 23 , IL1B 24 , and LRG1 25 , were highly expressed. DEGs were identified in the THBS1_Mac subset compared to other myeloid cell subpopulations (Supplementary Table 6), and subsequent pathway analysis revealed an enrichment of the “Interleukin-1 regulation of extracellular matrix” pathway in this subset (Extended Data Fig. 13). The expression levels of EGR1 and THBS1 are shown as feature plots in Fig. 4 e. To estimate the cell trajectory from peripheral blood to kidney tissue, we conducted trajectory analysis using Monocle 3 26 . The root node was set to immature monocytes characterized by high expression of S100A12 and low expression of HLA-DR genes 27 . The expression levels of S100A12 and HLA-DRB1 are shown as feature plots in Extended Data Fig. 14. CD14 + monocytes, which have high EGR1 expression, showed a differentiation trajectory leading to the THBS1_Mac subset (Fig. 4 f). We next performed transcriptional regulatory relationships unraveled by sentence-based text-mining (TRRUST) analysis 28 , a transcription factor analysis using DEGs in the CD14_EGR1 and THBS1_Mac subsets. The activation of RELA and NFKB1, members of the NF-κB family 29 , was a shared transcriptional characteristic between these subsets (Fig. 4 g). These data suggest that the CD14_EGR1 subset, characterized by activation of the NF-κB–related pathway, differentiates into the THBS1_Mac subset in the kidneys of SRC patients and contributes to severe renal damage through the expression of molecules crucial for vascular damage and fibrosis. Clinically, all patients with SRC in this study tested positive for anti-RNA polymerase III antibody (ARA), the autoantibody strongly associated with SRC 30 . Therefore, we compared the frequency of the CD14_EGR1 subset according to the presence or absence of ARA. The proportion of the CD14_EGR1 subset was significantly higher in SRC patients than in those without, regardless of ARA positivity (Fig. 4 h). These data suggest that enrichment of the CD14_EGR1 subset is due to the presence of SRC rather than to autoantibody profiles. In addition, we assessed changes in EGR1 expression during the clinical course of SRC. We collected PBMCs from a patient (patient ID: SSc-1) and conducted CITE-seq analysis at three different time points; three months before the onset of SRC, at the onset of SRC, and after the improvement of SRC. The UMAP plots of PBMCs in this longitudinal analysis are shown in Extended Data Fig. 15. The expression of EGR1 in total monocytes was highly upregulated at the onset of SRC, and decreased following treatment (Fig. 4 i). Finally, we evaluated the association of the CD14_EGR1 subset with clinical features of SSc. The proportion of the CD14_EGR1 subset in SSc patients showed a positive correlation with the modified Rodnan skin score and systolic blood pressure, both of which are clinical indicators of SRC (Fig. 4 j). These data suggest that EGR1 expression in CD14 + monocytes may be a specific marker for SRC progression. Enrichment and functional implications of interferon gamma (IFN-γ) – responsive CD8 + T cell subsets in SSc-ILD The results of the PCA and differential abundance analysis of PBMCs prompted us to conduct further analysis of CD4 + T cells and CD8 + T cells in patients with SSc-ILD. UMAP plots of CD4 + T cells from SSc patients are shown in Extended Data Fig. 16a. Differential abundance analysis indicated the enrichment of CD4 + T cells characterized by high expression of ISGs in patients with SSc-ILD compared to those without ILD, but no significant enrichment was found in comparison with healthy donors (Extended Data Fig. 16b-e). UMAP plots of CD8 + T cells from SSc patients with ILD and without ILD are shown in Fig. 5 a. Six cellular clusters were identified: naïve CD8 + T cells (CD8_T_ Naïve), central memory CD8 + T cells characterized by high expression of GATA3 (CD8_TCM_GATA3), other central memory CD8 + T cells (CD8_TCM), effector memory CD8 + T cells characterized by high expression of type 2 ISGs (CD8_TEM_T2ISG), other effector memory CD8 + T cells (CD8_TEM), and cytotoxically active CD8 + T cells (CD8_CTL). Quantitative analysis of the relative distribution of each cellular subpopulation showed that CD8 + memory T cell subsets, CD8_TCM, CD8_TCM_GATA3, CD8_TEM, and CD8_TEM_T2ISG, were abundant in patients with SSc-ILD (Fig. 5 b). Differential abundance analysis revealed that the CD8_TEM_T2ISG subset was most enriched in patients with SSc-ILD (median log 2 -fold change: +1.2) (Fig. 5 c,d). The increase in CD8_TEM_T2ISG was consistently observed in patients with SSc-ILD when compared to the healthy donors (Extended Data Fig. 17a,b). To further investigate the characteristics of the CD8_TEM_T2ISG subset, DEGs of the CD8_TEM_T2ISG compared to other CD8 + T cell subpopulations were identified (Supplementary Table 7). Pathway analysis of the DEGs highlighted significant enrichment of the “Interferon Gamma Response” pathway in the CD8_TEM_T2ISG subset (Fig. 5 e). IFN-γ is widely known to enhance tissue migration in CD8 + T cells 31 . We therefore examined the gene expression profiles of chemokine receptors in each CD8 + T cell subset. CXCR3 and CCR5 , which are important for T cell migration in pathological conditions 32 , were highly expressed in the CD8_TEM_T2ISG subset (Fig. 5 f). In our study, the ratio of the CD8_TEM_T2ISG subset to the total CD8 + T cell population was significantly higher in patients positive for anti-topoisomerase I antibody (ATA) or ARA compared to those negative for these two antibodies (Fig. 5 g). Clinically, patients with SSc-ILD who are positive for ATA or ARA are known to have a greater risk of ILD progression compared to those positive for anti-centromere antibody 33 . Therefore, we next investigated whether IFN-γ–associated immunological changes in CD8 + T cells contribute to lung damage in progressive SSc-ILD. Publicly available scRNA-seq datasets of the lung tissue derived from patients with advanced SSc-ILD and healthy donors 34 were analyzed, followed by a detailed subset analysis of CD8 + T cells. UMAP plots of CD8 + T cells in lung tissues from SSc-ILD patients and healthy donors are shown in Extended Data Fig. 18a. Using previously reported marker genes 14 , CD8 + T cells in the lung tissue were divided into three groups: CD8 + T cells characterized by high expression of type 2 ISG (CD8_T_T2ISG), GZMH (CD8_T_GZMH), or GZMK (CD8_T_GZMK). Highly expressed genes in each cell population are shown in Extended Data Fig. 18b. Differential abundance analysis revealed that the CD8_T_T2ISG subset was enriched in the lung tissue of SSc-ILD patients (median log 2 -fold change: +0.7), whereas the CD8_T_GZMH (median log 2 -fold change: -1.6) and CD8_T_GZMK (median log 2 -fold change: -0.7) subsets showed a decrease compared to healthy donors (Fig. 5 h,i). The ratio of the CD8_T_T2ISG subset to the total lung CD8 + T cell population was significantly higher in patients with SSc-ILD (Fig. 5 j). Among CD8 + T cell populations in the lung, the module scores calculated using the set of IFN-γ signature genes from the Molecular Signatures Database (MSigDB) 35 were highest in the CD8_T_T2ISG subset (Fig. 5 k). The module scores representing the similarity of each cell subset to CD8_TEM_T2ISG were also highest in the CD8_T_T2ISG subset (Fig. 5 k). This similarity in cellular characteristics between peripheral blood and lung may explain that CD8 + T cell populations with IFN-γ signature genes, with their high migratory capacity, play a role in the pathophysiology of progressive ILD. In summary, this study identified distinct immune abnormalities in PBMCs from patients with SSc, underlying SRC or ILD complications. There was characteristic enrichment of the CD14_EGR1 subset in SRC and the CD8_TEM_T2ISG subset in SSc-ILD. Our findings further suggest that the CD14_EGR1 subset differentiates into the THBS1_Mac subset and contributes to the renal damage in patients with SRC. Clinically, EGR1 expression in monocytes may serve as a novel biomarker for disease progression of SRC. CD8_TEM_T2ISG has high migratory capacity and is implicated in progressive lung damage in patients with SSc-ILD (Fig. 6 ). Discussion The distribution of organ involvement in patients with autoimmune diseases is heterogeneous. In this study, we identified distinct immune abnormalities underlying the clinical heterogeneity of SSc, on the basis of single-cell transcriptome and surface protein profiles of PBMCs. Patients who were not receiving immunomodulatory drugs were recruited for this study. The enrichments of myeloid subsets in patients with SRC and of lymphoid subsets in patients with SSc-ILD highlight the distinct characteristics associated with these organ complications. In-depth subset analysis revealed the enrichment of a specific cellular population, CD14_EGR1, in the peripheral blood of patients with SRC. EGR1 is classified as an immediate early gene and encodes a transcription factor crucial for the differentiation of monocytes into macrophages 36 . TGF-β stimulation upregulates EGR1 expression in fibroblasts and increases collagen production 37 . Therefore, previous studies of EGR1 function in SSc have focused on its role in tissue fibroblasts 38 . In this study, EGR1 expression in peripheral monocytes was significantly upregulated, and the pathway analysis indicated that NF-κB and type 1/2 interferon-related signaling were enriched in the CD14_EGR1 subset. The synergistic effect of these signaling pathways results in enhanced activation of monocytes and macrophages, leading to increased production of pro-inflammatory cytokines 39 . Thus, the CD14_EGR1 subset is considered to be an activated monocyte subpopulation, suggesting another contributory role beyond tissue fibrosis in the pathogenesis of SRC. Two questions arise here: in the pathogenesis of SRC, how is the CD14_EGR1 subset induced peripherally, and how does this population contribute to organ damage? The pathogenesis of SRC is hypothesized to involve initial damage to the renal vascular endothelium, followed by activation of the renin–angiotensin–aldosterone system. A harmful cycle of renal artery constriction and increased renin production leads to severe hypertension and significant organ damage 30 . In monocytes and macrophages, angiotensin II induces the expression of EGR1 40 and activates NF-κB 41 . In the context of ischemia-reperfusion injury, pattern recognition receptors–mediated signaling triggered by damage–associated molecular patterns (DAMPs), such as HMGB1, activates the NF-κB pathway 42 and induces EGR1 expression 43 . These observations may answer the first question; factors associated with SRC, including angiotensin II, DAMPs, and ischemia-reperfusion injury, can be involved in the induction of the CD14_EGR1 subset in peripheral blood. With regard to the second question, CD11b 18 , CD4 19 , and CD38 20 , which are highly expressed surface antigens on the CD14_EGR1 subset, are known to facilitate monocyte adhesion, migration and differentiation. Considering gene expression and surface antigen profiles, the CD14_EGR1 subset is suggested to have an enhanced capacity for tissue migration and differentiation. In addition, trajectory analysis showed that the CD14_EGR1 subset differentiates into the THBS1_Mac subset in the kidney. These subsets share the activation state of several transcription factors which are major components of NF-κB, suggesting that angiotensin II, DAMPs, and ischemia-reperfusion injury may trigger the differentiation from the CD14_EGR1 subset into the THBS1_Mac subset in the kidney. THBS1 is a component of the extracellular matrix and plays a role in promoting cell adhesion, regulating angiogenesis, and modulating inflammatory responses 23 . In an animal model of renal ischemia-reperfusion injury, macrophages that infiltrate the kidney express elevated levels of THBS1, contributing to tubular damage 44 . Other genes highly expressed in THBS1_Mac, such as LRG1 25 and IL1B 24 , are also implicated in renal damage. Given these findings, the THBS1_Mac subset, differentiated from CD14_EGR1, may contribute to vascular and tubular damage, potentially explaining the pathogenesis of acute kidney injury in SRC. More interestingly from a clinical perspective, the expression of EGR1 in monocytes was highly upregulated at the onset of SRC, and it decreased following treatment. Currently, there are no suitable markers for monitoring disease progression in SRC. The changes in monocyte EGR1 expression observed over the clinical course of SRC implicate its potential as a biomarker for predicting progression of the disease. In patients with SSc-ILD, the CD8_TEM_T2ISG subset was enriched in peripheral blood. A subset with a similar gene expression profile, CD8_T_T2ISG, was also enriched in lung tissue. The CD8_TEM_T2ISG subset highly expressed IFN-γ response genes and showed increased expression of chemokine receptors such as CXCR3 and CCR5 . CXCL4, a ligand for CXCR3, is implicated in T cell migration 45 . Furthermore, serum levels of CXCL4 are elevated in patients with SSc and correlate with lung fibrosis 46 . CCR5 also facilitates the migration of CD8 + T cells through its interaction with ligands such as CCL3 and CCL4 32 . These data suggest that the CD8_TEM_T2ISG subset have high tissue migratory capacity, which is at least partly influenced by the CXCL4–CXCR3 or CCL3/CCL4–CCR5 axis during these cells’ migration into lung tissue. This hypothesis is further supported by the fact that the gene expression profiles of enriched CD8 + T cells in patients with SSc-ILD are similar between the peripheral blood and lung tissue. In addition, CD8 + T cells expressing high levels of CXCR3 contribute to lung injury in SSc-ILD 47 , implicating another role of the CD8_TEM_T2ISG subset in lung damage. The reduction in GZMH- and GZMB-expressing CD8 + T cells in the peripheral blood and lung tissue of patients with SSc-ILD suggests that lung involvement extends beyond inflammation, which may be associated with the minimal efficacy of glucocorticoid therapy in SSc-ILD 4 . Consistent with these findings, a high prevalence of the CD8_TEM_T2ISG subset was observed in patients with SSc-ILD who were positive for ATA or ARA, both of which are autoantibodies linked to a poorer pulmonary prognosis 33 . In conclusion, scRNA-seq identified key cellular subpopulations associated with specific organ manifestations. Specifically, the CD14_EGR1 subset in SRC and the CD8_TEM_T2ISG subset in SSc-ILD may play crucial roles in the respective organ damage. Time-series analysis and tissue perturbation studies of these cellular subsets in larger cohorts will further clarify the pathogenesis of SSc, and demonstrate the potential of these subsets as therapeutic targets. Methods Study participants Samples were collected from study participants who provided informed consent, in accordance with the Declaration of Helsinki and with approval from the ethics review board of the Graduate School of Medicine, Osaka University, Japan (No. 855). Consent was obtained to publish information such as age, sex, the name of medical center, and the diagnosis. Study participants received no compensation. Patients were diagnosed with systemic sclerosis according to the 2013 ACR/EULAR classification criteria 11 . The diagnosis was confirmed by at least two rheumatologists. Patient profiles Twenty-one patients diagnosed with SSc and six healthy donors were recruited for this study. None of the patients had received any immunosuppressive therapy. All patients were either admitted to or visited Osaka University Hospital, where they underwent a comprehensive assessment to rule out infectious diseases, neoplastic lesions, and any overlap of other systemic autoimmune diseases, before the 2013 ACR/EULAR classification criteria was applied. The presence of ILD was diagnosed based on clinical symptoms, computed tomography (CT) scan and pulmonary function tests. CT images were reviewed by at least two rheumatologists and one radiologist. SRC was diagnosed according to the UK Scleroderma Study Group guideline 48 . Samples were included in the SRC group if they were collected from SSc patients within three months of SRC onset or at any time after the onset. Blood pressure and mRSS were measured on the day of blood collection. Four patients with LN were recruited for some analyses. Systemic lupus erythematosus was diagnosed according to the 2019 EULAR/ACR classification criteria 49 , and LN was confirmed by renal biopsy 50 . PBMCs preparation Twenty milliliters of whole blood was collected into Na-heparin blood collection tubes (Terumo, Cat. No. VP-H070K). PBMCs were isolated using Leucosep (Greiner, Cat. No. 22788-013), then washed and resuspended in Cellbanker 1plus (ZENOAQ, Cat. No. CB023) to a concentration of 1.0 × 10 7 cells/mL before storage at − 150°C. Single-cell library construction (CITE-seq) CITE-seq was performed using the same antibodies as in our previous report 15 . Thawed PBMCs were treated with DNA-barcoded antibodies, and single-cell suspensions were processed using the 10x Genomics Chromium Controller (10x Genomics). The libraries were constructed according to the protocol outlined in the user guide of Chromium Single Cell 5’ Reagent Kits v2 (Dual Index, Cat. No. PN-1000263) (10x Genomics). Briefly, up to 10,000 labeled live cells per sample were individually loaded into the 10x Genomics platform without sample mixing to generate a barcoded cDNA library for individual cells. Data quality control was conducted using a Bioanalyzer system (Agilent). Individual libraries were pooled and sequenced on the HiSeq 2500 or Novaseq 6000 platform (Illumina) to analyze gene and surface protein expression. Sequence information of CITE-seq is summarized in Supplementary Table 8. Reference-based cell annotation and analysis of CITE-seq data Raw FASTQ files were aligned to the GRCh38 reference genome using CellRanger (version 6.0.6). Filtered HDF5 feature-barcode matrix files were generated using the CellRanger count to create a Seurat object. Data quality control, scaling, transformation, clustering, dimensionality reduction, differential expression analysis, and visualization were performed using the Seurat R package (V4.3.0). Cells with nFeature_RNA values less than 200 or greater than 5,000, or mitochondrial read percentages exceeding 20%, were removed. Data normalization and scaling were performed using the SCTransform function. Except for the time course analysis, only the initial samples collected during the clinical course were integrated. For the comparison between SRC, LN, and healthy donors, samples from patients diagnosed with SRC or LN were integrated with those from healthy donors. For the time course analysis of the SRC patient, samples collected at three different time points from the same individual were included. Each cell subpopulation was identified through two rounds of clustering. Initially, reference-based integration was applied to the query dataset using the public CITE-seq dataset of 211,000 human PBMCs as the reference 12 . The FindTransferAnchors function was employed to find anchors between the reference and the query datasets, using precomputed supervised PCA transformation for SCT-normalized data. The MapQuery function was used to transfer cell-type labels and protein data from the reference to the query datasets. Platelets and erythrocytes were excluded from the analysis. To identify subpopulations within each cell type, a second round of clustering was conducted on specific populations: monocytes (CD14 Mono, CD16 Mono, cDC1, and cDC2), CD8 + T cells (CD8 Naive, CD8 TCM, and CD8 TEM), CD4 + T cells (CD4 Naive, CD4 TCM, CD4 TEM, Treg, and CD4 CTL), B cells (B naive, B intermediate, and B memory), NK cells (NK and NK_CD56bright), and pDCs (pDC). The RunUMAP function was used to perform UMAP dimensional reduction with 30 precomputed spca dimensions. A nearest-neighbor graph using the 30 dimensions of the supervised PCA reduction was computed using the FindNeighbors function followed by the FindClusters function for cell clustering. The resultant UMAP was visualized using the DimPlot function. Each cluster was manually annotated using gene expression and surface protein data. Doublets were manually removed using surface protein data. PCA using cell composition of PBMCs PCA was performed using the PCA function in the FactoMineR package, with data scaled to unit variance. First, the proportion of each cell subpopulation defined in the subset analysis was calculated, along with other minor cell populations, all relative to the total PBMCs. The proportion of each cell subset was included as a variable in the PCA, except for populations with fewer than 100 total cells. Vectors representing each subpopulation were shown on a plane defined by the first two principal components (PC1 and PC2) using the fviz_pca_var function. Each study participant was represented as a single plot on the same plane according to their respective PC1 and PC2 values. Differential abundance analysis Differential abundance analysis was performed on PBMCs, monocytes, CD4 + T cells, and CD8 + T cells collected in this study, as well as lung CD8 + T cells derived from public data 34 , using the miloR (version 3.15) package. These analyses were performed to detect groups of cells that are differentially abundant in different conditions by modeling the number of cells within the neighborhoods of a k-nearest neighbor (KNN) graph 17 . To adjust for cell number, up to 1,000 cells were randomly selected from each sample for differential abundance analysis. The buildGraph function was first used to construct a KNN graph on the basis of precomputed supervised PCA with k = 5, using 30 principal components. Using the makeNhoods function, cells were then grouped into neighborhoods according to their connectivity over the KNN graph. To test for differential abundance, Milo fitted a negative binomial generalized linear model to the counts for each neighborhood using TMM normalization. Age was used as a covariate in the testNhoods function. For visualization, the log 2 -fold change in cell numbers between two conditions in each neighborhood was calculated. Nodes representing neighborhoods that were considered statistically significant (α < 0.2) were colored in red or blue. Differential gene expression analysis and gene set enrichment analysis In specific cell subsets, DEGs were identified using the FindMarkers function. For the characterization of DEGs, gene set enrichment analysis was conducted on genes exhibiting a log 2 -fold change greater than 0.5, using the Enrichr, a web-based tool for analyzing gene sets 51 . The MSigDB Hallmark 2020 35 or BioPlanet 2019 52 were employed as the dataset and adjusted P-values for each pathway were calculated by the Benjamini–Hochberg method. TRRUST Transcription Factors 2019 28 was used to determine the adjusted P-values for each transcription factor–related pathway. Pathways not related to humans were excluded from the analysis. Preparation of kidney cells and whole-blood leukocytes for Abseq Renal tissue was obtained by needle biopsy from one patient at the onset of SRC (patient ID: SSc-19). The tissue was immediately washed with phosphate-buffered saline and processed into single cell suspension using the Tumor Dissociation Kit (human, Miltenyi Biotec). Enzyme R was excluded to preserve the cell-surface epitope. The sample was cut into small pieces with a maximal dimension of approximately 2 mm, combined with the enzyme mixture, and shaken at 37°C in a water bath at 160 rpm for 45 minutes. The sample was treated with DNase for 5 minutes at room temperature. No steps were taken to lyse red blood cells or remove dead cells. Two milliliters of Whole blood was collected from the same patient in an EDTA-2Na blood collection tube (Terumo, Cat. No. VP-Na052K), and the leukocytes were isolated using Polymorphprep (Serumwerk, Cat. No. 1895). The sample was washed and resuspended with Cellbanker 1plus (ZENOAQ, Cat. No. CB023) to a concentration of 2.0 × 10 6 cell/mL prior to scRNA-seq experiments. Single-cell library construction (Abseq) Renal cells and total peripheral leukocytes were processed separately through the BD Rhapsody Express System (BD Biosciences, Catalog No. 665915). Thirty-five DNA-barcoded antibodies (detailed in Supplementary Table 10) were added to each cell suspension. Abseq libraries were constructed using WTA Reagent Kits (BD Biosciences, Cat. No. 665915). Approximately 10,000 peripheral leukocytes were loaded into the BD Rhapsody platform. All obtained renal cells were processed in an identical manner. Data quality control was performed using the Bioanalyzer (Agilent). The libraries were pooled for sequencing on the HiSeq 2500 or Novaseq 6000 platform (Illumina) to analyze gene and surface protein expression. Sequence information of Abseq is summarized in Supplementary Table 9. Manual cell annotation and analysis of Abseq data Raw FASTQ files were aligned to the GRCh38 reference genome using the BD Rhapsody Sequence Analysis Pipeline (version 1.12). Distribution-based error correction-adjusted molecule counts were presented as gene expression data tables to establish a Seurat object. The Seurat R package (V4.3.0) was used for data quality control, scaling, transformation, clustering, dimensionality reduction, differential expression analysis, and visualization. A total of 16,081 cells were selected for further analysis on the basis of unique molecular identifiers for each cell and percentages of mitochondrial reads. Peripheral leukocytes with nFeature_RNA values less than 200 or greater than 5,000, or mitochondrial read percentages exceeding 20%, were excluded from the analysis. Similarly, kidney cells were removed if they had nFeature_RNA values less than 200 or greater than 5,000, or mitochondrial read percentages exceeding 40%. The data were normalized and scaled using the SCTransform function. The data from peripheral blood and kidney samples were integrated using reciprocal PCA. The RunUMAP function was used for UMAP dimensional reduction with 30 precomputed PCA dimensions. A nearest-neighbor graph was then constructed using the 30 PCA dimensions with the FindNeighbors function, followed by clustering using the FindClusters function. The UMAP was visualized using the DimPlot function. Each cluster was manually annotated using gene expression and surface protein data. Platelets and erythrocytes were removed from the analysis. Doublets were also removed using cell-surface protein data. Pseudotime analysis The pseudotime of each cell and the cell trajectory were calculated using the Monocle 3 package 26 . The previously annotated Seurat object was imported into Monocle 3. Using the learn_graph function, we fitted a principal graph and plot the graph through the UMAP coordinates. The order_cells function was employed to calculate the pseudotime for each cell, with the root node set to the immature monocyte population characterized by high expression of S100A12 and low expression of HLA-DRB1 27 (Extended Data Fig. 14). The cell trajectory was visualized using the plot_cells function. Public data analysis The scRNA-seq data of lung cells derived from SSc patients with advanced ILD and healthy donors were obtained from the gene expression omnibus under accession numbers GSE128169 and GSE128033. We used only lung tissue samples, excluding those labeled with hashtags designated for sample multiplexing. The Seurat object was subsequently created using the CreateSeuratObject function. The quality control of scRNA-seq data was performed as previously reported 34 . Data were normalized and scaled using the SCTransform function, followed by data integration using reciprocal PCA. The RunUMAP function was used for UMAP dimensional reduction with 30 precomputed PCA dimensions. A nearest-neighbor graph using the 30 dimensions of the PCA reduction was computed using the FindNeighbors function, followed by clustering using the FindClusters function. The UMAP was visualized using the DimPlot function. Each cluster was manually annotated using gene expression data. Module scoring Module scores for each cell were calculated using the AddModuleScore function. To assess the expression of type II ISGs in lung CD8 + T cells, module scores were calculated using the “Interferon Gamma Response” gene set from MSigDB Hallmark 2020. To evaluate the similarity of each lung CD8 + T cell subset to the peripheral CD8 + T cell subpopulation, CD8_TEM_T2ISG, module scores were calculated using DEGs (fold change >0.5) of CD8_TEM_T2ISG. Gene scores for each subset were visualized using the Dotplot function according to cell-based scores. Declarations Data availability Count matrix data will be available at the Japanese Genotype-phenotype Archive (JGA) with unique accession codes JGAS000XXX and JGAS000XXX (https://ddbj.nig.ac.jp/resource/jga-study/JGAS000XXX). The GRCh38 reference genome was obtained from NCBI (https://www.ncbi.nlm.nih.gov/assembly/GCF_000001405.26/). Code availability Experimental protocols, data analysis pipelines, analysis steps, functions, and parameters used are described in the Methods section. Custom code used in the paper is available at GitHub. (https://github.com/ShimagamiH/ShimagamiH_SSc_scRNAseq). References Cho JH, Feldman M (2015) Heterogeneity of autoimmune diseases: pathophysiologic insights from genetics and implications for new therapies. Nat Med 21:730–738. https://doi.org:10.1038/nm.3897 Volkmann ER, Andreasson K, Smith V (2023) Systemic sclerosis. Lancet 401:304–318. https://doi.org:10.1016/S0140-6736(22)01692-0 Rubio-Rivas M, Royo C, Simeon CP, Corbella X, Fonollosa V (2014) Mortality and survival in systemic sclerosis: systematic review and meta-analysis. Semin Arthritis Rheum 44:208–219. https://doi.org:10.1016/j.semarthrit.2014.05.010 Pope JE et al (2023) State-of-the-art evidence in the treatment of systemic sclerosis. Nat Rev Rheumatol 19:212–226. https://doi.org:10.1038/s41584-023-00909-5 Apostolidis SA et al (2018) Single Cell RNA Sequencing Identifies HSPG2 and APLNR as Markers of Endothelial Cell Injury in Systemic Sclerosis Skin. Front Immunol 9:2191. https://doi.org:10.3389/fimmu.2018.02191 Gur C et al (2022) LGR5 expressing skin fibroblasts define a major cellular hub perturbed in scleroderma. Cell 185, 1373–1388 e1320 https://doi.org:10.1016/j.cell.2022.03.011 Tabib T et al (2021) Myofibroblast transcriptome indicates SFRP2(hi) fibroblast progenitors in systemic sclerosis skin. Nat Commun 12:4384. https://doi.org:10.1038/s41467-021-24607-6 Xue D et al (2022) Expansion of Fcgamma Receptor IIIa-Positive Macrophages, Ficolin 1-Positive Monocyte-Derived Dendritic Cells, and Plasmacytoid Dendritic Cells Associated With Severe Skin Disease in Systemic Sclerosis. Arthritis Rheumatol 74:329–341. https://doi.org:10.1002/art.41813 Gaydosik AM et al (2021) Single-cell transcriptome analysis identifies skin-specific T-cell responses in systemic sclerosis. Ann Rheum Dis 80:1453–1460. https://doi.org:10.1136/annrheumdis-2021-220209 Nishide M, Shimagami H, Kumanogoh A (2024) Single-cell analysis in rheumatic and allergic diseases: insights for clinical practice. Nat Rev Immunol. https://doi.org:10.1038/s41577-024-01043-3 van den Hoogen F et al (2013) 2013 classification criteria for systemic sclerosis: an American College of Rheumatology/European League against Rheumatism collaborative initiative. Arthritis Rheum 65:2737–2747. https://doi.org:10.1002/art.38098 Hao Y et al (2021) Integrated analysis of multimodal single-cell data. Cell 184, 3573–3587 e3529 https://doi.org:10.1016/j.cell.2021.04.048 Nehar-Belaid D et al (2020) Mapping systemic lupus erythematosus heterogeneity at the single-cell level. Nat Immunol 21:1094–1106. https://doi.org:10.1038/s41590-020-0743-0 Zheng L et al (2021) Pan-cancer single-cell landscape of tumor-infiltrating T cells. Science 374, abe6474 https://doi.org:10.1126/science.abe6474 Nishide M et al (2023) Single-cell multi-omics analysis identifies two distinct phenotypes of newly-onset microscopic polyangiitis. Nat Commun 14:5789. https://doi.org:10.1038/s41467-023-41328-0 Wu X et al (2022) Single-Cell Sequencing of Immune Cell Heterogeneity in IgG4-Related Disease. Front Immunol 13:904288. https://doi.org:10.3389/fimmu.2022.904288 Dann E, Henderson NC, Teichmann SA, Morgan MD, Marioni JC (2022) Differential abundance testing on single-cell data using k-nearest neighbor graphs. Nat Biotechnol 40:245–253. https://doi.org:10.1038/s41587-021-01033-z Lee SJ et al (2014) TLR4-mediated expression of Mac-1 in monocytes plays a pivotal role in monocyte adhesion to vascular endothelium. PLoS ONE 9:e104588. https://doi.org:10.1371/journal.pone.0104588 Zhen A et al (2014) CD4 ligation on human blood monocytes triggers macrophage differentiation and enhances HIV infection. J Virol 88:9934–9946. https://doi.org:10.1128/JVI.00616-14 Musso T et al (2001) CD38 expression and functional activities are up-regulated by IFN-gamma on human monocytes and monocytic cell lines. J Leukoc Biol 69:605–612 Li C, Hua K (2022) Dissecting the Single-Cell Transcriptome Network of Immune Environment Underlying Cervical Premalignant Lesion, Cervical Cancer and Metastatic Lymph Nodes. Front Immunol 13:897366. https://doi.org:10.3389/fimmu.2022.897366 Zimmerman KA et al (2019) Single-Cell RNA Sequencing Identifies Candidate Renal Resident Macrophage Gene Expression Signatures across Species. J Am Soc Nephrol 30:767–781. https://doi.org:10.1681/ASN.2018090931 Kaur S et al (2021) Functions of Thrombospondin-1 in the Tumor Microenvironment. Int J Mol Sci 22. https://doi.org:10.3390/ijms22094570 Wang H, Wu J, Ma L, Bai Y, Liu J (2023) The role of interleukin – 1 family in fibrotic diseases. Cytokine 165:156161. https://doi.org:10.1016/j.cyto.2023.156161 Hong Q et al (2019) LRG1 Promotes Diabetic Kidney Disease Progression by Enhancing TGF-beta-Induced Angiogenesis. J Am Soc Nephrol 30:546–562. https://doi.org:10.1681/ASN.2018060599 Trapnell C et al (2014) The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells. Nat Biotechnol 32:381–386. https://doi.org:10.1038/nbt.2859 Chen ST et al (2022) A shift in lung macrophage composition is associated with COVID-19 severity and recovery. Sci Transl Med 14:eabn5168. https://doi.org:10.1126/scitranslmed.abn5168 Han H et al (2018) TRRUST v2: an expanded reference database of human and mouse transcriptional regulatory interactions. Nucleic Acids Res 46:D380–D386. https://doi.org:10.1093/nar/gkx1013 Sun SC (2017) The non-canonical NF-kappaB pathway in immunity and inflammation. Nat Rev Immunol 17:545–558. https://doi.org:10.1038/nri.2017.52 Woodworth TG, Suliman YA, Li W, Furst DE, Clements P (2016) Scleroderma renal crisis and renal involvement in systemic sclerosis. Nat Rev Nephrol 12:678–691. https://doi.org:10.1038/nrneph.2016.124 Colditz IG, Watson DL (1992) The effect of cytokines and chemotactic agonists on the migration of T lymphocytes into skin. Immunology 76:272–278 Nagarsheth N, Wicha MS, Zou W (2017) Chemokines in the cancer microenvironment and their relevance in cancer immunotherapy. Nat Rev Immunol 17:559–572. https://doi.org:10.1038/nri.2017.49 Hoffmann-Vold AM et al (2017) Cardiopulmonary Disease Development in Anti-RNA Polymerase III-positive Systemic Sclerosis: Comparative Analyses from an Unselected, Prospective Patient Cohort. J Rheumatol 44:459–465. https://doi.org:10.3899/jrheum.160867 Valenzi E et al (2019) Single-cell analysis reveals fibroblast heterogeneity and myofibroblasts in systemic sclerosis-associated interstitial lung disease. Ann Rheum Dis 78:1379–1387. https://doi.org:10.1136/annrheumdis-2018-214865 Liberzon A et al (2015) The Molecular Signatures Database (MSigDB) hallmark gene set collection. Cell Syst 1:417–425. https://doi.org:10.1016/j.cels.2015.12.004 Nguyen HQ, Hoffman-Liebermann B, Liebermann DA (1993) The zinc finger transcription factor Egr-1 is essential for and restricts differentiation along the macrophage lineage. Cell 72:197–209. https://doi.org:10.1016/0092-8674(93)90660-i Chen SJ et al (2006) The early-immediate gene EGR-1 is induced by transforming growth factor-beta and mediates stimulation of collagen gene expression. J Biol Chem 281:21183–21197. https://doi.org:10.1074/jbc.M603270200 Bhattacharyya S et al (2008) Smad-independent transforming growth factor-beta regulation of early growth response-1 and sustained expression in fibrosis: implications for scleroderma. Am J Pathol 173:1085–1099. https://doi.org:10.2353/ajpath.2008.080382 Qiao Y et al (2013) Synergistic activation of inflammatory cytokine genes by interferon-gamma-induced chromatin remodeling and toll-like receptor signaling. Immunity 39:454–469. https://doi.org:10.1016/j.immuni.2013.08.009 Meng Y, Chen C, Tian C, Du J, Li HH (2015) Angiotensin II-induced Egr-1 expression is suppressed by peroxisome proliferator-activated receptor-gamma ligand 15d-PGJ(2) in macrophages. Cell Physiol Biochem 35:689–698. https://doi.org:10.1159/000369729 Kranzhofer R, Browatzki M, Schmidt J, Kubler W (1999) Angiotensin II activates the proinflammatory transcription factor nuclear factor-kappaB in human monocytes. Biochem Biophys Res Commun 257:826–828. https://doi.org:10.1006/bbrc.1999.0543 Alaaeldin R et al (2023) Azilsartan Modulates HMGB1/NF-kappaB/p38/ERK1/2/JNK and Apoptosis Pathways during Renal Ischemia Reperfusion Injury. Cells 12 https://doi.org:10.3390/cells12010185 Yan SF et al (2000) Egr-1, a master switch coordinating upregulation of divergent gene families underlying ischemic stress. Nat Med 6:1355–1361. https://doi.org:10.1038/82168 Wang W, Ren X, Chen X, Hong Q, Cai G (2024) Integrin beta1-rich extracellular vesicles of kidney recruit Fn1 + macrophages to aggravate ischemia-reperfusion-induced inflammation. JCI Insight 9. https://doi.org:10.1172/jci.insight.169885 Mueller A et al (2008) CXCL4-induced migration of activated T lymphocytes is mediated by the chemokine receptor CXCR3. J Leukoc Biol 83:875–882. https://doi.org:10.1189/jlb.1006645 van Bon L et al (2014) Proteome-wide analysis and CXCL4 as a biomarker in systemic sclerosis. N Engl J Med 370:433–443. https://doi.org:10.1056/NEJMoa1114576 Fujii H, Hasegawa M, Takehara K, Mukaida N, Sato S (2002) Abnormal expression of intracellular cytokines and chemokine receptors in peripheral blood T lymphocytes from patients with systemic sclerosis. Clin Exp Immunol 130:548–556. https://doi.org:10.1046/j.1365-2249.2002.02017.x Lynch BM et al (2016) UK Scleroderma Study Group (UKSSG) guidelines on the diagnosis and management of scleroderma renal crisis. Clin Exp Rheumatol 34:106–109 Aringer M et al (2019) European League Against Rheumatism/American College of Rheumatology Classification Criteria for Systemic Lupus Erythematosus. Arthritis Rheumatol 71, 1400–1412 (2019). https://doi.org:10.1002/art.40930 Weening JJ et al (2004) The classification of glomerulonephritis in systemic lupus erythematosus revisited. J Am Soc Nephrol 15:241–250. https://doi.org:10.1097/01.asn.0000108969.21691.5d Xie Z et al (2021) Gene Set Knowledge Discovery with Enrichr. Curr Protoc 1:e90. https://doi.org:10.1002/cpz1.90 Huang R et al (2019) The NCATS BioPlanet - An Integrated Platform for Exploring the Universe of Cellular Signaling Pathways for Toxicology, Systems Biology, and Chemical Genomics. Front Pharmacol 10:445. https://doi.org:10.3389/fphar.2019.00445 Additional Declarations Yes there is potential Competing Interest. AK has received grant support from Chugai Pharmaceutical Co, Ltd. KN, HM, SM, RO, KH are employed by Chugai Pharmaceutical Co, Ltd. and KN, HM, SM, RO, KH also hold stocks in the company. The remaining authors declare no competing interests. Supplementary Files 240712SupplementaryMaterialsShimagamiHNatureCommunications.docx Cite Share Download PDF Status: Published Journal Publication published 17 Jun, 2025 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4728677","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":329143217,"identity":"5e8166e3-8c9b-4330-818e-30bd8ebfa137","order_by":0,"name":"Masayuki 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Medicine","correspondingAuthor":false,"prefix":"","firstName":"Atsushi","middleName":"","lastName":"Takahashi","suffix":""},{"id":329143234,"identity":"633c1470-46e6-4223-b5a3-bc2788e9aca0","order_by":17,"name":"Masayuki Mizui","email":"","orcid":"https://orcid.org/0000-0003-2543-8108","institution":"Beth Israel Deaconess Medical Center / Harvard Medical School","correspondingAuthor":false,"prefix":"","firstName":"Masayuki","middleName":"","lastName":"Mizui","suffix":""},{"id":329143235,"identity":"6b975513-e79c-40b3-9d28-1fb1fff71a7b","order_by":18,"name":"Ryusuke Omiya","email":"","orcid":"","institution":"Graduate School of Medicine, Osaka University","correspondingAuthor":false,"prefix":"","firstName":"Ryusuke","middleName":"","lastName":"Omiya","suffix":""},{"id":329143236,"identity":"794c28bb-a3be-4069-bda6-9a08c180cc4e","order_by":19,"name":"Yoshitaka Isaka","email":"","orcid":"https://orcid.org/0000-0002-0820-7167","institution":"Osaka University Graduate School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Yoshitaka","middleName":"","lastName":"Isaka","suffix":""},{"id":329143237,"identity":"9b31da97-dc75-4cda-9b4e-7d74a55046aa","order_by":20,"name":"Yukinori Okada","email":"","orcid":"https://orcid.org/0000-0002-0311-8472","institution":"The University of Tokyo","correspondingAuthor":false,"prefix":"","firstName":"Yukinori","middleName":"","lastName":"Okada","suffix":""},{"id":329143238,"identity":"1fe042c6-0cd6-47b1-8e49-d9b718627a78","order_by":21,"name":"Kunihiro Hattori","email":"","orcid":"","institution":"Graduate School of Medicine, Osaka University","correspondingAuthor":false,"prefix":"","firstName":"Kunihiro","middleName":"","lastName":"Hattori","suffix":""},{"id":329143239,"identity":"3baed516-5e1c-4b33-8903-8edab8efb804","order_by":22,"name":"Masashi Narazaki","email":"","orcid":"","institution":"Osaka University","correspondingAuthor":false,"prefix":"","firstName":"Masashi","middleName":"","lastName":"Narazaki","suffix":""},{"id":329143240,"identity":"5a301a49-f878-458d-8c73-dea7fb2fe227","order_by":23,"name":"Atsushi Kumanogoh","email":"","orcid":"https://orcid.org/0000-0003-4749-7117","institution":"Osaka University","correspondingAuthor":false,"prefix":"","firstName":"Atsushi","middleName":"","lastName":"Kumanogoh","suffix":""}],"badges":[],"createdAt":"2024-07-12 07:30:48","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4728677/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4728677/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41467-025-60034-7","type":"published","date":"2025-06-17T04:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":60809166,"identity":"e2db999d-2777-4bc2-8928-481c54f30e98","added_by":"auto","created_at":"2024-07-22 10:40:48","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":159873,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComprehensive single-cell analysis reveals distinct immune profiles in patients with systemic sclerosis and healthy donors.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(a)\u003c/strong\u003e Overview of the experimental workflow. SSc, systemic sclerosis; HD, healthy donor; PBMC, peripheral blood mononuclear cells; scRNA-seq, single-cell RNA sequencing; SRC, scleroderma renal crisis; ILD, interstitial lung disease. \u003cstrong\u003e(b)\u003c/strong\u003e UMAP plots displaying CITE-seq data from PBMCs derived from patients with SSc (n = 21, left) and HDs (n = 6, right), annotated with reference mapping. Each plot shows 30,000 randomly selected cells. Mono, monocytes; cDC, conventional dendritic cells; ASDC, \u003cem\u003eAXL\u003c/em\u003e\u003csup\u003e+\u003c/sup\u003e dendric cells; pDC, plasmacytoid dendritic cells; TCM, central memory T cells; TEM, effector memory T cells; CTL, cytotoxic T lymphocytes; Treg, regulatory T cells; MAIT, mucosal associated invariant T cells; dnT, double negative T cells; gdT, gamma-delta T cells; PB, plasmablasts; NK, natural killer cells; ILC, innate lymphoid cells; Proliferating, proliferating cells; HSPC, hematopoietic stem and progenitor cells. Percentages of myeloid cell populations \u003cstrong\u003e(c)\u003c/strong\u003e and lymphoid cell populations \u003cstrong\u003e(d)\u003c/strong\u003e relative to the total number of PBMCs derived from patients with SSc (purple) or HDs (black) are shown. Values represent means with standard error of the mean (SEM). Statistical analysis was conducted using the two-sided Mann–Whitney U test for multiple comparisons, with adjustments for multiple testing using the Bonferroni correction. \u003cstrong\u003e(e)\u003c/strong\u003e Principal component analysis on the proportions of each cell subset relative to the total PBMCs. Each subset was defined on the basis of CITE-seq data as shown in \u003cstrong\u003eExtended Data Figs. 2–7\u003c/strong\u003e. In the two-dimensional plot, vectors are derived from Principal Component (PC) 1 and PC2 for each cell population. The vectors for myeloid cell populations are colored in red, those for lymphoid cell populations are colored in orange, and that for HSPC is colored in gray. Vectors with lengths greater than 0.3 are displayed. \u003cstrong\u003e(f)\u003c/strong\u003e Distribution of values of PC1 and PC2 for each study participant. In the left panel, dots represent individual study participants, with SSc patients shown in purple and HDs in black. The mean vector for SSc patients is shown with a purple arrow, and for HDs with a black arrow. On the right panel, each SSc patient is indicated by a colored dot: red for SRC patients, orange for ILD patients without SRC (ILD w/o SRC), and blue for patients without both SRC and ILD (No SRC, No ILD); HDs are represented by black dots. Arrows show the mean vectors for each group, colored to match the dots of corresponding patients or HDs.\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-4728677/v1/fbc551ac9826d9611b18953e.png"},{"id":60809167,"identity":"6f2ce51d-f8f8-4837-9a7c-cafb30027108","added_by":"auto","created_at":"2024-07-22 10:40:48","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":178736,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDifferential abundance analysis on PBMCs derived from SSc patients with scleroderma renal crisis and interstitial lung disease.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(a) \u003c/strong\u003eNeighborhood graph of PBMCs derived from SSc patients, generated using Milo differential abundance testing. Nodes represent neighborhoods of the PBMCs. The color scale indicates the log\u003csub\u003e2\u003c/sub\u003e-fold difference between SRC patients and the other SSc patients. Neighborhoods showing an increase in SRC are colored in red, while those with a decrease are in blue.\u0026nbsp;\u003cstrong\u003e(b) \u003c/strong\u003eBeeswarm\u0026nbsp;and box plots showing the distribution of log\u003csub\u003e2\u003c/sub\u003e-fold differences in neighborhoods in different cell type clusters. Colors are shown similar to \u003cstrong\u003e(a)\u003c/strong\u003e. Box plots show median and interquartile range (IQR); the lower and upper hinges correspond to the first and third quartiles. The upper whisker extends from the hinge to the largest value that is no further than 1.5*IQR from the hinge. The lower whisker extends from the hinge to the smallest value that is at most 1.5*IQR from the hinge. \u003cstrong\u003e(c)\u003c/strong\u003e Neighborhood graph of PBMCs derived from SSc patients indicating the log\u003csub\u003e2\u003c/sub\u003e-fold difference between ILD without SRC patients and the other SSc patients. Neighborhoods showing an increase in ILD without SRC are shown in red, while those with a decrease are in blue.\u0026nbsp;\u003cstrong\u003e(d) \u003c/strong\u003eBeeswarm\u0026nbsp;and box plots showing the distribution of log\u003csub\u003e2\u003c/sub\u003e-fold differences in neighborhoods in different cell-type clusters. Colors are shown similar to \u003cstrong\u003e(c)\u003c/strong\u003e. Box plots are created in a similar fashion as in \u003cstrong\u003e(b)\u003c/strong\u003e.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-4728677/v1/db684f889dc13d1d3af6fc77.png"},{"id":60809171,"identity":"b999ac85-2647-4dff-b940-8a3cf89982e6","added_by":"auto","created_at":"2024-07-22 10:40:48","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":157784,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCD14\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e+\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e monocytes with \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eEGR1 \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eexpression are specifically enriched in PBMCs from patients with scleroderma renal crisis.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(a)\u003c/strong\u003e UMAP plots displaying the monocyte subpopulations derived from SSc patients with SRC (SRC; n = 4, left) or without SRC (SSc w/o SRC; n = 17, right). Each plot shows 8,000 randomly selected cells. \u003cstrong\u003e(b)\u003c/strong\u003e Stacked bar graph showing the relative contribution of the disease states to the total count of each cell type.\u0026nbsp; The ratio of each cell population to total monocytes was calculated. The ratios were subsequently averaged in each disease state and normalized to a sum of 100% as the relative contribution.\u003cstrong\u003e (c) \u003c/strong\u003eNeighborhood graph of monocytes derived from SSc patients generated using Milo differential abundance\u0026nbsp;testing. The color scale indicates the log\u003csub\u003e2\u003c/sub\u003e-fold difference between patients with SRC and those without SRC. Neighborhoods showing an increase in SRC are colored in red, while those with a decrease are in blue.\u0026nbsp;\u003cstrong\u003e(d) \u003c/strong\u003eBeeswarm\u0026nbsp;and box plots showing the distribution of log\u003csub\u003e2\u003c/sub\u003e-fold differences in neighborhoods in different cell type clusters. Colors are shown similar to \u003cstrong\u003e(c)\u003c/strong\u003e. Box plots are created in a similar fashion as in \u003cstrong\u003eFig. 2b.\u003c/strong\u003e \u003cstrong\u003e(e)\u003c/strong\u003e Percentages of CD14_EGR1, CD14_ISG, and CD16_ISG subsets in the total monocyte population derived from patients with SRC, patients with lupus nephritis (LN), and HDs. Values represent means with SEM. *\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05, **\u003cem\u003eP\u003c/em\u003e\u0026lt;0.01, Dunn’s multiple comparison test after Kruskal–Wallis test. \u003cstrong\u003e(f)\u003c/strong\u003e Violin plots showing \u003cem\u003eEGR1\u003c/em\u003e and \u003cem\u003eISG15\u003c/em\u003e expression in monocytes derived from patients with SRC, patients with LN, and HDs.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-4728677/v1/04259e4c0b0d2193fd29d7ad.png"},{"id":60810567,"identity":"1cebf852-60c3-4ee8-82ac-0f0105ca9c4f","added_by":"auto","created_at":"2024-07-22 10:48:48","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":179016,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eInvolvement of the CD14_EGR1 subset in tissue damage and its potential as a biomarker for the progression of scleroderma renal crisis.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(a)\u003c/strong\u003e Gene set enrichment analysis of differentially expressed genes (DEGs) in the CD14_EGR1 subset using the Molecular Signatures Database (MSigDB). \u003cem\u003eP\u003c/em\u003e-values for each pathway were calculated using the Benjamini–Hochberg method.\u003cstrong\u003e (b) \u003c/strong\u003eThe feature plots of \u003cem\u003eEGR1\u003c/em\u003e, \u003cem\u003eIL1B\u003c/em\u003e, \u003cem\u003eCCR1\u003c/em\u003e, and \u003cem\u003eSGK1\u003c/em\u003e in monocytes of SSc patients divided into those with SRC (SRC) or without SRC (SSc w/o SRC). \u003cstrong\u003e(c)\u003c/strong\u003eUMAP plots showing the monocyte, macrophage and cDC subpopulations derived from the peripheral blood (left) and kidney (right) of a SSc patient (Patient ID: SSc-19) at the onset of SRC. \u003cstrong\u003e(d) \u003c/strong\u003eBalloon plot showing highly expressed genes in each subpopulation shown in \u003cstrong\u003e(c)\u003c/strong\u003e. \u003cstrong\u003e(e)\u003c/strong\u003e Feature plots showing \u003cem\u003eEGR1\u003c/em\u003e (left) and \u003cem\u003eTHBS1\u003c/em\u003e (right) expression at the onset of SRC. The UMAP plot shows macrophage, cDC and monocyte subpopulations derived from the peripheral blood and kidney tissue. \u003cstrong\u003e(f)\u003c/strong\u003e Cell trajectory analysis on the peripheral blood and kidney tissue at the onset of SRC. The red line on the UMAP plot represents the cell trajectory. The root node is marked with a circle. Each cell is colored according to its respective pseudotime. \u003cstrong\u003e(g)\u003c/strong\u003e Gene set enrichment analysis of DEGs in CD14_EGR1 (left) and THBS1_Mac (right) subsets using transcriptional regulatory relationships unraveled by sentence-based text-mining (TRRUST) Transcriptional Factor 2019. \u003cem\u003eP\u003c/em\u003e-values for each pathway were calculated using the Benjamini–Hochberg method. \u003cstrong\u003e(h)\u003c/strong\u003e Percentage of the CD14_EGR1 subset to the total monocyte populations in SSc patients classified by serum autoantibody status. ARA, anti-RNA polymerase III antibody. Values represent means with SEM. *\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05, Dunn’s multiple comparison test between ARA (+) SRC group and each of the other groups after Kruskal–Wallis test. \u003cstrong\u003e(i)\u003c/strong\u003e The violin plot of the expression levels of \u003cem\u003eEGR1\u003c/em\u003e in monocytes before SRC development (before), at its onset (onset), and after treatment (after).\u003cstrong\u003e (j)\u003c/strong\u003e Correlation between the percentage of the CD14_EGR1 subset to total peripheral monocyte populations and the modified Rodnan skin score (mRSS, left) or systolic blood pressure (sBP, right). Correlations and \u003cem\u003eP\u003c/em\u003e-values were calculated using Spearman’s correlation coefficient (r).\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-4728677/v1/33735e5991af1c1e6ea7833c.png"},{"id":60809168,"identity":"92ce3e25-0ec1-47e1-8d98-719737aff230","added_by":"auto","created_at":"2024-07-22 10:40:48","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":152382,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIncrease of the CD8\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e+\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e T cell subpopulation with type II interferon signature genes is implicated in progressive SSc-ILD.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(a)\u003c/strong\u003e UMAP plots showing the peripheral CD8\u003csup\u003e+\u003c/sup\u003e T cell subpopulations derived from SSc patients with ILD (SSc-ILD; n = 12, left) or without ILD (SSc w/o ILD; n = 9, right). Each plot shows 4,000 randomly selected cells. \u003cstrong\u003e(b) \u003c/strong\u003eStacked bar graph showing the relative contribution of the disease states to the total count of each cell type. The graph is created in a similar fashion as in \u003cstrong\u003eFig. 3b\u003c/strong\u003e.\u003cstrong\u003e (c)\u003c/strong\u003e Neighborhood graph of peripheral CD8\u003csup\u003e+\u003c/sup\u003e T cells derived from patients with SSc, generated using Milo differential abundance testing. The color scale indicates the log\u003csub\u003e2\u003c/sub\u003e-fold difference between SSc-ILD and SSc w/o ILD. Neighborhoods showing an increase in SSc-ILD are colored in red, while those with a decrease are in blue.\u0026nbsp;\u003cstrong\u003e(d) \u003c/strong\u003eBeeswarm\u0026nbsp;and box plots showing the distribution of log\u003csub\u003e2\u003c/sub\u003e-fold differences in neighborhoods in different cell type clusters. Colors are shown similar to \u003cstrong\u003e(c)\u003c/strong\u003e. Box plots are created in a similar fashion as in \u003cstrong\u003eFig. 2b\u003c/strong\u003e.\u0026nbsp;\u003cstrong\u003e(e)\u003c/strong\u003e Gene set enrichment analysis of DEGs in the CD8_TEM_T2ISG subset using the MSigDB. \u003cem\u003eP\u003c/em\u003e-values for each pathway were calculated using the Benjamini–Hochberg method. \u003cstrong\u003e(f)\u003c/strong\u003e Expression of the chemokine receptors across each peripheral CD8\u003csup\u003e+\u003c/sup\u003e T cell subpopulation. \u003cstrong\u003e(g)\u003c/strong\u003e Percentage of the CD8_TEM_T2ISG subset in the total peripheral CD8\u003csup\u003e+\u003c/sup\u003e T cell populations in individual patients with SSc-ILD, divided into those positive for anti-topoisomerase I antibody (ATA) or ARA, and those negative for these two antibodies. Values represent means with SEM. *\u003cem\u003eP\u003c/em\u003e \u0026lt;0.05, two-sided Mann–Whitney U test. \u003cstrong\u003e(h)\u003c/strong\u003e Neighborhood graph of lung CD8\u003csup\u003e+\u003c/sup\u003e T cells derived from patients with advanced SSc-ILD or HDs, generated using Milo differential abundance analysis. The color scale indicates the log\u003csub\u003e2\u003c/sub\u003e-fold difference between SSc-ILD and HDs. Neighborhoods showing an increase in SSc-ILD are colored in red, while those with a decrease are in blue. \u003cstrong\u003e(i)\u003c/strong\u003e Beeswarm\u0026nbsp;and box plots showing the distribution of log\u003csub\u003e2\u003c/sub\u003e-fold differences in neighborhoods in different cell-type clusters. Colors are shown similar to \u003cstrong\u003e(h)\u003c/strong\u003e. Box plots are created in a similar fashion as in \u003cstrong\u003eFig. 2b\u003c/strong\u003e. \u003cstrong\u003e(j) \u003c/strong\u003ePercentage of the CD8_T_T2ISG subset in the total CD8\u003csup\u003e+\u003c/sup\u003e T cell populations in the lungs of patients with SSc-ILD and HDs. Values represent means with SEM. *\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05, two-sided Mann–Whitney U test. \u003cstrong\u003e(k)\u003c/strong\u003e The module score for each lung CD8\u003csup\u003e+\u003c/sup\u003e T cell subset calculated using the human gene set “HALLMARK_INTERFERON_GAMMA_RESPONSE” from MSigDB, showing as “IFNg_hallmark”. The module score for each lung CD8\u003csup\u003e+\u003c/sup\u003e T cell subset was also calculated using the upregulated DEGs of the CD8_TEM_T2ISG subset, showing as “similarity.”\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-4728677/v1/e592a614cf6f906761dd84e4.png"},{"id":60809169,"identity":"42ee8a34-3215-4340-b880-6199336b588f","added_by":"auto","created_at":"2024-07-22 10:40:48","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":225229,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGraphical scheme of this study.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCITE-seq analysis of PBMCs from patients with SSc (n = 21) or HDs (n = 6) identified distinct immune abnormalities in SSc patients with SRC or ILD. Patients with SRC demonstrated specific enrichment of CD14\u003csup\u003e+\u003c/sup\u003e monocytes with increased \u003cem\u003eEGR1\u003c/em\u003e expression and activation of NF-κB–related pathways. Trajectory analysis indicated their differentiation into macrophages with elevated expression of \u003cem\u003eTHBS1\u003c/em\u003e in the kidney. Clinically, changes in monocyte \u003cem\u003eEGR1\u003c/em\u003e expression show potential as a biomarker for monitoring the disease progression of SRC. In patients with SSc-ILD, CD8\u003csup\u003e+\u003c/sup\u003e TEMs with increased type II ISG expression were enriched in PBMCs. A similar cell population was also enriched in the lung tissue of patients with advanced SSc-ILD, suggesting migration of CD8\u003csup\u003e+\u003c/sup\u003e T cells from peripheral blood to the lung, mediated by chemokine receptors such as CXCR3 and CCR5. SSc, systemic sclerosis; HD, healthy donor; PBMC, peripheral blood mononuclear cells; CITE-seq, Cellular Indexing of Transcriptomes and Epitopes by Sequencing; SRC, scleroderma renal crisis; ILD, interstitial lung disease; ISG, interferon signature genes; TEMs, effector memory T cells.\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-4728677/v1/d2c18a1d17efadf19a94bfa3.png"},{"id":84861319,"identity":"f86f0958-2697-44db-a861-6ff04239898b","added_by":"auto","created_at":"2025-06-18 07:05:37","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2432271,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4728677/v1/3b5459f2-4a11-481d-9b21-6d70c84fefab.pdf"},{"id":60810568,"identity":"ecfcad33-3981-47e0-85d4-4ae08182ef6c","added_by":"auto","created_at":"2024-07-22 10:48:48","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":4311316,"visible":true,"origin":"","legend":"","description":"","filename":"240712SupplementaryMaterialsShimagamiHNatureCommunications.docx","url":"https://assets-eu.researchsquare.com/files/rs-4728677/v1/04e774dbd7514bb4f0b126ad.docx"}],"financialInterests":"\u003cb\u003eYes\u003c/b\u003e there is potential Competing Interest.\nAK has received grant support from Chugai Pharmaceutical Co, Ltd. KN, HM, SM, RO, KH are employed by Chugai Pharmaceutical Co, Ltd. and KN, HM, SM, RO, KH also hold stocks in the company. The remaining authors declare no competing interests.","formattedTitle":"Single-cell analysis reveals immune cell abnormalities underlying the clinical heterogeneity of systemic sclerosis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe clinical heterogeneity in systemic autoimmune diseases often complicates the management of individual patients\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Systemic sclerosis (SSc) is primarily characterized by Raynaud's phenomenon and skin sclerosis, with an estimated global prevalence of approximately one million individuals. Patients with SSc present with a particularly diverse range of organ manifestations\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. These complications directly impact the daily activities of SSc patients and are associated with a poor prognosis\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe specific organs affected vary between patients; 50\u0026ndash;65% develop interstitial lung disease (ILD), approximately 50% develop digital ulcers, and 1\u0026ndash;14% develop scleroderma renal crisis (SRC), which is the most severe acute organ complication leading to end-stage renal disease and even death\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. While vascular damage and tissue fibrosis due to immune dysregulation play a central role in the pathogenesis of SSc\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e, the immunological abnormalities underlying the clinical heterogeneity of the disease and the diversity of organ involvement have not been sufficiently investigated. Therefore, it is of great interest to explore the variation of immune abnormalities underlying the diversity of organ involvement in SSc.\u003c/p\u003e \u003cp\u003eSingle-cell RNA sequencing (scRNA-seq) is a technique that comprehensively captures the diversity of individual cells. Since 2018, scRNA-seq studies of SSc patient samples have provided important insights into the pathology of the disease. Skin vascular endothelial cells from SSc patients show significant increases in gene expression related to extracellular matrix formation and angiogenesis inhibition\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Looking further into the diseased skin, functional alterations of LRG5\u003csup\u003e+\u003c/sup\u003e fibroblasts\u003csup\u003e6\u003c/sup\u003e, enrichment of SFRP2\u003csup\u003ehigh\u003c/sup\u003e fibroblasts\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e, the presence of FCN1\u003csup\u003e+\u003c/sup\u003e dendritic cells\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e and CXCL13\u003csup\u003e+\u003c/sup\u003e T cells\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e have also been demonstrated. Thus, while studies of the pathological mechanisms at the lesion sites in SSc are rapidly advancing\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e, it is still largely unknown how cellular diversity relates to symptom diversity from a single-cell transcriptomic perspective.\u003c/p\u003e \u003cp\u003eTo elucidate the immune abnormalities underlying different patterns of organ involvement, we hypothesized that peripheral blood, which has not been widely analyzed in scRNA-seq studies in SSc, may serve as a reservoir of information that can distinguish different endotypes among patients and is as important as information from organ tissues. In this study, we recruit SSc patients without infections, malignancies, or other systemic autoimmune diseases. In addition, patients not receiving immunosuppressive therapy are selected for scRNA-seq.\u0026nbsp;Peripheral blood mononuclear cells (PBMCs) are collected from 21 patients and age- and sex- matched healthy donors. Kidney tissue is collected from one patient with new-onset SRC. SSc patients with SRC and ILD show distinct immune abnormalities characterized by the enrichment of different cell populations. Detailed analyses of CD14\u003csup\u003e+\u003c/sup\u003e monocytes in the SRC group and CD8\u003csup\u003e+\u003c/sup\u003e T cells in the ILD group allow for the identification of specific cells associated with each type of organ involvement. Classification of patients based on the diversity of peripheral blood single-cell profiles identifies pathological subsets of SRC and ILD, which hold potential as biomarkers and therapeutic targets.\u003c/p\u003e"},{"header":"Result","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003eSingle-cell profiling of PBMCs reveals distinct immune landscapes in SSc patients with different organ complications\u003c/h2\u003e\n \u003cp\u003ePBMCs were obtained from 21 patients with SSc and six age- and sex-matched healthy donors. All recruited patients with SSc fulfilled the 2013 American College of Rheumatology (ACR)/European League Against Rheumatism (EULAR) classification criteria\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. The clinical characteristics of patients with SSc are summarized in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. Detailed information on individual patients with SSc is provided in Supplementary Tables 1, 2, and 3. Isolated PBMCs were analyzed on a 10x chromium\u0026reg; platform, and the transcriptome and expression of 43 surface proteins were simultaneously obtained using Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq); the experimental overview is shown in Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ea. A total of 238,924 cells were processed, and each cell was annotated with supervised analysis using existing datasets\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Uniform Manifold Approximation and Projection (UMAP) plots of PBMCs from SSc patients and healthy donors are shown in Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eb. UMAP plots of PBMCs from each SSc patient or healthy donor are provided in Extended Data Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. The ratio of the number of cells in each subset to the total number of PBMCs was calculated. There were no significant differences in the proportion of each cell population relative to the total number of PBMCs between SSc patients and healthy donors (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ec,d).\u003c/p\u003e\n \u003cp\u003eTable 1. Clinical characteristics of systemic sclerosis patients and healthy donors.\u003c/p\u003e\n \u003cp\u003e\u003cimg 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5cOYXb5Hsdsu6u/VgVA2Lpzvd5iurbO0mKeRhx8b2zfYu6wb0HQ4lgK4bkCl3Wg7/ERtksbALbi+tbZLVH36FDvxPZAbaUal5qa3/XLzEyRBdnrPTqtMhjRVxfJlzWrf7lgk587yKEflJ/w68slp2XKqs62/4PZM1F9W/rGRIgd3jZUHxTTQlox9D9K4Cr1Hy/LzbBgGFWg1KIghezHAz4Hqnfr+wAjAX4L4NoYvFvaq6qQd/Rm4a7GsSmX2s7f4wVndUaKqMM7idh28LhuJtCZihICPkHpbGJc5kEIZcEOlYPHHR2MAzJ3Y7+pst3ptqjd7Cpza8SAN01r+Cv3WQmBBOJydeo6HdIqyqsoUh4wgvp2JN0VR1OGjpIBkGGXMGwuKTnaKQpn1LNtdwukowLCEHToYgpKdY5g4jFvyJFwysExhqai/6/7Dg7cZT7b+AO2W7t6gKts35xgPwX1AhQaOnyrQ5IaSSHpOXsKK4kcPEU38RKR4b3VyAikcO2/V76LhhtqqunFpbvY9w0j6KZmOOOvt/jwvsLXSpaeHBBmDC0+J43q0pLk72CFtn8bru8BD6PEBQRAEQRAEQRAEQRAEQRDEt8DGfwTiZ2Pv1ctXzd+9P+7+3qXZNLP/9G/6/0cnXSVccLrq+opv/t29pWYHaMyzO/1AwOWI8U0kdVblBEHMgfT2cY0sm3UEQTwqKbJ6DfNdThDE4zONOI/INxVBEI/O2zsfBmY9+I/+/7n+P76Cv7t//f3Tbun/v+yWVk///eD/15fb/EPSOvw3s/52+83W+t8P9f99IlUQxA8CTW0mCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgiIfgBbB0r9BLzFc6k6XFz4P/O7ISwi+VcETlaXIaQYBMeP66baIqr+/xzVId39vM5jehLP4nrOTRVC9fPWmNeYoISBC/OVL093SWTSqMQP/VSNO3mctXvypCdM8UjbDVEdYI4jeHCV6HCDv2GL+INV98SL9HrPlq91HGMoarcE3apE3XZfZpwI/RA8fwX7Pl6CIlcWVzOHOv4zruleKJ4hHTLZC6TRLEb4NV3an+eZlX7DIklaffCVhrTYwR4zm4sixjXMmyNVyDCkuuorbjGPEIcaKqYFMHpI15sfQuBpmxCvaF7JiPg7wIuoL0fq3tVjCbFCLDdXCnJ5gkiN+G8ja+4Epurs7ruGdvMWBYFZfLso3xo32hOuWlgzXhpBS8s5+NjAJtl9cxQzHAGI+i3Bv8ITO59zSW55XUIr4ry8KMQSa5ElsyntpsURmW9Z6pWJbL7bWMWWNAors/RdQngvhuhLxs4n1mbmFTyuUIGutoj1swCJfB51uPuYYkLIP2G0Q0EU/yE/DtYM2ttrM8ZSPykwnbGTzfhlXlACPgWt4GSYxxN8uSfkRt509hXaaVkux5ilT25iWJHfE7wcxpigqGuEJdZ0GNs2y/3WZZSHFBQXBK5nhESVoziyAuuuQliN0dbWffJ+MRo/SCs7gBPt5QFZ9xi+ArFzqCdDGjFkHsOhNIJCmr1IYM/89jxgTxW8ECOHRN+rpY0JlX4iLbUmV2FqNjwCL4ck82UQdmbJcx/7q7kAvw7UDbLd5qu80UKpoJZVl5kNxBVW/zPDBQoSB2HTjiCRiZUrVTxl4F+HdqrqbnJ4jfhZDfaDvLVS/TJsrsuTrM1l8P1GulXm/mUY4XDO4Avp3ica3k5422uxnJ9PX3yNiraM/EAHI88lykYH8Vf8f0cnt9qu0M05wrDLip8jhh9mNeFDHF/SWI34aTvNOksk+5AYuv5B6E4zjTUZX4qbEt61qum7SdV6aq9kF29v48kumLWuw6m6DtknFqQZelLd0dth6LUZaZvm09AR2438Xo0lXlLdqa174q8z4GwCeI3waneBPGmj3PceaWXRYCRy+laiaULLpj248XWXYl0sBK9un9F9R2Y9R2U7FTJT58k0WhwbdDsdO8Dtr+YlC1RiombYdDKs8num/Sg0KWxA6pTtt1WFyC+E2oVP2o7upZNwmRFLGWmC+Dc9RXVR56tW/HRDJI9XPw7YaGg8l4o+3GvMBnb/5USHZem62Go+ko2/0xKM44yo6bkcweyOUzyO1ih4tjl06tVUyCSBC/C+ytMk5KfalCrfZ8nifVNXquKim9ijqzpxH3rPiHfalPOA6ptPndkUwurqVVH69BbJ8msbMqjuUw8DLLDj+mkUw+ztyCYdl1VFu7cmvzA2Om8FLKMEgPCwni94FpoxDfDI9olSdbEgSIK8XxyQAYmaj4eiWsUGGtMFo+x+d2+WpjoNrl1QibDKg8loZUgP0Pm7BqCQ7UcVlnkzSLM81SkQEzxnkwYKuqQp3ehmUgiN8F54Fa1ICJc40UDHE96rPdcTIGL3oWVrgMdpgcut3satxIHfp2uAkXmR43KlDjzpgVcw7U55Mxy3qLh9MtPtmVKXXn+/AEQXwdVgkaFCGI+eIH6XE5QRDzY9GQe0YQc4btMorJQhBzhoSOIAiCIAiCIAiCIAiCIIgfhe2ddzdzyAiCmAs6z581SYIg5gPj+VKTJAhiPmie02dPCGK+SEViRxBzRpK2I4h5MyTfjiDmDWk7gpg7wwUSO4KYM6TtCGLukLYjiLlD2o4g5o5coJFMgpgzskvajiDmzLBPYkcQc4Z8O4KYO1Llb5skQRDzYUTajiDmTGv3dkiFjVwTYYRp/b+/CP2vOxDfAabt4ngaNAYXJUZL+2VhetG636RdzWg7Zg6asAejuDwNy/r3yIjRtYhHha3FvlIR4/GmxaV2He7sF4XZuNlX5slv8VnkmVkqzOQpXGt2tB7r2Mr/iMTIlMTjUnHjrvUr3sSiWFO8ukipXxOvwpNrG+Otev+FmRnJBLHLYwpWJ4uP/1vb6WXSdo+NLDhWwpNCXR/BUuB5f6ve8kui68D6J/y3CDQF2m46S4UFvjAIV5CSsRhnowpjQx7ryrV2PzlbXu5ULPOXOyVIpoydcVmKapQO1JAssYloa30p6Etk3wModI/2VqvkYFvKvTxE/gbk7xfluOIn+Mv81Kj+pZnRdj1TlJ18A9z29ahc5lMYc1blO9kojyEaNXjrQ2wPXu5CT2xCN8YUNZm5cBpj14DV6eNHY+KbJj/ie8DEwjjLnCkn4vQX9u2YiRp6bfub+C53fLvNseYcKhm0ncvsKYpd5vklvoIOqn895m3YKHiZDdu52c+yEkNPaqP8Rba4oGTmwP1g7HforeYHFC+UNCKeVpM69QvCorEC4+p/blb82tzx7aBfLfNXEsQOtR1/N4SVn96XsBO6GcciL2E3t7CabSu0fDJpCp2Vp1/w6CqvWm6hqM1O4nsBhR6afiwMfmFtt17kppLa/y5DKjO+HagtkKSDKhui2FneaDsQO4UmZFaqFfh7rQz0TfVIZpV79kGl5KgI8okqSNV9Xyqupj1ZOKh+Xd9Oxhw9lqwapFb3qzPzBkISu8xxpSU+t1urPbeVQZnpJIFMFNjdLoLYyeXOLh5SnVa6zYN4+e4PkxejQxV/XTPov4At5fFmTPmX1na6tp8yHcFZ+fWZeQOBmXTnZd7Rybfr72EB1NpuFbvccxRLcOBA2y13epDMVt5XzvBogI4oe64bSdt9R3plHsGbbtg7qH7dR8nJr8Hf0P0dRlXu+HYKx/5Hq+qdgj7WpScoF+jbjbq1tvtYi90HkMPONh6yNPA6Lq9jMpPDo8V+/JUf6M4bKfLZWQm/tLabhNT4cATpd9B2M28gsFDreWfy/ON4almWYGTKfgeqf1IqfF6btF1Mz9OZ6LssvK+Pin8MHfl23xEmBq/rHq3mj6effuE5mX4Q8Ge8HIZp+ddmZk7m0PRTh3Nc5ehRjBQOX1qVn2S60XY3RuZ2TONr5WnZgoJC80CbfC1b5BEzIL4L5endqUC/tLbDMRW4vfXa4vrVufMGQrpx4MrkfJyxxa4KIcR8J5ODNJIpFvBJuAPZkoqbuBoKlMYzZ2C/qCzLLFek7b4XTuVcQAWEgLOFAJP/wiOZWXYYeCe8vpn5/Wsz+wbCSnldpw53SuxnfVjd864cZ9s7K1AYE5u2j0qfTSrvQ1hdqu0BF1ZDZw0Suqx+6VdT5knLlUKE1dXVsNeInRc3g5q/JPIS2hE2o98A+k4mQcwd+pYKQcydmTcQCIKYD6TtCGLukG9HEHOHtB1BzB2KgUAQc4diIBDE3KEYCAQxd8i3I4i5QzEQCGLuUAwEgpg3s28gEAQxH0jbEcTcoVkqBDF3aCSTIOYOvYFAEHOHtB1BzB3y7Qhi7pC2I4i5Q28gEMTcoTcQCGLu0BsIBDF3yLcjiLlDbyAQxNyhOZkEMW/oDQSCmD9/0nZMavlVAVmZlA+IcSh/h5CB347U15/1TfEeSzkTjkNq/eTrqugvSA35wPH6ia5rmWFyJqoQLMOKa9ztzjLszrBppIXb/dPhuC8b3QlN9NVg/nV+mDnmfptPfbbPD8o4NTPIEi52WorQXpsUkq68dxuL8ao+WXM16dT1hgQbae1gG8vu1MS38KdZKjryzlcFuHCd8gFXUEVLsUn+FRa4UspOW8x6NE1IGOD4hKvNtn1I6B9WGp0xOL7fVQpDhjILp+liqsEqOPGCMk/qxYtegF0X4D9uZCYFHtefCcnjYG+OzUAHDLt2f1yEazEoGkykq1qopvlMOrjM1UmzfB9Gq3g5rgPXfdOYXSybFGJVV/VnbtxBQaS768JeTKTiv91qI65YgNLzxj9A2fwNd0cyWZUP3q80C/+LUUhhle+LDmY2UCLxdzjT3lr0cbkJ9CZ38tv45UwU5Xgcb1fcg7IAidEx2vGiddCbs/J1aRdFClGfkCWvxtbZz9MWxxzuaj20kVZmi86itWN3ozW8MtYKVbay3op5QHws9um1sPYFX4UcdRfyguxv9LjmBs69aGd11FfCAhaPjwaufFpSLubnKZGoXgdrL9VtXyHHdgwnE7nSmQxFZW2K498gOKywzoG2Eyni3Ldz9w0EKVTVff4VJVjGh4U43FdvH1CQvxXQ+LFsXR7rkvKDfKp+oOPlAcwFp+4GnPwqrk2AnnotimYZxGYVanrX5FO9qjt/n61V73pZdjLTEBFpOMruS+4ussnJx9sY61+L+xihD56IHDTaIp9VRpCt5c+a5L1Zi5ChNCkWepXCnzIf8/z2BGDS4ZWHfEajJTBuKvP5HiT3eVP8uCMIY8N1+2F6/c/c1XZQq/JdUXcQzFZVZbXHs0tfLb25lXOmeZhk2rtkMToPZoK0L06qunVc+apaqnBv53RVfZIZ/IWscFtPxN8hWue3YFUtGM+WUr1Dv5vfdLG7e69T2xd1fP37wF6mki+Xp8LDTN2arm/C5rk4Y3fdotXrffgJxWG93OBVinq82D+Hg9xCOeMqfRVMnKYTy0ubHVX8rtiy8sFRXWXs6KxV8dSsZVUdY0cWl1G4G1yZymBt8OLO7Z5VOVjMzJepWIya3q5eNk0Kr2sw/h6xPe/6duXTTxdbagevBgz/hWJBPc9tNhkJpYrCgJatYemmHE8B7VlYcNnVs64qwOiAPa42ikK95gaM0LdFULBSi6Io+u9T3+L431YtcUPJrXTQYdVLLBivpjZli5k6Wan7etZHo80OivGOqiDzdWg6Ohqmnbu+zQgEHkypmwGVBnB10snA7Hribk3MbEmlhnNtsFPoNRH/74E08Uo/cYeYNyv7FWTe3DPARHxxWwj34cx2dy7w+PEV5AhaGu50L2gQqbT5lknJMVjqLbrAqOEN6zE1bsRFAzldX9UL/N1tETycO9oODP/tI6dQ92drIFTs+mWeOzQnqivmFoqprSNjG4va9LHXGMeQtcRpYEynwNNYS4xVBx2Wlbkas10X1Ij1XDv12bsFHkr8Iww0WVmohcawKZXX6qYFSFX7xl7t3HMwEyoE65mZvFB9FUG32OVSQ7+qyptBrme5Qqq77cqlHhR03kFUamHvpvbqSPaZNnh1bKXWLvfAmQANRqmX0PZ1h8Md99X1VJOAHQib+ub+piv4SYvwtx3WSqX4qzQCwdjk7eBPViwUCNrYt7DydBqL+Jhhk6/T2MfBtfT5edLmMtxowW/hzhsIFQf7hoUDOP3VK47d174Cbef5HtaE52hOIE7VK07RHCrVBtRJahlWGTaMRaql5X4PLGsDR0B/iMel4WsQ0D+5CMQdWrvnuSnHT6xK5XRdBHa1eTOCAuWc2pEt3t1pMv8OSDPWJ/ToS0+ejKHDZGtRRX99uJNjAHrgoifyl6Bhdro3YywIKw+egYiDs7XsnfOxPXWIQnJBsR3i1eluk81XY81m3HJPqqfQdBzPP1275p4Rxzmov7FKHfu9WI8GTOJhwU2Jlzstump2SCUVB/+ToQ5FM+1SXFR5qLUbIA6Me3INigVvkC3Vt/2NzL6BAG4ontgPwJYdR3MGaSZA24n6elo3jjz4u+iFr7+O22grrB9XzbWA88nQMqg6hqv17G2OcjkKPNzc4aSxTYh/QO7lqQsb45AKFO5hNqqNeQQ0T0p6Je45kF23xkyOk6dgwaLxKg1jSHPqa83JXBo3XDd3GhYYP+mU2qY6LPl0TMHkabda2yU9fD+nxxanryArFvKKXdmUl82nmUhr8aL86b3Hjp4kK1CqvAMdVKsEKwzXsvJPRqZ98+lVuDOkUuZiegPSV287J6mDgzycxxsEOwEfHrQ8r+5Z9H/H7BsIY8VFWT4zOYiZXU7Xy8DTYAFWvy1LMBlr+515/jZdMGouDZ412+HmBHYo1VML/eKSyGNQCxq0J1owLWdydV5u1AX4BjUq8Y8M/6hdqayzadkGDoP07hiZtdgV9/WQ5Z2HDgxsGc9rzQne9k3Hjhz501JX5XlZDzx4/io5SA1g/TWCsFdLpw4K5Zm9bkbivhrbr+1orfAJQo1ZmJV4bOv3dhnhdiC7oao7hfV2N2V+/Cdth4w3o76GRnte4ZVDK79zKpGXd+14O0jqznIxWx4PZMa3A995OQLtAuxap9LwDTvni3I1h7X/J8ZQj/GkEZUk8dDpsqrwGesMFB4ZzaWGXD5GI9M42dvTMu0n9wyo7WS7HFcHJHb/iyvBLXoRZzuF3Vdxxdo3A1U14xyymGq7c7RF7oFu9GTNlVBrnpvUrqCdDtPKKZ6X44C1ifrhWHA/O0SpzWbz7H7nYy12q6lT2Fbq5inH1+FUkSQCupJGr4CULdyVMmY27+vd+XQ7slDpwKvntWyzt38ZUsmuQu5sga0Wdz2MN08MEmMem1SD5x2UNyide/Z4f8ftGwhH21G51sVkgnaFhH+YOyuforZzF2dHF5kc1ic8ss2pZSc609EZ+wMEFQ69YJLhM6XWBVTPwjX6ik2PcQaZ5id40Ib6y/0Ts0Cfljx7MCXGahP+U/nBdPh3OpK51L+ZzvGVDKNJfXpdhT2QbR3bqZ3V6gFo7dZ5QsNlrQuGLQGruBnbYbvpR0ewYhJNRe7HJM/sY7ydSvNVTHMGsZOTetLV0erUvp3Ul8RM/77aTnNUSuC7pZymJ2nNjmT26hsdhtxmRxN2kXowW4TUvVz06lIAXVgnsmaF5WkoeNr2v43bOZlgOop6JEfu9f3IKDyJNsm3S/cuV6e+tp0OrlQ84IgPq07TTTERrj1Pj3Msh/stea3tEp7jgwm2Q0Mq/xt8dgo/LEZ9Jkd6pC1fnk7WYGXtGYfuPS26TKapG5mt50jtF1C7nVqTVPwT/kBdh3roS9T2WU3T/UIVmy389SrtBNjaHmp6f71w3yGVFuhRbB3QjuGy0lj+zZhtC1bgrytuNOHXcq0CHDJZ4V9waRzry73j23mTClGDmknLiS+8frB3JVbT2pW6HcOhz2s74QuvQD7B0vsO7XfmDYSheTrNcO10VfoBOHesyqFHcBEt7LO9fKexRmTxvC4eV/BkfDfjrWUe5GIXi04HnGcD2g4E+VpgxRxVSdtdmOX7Dwr/Vmy/HEB5taCdpAaTZbvgg9QpbJjYe2/wP5ptX82kTDWkcWQa3YnyAgQG8wVb73O9CxM5KlUQp5mmXk9lAVI/ihU9ndNyJnIQRG1U0nKWX951hf4dp7DZywKk321iz55GV+pt+4O0osPvq9Whf8EGBqbbKbRmFjbrqY6g7W59u/2ImYM1P6u3oBOoExup23Ovb7xKkWa62Hraym6jg76RG2135OsRNAQrR4rTjgATf7CYHa3FKERQ5bQ/254+HL26zJPmRckUO3tRaLgu1b4Ue2EZ6rdMI5n6ZX8PDq9tmeubkTDi7znSoggi3A7jXx9gg2dLULhZyxdQFSpMa+rrGde2jI19qIuIPaCsjBEiRnAlpd+BHK9fDuDE8U7mYLDUCVZ9hDO34xpIlxNJhM1TOLxILUE+YFYJ8wZyNMofQzK24bK6z8B70pdeZsdepSZX3Xv4op7KATfa/giZxyYDdp6aIl453Pn4eYEnLmcyZ2nCGCKrwlwKleb0VDiDB+qjg+WUlOBh8WFaL9/CzSyVCxtuprMevzEg+qUx5qRMwn34yrRNddOdtdxA1H72m9Omx9CibUyJ2hBr0/yh3UuXjUMyI8BAwVW4kVX0/ODfOYfi+nLTO/UEDmWdCZMatoVt4r6WFzB1Cw8NVmXtTbgPxqRnO8PyOdogF39A5ndnYVgxrvetz1xfw9gkX3MXV6zhCjDYZkdsvhYwa02oxdVB0qAVh++24BUsdmDFAyZYZ7qozd11gRmkVQC0bvx5YlKvr1dh26yuAyu0vClUDxuTJ9xMPU7tN+B4LWzL705teSD/+C0VmQxKaWJ9uru0PtSasXffyYE6PqTJEN8B3771br47VbeWnh+AVtl+vGsZrcbtJvlN3H0D4RbdSZO4/D9M/nOpvzuz5u4zn3+Drajx7HA0MUfe3bqI35tD8eV7mF7fh2E9K+pRWIlr3yXvf9J2YHh/jDG2t/5BuCuzxaq4ec9JBJ9Udb+pDMT3Q5sHvC70VYCx+ONIHRiU8VWT+t6sxPL7aI0/vV0+g146KUt/9g9ismsXj9zS2/uZmJl782j9EPGvuGai0HdH2h/GxEQurJ/6o9+Zw/Qa3HfgH307giAeC4qBQBBzh2IgEMTcoRgIBDF3yLcjiLlDMRAIYu5QDASCmDcUA4Eg5g9pO4KYO/88S4UgiEeCRjIJYu780xsIBEE8GqTtCGLukG9HEHOHtB1BzB16A4Eg5g69gUAQc4feQCCIuUO+HUHMHXoDgSDmDs3JJIh5Q28gEMT8IW1HEHNnZpZKi9VRxhKQvvNJyz8vwxpkKBu+/vuXs2ch/g7WFGkqJ1Z/mRELu06kTSn5i5ButklP7zL7S3P7tZgZyWRGpRBmCBOxjikxpQ7CMIsOdndJqSL9V8cE+yoEhpgh/hl5GaFElUrxQWRZRy6w7ab8N7DIN+r0r8DERWhA069KhybUr4s34aV+SWbeQGAq58+adDW4CTVWs3cTbm2KU3YS8rDh8b9p3MOvIORNvBni75EqVhve+2vsnfReqh4d6/qYlK/3vF/t/31kip8Q5qPZ8CdtYzGeFKtDCbV29/KHRBD6eZjRdlKpvEjVyeTLpws3mi+RYgjOwmxYz8I9A/4gYTZYKPEXLsZNXNFEhYHnoG3mqdSO7CYGipLq9P7l/mPiCoUhpWyeQh87kb7qjtFMb8L7/ZLM+HYsGhMtyh3z3tQhYy30ukmTidTbMgfLdfh6WVZXGAcX0w0a9sadJ7tjqSHp0vEulZ/EnMaYDAPUdjM5EXdgfrZQMRIuq8DkzDHW27AJUmeD+0WK7olIts+2SWEpl2rTchxVvvf7aLtYpnjH4LY5gRGVZcWhwlOsLfEUdmMelhbMGKP/2dXrjE2juia0GSi1+Wm3lVn+LijFjVvDw6sW5HSScnoGOYUU3RZb0sKqo/g/f4GV3EutU/vLRhhm25ngSoXRgF1/Zyj1aP2Xs9Jl6k9kHVRcdkzVf1kXwC/KzBsIrCh8mXzbz3uyRGkU/ETKXXF6yTJxAMsVj1oeho/Y8Xp1hTGwIYn/Aeh+yNFb9a4HYpefaLmieHBSRzWGnPqVlMNwWia9ibF540hq6OLSocQMo6C62EVhb39cW12yh6GBoajGvBob6K9mbYxfgnWFYqfr6Kul8mP1fD1t+EWZeQNhqIpDy7HT2XjWE6crmeYRpcIpcwbCsnIki+TKWWUY2JidSdYTuYoIGOKszEtQa8Og1jC8OhjsTKWsS1Vl7jTlZPudFhiZPtNF0eSEipOYxfH8hbVVCp7NyvPa1mI7aHmC/flavLHWcCzqX4irHRyxYz5FdHZKXDhex8T/VZl5A4FFpXVR9jIXbPYlrybSQp1XwqD0XR5UzG7upB3PQTavxcYRarvVEvHDTK8WqaCc+uNikacBKaOewF9fCPDsUk7Pu3ECAuyPvaongoppnHbiBlmlMUuLY3nbMYXzhro5QW135GuXYFRw+yvJXavi5hDuXCxBExoZM8rcwuovHWz77kimlmJVZx4sTfEefIntNV/mBbhsYGQ+9WDodPzWG1+Z3Gf+DxAYFjYx0nzCFfEENn4S+Spb42nUJKaovZUCy1JazCkOIo5kWnBfgt9YeVNFSNeHE3/iInKb6anvjA4fdHMrvH7AdfJLqbveMxWxHek2/GUlpt1C6rh/WWbeQABt5zL/2rJK1B7YMdiQykj9GsUu9+ycc/VRFSoam5U4kA3a7mZIxcFG2PYxxiVpeRqZaSdL8lNRZq1XA6VWpVZNToKj+1IsR/OrjMh9d1in7zOLnVtaKnk1yS48r8fV116//HXKDe4NDWo0lOBuLe/Y/c+fYNWvbAjNzMlMrpvbrKwAaQHhOLP91aseyw6nwlIelKy329velS0p8NkSC7diN+ZG7+JWuX20ljpj0Hb4SKZSS8eWB5zt41S8QN8OxO4FY1e93eEuSd2fmdRFwkx3UaL1Xi+dp6cKToW0wqsvv8xMHxkGH5KEyep8N5usDPrQI/N80K+n5/ySzL6BwFDs2IfzIMBCRLHbytNUHZuMTPDtoK9NO24FNy5R3lDbTcdEtKn9tP3n1ZlNzxwubrQdq/JUhj5fPs72Dvw0p1bVucZfYgYXcaA4k8uvtQazomb7RRrJTAYJALrvV3mGIMWpwd45y65LvHGpn7ixq3h76zfRdkMFdXpcGo4igtptJQ8TlKccxW6wkg0Nx33f8LauSvR4e2HTTp+8MZ+j36HN4FN2o+1QqCpVgdgJWKFjDr7dq/c+k22Oj6GqA/CeibtYjqLF0Mq3y9OmdwXaDkqaVQc4m8Px2GjBn55eBYZQnbQ4rNLg6kG5X5bZWSqKozPLc+xiA6zWQe2V1bsPm+919hL1lQORXCrRIQvnWCrbIfc3xg4rc7N0Egrolf1gBzcX+DQiq/jOsTZq722197zLZco5c21+knJKhxIz4CzFshJqT8pq2iKxcMG3A11wstwpq/iXeek/LXaQm2qpKqu3rprOhwYWf585mbshwK2yl19QZCr0cl3AZ3Juq7OfvUn2jg5xOQqd9Zq5c2VnVm6WYGMbNzjjUdsJgbpsLUAbwZyWd/YrOMNJyukac7q8LWfiFmuiis+OsvWVNB8IYRtTe9MXsfiFeiuPj32X4Z6it2gANTwx1S/dNm7fQGhlLexPG1q1Fqvff0r/kjU5aV6Imuq44zvj2DcvhbXq1fVCnStsgsQ0t9uciL9yxi5S2cxMnTu6WWBQck3yV+Ds4gKbDbaGWXe1aUG/KjPajiCI+TDj2xEEMR9I2xHE3KEYCAQxdygGAkHMHYqBQBBzh3w7gpg7FAOBIOYOfRWaIOYNxUAgiPlD2o4g5g7NUiGIuUMjmQQxd27fQCAIYk6QtiOIuUO+HUHMHdJ2BDF36A0Egpg79AYCQcwdegOBIOYO+XYEMXfoDQSCmDs0J5Mg5g29gUAQ84e0HUHMHZqlQhBzh0YyCWLu0BsIBDF3ZrQdq0RYDSasvviKYCvS2SzTovzXXVmZIuDfE1v+0nGW/hXpoR6gLvbEizrmIuCwer65WORGdVWnvNA3NSNLyHs1hLuhhDTG9QWYh0tJEQ0bYMVqSHEuqxQum7gnM74di3nEsl8txOG/lqXtQHnL8t9DZVXFQyrGmpvQbr8lQ2zXIAZP8/ZU0HRQq0F9a4wt5uOLOiSlXj64dS/sQKUT3sldhvwT/rIqFmGV34o8ZNIOJkKfe7RU/DJxZefJrLYzTSTyFf7vMf2eqa9yCZlWGNj1/qzFDepGMxm7i9Nk6GKcQNVpdNUDcbEOhI0ypZqQeShYGFH0Lkzv5SnCKLMKAz6K/LLegKHTDcsmQsEFXZQY55+4JzNvILDVfl0PUAnQkaWQY7AAfzEWncSY/0dDKYcSVrOSn8ubiHiwDlemQzB5KzA9YcZZq84pZQV/m50xOXsgpnBbvZGJOhT6b82kTFGrE677BxZMGTfq5QcSitpoZV7lKgVJT0t/Le0za3iep6ixSb6y9RinBojga/BXd9qwwhlBFXVvZt5AYCYVL6BVPIR+Ea1DZmOVSVEJVQgG61ShDOwV+MFmdKPQgYKHGlSxwFxcENaoYvWmHi5s/5xlT4pkMbIKjwRbSRW1vaL3PhYKgy4zL0RQhc5WYFshUu2u5dXurx1a8N+x/CauMKsOUuWMP4a0/DCY483hTgmz2VQ3VsqNSDUwF+ObwHEPVoudjMvNPrIWwIsSVWRP3CpN4muZeQOBPUczJqUMdHM+X8XCfZOLrKe4qSqLUbVXVrzhvuVWudmShwo6SbD8g69CdweaicpD5UtwQJpulJVPoU50O/WazBT7xw5cgq0quSju+YdqZSug71dyVW6VujLCe6HSeaUprlMevy/bIbdNQV70yiQCmY7FnwTkXghVK0sZ4lgs+Klb5kxhjPkw6zfItf3pOb1ahcsoB6GJ9quXzTb+fuI4quK42E2ria9nxrfrmcbIzHoh34KuFtUO23paZrtF2klunqKWgj6YZRX2gNfYAXreBh9dmtyxRZWMorf51M1+YlK/6Afo4Dm+k/XaA9yjyl+e9VC24QSFkpMqx25dKwMrJr7sXUB/UC787r0olGwjdSgntVLRbSzthyJjPULDqq4/E40rD1Q5D+9ETGJ0y+5eLXbMPw9laWorBCrIbnbSfhX/dAZ5KqN/d7Pk3sy8gcDMjbYr8zcgXXtJZHiZDWOqIb3zBv7Yajn2siUFh+1j1ytq/8Nxc+VU6oqh/2tqyNXmpS46oBVLvgKbkoeSheV9Vpbb+BwiqutWBSoVG0UxVZOA529/79pk4eDNrdg1413r7T+bg/dBb9YDxOP4Ch2FG9/OmnP4ux7zmzXI9s7TWuz0ZRH/T/DTJwh2AfpdwCcxZaL43fvH+zMzJ5PdaLttka9ka8l4YD4vQR5UGllmUh72Ofji21mJI5kuFkPZrrdBWh4uREyO+fSZge+W2DeDd2AzWRgNHWQpkdUFn7V60gXILbrjCk6SRhC40M14y7HlZWPU/KY4FW8Vm1xVaUxzFGdW3pfWeEFgma5/QOMidP8sLpYHzbTUUqaSl6L27UoOwnq0wk1TH2sLtbnZaLvL6ZAA8bXMvoFw69tdBVhp+3vQvV0kbWdUGl/2hVLcO9WXYGQuHYOjsazBv67HR6LS1yqizNxqO5+LJERWiexQlVmret9VQMH5UqYNpCq32rfH1UEanGaen6rN6KEys2yxO83lN2Wr3zlqkthz1QMguj0d2HgAR7ab6mNnGfJqveJ1Qd8iN6M9wfqph7y2dwZ4Tuh0sfYnfwwaT9MVjbZ7n7RdedOCiK/lb7WdVKc2W0zCc+xPb7SdK5S3LhsVRS8r+7W2k8O43Gg7Ix2P4JVBp3lZ1w+YITvJ+WYf42EFlcfOB8ID1mkJslxaqMjQnWo7wFkvTqPFXHz/8vfWdiAWTQrolbWR6V63sXAexoXto9jJmCsTI89f/+n57IhHp7F+6ukSjbZzPKRK3ODPapddN2JXj7iwei/iPszOUlmdlt948Fxmn7lAcwaNzO34Eet8K3lgUA3dXfDtllrJt7uoR5lBma3KG203nbxiXyf/EB83iTTv5M37+mxuQ3+uR8d7ZmERxA59i5qznYG4wudGoGZ/Z5iprfeaC+z+ANv9lgcIhyr0QIv5k1KUohiYpp6ObJUS+vaBBcIuk2+3363Xgt1T96bHJj0iB3nDCxzu0BOEe3NnlkpTfi4lDlMdaJMvNdrurMr3cDeRKxzy38qy66IYgoUfoDZgrWeg7VBB2fdT324fVGBKjMGJQ3fdxYhVNeIL7pDHdUg+42qq7SSoUmAlVS94FL93beo0N+QG/RGNefZ8+VtKRSqDZV4j+HQGzEU9A0VCDzo7itVoO6j99GP4k2ZryXFk2qoPWM2y3b6ZNkp8JSB2tyOZg1IDNqgSrIpdqAv9pFIgEcNiEyvbQflrXcUDLrMt9cc+e1KoEVROd8fpt/hUYcxBIKE+BlOvbLvuEGtZTT2kV8Zq1+EVTgHdgZMZrsC3S3r0sB3HuCaOoVJlmO3sf0PG/dXayJ5IjcVZcaN1CQ7yt/CyaAwaILxP0oSZu7hQQc3WY9c3YFeKv1ZFq7XgUEcTjdOndVBb2pnUg4KKrEdHiXsgVT6dbcQM54qrzQXjsFdr9UAi1EusaGmKJ7Dm2Me+UsYLEAj5DsQFSh46T9BLSvFLcP8X04M38ApLMGWQoxvDpMpNWndh25BHUqs6ctVXdmdziVUHqTUtPt/sq65x6L2MeT0a87tya2SzE4Xz944rKGX+bROPzzzKTg3bS31ppbCGQJAWVErNIC9rg+PMmX5XpacFupPcQQ3GS7+TpA5q/1aSia/kYuxv+qrREzd2i+Px1M+Wzjndw94w9XFQ/tpZq6H3BacPNkqmNbYC5tx4Eb1uWMbd2LWcuv3rofHalwbTOoU8Fms9tu7GY3fWu5bZVerPIdPxeHFR4/jdpOTum1rYTw+UYpOSi3Wx7o/d+K5g3Juzev5ColaicpwedkvIe+ahaU29B6DHiy5tZU9cWgW13zQTHW7nAhI/CMfj+k0F8BtvqvuruJkpT3xXfPw2K/Uv4AA18cMhomfaizgduPk6dDAzb1US3w1Wxek8z++Cjd8ysko8FnKvZDYu353t96/4vd97POXx0OXU8f4eMLH3PYWY+G4cseyCsXv6aXAQ8ThM2MOft/+Voz9NdCEIgiAIgiAIgiAIgiAIgiAIgiAIgiAIgiAIgiAIgiAIgiAIgiAIgiAIgiAIgiAIgiAIgiAIgiAIgiAIgrhLJYASP38+qqYfAWZe3PuTr7aqgx98A6wqvyIPd3OZD4Xp+uv8BPHfMKpUNLGtLqG9rzVhjLNMnhgM23MfWMi/JZpagolw3ST/B2X+rd/01uGcxI7472BfTjG6TstvRjcTR/whfOHf9YP5/0x1+s1ix1+lUL8E8Z8wjnVoabajfDbupzjibCo9DJJAs4Sk5bRPs/F2dSZm4uPiirTtJov6p15Xp9PG+tC7zBxzswL/1itB7N6/y1gdK/RPW5oMm1W45nZjsy0lx+/fyWYzQcwf22/XCXktUduBEnCdaFllXKZF5d/FCKkbrIkxfoAVTJS4LaYogazClOjb6TfumYf9AkqhLddMNJAqY2y/rATuf5tJWXpYfxvgh5Uv4bShcrDz3udsGEQKh7bYAY3MVpqjsgou8zykq9IBgzKvwZZ0JVaUK+0YS6Y7cH48trULqYi2M6uCg5OZimV+OefF/aIKEcR3ZL8Y7NxEkx5jOFUX1TstTQ7K7+lCpywFb4I9JvGCFWUXBJFx3hGQjIvQ9kV8V5arddhVRJcqlGV7GcTwWV5A8pCVeacUy/18CUTyNpM4MOKkLFK4a0TGwWJm+QIcIlRYvzJpCxN52ZKXeJLlCOeoDr7AqiQ2Zb4KV6Uing12rd53v5yUUQXIYE+9A4vZdQaifKdAfOVeHi9hP+WZC4N4/yEjgvheMK/yWPk6/v5id4c9SU19+2VuM70AzR2bdhNbtfV58BqDyGPw8OMiDb/4p2CjgvaBtZ6rqbar+Cpsc0rpzOddFFqbB9CjnoOw6KfLuCZFIDc5Rrp3g1ifIGOmb0HuTzGaoXj/6dgpDM0ko5KQZ5jArlyN0vmulLmCKwoc9ueYoY4LDq8BugGn0piLgFtgIX8ByQr6E5B8jFapVdTZiIvfO/or8R8Dyqfgeb6AEXcX+8KbJDwShyUdLzBco1PN+ObEorWodcn/yJhKoao1uIZMYVBy0En9JlSnNHXQTmjsIHYfUHAMSCDsElCHPocD15+8GLwEKUth5q9M0ejToVEOPEyUxcyrL6AO25C0myFrxW7qGaq8Yp9QzFfxHLqA04daWXp1wjxHm7M5W8X9xNYB0q9CcX0suIdORIZ67Ki+JYL4j2AgeTkfgCvkeFT5K2yQ8lW+BvLWxubrFLblBNtlVvW7oExYBAGBdm+i1OrlLm484Y2207GOee1OO1c2CcJ+TJKUnSjQY3IbMlEcMwkpgjzrJDHBVNJ2qjOEtF8G4SoxrLIAudIKBRBEkHd2QbhQymDzFuQ3KQqHQyW2MLtpJYhdgf3AJ15lb7olnI7Jc5BvkTqKIXiumeZ7KTeC+O+YrOtxf1CB2OWDPOIDOxkG0P4XUnDi8cJUNeDQCZiSFe9k26oWu2Wz7fr19rfdxToGoeX16Kh739n2Sa+42MFmzpZQiqr4kS+kTBioVlgtDdh9CXDmUNuhQVrLlVUfsu3XILO2kf01HnorqO1kNNtnuLtUXBVFsazyoudRrKEvKPBsoO2y8mCzKGAzzz0L3XSyzjJpO+K/hVX1WCG0cv7h2C0UvuSomMC3Q22XBlNujExo+7F6A7oCLDf2uha7GK9AOyXVUfVt7TDBcWmFG4TG7HPLtWBVCyDbkMknlzKZmFrbGdWM6jCzMJ4e7nH8ESxIZ1H+pnmC+IEoo+t22fcaZVErdV4B4J+eeXUOW0DbYXfxhn8Cv/TDEmzbWLNyKPp4st1OXARtF1JuBPFfAN7WVp2S0ITHfCebwJqzxrdrtF2jzTJZDmovCuzD4Y22YyMcpADOkxEHyFj7avZ9eeH5HlieOm5iMwf3auuoTP4cZnIB8obpW22Hvt0RiDGeb0XheE6lXrSXIV/ZnOQNL1kzhNPuCLWRZXD6JEJHzjG/eUfbrYC2q58TSC9ZbWTK1XbSdr3vGR2YIO6Fje2kaaAtn2duEwQMtIfLhuEpOlmNb7dXx41n52nUfvh8xreLkWV74ERBsn3z3E4MyglYjK9Al9Xaji3lWyBDOua+VaZMQK4/TH274ep0SKXx7Wptl5TsYWjnyQ8LgxIEZRi4bdXabih4TDPYLvGxR9aq8pfMqx1Y0Wi7T6DtDmNyG3XkDnw7Dzlsd+I4e3KaPFiC+G9gJS+clHILDcrx+0uw6yqQlGYkMxmZYy5qcWJvFj64K12p3GS7U20Xt7PP7WglHHHz3M5FBUZdeQpyUx28wwYOsmzl/h64WNlW39SZrGasXSugeuQxpbrg2/GQhlTS8Agr81o7uognEajoytM9XLOS51XK26hKSo/CWi1c4op2GlJ58XTlCFQenk1sVscg43gy/Rx9u3643q3nuRDEfwCOKiIVqBSwvaDB90z+dj0k3y4Zdq4/VQ29CnYsjG9H3SvS4wIQOzhOv+OquPywOdV22XXYhB3xrYZa24FALXMVTVAljquoAjIxy3o6knkjdqDtxmBkzmi7zOVJvlHvcTg7KraKv8IVTkHXgAz/OFVF8tZwZDOJMWq7ioNUHls8qvDHqB39EerLj2PQ21ydNzdFEP8FzgNpFvPuWELDzPTaNdN2N+stprdwek5PFYMcw66w0bEL8KRgBXP7uE3CaqndVdoJ0bbJUloN9ibgYI0r06N4SNWZTFx6/waTaZ9s8mQM6nYxCaF0KDvQLXyuM8g0HIZPF+Eq0g7MLTaH4ektrpMO/04OHY7tyDFmnuHZHFzkkXb4nINd48mk9Y2kE8Svyu6nNLLBYvyK93oeDzIrid+JkeClt16YtWYFQRCPDqsiuFix9tIIgpgLTK5LmXwtgiAIgiAIgiAIgiAIgiAIgiAIgiAIgiAIgiAIgiCI3xy5h9+4fAgyrNI0aIJ4CDLP8e3tB6Dz+uPpBEHcE9l9qPCA2KUvohAEcU+G/QeL3SmJHUE8CImhQx6EfkpiRxAPYriQLzXJe6LxU30EQdyfb9B25NsRxMOQCw8Vu3XSdgTxMB4+kvn5gMSOIB4E+HZvm+Q9GQ1I7AjiQZBvRxBzR6oHix35dgTxMEjbEcTcGfKHPrcb3dV2x27R2jp4ydWhbAKIMJ2ClXwFbDSNVfLvTKSdnuCXBkpvcXxbLEzP6a6lbj46DOdP4V8ACdWbotZkzNkUXQbq+eurjLjL99J2bE2pvlqIWBNb/Y069HKmn0+Duv4bGmOWfyXsTfHAa/6pYD72N/txqwl1xkozH+tCivrVEuaiUjzICSR1UFwZXM0+9RVPPbU8CRQ/94EMH/zcTs6OZLZK9Ye7vnZBncjM5xiyDpnouof8d6Q5+PrXiHrT7viXpuLmyfX1uxTYFrDqtGrikz0qrOJ1MFHXjuN9HzEyoQxdr515PYa1UThhPFyTN6TtHsp30nZWGQzXmj0pQGlV/NO960Ovfr22+z2QimOJQIli1yUDz1NU+MfGmTxP8WTYyz6er1IbDGoU3w6z8ctuq+x+znTsQIddYnRr4kF8pzmZPoX8B63n3o5gASMh67LUzK7ITHs3rkSZoiPXjKovlzv1sqwud0qoZR0WsK4l7PglRWG21pYCTiD9l/MvtYdoS0guMjB5KtzXi1LAKXDLL0hrd8tj8L5WieFx5V4eIq8a2/0RcfFA8OUmqi+WbfITQhcjyrNSjTOhNMbq3c2qPYri+WC+k7bzPN4KwCdeHYEcncZ9WeQajaVXJqokiwjToohG8bJ3caxFjO1lc52NDNasFjxGhQ6iM8qYWGbyEnaIcQWEDVwNyCauMVbmJUaKjrCvSVFef2GYQKXnTMnE4La8Hw0fPYvJ8LAq4IohnF/GJIFsg68wFDtpiiEzL3Az8SAePifzjrbTIc9LLeuhNtB2FzqgmGkz0JnN86UrSDZhyaEhYbVK/Cv/6K6wCw0yK1HbjdJBhxEa2uf2YGfIGDS68uKCmUF11vu4Cl6GNkG2qoNzDMq+nV3YiNHUf2W0UahpgHcH0Js9OhcZiN0iJLx6h8us5LZRfJkFP1NwFDuz68tDJjW76WuJ+/C93i4HueNKdZOpWS18ehK6qNx0hEryeVzHtdNWo4NCUZnIFgjoF9iLLXGffLstHrAabV4yOBK73PGmwXDnTpkRyBmksuFuawJZZf4gnf1Xf5JwLPJUJkCYh7YDtlXSds/q8mZld9H225g8g/40eRA+bknQikKpQIbmg9jm+QONhT/NUpHOdvI8xzEuz43hAhuLNiB2ln/AwP622wzJsXIQfRp5Br8laUDm1pO2E82iMVrHPtTo0cppfVB4amW723xtiaGHv89V2E+LvzQVV9jvICH/NJfxevY6abulWux6Zd8udhttt1BmVxWPXbHuhfbqxBfhdxhT/v6MvuMsFemrlzn0lD5/n+cCVZtuo7bje1BpR75fNfH99Xl++lyUOpuI7lRywJa6ZmEQ9sQf7zoc3InlLlTotsDxBCDAuazJN4UAo5K9HbzN2NbHvBBioxblXxS2VI8qJgJfaVKPS6PtqoXLtLTTtYvKYBJqcgnksNqppDaHYGlm2WVsPAfiXsjvMkuFuXHd/C9CXmZrAyXaacg5aTvPwxVsQccg7QOUYbXIjWM7/Wmtyc6CG4an0SDvzqVuo9ixL7Upmb1EA0uXH4zKBfh2p5i5Ex0DV/8Ld7e9Mo84qFizl8/Dt4NCL/p40mZIBXy7RR2XU9V5/qx+csgqcaXbL7NsLdYj2MT9+D6+nYybTac85jsT/77MDhWKTe3bJY/tGJyCRtslZMgvZclTqzqWEny7J2w6U2VXTsDIRLEDczId1EktAXBxsHVRvT+pl8Dvr+3SXxL5Lp+d5BMazf/Y7OKz1+RP45Ls9PWZ+YidG46u4Coo9o6GmniH5f/Azz3+5jz8y2F3Zqmcq7dJPKZeN9go7/fkjbbDR+mWv220HUtdpl4ww0YDjoslHbjLyvpaRsaM1mMXW5zjq+jarMe4n9VHgyAep6e36cEBtIT5WF7/AWBhp7GoKX/k00cwjwsrFPZxux2VaiCuyqzkHupsFJpukZWg41wbtOFKnHaAxH34Ts/tQK0ltWT78TB7Uz87AANyKnY9qKobbafDKjSf1gZYitLgPCTZ7o8laLvsOuJEDAnWFPtcpOFOGZKEfXhaHTuDrY594JZVByeZTzMUdd0z/4oclTnOy7plXiOZvdq3a1Uc1B3UCyxYBWqXld1PtZXrBVoiHbA8O9AdEvdHqoe+XX53JNO9OzWdsBoFVNKnNCfTDbjVMQexq5uPz8/rzppVyqwGo/6AzvQwFM87RvmJNDl0sddBmRDVm152reBIQIsCdlblMJM7sC2YopQXb3NxdA1Hroa2wtmBvySHKu/vhbAaQvMWx+pDa+qesM33yaLvldx04jIW8GStiFj0OCINNRtST21NDGo+CviX43u9gZBdldhEks3oSqy24yo4ufFlCItooVw4nANWY0PohMs0iVNehtV3kM9wJT331iKs7r3B9VUzACNPQghpmtSk6kAb3GBZa4xZwZGdsPfLenbH7q0QWKSr7xqx82LG0XtE2NuqPhGroISbOl6DHmAqYs7X223orJDUPYhvGFK5+9yOIIiv5btpO4Igvhb6lgpBzB3SdgQxd8C3e+D4GAgsiR1BPAQQno0meU9I2xHEA7nafOgbCPRVaIJ4IN/zDQSCIL4KqSi+HUHMGdJ2BDFvWrs0S4Ug5g1pO4KYN6jtvs+3VAiC+FpI2xHE3Hn4SCbNUiGIB0JzMgli7jz8fTuapUIQD4S0HUHMnYfPyaSRTIJ4IDSSSRBzh+ZkEsTcIW1HEPOG5mQSxPwhbUcQc+fhX4WmWSoE8UC+T8QfgiDuwfDBRibNUiGIB3J3lorU2mmN37VnUtYRBHHlncAzU+5oO1kf2Rz8bTAGmcBJp+f/W6T824v6pWBSH84UKJN1hLJHRzYB4dP5m2KG+m2SDFL19tsmQtyT4cKM2MmSK6X4JZSqNmZa39Xfh3W5M5K5UeCRC/Cv+mZxYG+XbTYu7kaZ+jO+W6bQJb8y43ZfqXhTyBsptNjjw8pQx/DURqn+XqoGea763TaKG7PQQlKDYBsUuPyhzGg75ozx1i4KLGqn1FTW9PhvS3dW22EstrFdtIs+fnvkq6HIbbZ78uF/ilWVi289z4/OG2WgNkL3TQqgmVlo7SnxyLCKF0nsnIl+XBUoW/rd5taiN2Yf1z63weAO3tgL3I+4P6DtprNUJmEhfamWhbyajNrFvzTrO9quTKHKAXda3MTTeiglRjR3GLrwnwGxm0sg7/8OGaH3gXJQqUDZeT/nK7UAPio6nObLi5CY7CQxf9GFftTzl1DaVole9paPM91+zlAppgOIBzCj7WS3seu0sEc6RhA75iuXaa/BtHByo3qxMhNh7Y5vV6Yg/gCLaa30VfV2RYIGrWOhMWcl5KOrqnJJnCWk3no4H+yBZ2UWo7gxB6tt2V3Mxq8wph3s/7Zy08bG7KJcqaq0f3VQwimqOrwdXGadhNNoByeuLxMzQ5uXSQ9r4czQkzeH14ek9gxXZqsXKQ0n9HBVeLS0+9ewy38YtFKefDqDn6MvGDBcixwsvjkYmc7kz3nEwtDL2ALQ25BZ2MQyYV9gwzslM2mgT67ENR5APAR569uxyDdSk0T0MpQs2htVq8xLtm1iGVXBQ+NtA3e03RIXTcrkIIBD3LkYXErmD1YxT2mi/jQIb1WxELEpy3KhULELGo0ZbsEzT+GWmY1FoYwAbWfFFawU4NvwdADCjBKFKpK7scWNKYr+exRW6VW/gEbJMOayEHiZ0ErYyCwUBb+EnS03O5CM1kP2CuNVyuoUMop4tOClgUMUOC4MT7isDCStMn+YQuXf7qp+I60Up9+ZwMqDCuXwcfHxZBI3azW7iiu2BXdDU2AxYBxsJkACh6sge6s7uJl4EDPP7ZjguWEALhzGeNGqDow+zs7zsiVNHjVjYlDeDF7d1XZTI1MqaCW7gW9APuWByFgdCHvjdcXe8PyEsXGMOpsYMF3Y2RdetiYgdrCDNn2ZrfEomTx/P3DZEZxHruI5weNcr+1JGXJlIVsObt2bnFeyN95UKab2S820eb8GFlIOoiQr3EOrwrKrrX4Ygtjhmb3iIFAjg55LmT+XPW2UPcpEyjRFetbQ4BgDIdWZO8gFZBpP56Bh/idwkUnTsPnELofzsNqsXVGpJ9095+PPyqSw80ns4HKkMcyXh9lVr+kQiXvC+O37dqzMcxVVitWLRqbnICHYRJdaoJOWwH++Lto3vf+dWSpTbcdEDi74tUrm6vVmGwUSxTpsjo88NyNICu4zvZDGSccKfjr9NUiuh65shdTNggDhT7oG/JEg+olhGCRNhYLq8wiZgSb2mSuWP8NWDTYy20th05kCeQUljQeBMssWFZpNzBzgpVTQdnSR2rKLcJ1ljtpTdvghbHqJl/XstGw92QQfBvXkfz1yU9aR34FwUKXG/9iwqPDWoe9KS+BpOxXTmS2UpYdCtLGS7S12UqhXWIzEvQFTcartoO1ZD5KXR2i6+3GzVHEf15Z5dTw0CtPaxBux+5O2Ux2DEf0HOBIix2A8vu1Ebnpgq4Rj0DyGXVS1RizVxpF0sJcIkbcnmemikI2Mklp9wB0u0LdDts3gS+1y1Uij0J1oQaeLQyqgD8EK3so+NSN8r6IbPj9Nh8ZCy3ZSs5ntPu+t9bEFMfMRG8lWf4lVKo0jtcTmdeoGcPiUf24Fng4Z8Th0C6m1u/5/LHYbHOy5mrloO2BYGyhgVOBSD4xc0P84ZnmGBS8vldkUIy+0Vzsb6pcfT34c/vK+XVUKsDvZaBXlL7VCUBvHuyYZHtemfdO93ZmlssQ/7v2xt5znIVWDtCdhYAxaa6wDR1pVZkcrp6keSwVSIrdKkZsOVywzfbD0UKRA7JI3kW0k/QeAf69E2QSoB7lZRQ0Hq/kOaDus8LNP/E327H2nRFTuWXiKMjxZjlqDxks7Q3qxW4tdgVL7Ri2BnWqW8JACbkHwN5ATWNjgwihUm2gYa1DYeLj7j9uV57fjKHsH1RxGMuH2Yx/7rqo2MqGsUNulM9sF6JBZ+VJouerkc7BFxOvaMCHux+1IJpOuV6fAuJTanMZOLUTladXqRfUEks7Em6dpfzOSqVdVhXnIvb6KgsmIurFaAIfAuKxVgbQA59CQtsFVjHsMRINlHxrLspCHC2lI+rhK3h4yCiaqpEARaeI2/qKt86m2Jivuj0uwjBETnAwDbDEsLkuNMg84ULS2fw4p6Dpwzac+XE99SNu83D+utZ0UXEtQkniIVFE22m78nxqZrAK/s0nPT9vt1trON2J3yR1Y+6jtjj1vuuhWFXr7cQ92Wm58euI+zLxvB034WZ1aDwpstI+ahVPchiOZzKSquGNkzvp2zzg2bPSQvoBkgEeE84b0clyHv9FoJa6yo0+11VJyD15jYGdZto/P5PcWsGXJVTXSqvYcb8UOLrDlIi/r/mC7U5/9Dch4re1AQj+1wHtk2aR1wSQbhvSs66IN2i4Wh7gziN2ZS2fumQK7DjAwmQAHZXIxmcAhoO0+QU490HaT592k3qUywyc/gLYD97Q2lGteJdf08Wl8OygBXML+6MwoNDNYNR1gsuEwO4zvbmSTuCe379u1xjzUquxJNDJ1cDYZaud51ZK1gQba7lbsZrQdNP16ONlx0B0gwCe4UHHUGGC+CZSjyZupb+ehF0/JKoeTBHw4DpWohqytUFLky7Tmhq3+5XYaygRDFFshNAQLh9ba7r0HCTzHvrglzOFuZ6rtNNtL9iY+4EvqEdZOtd0S84PGgDKH6NuhkfuOo5uXHpVZ/u4YpBVbmv0PfbvhDk8DP1Pm7NtBlWNdp2EnkSwSGZpegJVQfC6JXZxPV/CrMRMDAeQjTbKTgW9c6DRLpczB7CvztxPQdtieQduB/qr503O7yzpR5Qsu86cobzrmddPtphFR8MNwFASNTObzDuTuYq6OsyU8BysHXELfaa7Qxs3TuEimwzkOoJWDF3XTZ+/SqB6oStg1F6ACQduBkx/SHMGtfFX2Gm0Xi/3MHRTgqYEdi65lGn+ptd0nBcr7Q+psKrxOwVfg6G3x3oFuw3alCxB7p5IX+19qu4rXruyUcPC3c2O/O6DtUvlXHFxttofOZd3/Vl3s6gB7CQU5fA4eQoh3ekji62jNvl2uRdEW4tzE6io7THMydRuUyjmoJlnw5NsVN+Nqd307kTfGxlXICyf/6D4XIuypPvaO+nmO05ZBxaV9BEiKDrjDH0HxdRDlgRDiAwexG5YxiD3zMckOHBhUgGyK9EQDkOEUtouID8PLZGSCGQZXn/YLfdhNmnQoU6A28fmHEAq8SpRRPDx2MaMXg7IFapvDSeM7uJuQCkCG3MEhMYrLVXzwbvPUwdhmjGj+MN3PVXkpdkQ5rp+Sm9uaelQkbwZ0oRsW5jXKOquUEQHc9bTDk5AuxMeOWC5pWuZDkGq2Mr0xpp0mussS30PIXEcwG2yLVanty6Xbef93tJ0N07S+hON3LyEfIb3A+mM7AzTjpvt4AZKhBZyp1F6AMI+CMcJ6gTnjBVRjkR5cwJEbsGhuTjnsfNwIbYPzTuDC0tyV8R/ohgxF27RRPnpVwENb5SXqCcwMpS7Tf+CZJ9UO3sNYWNChMphoSszJB5yutr2Fwpw5uJaAkqtFCYoXfqZTZOaOE2EVb8CY5hJWmhcDHptW2fRzYINDbaRkKsvz3ZRsuaqeFrZmzMlNL0zch7vv292HO9ruf4GDlE3y28AZZk2SIH5mZPdxI/60wHIrKvTpvh3WSTNyCeJn57G1HRNxM824+g40s1QI4mfnrm93H77yWyq2rL6XirqwvnmgTxA/NXPw7QiCuAPOUnngdzLvjGQSBPH1jHievuRwf0jbEcQDmZmlck9I2xHEw7gzS+V+kLYjiAcyfPBIJmk7gnggNJJJEHNnyCniD0HMGdJ2BDF37sRAuBcU8YcgHghpO4KYOzNfhb4nNJJJEA+EorkSxNyZ/Sr0/SBtRxAPBISHtB1BzJe/fBX6qyFtRxAPhEYyCWLezHwV+r7QLBWCeCD0BgJBzB2apUIQc4d8O4KYO6DtaCSTIOYLaTuCmDsP9+1I2xHEAyFtRxBzR6rv8p1MiwF04L8ULScbhhQ+54a0zJy9s/JsHP4mmg4rX6YoT0TDmTWpaFN0okfF4nnqEHqywuTMGVkFG+tAQC60TR0IzabYS8QD+D7ajn3JlUBMxBiNu+ezVQbL5ckok+auLLIK40n+GabqIKxEgxR5wJL1vceNJMd8XBYiRBRvKdQ7SF7K6SnlJf8ggnoHFaiD2nvdwZp0z5sok8S9GT5Y7O7MUlmqAyRnevnpPwWEY90UK/aGaXTXu0zadyMo//YcmhRC/NFxHMMpTd6dlhOM2ZlhYOwbsfI8ggRW/FxmG8pmro0BJkuMyEs8iO/k25X8vE44Ffch1x4GIJVaazmULGv1ZMbse+NA7hiu1VBh7E0K5I8wmQQSA/iz2E3Rx5udmv1xM2NyCKnfrap9rDu0R4b54hP+un671QqrGJXTxXYT6WUiUnxXHc36kehj0FwMbI/hQYmH8fDndndmqZzwL3WCidMqGxpzCJUVlFJmx1TZtjHabuZPu5fQe+PaFGzc34idiwIFK7WwmLSdj0otJD/DGdh/DzpiVoo/is3fLrBkpSp2PIdIxS2JEXczXSiWDVPfdhjN1MosOVa1NnGUCaWhPpXMwt/YKsRX8t203bRPRgNFcuUyGQbndsUM8rew3HXyE2+v6MzG4K0NqmTH1VTsmM0DBkpOK1DbnZU8WCti2WJeGW+9aruMhYH5ZP0dQ/U3QJxGAPuduWCVadWp3ivlp4IFRiYYIsnqfAliB9pu+8keKbuH852e2y3daC7Pn2fbqniCcfrB0nT41WmmXoPYbAaWyZhGTFgRJWq71MFm2Xizk7SdEtkFartRUmrMcCtj6mer9+J4Iv5uCOZXR5q8U5ZfYtvOxboGY6V26Jww/La4mV0NIZgV6ByfQQXuR8FCtWtF+O16we/E9/btWp7vZVJFLVfBEAEE5C/Vx+tstPBBZvJkDY70VTfqyacbUbULSduh2GVx07FyIeXsSut5fXVmWTLM6bdDnnxBRef7cb3pox6To+rApFpj47Bq9m4e5Uj/zqya4EdHYPSbyoRDZ9yTuGyKjbn0Br8c8vvMybzVdhY6yZ4qtAZ/DpcrVYK2K8DoVGYdluX+muHqaXRHoO0a12GxHuSsxW5hzIRqDBj27LTUh0/2deSWiUYEf0e2RdL6jwzzm9OSB9xrro9TilX5BxAvy7FKdSyU3X1ppSjAwYv0lPUhfKcvh934duwZmIISjEQdV1GUWKWWQOLA6NQ8jLKJXV7oxjXdVvsT/7TRkEeL/b1d+G203ZOeUON6S0885QrhEcUujbX9loBf9fg333t2WjQFnyjz+uF55gqFPSZcBNY4A7yROoIRWsXftyv8Fob9B4vdrLZ7O9V2rZAn7aZ1u0Btd/RpRtuNsvXXyjudnRnlzm59u0MFEtmIXfuOtvtyWjpEr7PfWtuxt2nw91GRX7jBhzc3QAXVrptVMdWU5WU93qKFzw7be7hlauUQ9+F7+3ZaFdfJtxsanoxMcVBlvU1YOeJgSdo8YOvRUV0f+6fT0c8nXXz8mlWoMmN3nz3j4AHCXmW11NhW9oUGsVtJ6d8KXaYCGIb8jkQ8AlJwU1uMstxK1n+VV7WRafvt9Dv1tFnVYdm4DRLnP07rkLgPD5+TeWeWykljZMo9vsSyoVL7mc9xTMzhl8l2/y9qO77ay1wesQMVg+gYdKZNBw5G6GGWjQJOjsCRzGsV0agRfGk/vkazx+YKxO79b6jttMrTkIqqhzoej0mpklcADE2OHZyLqnHcZDjFotemsUIOd6DmtQFZLItbX5D4er7Tt1R2cuPceNEK9QfUneTqSSYNL501+AAhLY+WowePLy/HroocKrBCKUuwMn/pbKnyyyxT3GZHJX+5uFgpwY5XNs3a2EbYnYWHXunPDKsWol30sVFEjwZ0gjnY84uLi46hUbm4aM3C1lHGHCzDCvANxkK9Tf2kFCf486zwNt6d8Ed8Hd/w5bD1PL/18jcKrlRfbcY1fMI6jOYafjpKqSAK8O1MdNnEx03B1k1X9aMrlT+zqjFMAdFXy+elAZVpltGa8h+VWkiT7semr/rY6KA7vhXz34gx31T9NPf4MWGlghpcgEo0T7JsP0BlRg+mpq7HKsErwBXp8XnL7SQV1yu56oCVQtyfh2u7z7Pabnek9fW1fjKqHwnINHUyzaa8jD5rSQmuOJPXqAlhR11Pv5TbN4+iergrG15ND2UjfVjPyczkdT0ns9ny+4EF9ug6pSWhBuFEUImp6uA3nRMqIpX6OqzQzfMe1swZY03FEPfm4bNUeqXYb5J/hzxJgyesqB/f/QtNhRLEb8HDRzIvrnr/S/v0Kr5aXp6b8MhOCUH8fDz8DYR/xYbYbn+VriOI34uHa7t/h14MIYi/5eG+HUEQD+QxtR1BEH/Lw99AIAjigTz8DQSCIB7Iw99AIAjigZBvRxBz5+FvIBAE8UAePieTIIiH8Q1vIBAE8UBI2xHE3KFZKgQxd2gkkyDmziO+gUAQxN9D2o4g5g75dgQxd0jbEcTcoTcQCGLu0BsIBDF36A0Egpg75NsRxNyhNxAIYu7QnEyCmDf0BgJBzJ8Zbce8+FPUJGf/7Rv3GsOD2OBZJu0+y7RI4UJucOXWbh2IUFYlRo68D7KqriaQd7P4e1JVdSgCG1bD4xYFnKLzfDWsVsfrOykRhPAztcmquqHoEJovfdtnPfqI/sOYmaUyCXlokjWt0rj//YlZVh0cgnCh2Nn2JxC788s7Ymfz2AibjvlsfN6v4KKnlK7z/n1xC+oabRIfY1gt1GOWBTM5iNpqqI5lmRIxz09uz3f0iUcMMimFMt2AUWC0aIK9EvdmZiSTifxuaE4WUwzI/4HsbF41yWd/F9Pe806j7bRR/ytQyd8hY/s3/5K7tCr/gAE2t3KzjV3XwN3ESPruOHW30838wNTBXBG50s9X4Xfilc9shIbCys7v3CF+G7NvIAiM84gB4Yd1TCuM3tmD37SMK3AbbjqCFUOQyIn+wMeslbEJVMIBmkN1ReABKQfbX51qO7Pg0vGQxr+YxLzSAa3ddIZ6AUkrtmMEsUvrGJyuCbN1czHT0/yPHX5uznoVP81TEIlyM/VpN8HEHwOvLptUjW6/vu31tOgOcgOJM9HVmTQRLZs39Tbi/vxZ27HqQ1UpVZS9C2fygXq122JvVaEMun32ixBF4TG87rKC9uAMz1U5snFFl6c5j/tg90O7kGVURbEKTd/yzrDOHERYZ9ak+K02eqjHYIMq2g47VGdUYcogbqr5ugMr/LKREx/h8liAK4obSXGmZO1b4HUWq3iQhrWxjucry9sdfnJKHlZeG+y35CjZDI6LpjgfgdLcNVfezdg+63/wF3A1kGJCSRC7YpgFcasLiXsy49uB2F2CP3ewueN9UIJdedX/Yifysni1smX6sJstuKgqC9JT+TJGJ1ciL8esyt9JFwZh6+qQQ1+oRSw3/CUPIGeb05DbI6Nc5p9CL5llK1ChLuam2jiJEWTFmVhulSovGmE5GxtTbVWRm/WjKt8DdyI+++RfdcsexrUPvjIRnBxWvn7pN1ZUXASZ7lQe9odLHIki+JX4SwR+1X60vowaf4rlYrdJfn8CN8DNkJjmM2c+dpaNeRtSIHY6214tpP7Nx7q+jT9ru1Y5KMCJl211mGWmDZVQnmJ8yH2lRmAzYhB5Fjg4GpktNSS7sK3iJYM/KEAFeINlHZNc5BbayTS2ddJ2nqdQk35QHevlvIQe3OclkwEj0bOQtzHyMgAnR8X16tTIVvW+zGy6RPnWM5BwzOEwqdrcYGYlXHSV/EotLMjiQMBax+P643lBc0TjnU6R9x6WugdS5UaIoJpwzX+NFO85GplHZe6gzxTsXdVz5bnFKiDuzewbCCLfyVpL8AfTIEUtgxIYUQCx1KuLsSquknhOB5Zl4FBL4HL0oOmvXEB9LMtsCxyQXWdD7rNFPtV2ybezKkmK5y8mOoIYwur+KnNqD9eOiqm2s/wLrgDfTjLPL9G2wrj1gG6no7IVVWXj4LIjZwXoZa+m9ul68gexJ/j0S5hAurkfhJX5tDQfgZEA6yTLTnKT7FjdxSHUWWwSO6hi418ap42Fyogff+tx5ocz8wZCY2TWYrjXB9WBdY79rdRSVlwwkCL0MTzPO04OocDXO32oq+oAtF3J/XHmVFwHeRmNhOJ8sALq8Y5v53ka/PL8BPZUOAaq+d7Rxvvkmw8jBqsHWK28siMT5QQ0KbgSp7xKIybjTTjxSGpQerCfXF/J+13QrTry6CVG1F7k4RB2kCVPGvenZ0bbgSKfNTgfCdlBgwbq4H31J4GqtR3Knfq4JoWX4qOcmBllTHw9M28gNEZm7UmjtpuYAmy5YqCQhdMg97sRxQ5UVc6VQlcrgC8HFQKGHcgKiF1RSDD2lBoIV76vssXutH+Wpvsk85uNtnsLkgKuOYpdYD5PNczMdCAEFGeyEA3I8CeUH5AiOB9sdgfwi6DYwWl4dCuYHIa8q5QYgWKEHTbTDn9qNT8n+sa3mwgek9nxyAisx+zqXb7WrJiy1ohdBp0weN8aHGqoquJPpijxVdz17c7Rt0vaLoDYgSBoMAyj99Zbu69bjZ0Bnp61zxSvwC3jIDzJtwNtN6l9u/O+8BZszUGF2u7GyARtZ4sPOK0B7FXYU6EeBLGbrIB/B0nZNrXYgbare1rQdpDGXqDnrF8FE8vmcSVdjEPzM1gLeaYBNmmtV/m59AtmC7b78f6v0QvvT7VdzzymhXkLExzlTRd/UWNTbYdo4S9cfAcrVXJJiHsy8wZCK2m7t422QyMTRUWrNPqYsU/uaLxZpxMeWgSb9e02jlDsdDoK9k/ajq/eiB34di4G9Lg8L1sz2s6isoQrWZ5qO1urKpD69SPQdmnsHLYH7q/7Jk2b2d1y6GFiskqPkxCt+u6ahzNMyy33S8xbmvp28lX9AO/RmOgqDdcMsb8Fa/6vTwhvtB1QdXZxXAWqEv8Q92Z2Tmby7c4b3w61XQQrj4VNXIEjW2xxAUueOayYTC905NCgzqpOUdudQi8Jvt2QRY7iYzdBLEAVzfp2IJWwKA3fQm1Xi90e089xLGWylE/tKRBJPEPFjTxCbactztRAd1OKQQX25/A5XAwO2UBmEXy7fY9Dq1lUIPNdNFBZO8f9fn4a306KRzeaXf4RnxCu8IDPKCo+My+sZkbbuXMoeh1huYx/tkWJr2D2DQQQO+i6Gt/uFdgaZx3lQd19UJXWJQe3zHIFlSFf9j9p7YSq8BAP5l7+rge1suPYE5xGWfLgYPMCZGQ5PoJAtDl1Wa/kpdMVz5+BFYPmaaYHzyXYsR2rrcobIzPLFqOx2sEKDcpMMPvx5aLWqF1x8AQvRoke813YaV+ovAOWqPiMa+EyQLxhh8t+UqA/P1oto9ht5NzrxOPdluCr+9qaOAbrAkyVZEpA6uaUfhDrBGxNXkEZvTYm9YjEPbmr7cpsUp6mZYEKx0cO6kkLvqDQfcMHALDpAsdMFlSal+v4QrgGo5FlutNXY+gBZSYvOWwurRJssX9H20FWcJyoFqrWdSySb7eAxoxVqm/KeCN2Z870Vawgs8kn0HZs7XVfcRU0GJigS1VXoe/HStWHzLwxslfGTcV52bvIjnTgCtzOxjL92al9LBlwCAvuG8qg2fD9YUtYcK/SCXoijWcCOkxNf9/v1ImWrd9UkaKrbqqMuBez38mU1yACVy7pJ7kPLftMO3xgtjt21qXJmbqudTAz3fgJbMlaT5zr7Wp5lF1IZ7dhBxQNN3ZjeQw73/aVWZ26cs6Ojq+vYMs+WoGtwxE6a5/d+PrOk+ERnAEOvoD98HL2x3DCdF2ZdIuL9VM8psdjN0oZsyeQHNczOOA6FsfTs/7s1AU60ddQbouLi1AozYZH4BhKtinkCzmtN5ZaQEo1lZ9d9JqN24uLj9cL/Nr8AN9SOaw7T5uXNMmP+D2YfQPhPwLsT1FVpQn3fQ+WIH5SfgBtB65LLIqCRqKJ34ZZ3+4/Y4Lv2qUHcgTxO/AjaDuC+M2gGAgEMXcoBgJBzB2KgUAQc4d8O4KYOxQDgSDmDsVAIIh5QzEQCGL+kLYjiLnzQ8xSIYjfCxrJJIi58wO8gUAQvxuk7Qhi7pBvRxBzh7QdQcwdegOBIOYOvYFAEHOH3kAgiLlDvh1BzB16A4Eg5g7NySSIeUNvIBDE/CFtRxBz5+4sFS2QJtjLFF19ZYBqXaWvqj8ex676xyAA8ryqv99fo8U0vvqvwFdXwTfC3th0HuawGcycsuV2hKiDfY5KsVMHHHEbv1ARz5fZkUzmgjLRqHi3xfo8bn9NsDjm8+dN8pFgIq/+KU6CNuXsVbtOCgb1a8DKPEWffmzgPCk4q/QRG8Jt9HJm47KJEVfIy257U1y1oMRf/vHrFPGcmX0DwcUUVEmG02dNeKyEVfHrejXHm1BMj8Vx2YRX/s0Yx7mInfR5HdzQdzHC5/nCTc/lolrPtksOCtAXb45tPAGxq6YBsol7M6PtmFArKeFiwALFL6Rjuft+qvPpYsamyeYnrQOOLYb3/8uOd/fH9c0uTRrAndLyzerpUWnzzWpWnmI8+5qblTM71p91ny40+9wu/qRIkz96MFcoK73H89QHb5s+egvrH4omjhbb4eh4POkEnQmlMxlNC8x4GhR4MDO+HROpcDGcGgYwYx7MCgxjaJUB5cdWcBGrw5awxUAKd2jXzoDFjVWRovdXEdKgNlu+rHDHT+8WOxEPwA21JQjrYZ9pZ3k2DlUdVNLC6ogX4UTpmtOj/Qhrn8MJW7PaLp0SVuqyLM3rT+vhHPLDS4po+7gAZ2JrmN/Pbm2ysm26j6/tZFA7gl9CSjfmTZXX7t3RdqcOR/+i62uxW1UyE4/fE/y6zGg7MOHiyk1RypK/K6HC9zOL8ZPlperA4jLIRJlHSO6zSpmyXG2/AXXzBpOhjdpOCxXKE2XGGJY3hrJ0r/JYliIu/yFg9y7UpCxx/TseDutTsTe5Oi/LEas+tuEcagPEh/NwUu6l6KXWQOaXBgS8dY5mTkJWcJrStF1mi+7z89I9yeM6qyKcozO4lOCQmiEswi2s8p87oDLzqvL9x2/j0q8NPUcjE/rZdLaKL9VnBe8DE5MV/gZMolE2NHEoA1QT8UBm30DQIc+F9zZ1dR6FDUVOOtVm2QYkoPwxNrnPOfZ9jhewRhrloXtEc0S3U+zz03cTPA6OAfmELJjII6yp8gFIYgrZavNVrEUxFfiW52offteSS6GX38Mu6gA3lvkKZHuKGx0H7Xir7azCqOiuW2gdk5J2cIEyYnhtVgmMh26u1jGoPSgLjNP886KjuXJz0HbAUZXcBKikVGLVaTNK5VS8wF/L37Iyd3BJgYklqauqtnWI+3LnDQQtCpXn+Z4EjdTYFWXQY/DtWAo9jsLoQew6SZpqk9SCOJQcjU/YuJfJxkARahFqCCuRBb4GPzZHpSMxFLYH0ZtotzNI/jvs4bnAGM3PN1M2dvCC2X4b12BUdB2ewXF6ow8efMm36jFV9o7j6A97Y7RWYPGA43FqhtqY6QMGuKzhKLbTRf/UDIU6zPzCXCw6ViVtxzoYuB5s+6dv67NC55t+Pa+y8evghHE6Om1UEe1Z2kLcj7tvIFxMZOCD913fWo9FKvIWSzYH6BGNoxMoPJ5jGxgZnmxEDe5dE2Beqz+y/W5Yxx1RL0FvCWtZSFst/wJHydVlWJAMLFTF8/M6sP8xiB1ui4VL5/i4Kl039a+Wn28fbfeY7vCFAchQCVZOOkR+qLuBI3YMGhjX7YO2O342eH8CfQaw2DXyTHDeLP68rKgXUA6N2ffIHNfaLrObUe9uv+Cn5XZab/vJyDyzIJUXY6X6G7KsZKnctpmJN098PX95A2Go9bNcjUYFWoYJv/lh2ym+rKKKm3lA3QSV4GJSMmgD+VBcY9IpAYLCXyvYU+U7IHoodr1ab6LigtN1QNuxMioeXXlwq+1KfA5U8KJIh7YlmIy4xT99BmIfPyq15ReS2G3Vvas2Nw81nEodBBqZWa/KuUqDM77fuWoWV1Of8JPiDPZx0NM1y49K01FmZz5uFkUFug9LFou4nX5B2x1nF0/cNRuDlWE+ZNkLdPaJezPzBoKezkvoPc+tjsv1Qupqr0ClVIgf60mt7cClSh0dOFDjkCw+WLUHzT1OdwQ3L2m7V422SxoNxc53TeVdswYA3w5TulBlOtS6i3E/onzZUzAy2/ykckfDAhy/t1Pfbt1MB7fR38SnjNc8dbzWVyEvXDbmqyCXR95XnTz+49SWH58y5yGYOOCr08GkRwS0XXpcDoX6aamS42lp63bq5KB7bLpouVMxHd+BIEJPS9yf2zmZLccbDXJWDaw0yXTLriuJFg542WnTsd3PwBKBTWCNJll70n2lRV47ZX3Qdqd1Pex6Pam13fbzWW23GvfZ8/rIsn42e6PtRtPH8ovuuPEm/HswVd/joDZoMxC79MAWuapVaDbyGvx9XOcO6nEAyC5AxrbfaR75yzBoXJSfES9EWN2LT1UYP/5NTH07m6ozE3XHig/yUmmz8rTekFWrLBsnsSvO6zXEfZh9A6ElVInjGNk1lnLJTyApP3DnQOzOXi7gtKyLnbwE3YTabuIHAfY+Btli0MZRtVzmIts1yR1nJvfZEsc66TW+3WAH5AC1HQsHyWOPU9+uMVszcVriw/AS/EcQsuTbDcqjjRwNLFbmSeymI5m1AQQSZp8UydrVoO2YS+0ETpV8u2bR5z/7kzs0OJrUo9L4dqx+XG6juUqrsbRPoAhdbDw5XUKb0QauqYr1DAvifsy+geAM/yKldEFB476O3ElZdUvUPD105SwscqiJ6nQPm7GMg0pKj4/WGAiMlBsKRy79clyU8nwAsiLSUOXuahI7/xQb/7qJrlXyd1rqy8000Amwraeo7aAii5QjKL01jo8CUGJaliu4EM9R7M7RuUhoozysHYirw4Wkl11uei62NVy/4Taz7zvgkBq8HVMP+PzM+GYo8ZFhVW2AVCpICe4zlNtESuj/NAii1HX/iV3gOZT4mYhORrOeVhH3484bCD0xKAql0ij8EZSyAm8LRzLjbpYdhr5Sag8Ui+evsJ3jtAalNs9r8wOO42VEvTR+3lVF0kX1mMntSCYoR/kc6lKec8j6j61iOgzWaLtMilPIBmevWB7xScEa+HZnHvZWoeoMbFa+/5R2BEaXCs4pZHZdj2Q+4Wb9zEbYVSl7AUYmaLu1CHfQjeN/mj7909DMz3tsQNslA4R5aAVdnGmUjQIOULV0B6o6Nk/pxvU7KuuCK2O/ZpI88WfujmTuWg88qRc0LGBBS3eIdTGCLelJurS6LmuJa2o7hI1x434a0NS4GitIuxH8nejklezadThqcogiLfE0+mj/SV2NZzLtCMg13ACJ3TE+IseDjlPe/pDpxV3IES+gBjPB6+k5l5rK+DPktg+7emwu0u3DWoeLKaefGzluOqhHBqo2/TIsuJQc2rqGsTHUug720nUtQP0384yIezL7BgJBEHPhL8/tCIJ4bO6+XU4QxBwgbUcQc4diIBDE3KEYCAQxdygGAkHMHfLtCGLuUAwEgpg79FVogpg3FAOBIOYPaTuCmDs0S4Ug5g6NZBLE3KE3EAhi7pC2I4i5Q74dQcwd0nYEMXfoDQSCmDv0BgJBzB16A4Eg5g75dgQxd+gNBIKYOzQnkyDmDb2BQBDzh7QdQcwdmqVCEHOHRjIJYu7MvoGg3eKiXbR2Jr5Hgjldxwh5LI6GXxdhXOv7RyKXX3MIcz9uwNfjfaiT+UQeydhMATM9U+tn+uYimJs2kKufOEruf8yMttvt5FwpDKeFoa5m8Fz8SRC/M6ysmpA//xMm+L0jZbOQYsH+C/rDNBTsDwezUCE8yGkk+UfFqibALmCV2cVQSghzeBEpLhr71Fc89dTyJPQw9idxf259uxYzp+Vnfa310mAaeK7G5his9RHR6utOsJffO4D3ocLQs//G8fr91eicgNbvtI8YZe7R0Sq/bCTtaDvkTUxrwEZjtTXRHWcuCle2sR5sioNIPIQZbcfq+MewLuZ3tIrPXz1ut6absJL/Avvj/tpu3P+5Y9rrdgr0fsIfP/66rFR+2xjKPDcppDYgzVNsGW8wWKhQLtOxAysvd+qtxP2ZeQOBmX7dqll1WjJXYV8GPxq0XZDMel0JUcnMClHW3dx1CUnUi/KTc5CGjXi0F7gHdJjO2heX5YsqCTMbQ041xxUemOKXf3KVKKvA1Ts4NbOw3kMmeCTk8ulZc+RJ0+2Kza2yTEe6Ml3qsTvR0lsLV9boQcwa45szXTkvyjKcFqWbZNJj1riL9Q5O8yXlrGFlOuGVx79peScFpayshPRGc97/kN0q3aj7s+H//ZGlimYwFSWwKrttjJ+MbPsUoXykzAjETme91f52Vr27YxIR92HmDQTQdo3Ylbzs7eTYv0qRWxA7wbZNLj4YpYQNsa0wqjVzRpmogmth3PCX7RjzcpgdyZNoogE/YJKJ5fZy27QHKQCwi7GpJuhVYzSQB8ve5LCvMUXOY5XJFQUZbr4dwgVAC4gx8IhHagM1jTCxEIrY5kof21xhM5Sd/rVVHw1ch0Khkv4Ur6m6ylpVHuFKO8s573hsUgVkiPIYeAjttlKLkLHA06iyd3Gt1CibwImi6T6/Btnsq3LVFKr8r+Vu6ly97eK1PypaCF3xxre7/mAq096uF6ZU/IQxAQUvTSGZuXUDifsy8wYCW+VJB2QynFYXJZQxSmC+ltlBkLuvMGQ/SOEAOj6LYyz6Ne7uChDB64WnAqrIYFZlijq/2AWJKXPYxnRnARWI52/qhtOCPSDlOORnc5Bq1rvGvvxogwedTXZysAorrtzZtlzt4wV59axpcjt5Ckuet2UmOIrZWJVskYMyhpYABujE5+CVynTpPuduwi7Gybc7z8H7ZwEb1U6+aSdwB9B6Xm6OoScXcJE6FhrFG3KHbl7DXcEBcLfpJP85PenVXW/7kTjb4rVvB/2edR9vfTv09eSawo5T8EMobMO2Ss2kZj9C+fyE3PXtoOVmLNvIjczKU+xfe19AttZy0esFjvt5bOLg/EErWBqgfLGKn2duoaglS2SsSEpNxo+QRR4gmZXYeKEJT5XdKmgW+EEd5mu3XW+K3oVU4DXA+jZkUOVpIKTCPh76V5AOhL3Lz88wA8jKg8Bl7BlcnX1aYB72aZAyppOMDGZxkMwytwBSvK/auH4/toeZyF8eQVah+5m1X+MeTE5A7OA6Srj8FDZ/h7miuaHz7f8+JD57VvDGDnlkWtX7WoV5VTGnzDAtJFgVuaqOsUwq5uOKjB4qRkFHSTyAmTcQWCcH6w8AwxGEZfACWj4rwZm2eWeXrSZLzycdOIR2vR0OsGVmI+gUoYZQkhwHMXuynrEVE3lxCJKbBu9dAVami9Mh+omGfStTbOYOBDqgIZO0nUutHk686dknVHlwZASdqc1NrysG2PqY4KCfwM7JdAck2KqAg+vbHbU/VnUWFf8EV4o6FfQhXBNcdVp/DgeCAQ2pSQmKVOTJ7ARA261nplb216qQWkVsclY98pOTr0NbWxbzsHehy0k1BkXOsidqVttlEjxovAi51I/dS+kvtVcnvkh9G3FfZuZkMvDISuAyPUQ7h14tNXHUJ++Gu1Oxwx4PtZ3+mJRWpkG9uYXU63nULD0vAjfvwHVr1S0cFJ16klVqepqsVwlo8KIAsfW52IU1Txb2wCrkUSDqoGRVslTx7J/hyLoHhsWQRjLlXv8a+oMBXJgqJ5lfLtEwgrMc+qftPchhL+bPQPSWUKTsJmjg8tTUWefQRSetzUQXRPddngdRgi7dB20nCzA0gc+xK69V8kfX1FeNsM4BHeF6Hx0wXbCseyHuY/dj6rU3gDEBHRM7KUupzSFYmll2GWu/hLgXs28gsA+bM2UINYBiV2u7IFloxA7XbqPYxbQiW4/t0RO1iulxN8ABPJp3OgtgMS41DjqqSBwAqwF3MRoQU/F0jGKHvaVWz7ePN7gySDi3bOWgVltr3ZKJeJjSQO1rgb0KTRA0G6vwiYePFWq7IQi3z1MWz4MYH2/V2m5RvQTV9r7JupxqO3beX4S/G8EU+Udw6+LyaFgbltmhUajt8Lp+EG0HXFTvH31MJWm781Z2sThQ3nvR7764+2DuorEgoOCqd0xHqKM1/EPcmzvarnlul6gOKlAi7JwvZmtPBRuapNzQsse+1+ihSQ+UwBZZZW4hPe5e64vsmidjEjw3d1ye1mJ3HUMVk5uHOBXRsJTmNGk7fDZ0qELv7E0jpBPJLhptB9aO8ebmeTfba7TdAoiwDNEHHOn0MVmQErqBjeYwtr7bdBuZhWsCQa/vkUkGoltru+m9SjEI0ISWJSj75EOCOTwEqxmv0f/32o7pJPig3NMY/uPCkm937NsfFZBzHORN6+uLOK5ybBOAh25zHN9hCdUlTtyPmTcQoN3NOO7+FJutDPgAYTCj7fCxwi6OWTw7RXuz5cF5OqwH2ixoO9d9jl7RuJjRdqws4vOtlAQsj6idDjn4djZ/hxWqu2GI8psqt1RrU98OrZ4PZnp9U223m7TdxHOzivl7Za7gx4G8g0RjFq23Cz5rtN24v5cuDNPsHPTZeZrZxC7Bt8N1yYEcyjZ4iiVPD608BzH8YbQddAL4I1/ef6bA/QGLA8udMdZj0qqoWT2gpE0by6oneF2L7ES0sv029KQrdZ9H3JO/m6WSAOmQ0OzzHLQd6KTt+uFZo+3aZh8cMmz912iazWg7zXE8Upo8Xt9ou5ZT+d5N+00j9Nko5CB2oO2wPl0fxAIUKy6kwc0qP693/pwPbgfLmlkqo700Xim7T3HoJ1vjHPpgbSC743KAcgICCVk02g4bEnt1gFdS4vjojbZzcu8VXtTSQKC2G2WHER8ouAIuz/442q6D9QOm+zyupNZ2CCg50PjTU26HHJxo9oynAsuyrR2ogN7zgmUd9AKJezPzBgKL+ZsmCYDEtTshRNB2Pjdy16S27vNzqIthsQwN1EbVCdHY48wN0lMDOzDoHqgQzInJPdh2jeHfM7m4mV3GVpQKq7APtCdfz/bsdZQpUSm2VwPvQEW+zV81O4daMGtCjkIPGjiZtyJP7cJHBb5iTI/Le28HbXDXBFxNVduvcN3BgyXZNSEUKMEhR53GRG6ZjzF0Ag6C649d2ORg36BwkMDhYz2U39ve4r9CC2469S09OlDnt65aXQayxEKTJTfBqOYi9gP2XBdjE4Oag8f5KzKr7Xya6TWFVWH1cm0M67RYm7CtNILt0twpVqV5YGMRVlNNjEqPluVnnLF17FGmmBPu2KYJYEAzBNnAVqCxl4e6HGefxVqqNrcTQPjZVoAM65ynR9bKqWbiz/FszJ/jPuxFenAIYrf3RnRAthIl5H0JebbgSs9guWVD2DjKJNxMOEE5tJdJZj3eju0AeNOyqpKhiufHzbpMz8l1aTGP/xZWhtCZT+uGWru1d0blBpx0dJJqGC5iNSxhsWPR+rqdjDudlblc16/HXN4uH+Lj9QchzT9OvWedmIZA/MfbHpogfgpmtN1jwaTvbzTp+wFHqmbs7M8wOd4sk8MPDlhaQxA/DY8fA4Etqc1kFd6fpUKJ9Ez+r/iP6mWtQX+AcQ+CuB+PHwOBuU8eHacH4Cr7T/LqthoHI5NO/71CJIgfFYqBQBBzZw6+HUEQd6EYCAQxd+ir0AQxbygGAkHMH9J2BDF35jJLhSCIWWgkkyDmzswbCARBzAfSdgQxd8i3I4i5Q9qOIObO47+BQBDEn3j8NxAIgvgT9AYCQcwd8u0IYu7QGwgEMXdoTiZBzBt6A4Eg5g9pO4KYOzRLhSDmDo1kEsTcoTcQCGLu/EnbMe3gv/RZyyao2b8jtcTIWXfAaPJNsgZDy/0DDICz/emAW/6S172Q/3ziGvb3e/yPC27Ay4abf+Bn5r8arJInD/u878ORcNLZc0L1YMPAioBkUx//WrTEP3HXt5v4BQwoKOrA3ZdfV9nVX8O+XPTexbuRQMfl3eUZRhjnw7X/MQq2rkPrPZDL+C+B4eRe8Xdndv8YfGHKNUZaget+5LbnOdTIqv5Lz/aY6Mu+6obbczLfTQ0D6ohZtZCirWEs3Hn3Br8Md7Sd+xBLO14sOTY5nweUvn9n9DefboYu+k5rZGJ5JnbeXVbUEsuku/6nbzvrIv8GsQvdfxE7HfnftB4p1HWT/AeYQIGW7nG1nSyVsNYb4+oIj3PBGVWNF0286Xjkq74f20ULas7FYN8ZDPrijb2Jnkbcj9k3EGTon6CwtMrc6MzyPQzn/50QC/+oPPy/DOroJlzzwxDqX8RuvbP5d2IXin+Tp5s4zI+J6xZYCxt8jpplsjPAGID2o5kGoHhipiEmJy+6Dnqq5+AWlO/qVcT9mXkDgVWnl03KgNit8R1fVRUGemNW26qyUNS4Zgz9LnNWYvoJ7K09WiMM9qhS5CsEt2fSOgkr03GRCw8NR25UL6okRJjVW1g1sSYPS5JZUI8unafJRW68qM+u2ymiJYC5rsHKtCj9Sb29zqtCGWAOTwLXYndBd0Jen/SrAsUuXewd4b05ZmQUnjUdiPstYaZ6qeA77krbfQungzvEjXXmcEtL1QiOV5sv1xjc4zFuqm8GtLzd13gL3ysunttJsq3jtxja90Qv113OOZ/2K75oorxmKZi2NAXLKoGVTzyImTcQejdBlI/Raba8Y1ShDqARymgg+aq3WylY04Y1Fx9UaYqCYxTXEgOuMl+oot8GEUtI1FBjHqtY9MH1k2GQY3xzWXL1sRshd2i1mFdYPyoxNv214/EqE1yEWPA+bJ/oEjarhUqitmvsPRl4MIXqC5DzUVkUhUpehvSqD/vihZochewsKpcdg6n0MYr4Gk3BlNmH6dUBzHK4XrUGEha4gLvDqESTUYX7QabO8EG3HK1w80EZK+ogpyL3E7A+T+G0QTLD8ZYsBz1w7DoLUBjoC28smBJu4fXMqb4H2vyr8v1+OGVSH/Sm9uEAr86dcziSwgSI3faqkplJkd6JBzHj2+3zO8Ef7dOnpWRabY4zuZwLyeSkPH3JmA6b/jgLuRoz9nYQeiB20BW+yKElXpuPqe9HsYOGb1UuerASpJmFLjREHbovQK8pqLRKlYyxUn2CPxxky/I2g5yUl8xj1HQNRzEGHtZGNrrRdlLk3LNexcUuu1T2mH3uwGlY2X2pmTbv1zK5mqOqZNhdj5VxkMFArYGDNzhn7In5OO294RguRj0dwAIdhZyPmXzbhQsqOZwU1rrWtXnt2GQj55AHS3cIuUDvz1bVGwaXaLDfB0EHsYN2WsCpWHkasqzip5CPjR+/r5TY/mqShHnQmkYtr96n8O8oazl0kv0C7peJzRHUiGH+fL/Vo6HMBzLzBsK4f1fsBhGVTHVQZtsxKRGwdDBAvIvQqPdSTHFQajpbyksm2+oQj8GxLmS7s+COnFKLkP6EwftFH0w8332OozQeWjE0cEilhxT+AAR/UcUhiJ2B7UwMLOaEVWpPxSRpzgQT/F0PzhpOLfS6eKbeEzBNVfwMSd01ciieJskCk4yJZF1uR+6zQwWCjFfXnrZdHZMou6g+D8NpCSahDB/HTabDz73s6hVadaDtcEWVn+NBgtuz5rpEbjOBUmw3QQD/OMWui4WBP4Y+AzMuB9817DGo+Wp+Q5kypntgO4MUOBtPn++467Hg5Xa2dVBd2FgNweYpl+cTUv0XZGZOJnTcs4Xo37+DQm/50xLqoYvy42tbCxq/Z9jzY31010FYlibjzXrT2NWto9Z2/VV0cTwotiwoUEOhlh8WzRCaZ9OVZtVpdQwiAT3sTroW1DmZXgST8STEpwJE+kbb7aHwQo6DslfmodFdVRPe/FV0u50cd2Axrn9uegCxbFlV36NcBc1dU3HQTHgrAy9NGlJpeTCpyrzTZKo70PSOKuwx4IJqbSf4IntVG+Larh+LAsVuoZNplZoplg9ryqg6+PQdo57DZc51rB5MAfjrB3ypriI2ttvwA92uzeQXZfpCeqG9EhWF9HwQs28ggNaYFTvLMXo/tEYQuzaqrVbT+rIlXu2C6F2g2PER6IISDMc7lv7R9gcQu8ZYAceAZXuQA8iqKAHBF5xc4nmnPME2XL2vzlDbSRDgt6mVo0jLamlVGcPDELRd47wP0bEAtArbGgxOUVawvHTQwVzBR9xiAbRQll1ENbpOihFyj2tMPN3C5EQseFuW52U5fDtIQs+qg2rUKdL0ALjf7DZTCZZmdraVxG7ydip2loWIHVDiJY6RYncB95mG/CAt1wZJniv+5vu1R3nJzb88zfi+SNHFigqDnTuPkKD7egH2w44QemScXI1QJDH1QsQ9mdF2yY2rYU5eeI5PzVufnqK2+whK5PiSp2cNIBa+V2u79U5/BMJSMa+aQdCGWtst1GLXLyfZqz64iGZQxHbRbncwNLI3MR5w8AWrQdVCY41llwO8lp6AfXXgMVbM8QBe2422CyqJku1jJ7tnosqDBl2kImKCAzsPpQK0nYQjk4Iojd0NYGji6qBsCWeNbVkmsxBu5dTrYDDTiYX+BdsRZPpBZ3oV+6Ba202gY8G9QdttzzzMCvgo0vYDXmRqnh4M0EbblacrtZP7HYCiCE0BzAtWQim58c2QSg2r+EmtwydV6O1HuFO/XPfExP2YmaUCquJZkwSRO7N1u0VtN2wn06ppUi0ceHjHPbQr0Hbg2x2gtkubst3t+qkuarvjRtttoZH5Esc+jBq3gKNh7YpfQPcJ6mvlIBmZybe70XbQ0iWoU2zRoO3QbwSGor+Ox62dJtvmItMmF7J8v8GySeuCSTYs39farpC6MZnLaCfQMWCS7eHDw+OLi0m28T7lwMoB2MvJ4zuyPDlw2dF6J3/HhqjtjpJbihp/6tuh5GLyeJdlr1DbLXZX2ah2LkHs3jFfW6+gwdMtfjst6HXm7UENoTzhvyp1rcBFXV/H1fulek6DDfvZYXyHt1zXO3E/ZmepgHaqn49KHEIBowvHN/wBajtog8mIwke3I9RktbYbrSrUdktM1xKmQ6f2QUDbPYH8VnElCG5r6tslrSNXp+1ohIqsOnjT5H2eg97LtgUYpCIN4hyDDzac8e1SLtmVyFfqFZnmq8wPvqTZEsI4cIJQ20nV1tJ0k17qwIVa/hJ76c9xub46ON1mxEsbmQXHTBezZ19unqt/5kbKzrLOLiqO/UBr6z326a0Avl2lUtfkI4grGli+H7Kh2UztM6n9RtuB+4u/384hSN0dU+/xuQpp2BTqsCmuaxNQ3GQY1HLIStHKXBK7eNN6iHsw+wbC5G2tIaTJ3+GQPmo7sDVB29VP9M5epjYFDjdDCap9OxAb8O0av29p2kTYKgjIrG8XcDDEoU8ORiQcUAUUCq1A26UBD/Dt8FEE+vBJ25V5mKCyy1+itms8m94lasfkQ0kRsAuwcEXDkFz/rRwai0ctNgmD9j5cP45Ceg6izsxTOMXZXtJdCYbXgFaTAL2W444W/EXIFC/fDsTxepoICr4dGqBuExVixdVaJgvsgaQ5ddlLFDa4lmM4CZbbmBdwAY1vd/qdtB0THEpvzkDhwN+y+7aZ/MVM6ps3eCpzKNQdqBC2Cj1X6nqIe3NnTqasohFCmEGJvleOYndcQcOWqh6C3O9wIUJxLrEiUDfo1cEIdNT5Geg5JcTLiKMwiIxwxFqeVEr1/gsYLMoI2bIG9jKbVQ+6SUiJiI8Ax68L8dkPPrJsL1U3KDOL5mOADMNT0FtF3gyp4FO4P8ReBFdnWKoOXItCrwfOHURII0AgLc/FZcjjIT6Qb8PJ+Ee4UGv6sHN8ljzDhA4DOEbBrcCZlkWdqTyBozFTOLo8fe71i/wS74CVcPXnAiU4s7GAXHE6JtzSs5HPoWu5qgooN4UzFd/mSexA8X0f3+5tnpsSSkqcY4c4J3SAewzgWmOTKOHELkBtQA3XtatDajJrsSOWy0YyiXsBYjf75TBn2saYVKr7AVwmLHGLRkVd6fIctyZZEg7sDlZBTdjgIdkrYdMXHGdGYIPOtEi7OgEG1+gEJ5xBprBXOqGGhPmAfSXzJjp9DtpnLVhorBMv9mF7B08lIR+2FJq5gdtiwQtj8MEGOFyYQT3WMISVpn4TQF4aI3SJ/UaGe1R+KalV2ANn19zSgitp70CjuareWdj6B3qNmV2dZiqDudTu3Vo6hlWw2nmRsoKkQSP3qjLBwT3iIxM81XM8zNVN0k6fbnwr3mCJIanjmxMSC3QD3XQwANDUGHagYTS2QsttJF/7Ys2Yk6abJe6HVIM0uP5TAL5dM7hCED8zkzI5WT8HbG/6BI8gfmZ+qnl1MkwfJRAEMSeY89/xFUCCIAiCIAiCIAiCIAiCIAiCIAiCIAiCIAiCIAiCIAiCIAiCIAiCIAiCIAiCIAiCIAiCIAiCIAiCIAiCIAiCIAiCIIjvhS5NClp6F1t9VZiWq8qxTAehMy8g9U/IsqSoLwRxS7WQn+o62vQt0qSoc//GxCrPQKiq3hnGm/tHDhfacw42ShA/MizEzm0A0yk6phir/4qvIx5DNhhd9R+RBcZCJQiixqk9l4I5ZoxJVEnww7a9ivsoKFJr3UT7waTGdbAbgwVYzaTg5Yhlw93WpFywuEe9L26fSY6ui9WrOnfI5yeKHkQQjwKr8mdZVeusUmGQ0VYZrTf5oCiHYD4qpdppo6wgqVA+dTB+FdJ2Aiou59GNjBnhwR1YmXy4yVqEZB3c1RqlipXY0b5I2872DMXBIn5zZCyeZDZFIGchhUpmYeBAxgqrM2eKytpOf4NlulN4a8sC5M7F3Hj7xny07DpwMd52vNBZmSthLWg/CaKsgrVVv6Mz9iYl4yCwQ1VgbEpXPCdtR/zeTCwXx9l6TOrunJ/A35boj0EaDSTLUwF/daFcdjKNcu8z3U5B++2BYLVvp1XU2VJe7KPMdj3YrQqS2SUXTMcka4KDqyj4J8xB/TzxmAniUZAGRCrL3uZlK2OCJyMzwCpdgJzIAsQJ8LDVgxbbXvOGb2X7hcJY+7ILKjKZpw5tz5L7Fqx1fIdVp9UxJBn4h1v8DeaQsgMJR+1qUCQJ4jcGFJO/fuKq0zYImOBoZGaiazMdI0NxQm8scwcdmfW0EwtKPa2OdOziat2HtVu8AgMUtV0zkilVONxphjdN/9Ozei0zkBMzsJtTf/OQkCB+J1iVc5AlxTlKSq3t2I22szxMcC+bv+qtv+wrXuqSVxP9USWx64bhVNuBPJ2rpBm1Ci50UYNmWVS+XKiFMZoh2peeVUUtkgTx2zIyB9a5Mag7HlhWKfTZMvTt9DKI3VTbLXIh3/aFcz3w5UrQhLfaboWDPakV6Mqyn2QNxU7wNUxmRtmlJMm1tstcEfSHTpJOgvh98fVASZZdtbufJ9XCEiQnSdsp9O1i0fh2lV5V15Bi53wp+1xMtd2Nbwdid16rOMcvWfU++XZyOWpwC9GmBOW5DUd3VNl9c4S7EcRvCxO5bzytMhfHtotCaJUCbadwJPNygI6Yjsoxc4rGoVV5dTGr7ZLYJd/u2QEqtGFQNjtUaZymxJFM0HiYEU96Ex/91fYnQfy2+DyiNCB2sKCliZVdNFwtgqJTVl+A0FTWPe+CofiWG7voxcd8h+lNnsRusDoEo1OM5ROOQyp5Xo4Xd1TFmud2nq+CrrTRWPumyEFE4RCTHhASxO9MxcVFk5RCeaYDV8qLCBrJL2yChMBapSLqOVbBpoVKv96TI5OEVUcBOwTVt9KAgFVFaWBnkLosO/ZxUynYDBw+V+rjlgk4M+z4y+lfZn8SxG+GbOZNIj0N3pfUeh/nZIKY6WvZSj+f6zEQhlMyexd6t9WSMgmr3gY3racP2USCgPUkG+1PJ2JmI309TUpYeyaH6NKxsPmkXkkQxJxw7dBrkgRBzAFmd2J604EgiHnBKmPoUTlBzJeLNOWFIAiCIAiCIAiCIAiCIAiCIAiCIAiCIAiCIAiC+EGYpHeBCIKYI9LQ974IYs7IPH0HmiCI+SG7efruHkEQc2PYJ7EjiDkz4iR2BDFnhgs5friWIIj5IUnbEcS8kQskdgQxZ2gkkyDmzrCfwisTBDE/aCSTIObOkHw7gpg3fxrJlOXeyl8C9zDtZcZ8GJ9NV3gRVoOBf2UKde6FrTfJaqc+2pVia7r3P2O/2MeZh62rEq7DvvLp4mbCQfyEsOpDJ2w0C4+NE2mGrhZQudVMQ2AVVHbdUHQIoQ6pZp/1puFtiPsh7z63s3neRCe/5aJXmsOM2VcpaDLCTK46SDwVGvIwOUYSAnSRH6ZEmed15OX/SZmHx5EIp/g4y0RuQJ2bPIUq+lmRgptOO0LHNwdYKrLMBQW9ahR6+tVhWcJFmAIFUQplugFfW9GiDvxE3J+7I5m7lzwMdpqFGz5Hc9Uka2RoYinLMIA2LffyHINUZtlh5Ov4y6IyvNGA/4Ol22hg3xdXxH0UOwGX+OEv/cjPBCtREJjgfg4f3maeY5GxmGORlad1pcKKjTwyuBSMtbahfGZjiVfW+Zm7s/+Wu76dM8aZmNQUA6TEXu1s3G47+L0tZBamTdnlxSF0gE/zOpC5NjyF21rslnZ5JswkZjZMmaUlTGK64oKxq7QWdmjBv92018y+skliDpDGhITf+pjpxjtJBKPUJmWaZdtwrbcbfjq0UdCBwE9dK4+LVtB/Ztn1cjJC4NRNfF5pFjAlO1DZO5salkEK9fmbeitxf+76dtVBCX3aCqQuKmNFURR7LPNqcKoqWcUb9SX3pmInFXeo80KRmkUThJn9AU09dG8aCnOm9EoVaJHCMWWhCoP1+JaXvbJ+308HIauwFAoVq8xHVeztYgw+TMEK2F4KET+egxlsFOyDRzMBWRYbuF+GWRY3RjBqO9jjHMVOrjaa+efEc7T6QLXw27t7LORlDBy1nU4x06BzbWrQduuLeMvt8Ts1wpc0h1kQGMWeeBBSzTy36wUQIqtWUXTKXIlqQ+SllKVS5aEsb30k9moqdppDPyjDqfc5HgXaDmrqaD2CEHo4tN4py8abByB4ZYHRuLRQ5ZY3C5ADarv6wGyLl+BYxHO/EnkQlX/Fz8F6raKpVoICY8dF3qkqC3IYVjZAhD3oWFOubAQF+0GjNB6SNxcI2g60btJ2qJl/Ym3n+Sr+sGqw8u9DVN8Gq5SvOMa4r5GpMhHLI/5crJxW0NfpbNssSx2aJkA8gDvazm++hDVxcwzpt2lMREYQxJEJvYyd3/pI4NvVfS94Hi8lKpT9q3a+dQbNHWuKfcI8HY/18AowLjgO3JRowqQ/mVOFzqrTL+BIQAKDwY5wCGQ7y1byAWQuTV9jdcO2IbiJkPMAT6852Dg48hMm46f4fq488axlcwOiK2PRGEWQO567zPdg7epP7dtZ/hx/dgVHG+RRsdC9+VQ5NRU3TX/lVBtlnu2AJ18eOOgDBdurmCvPH2kk+pdndkjl4iWqoKxK4yMnOcYiB7mCJt8GLQUa5Vbb7fF3FnAn3EDzHoZ8DO0DnJBa241QZLLs5W3OiwrlApWQZI3H4E/Lo09ctDLIF61CqGIxQEECkYG/7JKPYUWSbg3tAXLGwzQOcGtbKcP2eWieDAybXsB+fNlcoU4SWOav0safWdvtdtJ9j1X+6ZHvQgYwH/3gRtu5ZW4xPDaw+yoVsFvOX2SH0fiXxmljoTbjx5+5bP9DZrTdkVbLVo7kUl5AWZanFdjurDy1mWubdRQ7f4xRzqWcsJBzpTZ5fpD6Q1AoLtsWYDHqNoodKB830voLn0rBke2nThQslLFTJnkOoLDYG/QkxrEDulXBVbxUWLk2dqBrhV0dSOiiBGzfSB37yWRlUnrVX4CDe2YAHieOo4yUsXJ9JBs/CJj6dqC8d83PrO1aYGW2odBL/v6R74JdRjhDdTDVdi7e9pot2y+c1G9TW3FRKSuF3xWFnBgK4vsgwLe7Kd1K5SBMSuXcgxI6QOXGyqeg7YwZodhtyEoBnX0m+DOpR+D+JS0jA6hEMAtzn7QdaMhT3K+ff0ybAafO0++lshYUFSYX+SrzIKnZdgDdGArwxcRHbFp2+TmeWHCnwwFcDfw/iFq2OT6ZxzEWqHVbRHnRKzmcB+RLdp/i+XC/xpuc+nag7cBf/bl7ZDAjVKyqW1vjcXDqHZzgRtuB1KG1M2UMpRuXqu5bWCfX5Zk1WmN3WRU3rYe4BzPajkVVWuutLVEaapuyJ8C82MfA5ODbrRxrb9e86zW+3VWp0tikDAM0hKB9VGheQnfo1zAfwZuvI51Z/gx/wY5xVj0HBw72flqyCrVdVnWrawVeGMhe0nbLOIggQduB8FSQj7dOT3SRxkhBaDcsGLMFGq27Y+s7T6EB8NcV7mb3dfMYsPbtkraTq92fWNshzvqxrpKt+XhciZybGDdz3gF/jXn1JzG/huLVvjbma1sfHDwQU/WXp7zEVwC+3XQkU09daGlAi5Wn2LNNtV3t26WtwPS5HRN5B5r/MByk6iihS+zqbCUJE3C9OX3Y5FRatQ426G5UnzENvl0Gvh2c44kxwmDeQmGuixEvg4kFNDLr470H8xX9xdabgyS/482YHsujJHMvwWXENPNTAZvx7X7y53aySkXLwldM+vkWJraqLssdc6BKd5b5zfdb+FymQdYFewZdYVrOKqgiF99BzaDsEfcGtF0z30+KqVyxk4OSLaXuDjw28O1QEJJvV29PwxQpoVVetjLdeZqq4yrk+YJk9eAHwD6c1jkej1WRRkdRIPc4HFI/i63eX+JuJVd/oAXZaLuPYYJqtvsEZ7Hg9JgqF736iSCr8nNw83c7IO6jer4UyCo7eYrieyRQuyVA200fIEjTnwrjz4gs0ih+tTBr8j0efoBi5NXMM1AA/AesUt+/3E3LroQi1W3wpEt0CIl7c7WZv6hTDp9813zmyt2MZHoo9ejlFTh705lc2+HpVp3yYKOy4XP07YCxyk+1vfGwsjd5lGkwzEW0BT0aq5kzakNrMECPQZ5eYWNyB/kJ/tYP4Wvnb/fd+zFamudOewU9/f5yan7jj8rr6yrmcd8WwUGe+CwQugGh9cpymGoErbBfFum53Wq+NZcW+0hscLhNKDnslx6fKvVUMQ860cuYxuFirz44bafjJ6w8xxItl8GXTw9difty874d26pVCzL8wKu3HF8huCpBFid+U53rUm0148lg2U39pV7JC9cMcmfZRZkrfKyeFgBwzhxOJTwCURJK8XrqrA5pkABUZ7WAuisbxVps/4j4sxhR2w0FToqS1QIc1oE+9ro2JJlVfbVgbIiO2ajU5sIeNgWweiF5+3jeRZyTmZ4Qgj/5U3fIxx5KKxnj88CjPbK1edD9qBYUj2sXo4Becgv89j7vsGR4HluRqmskVDdNNiLujVTTNxCkvu24pJP1Ymv4BCr8+MlYs95hbWEg8vO0GQy167UkTtlEmNMTOLZeAIdhtF+n3WYYOTvdIN2i3ccjrg7TmvUkJLB+HwdboH9NC+mhHHN2cZyGMHUzHV678fgQdu1lF3pxPG7y7DlID1MSqfvoOns5c90/Je625B6dVGTy+jPUEJwVTssO67p1buymtsR09uvu4uJ0FXE/5vN2uV34X5732mMPjhPED0Vrdy6fMLK8MzMwdgdmK3rmSvxmzEfbuQ//eBIp1PPrJk0Qvwezs1QekYv/397V/rTNe+2kdhTsmRgVW6Gk0f7/v2FofGEfqg6EhioN6MbEBB7jZUWg6v5Qpuc6dlpgu1/G7tE9Nz9flNZJHNuxfc51jpP2/LUVyfxX7yIi/odw//t2ERERc4DYiDEQIiLmjMh2ERFzx5x8u4iIiFtEtouImDuibxcRMXdEtouImDuibxcRMXdEtouImDtuv4EQERExJ0S2i4iYO+6HHomIiJgDIttFRMwdcSUzImLuiGwXETF33PmdzIiIiPkgLqlERMwdw34Uu4iIOSP6dhERc8dwIT6lEhExZ0S2i4iYO8B2UewiIuaLyHYREXOHiL5dRMS88c19O2ZDUJD7oDAgTFe3P5nO7oQp+Rvo6vEDwrByPK+4HL8HzFbVna5/VLBZeBFKTwPKAKxEI8JgCrQn9Li+kyHiQfjGtyt56qNd3QOrumXCCjeLisrKzg8FryocRYR9XIj1/3hs8n8Aq6SU3Pn4R4+NI3snopddmMUpTM6sj7tFYsZecskvKeSWUBTKN+JncN+3Y0X6J49G7xuKFM5EiHQFsPp72fwz3Dnl0SDaTWTZJ4pC1lqM224OgeQYlG4TbR79atL2VARblexqURoadftWaWhg7H0ZI8b8NIS8+0ymrl3lSMbuQX8bS5TVS8+a5G/HsMOrxxfu3wYRQlKv8NuYmY8FUch0JnaTPE3b0ypF9z01Aly4m1z2SwpmPwHZ7YSjEQ/Hfbar+B7LJTEZsy9uirquXybJ2PDNz6tirHzsR0DvweAoMCYlMtQYEKaVtZR5l8JpiQrJgiLDjhWKYrRZU+hyFIrUJQ2mLVaxe2810Xld+wjKiVY4SFpU2KJStWKYB9iz59W8LyMYkyXOCMV5COPb+1QhKn91paxvg2Y+Dq72+qZ72ogds9Jtml4TNZutrtKHlrVo5fKK+pwlKo9k99O4v6SSP6+SSh7S9FbvTW062ceKlYbzdiVUutgYHaLuDxy079jITkcay6AHJTK7TPVwVEnTMdklBkWlh4y9NMZ05AUEiq0YhyQF3n3Bs7ruLPQLVXcch4gxnW+0O5ksIG01VZ0PxSVym74BsVrjOh0nvagb3jFL5tbPBNtN008WE/X4kTeFUlc+hjJBm7owt76dx1GxgfHNpUafS8E+nzT7Ix6Oe2xXZoYl+zIjNaZSDkrRHL0Mm0Ik7JJX09jlvZpcDSHJ/tFuqUyeyTQfeQnADEn3kEXxfII3dVz6QK6lu4Sbws02MSoqWUwlSq8Gad4jO+omER2+ckQOhU3WXg9ItbM6BdUmY2QXkk4U9Z5IrrNTCLC+pTic/ZTZjiD2P0j02eOjVfDAdiKX5VjOfDuCOCgkpsEk5zQhalaoq2FZNuGUIx6Ie98uP+ev8J6nYJ9kcVDjnannlsTuyivcqQ/F9pZscvYyqMZVyEUpHYnqeNOxocv+QHJY98eQs/OzsQwKFIUZ7m2V/H11XKUGKe0WyIQsIK0Vp+oSvVEL9olTk4R3Ms+0c+Jqs/aKlyWTRh/bC58dEDWvzkLyiYIVmSQr4PFxjAHzUXdX3r483s/ust1kxS1ImhcWXuZLV+l2dZ0veMsl4uG4y3bCLR3gozp16F71nkYaHGdBVZ01CODtiqGglczeeqAZyIW2QbZ2u3J/lddeOhcHxdEilKd2/W5wCrUM41gNchbUqjYZzSaI3XHwKBNm3H6vJp7F0W0YPk4OnN52sHJpVyL23vp8op01c0KYDS/MTxji4OaDPPd+8+OCFe89242dGcGdbMPEmEEc6ELmsHqKDclfiJfqqpBV6YI+jHgg7ny7/MxupuZzZ92lZDyqgRe7GdtB7F6KCn6ayTV7A7Zbc9KrOvjX5bNgnMDfHheNe4ARhPLMWXJgUglPAa7gZlgWsLwrKknPxsBWRB3IVrH8ueuarjE8tewwyLNQtduolYRBq/dSbjp5mWyvD9pdU3fgbjZ6dtjpP33fzpvSjy92Z184fIFku6ZbAzoj7XsX5ESMkuPVd1vXN+bgysBgUdlMF0c8AGA78qAIrOafD+t6742BS5aoUxK73leIwB90A6EHtvOLknuFGNbuGbgxiJ02YLu+f8KsV8tnrwaN2MFSDMpT53nNBx+E7QfDsOqD7SRxrHbEdvAoKrHHDS1WHioqndPtCbEnzd6rbWYuQMGiyGuXfhYiC/n2VPOkxP+CbwdMitNbX+DREIwQeACbxQdVc6nsPcE7rk5VkH2mzlnpMNBVdu53RDwM8O3InwtJ76B5adCJ4vSEiWe7fQPtxyCH/ijA6gsLnRisTr3kRLnh2W6NiG8jCFdxWkH0pg89jOWm1Zlfq0mqDcW2pBdII8F/JHbw54LwCM3EG58u+TqdLEzW8NpaNz1h4TYW5WscTfLt7k2OpwV24PuMqY9z8O7AdqQzbe1cBus+dSdBt02fGSueLx77RNUVSWn2kDULSjbiYbj17UjVhanMcl60Attt70AEDmhxA0bmSuhzmuoQBVakZJHQYkhSLvjnhKoFMyXBK0hg8oGrFgsjl59a1pEkp5AwCKQk01a7JdRBRmZSDL7STSLt2hqsS2xnubdJK+6WW9e+YV/656jUC3g5u6kP3+4ps12ZGer1q87m7a3KRwMrPlLvjlrJpDWxjSsOlM7bm1f1VDcqZINfB0F0cyDhp4fW7iy+nXan0/lrT40ubtkOvh2xnV9f9GB7tADCHO05cBDBUqbQemFZv+Cd66SliOhO+CWzmec1J/9IMJCQyJd0A6EIbOck3VUv+Fay+3qBbpDnILRhPaCGlP0NSJ82qStvDHx5MoLfoVIiXVDcdFl1uP6kVzKPXtO68nBnY2e32fOIIGe8SSbJ/q1v16IbsCO4GYdBEKvLKwxHLkXSaQykiIfhasp2kyo1az4Fc+5tWuxAADC/83SV7EtX6Px9MXXq6fHcXNOda2Nkt0xaECiDpBkfkSrERtvfOVcQRl1ndIgeo2VVWxrTrzFmyq/BHCzRkgr7kIIF9SVOyzbgTfibd9hdLCC3K8ygEkWG8p0sUKamSrP27IEw4QZP2qsXihvnLuhJgUcHWyTt2cByB2tD5zUES5wsOPR/84BaWfspUxrXdivNgywRD8Ltfbvy1bOpEXlk1bgsyFZslQX1epFXYrlYDkcBVuU0D7TK85zuDlj5ZpznO8HtatnLPPf+VlnAMuq9RKavgUhLnLBIY1duUd7d6iVluymojOsiP9x5hwSzzRyrdvL8kukPyGpRRigzVHprcSG3nt7Gf5JgBa7X99PjY9kPeoB4R/0tCuX5jAaRtB5wdGPDI7oH0yGJeCjuP5P5s7D96FlHRPwwxC+JXW5Po9hFRPwwfgnbHdnN+CWQiIgfxq+J+MN0XNCKiPhh/BrfLiIi4sdx575dRETEnDC7bxcRETEvxF+FjoiYO6JvFxExd0S2i4iYOyLbRUTMHTG+XUTE3BHZLiJi7hDRt4uImDe+ifgTERHx+Bj278ZAiIiImAPiUyoREXNHvG8XETF3xJXMiIi5I8Yuj4iYO+JKZkTE3BF9u4iIuSP6dhERc8c1n8VAiIiImA+ibxcRMXcM+1HsIiLmjPiUSkTE3CHkvWcymS719z9rz7DvWD8kPvwwxpL/NRDlM/vM2nIO0fnZPmpqIpxoJO9OhDO/wydZacuQ67qMg/yT+GYls1xIv48Cz6paJ6x4QLxc1gSsiPi3sE7KvpQL7/ljRx+hME6SU0SzhFmDWmsKZB/ASjpGoZUT9qUvuX/CQpzUvRjv5+dwf0nlbCv9k1+J1p02OlzoEPDlR8BMjHv2a8D0vr7RWqXyj2k8pkdCJY3WlTMQttK5Uo/N21kMZeuM1da48hjH8lK1KdKPNZHtfhb32U7XspKfv+1M7bohpuEP6zbhKDZaxK8Cqze+s0F+MbSU0JSjXBZQmj5k4MrGm2YmCPOcAqW944oluSxpQmDnZYx78dOAb3fnmUy7UYucQrJC41W6UnmO/v9jr79RW1YW+lbfiuoy3wnKzqr8kuINsuWi1BTJjiX6fJPXFXwFu5iTtUlh7ShOXlKuXBV5riwFqdsJwbivC+XPgZFTWtQnkKB6v5X9/2W01OBTk3w0iMIPu714zY6qFep93Z5GUd6uVujjSporiJ1Oep3+dlIcRoPmp3GP7VgOrbYiKWgWy9PX664tN54x6wbcrYjL97OMTFw6Z5aMPfMegXP8BNKymBrljHSrbN+85071vrq2a5sbVjkkXI5R2klr48xGu1KmvXQK0ZqIPMuMc0iCIZG4ZEJxyl5QeOUIj+Usm9MUZzsZRfb0qC7ye7pvVCycMB86WZhMMEPxeCN+Dvd8O+i33eQge0sGTZHyapKUfSi3fWP2fezy6SiwS65GR2sO9oaPR84KXrda7zgJZrmEHduOfDuVuv3JbmIX5BqF/u9oFDoYJ0dVmoIexQVOZ3v8nIUo6NvttN4eseQkNdiTc4rhHEFoqdP5THFx9Q7mjk/urlk4eD4ZwEQlaVBzfgCxM2xLaSY0i4P0U7jHdl/5SZIc1wPao9I9dCl7zWEROgMyO+ezlcxyoSbX7UtfiS6O45wOvG3IHg3Z680q2XUUB12lNbZZ7U/czvtbo1eQrCTZ72cY0Ekuq+QZX6eA6aWsmWhTCPNk2XnNrg20aoTHDam2OUAUkrswyMxmCz68/BSscFwW8DIqaN8Kxg8MlHxDUmDziIfjbny7a0NedbL63kHgPgxekdgVzyuIgNF32e5sC+QEsPLqpl/7nZVU2HtOSQVpGga2G1xiW7elD3VdQioL/g7ZddbBHra4UCXFaRjm9Q3NjJfgStJJSXLC7cQn/udxXKT5I69iBky0tXkWpoOwVrm7RiZ2FBmMlJ6Sjudr1aWu5CubNeQY8TDcYbuWlafreZ6blJPMnJKU7eaQhX3XAdspXrGq3vu0V/yBZHOOTbMap+QOxFYE9Ugkdu3oHs85pzvxdtO1aH/Ju3rRS9aNfI3BYpDPo52ByT/hfM7tbls+w0F4dlRgDnVwRKdFNBbFfLAvpW7UHTPp7A6Ch3DcjjBu6uRam1KYNgbbza9pTwnw7WZPqeTcGaDjaKFYnb5An/fUcxiZM7ar6PhOWdyK3WCDdpk6r1rvggeyA7FjS57tvByOJZEnrEe4DTgRab3UxVESu9Hlc1+lydV+z2xiCFuKS2y31/eahdIIId1+k5wDzoMlQ6jCzfNbVDQxCGwxZ9odwjJaikHrfwZgu5fT5GZzj3uffGdIGSyb7R3PdvDteopvNfTTmoqdENXHYIhMxPC4+Dhju6H37Xa82GkZ1qEtxizQZJnVOMrOZXVMZEpgYiLadOeidd64FCw+XtaAOq5JPh5a9AAgwN5wy0SQtiJtlrWY9jtYkRbecEnosaVxG2IH58LviHgY4Ns137djUG5NL+fQeIv8A7aYGtxhO38UKIMapAcWloImLiSokHuvTMmtZHfJwXtT3tljh17WWMEXSV5RqM4+k29HMtjoT9Zx8O38DUMrjd+jlqL54oGOm8eibin96IvPEuYj1CwqPvejBWjTpsR1zrf8NjvJW1DGdZKsuBO/J+JhuPXtrmC5h1RSndb6xK+gDImOSu/bYRDOmuPX9SlRpOHV5B08NhiSfafh+c/YTmRtDNxlIK6KE4tWC5DdGds1RmYiOl6Y8zRnge3ohiHZLUXaDSr3fx4i5+Mm+YhoXRuaCGwPehBDsIddxUcvfcDwU6omEDbZLKBs7ZC10nHbSXee9u/TwW3s8kmVNjamp8BCpcRDGAF4aoqblxo7msMQ0TfO1N0MOVgll+qurA/IBPF2PlHlaGfDnDMVdrCXmevW7nMJ/ku/oFDtH6pl/v67fi1NbSTYs7cUTFdMM1PXLi5NNxD1+7ncPripZd01b8mOEecXXQwqjZJQNBAC44lRCmPS2q+9pi6Nq2HkUDLigbj9vp3Nx1M2m1S5tTsl7Hhmv6KrdV5XV1bdNIcBsVh36mCCFHW3+wZGY2u847Wyz6df1IqNVVDTR6uH3a6i+3NWafiH4qTqIX8oULyou3UxQVUFPWIGsKLb7RaR6xoMX86pL64uMab+sTAMAZJ+OMQJPV2UTBRGaWrrlpUXP2a73ZA94qG4e98uIiJiLrj3lEpERMQ8IKa+XURExLwQ2S4iYu6Ivl1ExNwR2S4iYu6IP08bETF3RLaLiJg7bp/JjIiImBMi20VEzBu3z2RGRETMCzEGQkTE3BHv20VEzB3Rt4uImDviM5kREXNHZLuIiLkj+nYREXNHZLuIiLkjPpMZETF3RLaLiJg74jOZERFzR2S7iIh5Iz6TGRExf8RnMiMi5o543y4iYu6Ivl1ExNwRn8mMiJg7IttFRMwd3/p2jCXfR5Pw+xgO/TD+rJS/wA8V+zeZHtKsGfw5/3jiTxX9y4GOn3tDvqvT7wCa5HRn+Ix4KL5hO127y+/iy7CyuEpYYew0ItA/gZX1Dwcg1fU/xwOlupvkt2DWPDieKLMVrpGpEJL2r8HU/4eA+NYtZfeC988BonBLrgnARGDWUSscReGyxoWA5ayac6ueELbvxC4HqjRNV5r0DCJ3ZXJcFj8eZs2m04iE/wS29wNB589eh0h5f4YqNU3qhyFMfTALX/o3gEh/r4PmDFa1nSpyV4cYx/OByGV9otq3IQbZ10G+qE5UxUgxK2MOoIHHP65bI77B/ft2It/4yvNRszWFdvXD+vfIynrYpP8erJL/xDkA+3obwPlbvHtfN6kfhuB0PdVflzlDJcffdsacUXJJgQEVv5zfFGfqtJ4kyUueTwexNKaJWz8q+JiiZ1OuB3d8xBRi4a7YlW4d2syzmtBMj8sSCk9U2cVLcdbT1z4PwLQQ+zhIM0H7cPJMkzZu7ZbYi+1SdmivoM0wXa5LpCkPcgoU20wibXywUM0E1RUO0yHUQB9NC1rKh2M+85vhTJRhfbLiHdrWz1C+r1PgkE+hFKHFMrbCKZqaIJKj7Yq76kZgbh0g25FuGpbgosrxH0M0hq7Nl7BGUdt/K2ztH5nVTs6vIcO2pClwnPNnjbBZN9XFbGdTJ9vmgiU2/2czJeIvcO+LPy2VLk4K6e8oKFnUfclhLFYb/LS/KJSsWj4XJoHcU6Yv38PmEB0fcVx0fFxkxaVcKFqJ7ROfiJrL/qmP+UpH+tKB2bRpn/el6vlhZO+IciaVVEr2FwwGuwzxsSt3iKMWlSzkOmEUmDlp+c0uzQimUbS8oAZVKZQuKz+jeJ6jVNWtM5mFMLKlaSsjFzKLJjDhqAmQ8ooP0o16UaYc9u2ECu2bspWweu/Nguw+y03lkJHKSnY/hMDOvw8j5jtdm1mE60fHUSmNV1QFD/F6k2RFFqK37Qeyllew0rPeaP0v7f6If8Swf+cbCL0OdKqVjia+SvnJeLlIu5pVS65a66l0Fqda8I9dW5YOc5IZPzFFG2f28kyVN7lUEB4zTK46Ui0f1FIdj3Bk8WC5NLI6Grq0HlsdVmfEa9KrZ1XKz5cPtihY9g1v0/yqJDy2atMtl9YZ3VKncEAr6exy6cgqLdvOlstdDgVR8S60sTQHyzeKjMfFQVaUNrDdjUnlVmm7/hRjrK9jn1neXtUCuW92z3C12O0LNRBDsGmeXnzBVQwUkfsN//+wqkLaaI60i8r8Ra8Mdrb9juRF6uSFpHWtSb6hSex2y0h2/wL3VjILDg22a/gq0iol6euZQQlVC+3HLvmM7QQfvMNHNaghdpte7IxbO6o2Xh8jmclyLGvG1CDHCcLJ/ZYN6x4FVyNh/LkB5UWNyd2C1UccVmPyl7JLQ17JPGFOEmnBwOwpsJ1wmzTQFWSrVQ+o0VpC1j3bued0iLU3r5IiNdNmwmZOyTgtwdksT6mdiQE5M8/Flhi0KdTyLktqv25zvZfWKGA58/TSc+0DOu03A62fBg6fA3Tmxe4YPR8qFSatiy+vzAXYT3206FfVMxWrjIkh5n8OELvZUyps3dv01aCD3v5wSgO9XXysSOxg6H3gsB4DhJTL+MDwJJPPCzSdmZFXo/riGR0dK21l53jo3BVtWqnYHwUK2Fpc34A0uowqCbAQKTIyuV9ULOQHiJJX6/bt3nFJSgAzv1hh6n2RjPk5bSb5woGQmdf9RaqYHYDtVtCGm0JlKLogMWygiYNp0sJashAyXShi6Ctfh6XyxqGOJOfl0Z5XQOwTJ0EUue+Ls0MyjH83jgs+R7JLkh1+gvdSnjb3EHqVoupLiT7RXafaXV0aWDumzuJi5k/hjm/XQrcW1to8lehtEAyoazcf2GTZQfvBO9tiGodXS6Y3PBWAmUje/Cw1TjA38z+srBPN2xWy268cTCdKq55LmdYTcZsLcvOeDFdWcUUSreRLlPmZls+qi/wIe30msmzATKDiZyjumeNbKB7SSsyXs+ojxC7R5Re3kHH4dB8a6STAsKRZcbxC16hLa967jcFKsrYARoWsv0gmKHRMhZq0Ym+8AtmuN2ghQXe9ZLNcfnc/Ze5gxULjrM4JB0ZuWasyriZ+e7qcok7RQ3Az26WoragzWAju/4Mx8N8DfLup2CWLnEsC51utBASDKdsjmyKwneLv2GJf9jdqLaQ3Cont2PoGTdZhJxMjl+37cpLkGZzykp9uUmkZRHBCKyC1AAky1r7DdsWAtCWMTM92i7IA263TdLfZIQmjzwRA7CavmtZJ866Sb7zTQQanZ7tV15fSitf9cTCUG5Td4JkVHDS6gNOL7a8fYa7KDuqw/XNM6GmhriJORN5e3beYZle1J/RmDfW3oqfgfzbpOUHXUvYtbBEalhlacBKwYzTBiHWEbsOsqNxv757/JO74dvDCqiuttah4dzdRpyR22zlMrn1HYncOS03gsBYTseHXPcBMCdt7S5MVbDe8y3bwniw3pS9ODFtFml9plqzyb9juy0eyZGdslxUwAP2th1WZg46mQwqJ+HKmBipUL1D0613aXyycgO3eoOVZpUHI9UZ5VJx+9ecQys+HNG/YTlptfx5YZDnK+UpyReskXqqhv3fWfKFDxmovdrthaVZ3fDPBdrTzd2LtEzqySc8NDH2CHrIzN5kAJUUWEFDuPYODtwexk5d+R8TDIOTsKZXS30UGBE3AxcEHkgg1WJ2x3YwWRd+z3XJmRkl+EYzMJZ0chilqa2uzzkRcBN9O5yCS9y8pCReFbd9lO7v5FdYixtez3Qe5SExEYleBIg/wDwiVMwWOqk6DFK7mGgrCl6EgjcR2esMbk8J8w3a6nVFh211u9RJZzsnIQMs0bEdSvTrY8TntJw1Gpgtke9zCtBK1r6KVeyH8jRA5NzdNek5g557l0CGNgtS57/rpshTkDzPF3zOvssh2P4OrdLqkIupBo9gnICeSMvT97vlH0msdRmK31dw8xTT3VFDKukXLXUiq07aAEIElQT1pCedrghPoKQfRHkDswooifDschoBOUWafIQzEa8G3+5Iwt4HpvvY5zaf3Jqgxl7SSabxU21SuJfnHS6jdUkKqqudv4EZeUJn5ABL94Y5VWDp/04NK0LKPycuKFDPnaoBZg0px4dNCn0udBLaDvHnfLrCdIKL/naBeJH0xTzDSTaQkpwrsyqWkfKqF5pG/8Ve4msLAZ8/dXJ3OJ4NhPX3KeJwGCgG05FalpPK8gsNMVKU4T4vGtYZl6rOW0rHkxmRFVRiOecs+ZHVV7cFDKwdmN+ld9rFZZ2DNsUSmKnepE8NsVg0K2tnExtkW5AJbXoJXuKsqtZR+JqnJqmqFJr4XW+uoEEfsqmuXI0kiQ89ksvy0g5P26Ab+vZVMw7PF6sPF5/1RT3FTVV+MRElDk6nyCK2vdFK25auqasvVJOn4yca66SquU6+T+CcH/HDek/4+qtMUV0qYYztKgzEoDDnGzNI9UOs4DXJj7IpAfi8zVbk9b+1HPBRMhNUqVrnZrSF4NC8LV4FQWEHm5NhJpQtnp2wnwlOy2pA6tEbKzIaH9beklBeYvKU7J5k9x2ZGFALXG8kTm3eEqLu3/NEC5ZzRUe8zbBnK+0JKt1P47yXcwLOXuU5ayi/jk6Mvu37ZRigk/SyoHHw5kWNTantR4TJmtjBNn0sjM7ofkojLDGdUlVHJkXUSLc8lZd2nQtcPaLnUK6Dt3BcrLukSe1/93YTfCLpOj/DI3pxQYkyltzR17btDUxNq7zRgxJVvCyukPPy9tsATAGPBXSZMdqdfqmL0SNBoW7Dk7M63q0Ky1WS5HgrsIek9Ggqk8Tk9OWzSM05ieA1LFbvvFIPZXZMR1xQd3ltMCDZp9uB8Skw3h0I0z01McMTfRBj5Q4xyJqMeqsD/FPRIFc4JO856QuyeJXQYrSGXkq7KF7rmS5pecegHRvcxdHsvtP+3gW33dtFwXPjtZc0B1NO+QoyoV8vUv76XKM2C/p3MuVERvwqtMUzSR0PpwsOFPwv27s7yz2/D1LSPiPhlUNnjyV35757bPy4crchERDw5CPWlSf16iOJfiQ2rdqLURUREREREREREREREREREREREREREPA2wbdGjZxoe5/XPf7vNm6AHVH7g77r5m534b95QKRLT13UovTlAWf7qj8777uVPpI/f/2oac2/fo7/Qcz/y9z/7mj79RGBFJi/kW5lJJ3/96+23r6z5fysvMvrExvRP+h3TA7MM37wo3/Tt5/+oLl8IJZyvCq3Fe3M8HPi+NdPP5tx7r6bEx+nIh7wu0I7Qnvm+6J866O/e8Pr9HfR7Xm9le/q7ahA7lUZERMwDt78qfn3e7IqIiHhc3P7kBbMuy5Yyly0tzeHfZW+XnKRU5iRtIzn783so0XzisKT4Ffde/s+X9Cv+qBiUOk2Hl/9z2QU2/G6017c1fN7Pevfdn4YcF5T19/yjl6cNbD7m9qJhQZf9/V+T+88b/+T/Df3qcQNW0k+O4/8ZfdIvlD/mP72a+kKdNiTxalL00ezBC//hVOz2rzH+kJhl+InX/VQo7Hbfdy/0S9M14RPv9zPcbQ9yUCK8zf//u6b96a7Hefkx+nbn9EXH6BMftx3+P/b/7P5T9v67UHgLr9vU42wfzd78/yzD94nZy//PPm7ffepPE3/6+ottwu3WdN/0jT6/+2iSs9fdJP0f39kxx1f4DG/TxJ3Px355UHJE72eUHoVNf5SSIU+T/J97xS9kRURERERERERERERERERERERERERERERERERERERE/CyaX0n2mAgWoot7jHq7t4+f/RMmQtw7+Vsw9reHfwR32oNGB/xIA9n1KDnCVf7L6v81mt+f/hbomKMm+a/gu4eJ7X8uTLDRd6PB/mX3tGhsUCqa8IBZ87dAaU3qCYKZ29/Zr9zttxowOnn7x0MBVE5mf/fzlKWRNf3Q+b8AyztNS1lFv9YP3Il88Nco6lbC1LxjNH4HVr370594LxwFPfn3OHpj9KR6+889Yl11XGS3Xxsj6Or+9oOhKWiCdYox9YBZ87ew9crTlTuWp/l02LtpEz/Xg3XSHw0lfLRtZFHpv+kllaY+wP+/ADP9poSzL+mSj4eTD0Lg1r/DlZFo13K19pvHULg70VfuQPmwYL8AjpcQn+V/kmFd1xr57reFQs03yZ8CKygol6hKRtGifs31COXK322hPB40d02gEN13az4VIGq+2iT/EToEg/xLiLa7lK9+wAD6O5gpY7GVJpydqNNZwKK/QilNk/q9ELKJ3/kN1OkvUurmTiyzv4ZQf/ZT9UW61aR+Duz1NBhl79AHDPwVEJ3ubw4B84g4yn0cciS+bKhjXKwFjdCXioYUcZE9K2lSiJKo7Hgfh/w2WSVVpRtlxG4UlwUOsGe0l3bpEjnKWa/ZjVxMrVlG52pdihE8Aqrs7jQQVC5Vwcp9gdJsiKRWIqW7M7GrprEPh5Jb+toTVYQz4EGWf5QVBWfzDdwH2RVSgoevfJYzqo5awf4oGdL2TtX+GJ15pp/p2zKaBgCs1NQ6OpBorZEdZ1NvrdKe5nzfOdTcyqJzGK7SXy0yFhvoIhy7UygVJ0IkzwDfaN9Ls9YEoP/R96tl4lvt8x9RJWVQZNQ9QxI75MMmo0MUGm8krKBK/pjVkIzdHoWtHYuELYc+QL6DT+k6mcBHNH7UyWg4LhAV+aJ29Xg30aGzcEV498P0jIZpmTJWlRnsgOlKfUZht5Fh1tMerd1SoCBs+xPpAqg3m9qbBmuq5e6UGNlfZQj8f4S9CGp4zQcQ9DHkJBkKux3I4/4pxcQajftgM2YpRj95BWfCIMXrcbBocE7Kocwp9hn2ktSYt4dS1gf+MM781K8mJ0ENsmeG45CjGHI9NcAJTbRQgGkKWbcgMWXHzpwbubnw0g8RKnZfXftZk20WcpS9GrxIdIiurKW5nhTSdKTbZ3Z9w5fMqixNXSHy0+qYWFLKvr/KOivcJtp6W7Wl6+5fYjoqXhu5rpN9aigveo3ZJpzJN5GHzLHCrC9BnBONq5QyX0PZ1QVO3yhQICuzBZyIWcnUe3VJXXIAM+45lzu4Ql/oIl2VrpE87yxUjRHASoq6x11JpVG5Uk2bV8i66ySXGl5tn/tpa5dQCfUUkhgN9yJzN8cFxZxmPq4gV1fUUXtFH/3QDBTE4ZBTJ+aQdejBgjLCH9vh6YYcJ2x1A8MqoWFFLqkPhqGoRXNxg14hC4PVnGK6nqDl8KwZfDqZO+ncIN3MtX2fw8jkdkSKka5k5naMXY2CimNxSSdKnIjeVBgB/xsJYd6sG+JhXzRfv6IGX0nTBNd7gmDdTT8qJf/UoxiulRC6fl4kvTeQE/2cwgoflbw7SippxlfC8AJuVnsshM3Wm17BnHXQguq0FqI0FPi7Tl15pa/D4WQta4vkGfehiUuHrLpOMXkwlJ/AIEvOB40EMIgllQAnTst0vRQ3nym0uH1rxmK/HviA6cAR2C44oZOK10yQV4MBk5CygkurNdpjBBoo3RqzWaZZK8cFJZAnLcrPGQhyL5UgAsUhZh4YeaUFKCkXTKVLY6EnaCi6Ih/kU6kwqdsS4vUAclcNZHF1s7tWcwU6kZ81OqfQQud9qBZUa3GF1E8qPS2EWNmoBSvRRUNaWvKFQotpQ+UrzkmzEFChFrvWvS2TylFrbonwS8pRfJHy2oqStAzkEn0CGa5ALBddJD+jx4++pHlyXMhLXHyxUbPjij8/vxJ2qf1HKCdZc96lgEM5ESZFb2uSQHbCv2p2tiINWIl6X+SpKdGP6F6QkkmzMjn3IbEhsHbE6owmCeYHFVLvg/vfnFbXzMLVHn1Fk46KDQxe2Z6FgC/5QGktWJeufrj+sUi2XUqzqR6g1Iq/XRPjTophHOYyx5TYyGhmsZ3NX2Ww/j+E4hTjBioPnYSeowVHi+HbXseOP4KsWPhuwm1SLx5gRuvANgcHU21Wym4LkuLlBxOCQewaPiKwDxSpGNJB54dg4XYJQ2K5o3iRhVf+BBXO2kL2UvrI2fZjnuh6k2JllyGIM3DLdiiinui2XEYSbNdj6vQNlbXuI7KPar4MLoRv18pJhWTerbGbmHmhfTeY6PgAtPPOCUT3aqJOvQqu+Qn2MCcbpYAZRhNvn+J4VWlG1Xx5X+MCoD0qlp/682G86XV/hWiOxhFyT5i3/8i3Y59CoYZrdumD/JHkNHIdYr2jEywmN13qsJwq+5VUohz91kfvL9J3aK/vk31uiLUos5VLmr0DJV0F8r+WTowKP3yjuvEjoLDkIX2e86LlFSidB2ujer/i+4BOHPN6uLv3kdqppS9KEW/t+JYf530oBd5BEh8KlfuLBcehHmhDz3ZJ+Tb09CwCe8l90TatSV2uYPiEG1Dt475hvnvobHmFNx+csPDmJYW3x8YTxbKkyUdBUPEOl4AVuRnUZz0SEI0eR5YSYnfQzHUl7VUm1ZShPEoau62Bz4D5WiZ7PiR4AxEizlEQf89JtI8CFZMs0GFfM0HDgBWo/b2CjGxSPr1Zgyde01Ak9dJUec58u6SETr8Kw7bmjDguwkBZ5CzV6wyV6CWHoUZVLahuOsZeDyx77VUIuL2xg4XF9dj89aY7wCyjMRey48m6mi7ybbd9NdASBaYprdP0Pm34hkOirou0toGB0SRv0i3KqoWiKJnDHhUZLty/ARb2Y3PVBZlcHtZCdalDx1do9k33etCExhV2fT9W/ANm9I4/kEtb8twHu62zEuyWgwiRaZznm077bUDN6gCp04d6T2LnS9MGklnRNJ8uVF1KC+GhoUHRdJ7v4GBkEtvBzQuThNfbvdD3LP+ID8v3YCvgzGYUknxqnyzLjOpao9mlDg3vkjqjE3U7YzdhXNCegyQPq9WMYtfTtPrzZagngd7XgYVdECyaoX1Xn8JWf322vR58uzXoOCtzGBzdoiq23jkM0UuZupd3lhvGYDiWpz5ondd3ZKBOMbGpVFvvtuoUZZVyzy/EKP7sbJ2rl8WXFSUHfj4Dotoy0i2lqrWceTsDIgcd+YJa1jr3YcaBu2zXr1nj28ET2GYfwjyHABeZhB8EzZs5NOE1bFqYU3SIfe1XkDciC92ZCjzs5ApereHZMqiA2j7GzEfr3nXTbhh6eCNeZDBFMZ3rFrgGfPHl3dY7NXAaZvNgZ4VmfJUa9NLWO5BjS52+o1NqULumG5flhsOxL+/qtD5wYZ1u62K24I5GO9nOBiCznKf5nTWJYoEG58pLKgaiSIrn9UuU86XNC9uYooegJO/bjcqK/C3uDqCFvHSey+mtoFz6MYI6aIm2F4WS2uEHX6V7KytfVgoHz77GGJKAK1xmMoSAsku+SGfuSfiGwhY5xySBT2F8IcLTs/34NbDdziBH2959QEl0Dg1j8NLoxNTBvkzY0oU3UTKD6zmnY6xGLYZjphRfvgaaXZZPeC0TPFbvDnHRSIoaTnW9vS/XGbqe2M6QWwBh2f3CF+hXcJccxfgvu28lT9U0sPW+Fzvu59gk56tJ/vw2biRTA+nP5P0vNPt8Tyq+KjqpzLILOORetQG6wy+k2oaQt26cH88b+eYMtgrNq9HsRiwpcZoONAVPa/gXfoyIScK8w3xxXL61MDlxBc7hbNLe+WkQO7IJ9/pw/GG+Ti3I4+K5lF3tiwpsN97kaPVbtG7Gdo3YnSq2CpJFJ8A7ot9qzcwl2rqzlMnUHLAqXZC42gvntlqLQdL3oPU90ZWSS0mX3D7fd6TQUNzsMYMSQi+ribe52YqTMl24aQ598ZSr15dQD4ndcTHAOL3NUEkF4vO5chfY7rhYkNn6gTfdsE3MC7abGrKhQeq0OPZLnyjUs93gwzHEDmX6hpdeeKifw7XXyLnYsF3fHg3r0yzLGRx+sT1lOy92/M2QeneUpyjnLabKdO0Zji2N5rVBn9bsgEPsnA9VTaMzDkpU5PJG1Kf0C7logp8SZKjToacJUWcaUx0sNMK0vWITmNydSa9L9kS4/nE/B8Wo6x5ju+H3qBkTlYQ55HEMbcYY/HTaYHn/Jqkx4acA39ww1tve3eLr1JN+8sKSwRy3uz02ZKJRacRHVDipP5xE+nF5IU/sc+9vHufmu5VMsfe8SEQHFEVj1KFFGmoDlcy2Pe+eocJRcnTIq7PGTOrlfMzWvbd/y3a0+rLLkqGTy7AMqe3wGjVj27s94U04FOqMT6GKI7AdpvOy62t6uK7ne2TCtnXNX4vivRL+cvEOY45OmbFdKNQfgyfs6y5gi9IneYBVb/soMA918BWIoemZok/ub2juZAVi9+FUoRR03TakMPc3ROv2fqv4CPOcm7IHwXXyBh3liUTByPU4ggDSJ3y7Y3QSNQBst5YU74sRRHIRbWMMAyz2/IKnDWzHYNwyNIHO/AQxKz4eMnZMF9NrCglsh5Z4tqNxvO5to33Cm9skdjSNoBSRgeFEk2xnftBK57ZhsVAeUvx+4BjOFUO6pCdtZFJ/FXASkAAx+fum705rtu1XMr3YHdmNOrF+paGVVFNbDxPE++eA9+0wDNRJ8AR08ua9Zz6PL56t0I3bBhPeZOROeSsmqN6j7Z09Gjq/k0w/yM5XWI4N23kj0h+fPaVCK5khhbl7QGrSW4ygk7CCTruJSSAFuIKlKduRJYy9wvD9pOvLWoM/hA8AcnSMD03LNjBUkU9seLlPyk7DRg070LxC9i6yD8mLBXb3piv9qEyDBLwRUHVWGy2Q1FO2E42sjU3lb4sCytuPdMMqLN4MP52+ChWi/WnTvIbtuhly4OoLWvPymYr1spHfiSHfbqAwTn4YtGx8PWBaBxolvdWpPtJKprxBUrdh/5HhnGzxsGhb1CX75BtHK0z0gSs/2vJe4dkejZtfDYGv7tmOpGc7P0VLbX/vmtgOE8NLe+ukbtoflg/oCRbaekFGZuPbuSXWuPt+Veu1XwtDeTld01jSTcYnC92WYQUJjPUVH6VM34AD0YHC0NrDmknzZLfeeAHdB0dN69x3TmOxAGP5eTvZNd6Ky/n5UVKH7iNoEyYn+Eql+QjuBlTgCYeYlxl1PT2eFiYFqz1fWp5+ILOEJKdc2CMaJTOqSP1AAUS8PqG98zD0/j8zKbIG325NemV9mVIl/ikVupZdQ89ijBTPj1m9QRmCs0SoPLHQmvpNK/h2bKe/t9tKbvqYZx44mEPWCrrZF9ju2PoFJ9R8Il76RTswzW7vkG4x4CpAETDmsHdSZ2A7b5cqfoh8WnJ7ZDdptlnOG7YbOt9nRQobuPCzTm/Q+iWhWPBsF3y7Ff4qEd0+SZJNM1rE+EolD5r7dqVf9Rya1Gk47I1vNx0NK/16jxp8OZr5dusalcIn0OsbKzgI3/Sq8e2gYojiwLo6WeXk4xb8bYltEuZxP623p2xX00qmfd6sZF6F9c3i/dRGhMajludwd1FjltKSitd4B86NmBdjHERRzyQty7JP/seXMc7UfU8WrSINi9fJsuG5UvX6qbvCbKqSEawv9Sp3Kd1oei3zRbUEex3jnysQZN30alL6J8xse+PVSe4+QV7M7UpmMTOVaB15fH0p8xP1WdItGeukUofu6/S4XeLnSuUmNUPMTCq8PF0XSU9t1ko57prJc7aV4rxFVRhJEy45MG/RMJwlJpBQ7DguOLUazVZM1Kmy2xDoFjlPKN1BQJh5biFCtxpB7A1qVZy35fuKbmpRqUMlu2rRZdMZy8yGqxeVM2DrIjVEjuzLpvlwksvLa9iK3UWlDEWmgMVFzV23CTuHAgFI6LfXZV6Nekp2PrxoL8E6P9tyOLnmzYoIMRGuagdXfygqeJS4vP6X5hDoAylNa31UOcZKd2X+QUm69z9U1C7zHuxWQCCgvDrqRV5LVFqkXsry9yAzD1iy1K15+mLS3O4sQdAQi/aOTva7/b1XGNUSYhR4SR+6vLh0fKmEWMj6w4vXHFJVOr6z+OIQ/rMYhkLg0NaVtmktID24ttKgdXl2Z374ass2ZtCL1/Dwdoey700U2ad77vzkw6Ehtj9bpSuvpb+f2lt/O07OxqoZo6eH5dqrV6CsM5edCwUf5GSdOgYzYCl/ltNNG6Gyxtfdzp3L3OwhiiNdK3K//qjhRftZtGjoXI9XbrqMhgK6UKLKOVflC6ROYdqjm2lmBNg2tgtW57s69/RxVfuHLs9Rb6EUGUXAyNZ03lJWN5WUxrn6IFdsUtF6D+lJat++pmV4ixpE0fWDjHyOHvdmqiaDTqjpjSVMNJyQ75MFPbWiqRB3+/0M+HaFW3J+Qtg6aCnkda79ErZZy5oll4WrZuidJa/eQ1Gtkz26PdF1sMlDoaGCVRRXFPnYm3ZQFuhqtwSXV/WSMf1afbgWgl2nZGgus75QkaPBwU8+VqiuUuoKjUC+4eu2y7oadZ/5bbSyDhUCaoP0IbVr2PRwjqHbxZWtoswuWkSO9LAwYa1J0GBBvaEXxCU1vKKO89da3OQkZXlYouy4er9Ed7eKz9RjwqCkvUZpoOPr8FzCeB0z6ESr/EoEMxLDDP67ovEscn87hqbEkrdRk3KQ71KHzbrhyaEVDB2g1Zq0IAeYm/QBjCYTdF+YGhPGGhmZsMlkdo7P7j/gMTd7m7mEfbdSBZzB20fB8J/9fB6hnDvFJKOzCRWA5jQtmhY8oe1ZmdSoCTu+LdmfdRfUPrz7vSOk6LeNaXfT6lYo/vay/SFcJ82UWTWM0a4G2zDx0LqwcXsiLjkkjpC7eUjVNy8k/HsocRRy4pKn7Ubxd1tAp4UslLlJB4TSppnD+dNroST1os/jWe1sQl3jG+NzNCNJ0OteVH22cHZ4H4WKzyZnoaqGHanoEfl2lETLQwdR6+iTsobslG9aVMCINV3uMTuCRmM3ndTsavkpgT377WAVjXw1AFv0Dvjxn39PMeIhEF24EsShjT/334FwtHz/n0eVNc9r/ziae+KPhQPj50Kz/HSL0v3j10sifhCjVSeNMe2ZgfqfgVgKC6r/cTCVNWs4PwzR9ivMj4TWbrHkMCXMy+kjvAFl55+/TBnxwxjnQDG90f7fAfPfpfnvQyw+lLpYtfKoV96yh5gS9o5NStBF48pHREREREREzB9J8n93Ounhj7pUPgAAAABJRU5ErkJggg==\"\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003eTo analyze in-depth profiles of each cell population using single-cell transcriptomes, we further subdivided each cell population using previously reported marker genes\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. UMAP plots of monocyte subsets and profiles of highly expressed genes are provided in Extended Data Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ea and Extended Data Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eb, respectively. UMAP plots of monocyte subsets from individual SSc patients or healthy donors are provided in Extended Data Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ec. Similarly, single-cell level gene expression profiles were determined for CD4\u003csup\u003e+\u003c/sup\u003e T cell subsets (Extended Data Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ea-c), CD8\u003csup\u003e+\u003c/sup\u003e T cell subsets (Extended Data Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ea-c), B cell subsets (Extended Data Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003ea-c), natural killer (NK) cell subsets (Extended Data Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003ea-c), and plasmacytoid dendritic cell (pDC) subsets (Extended Data Fig. 7a-c). Next, principal component analysis (PCA) was performed to visualize the variability in immune abnormalities among the SSc patients. The PCA was conducted on the relative proportion of each cell subpopulation to the total PBMCs. Each vector representing a specific cell subpopulation is plotted on a two-dimensional graph according to its principal component 1 (PC1) and principal component 2 (PC2) (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ee). Individual SSc patients and healthy donors were then plotted based on their respective PC1 and PC2 values (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ef, left). The mean of the vectors representing individual SSc patients and those representing healthy donors pointed in distinct directions. Patients with SSc were further categorized by concomitant organ complications: SRC, ILD without SRC, and neither SRC nor ILD (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ef, right). The direction of the mean vector of the SRC group was aligned with the vectors representing monocyte and dendritic cell subpopulations, whereas the mean vector of the ILD without SRC group was closely associated with the vectors for T cell subpopulations and plasmablasts. The mean vector of cases with neither SRC nor ILD showed an orientation similar to that of healthy donors.\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eTo further elucidate the compositional changes in PBMCs from SSc patients with SRC or ILD, we performed differential abundance analysis using milo\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e, which is a cluster-free and age-adjusted approach designed to detect changes in cell composition between conditions. Differential abundance analysis revealed that CD14\u003csup\u003e+\u003c/sup\u003e monocytes, CD16\u003csup\u003e+\u003c/sup\u003e monocytes, and NK cells were particularly enriched in patients with SRC compared to those without SRC (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ea,b). In contrast, memory T cell subsets such as CD8\u003csup\u003e+\u003c/sup\u003e effector memory T cells were notably enriched in ILD patients (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ec,d). These data suggest that a skew in the gene expression profiles within the peripheral blood of SSc patients is associated with their organ complications. Specifically, SRC was linked to myeloid cell subsets, whereas ILD was linked to lymphoid cell subsets. Differential abundance analysis further highlighted the distinct immune abnormalities underlying each complication; enrichment of monocytes in SRC and memory T cells in ILD.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eEGR1-expressing CD14\u003c/strong\u003e \u003csup\u003e\u0026nbsp;\u003cstrong\u003e+\u003c/strong\u003e\u0026nbsp;\u003c/sup\u003e \u003cstrong\u003emonocytes were specifically enriched in SRC.\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003ePCA and differential abundance analysis identified the monocyte subsets as interesting targets in terms of elucidating the pathogenesis of SRC. UMAP plots of monocytes from SSc patients with SRC or without SRC are shown in Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ea. Five cellular clusters of CD14\u003csup\u003e+\u003c/sup\u003e monocytes were identified by their distinct gene expression profiles: CD14\u003csup\u003e+\u003c/sup\u003e monocytes with high expression of \u003cem\u003eEGR1\u003c/em\u003e (CD14_EGR1), interferon signature genes (ISGs) (CD14_ISG), \u003cem\u003ePLBD1\u003c/em\u003e (CD14_PLBD1), \u003cem\u003eVCAN\u003c/em\u003e (CD14_VCAN), or HLA (CD14_HLA). Other clusters include intermediate monocytes (Intermediate), CD16\u003csup\u003e+\u003c/sup\u003e monocytes characterized by high expression of ISGs (CD16_ISG), other CD16\u003csup\u003e+\u003c/sup\u003e monocytes (CD16), conventional type 1 dendritic cells (cDC1), and conventional type 2 dendritic cells (cDC2). Quantitative analysis of the relative distribution of each cellular subpopulation showed that the CD14_EGR1, CD14_ISG, Intermediate, and CD16_ISG subsets were abundant in patients with SRC (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eb). Differential abundance analysis further identified significant enrichment of CD14_EGR1 (median log\u003csub\u003e2\u003c/sub\u003e-fold change: +1.9), CD14_ISG (median log\u003csub\u003e2\u003c/sub\u003e-fold change: +1.3), and CD16_ISG (median log\u003csub\u003e2\u003c/sub\u003e-fold change: +1.6) subsets in patients with SRC, with the interquartile range of neighbors shifting entirely toward SRC, relative to the baseline where the fold change equals 1 (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ec,d). Similar results were observed when conducting differential abundance analysis comparing SRC patients with healthy donors (Extended Data Fig.\u0026nbsp;8a,b).\u003c/p\u003e\n \u003cp\u003eTo determine whether the increases in the CD14_EGR1, CD14_ISG, and CD16_ISG subsets were specific to SRC patients, we recruited patients with lupus nephritis (LN) and compared the proportion of each subset among patients with SRC, patients with LN, and healthy donors using CITE-seq. The clinical profiles of LN patients are presented in Supplementary Table 4. UMAP plots derived from the subset analysis of monocytes are displayed in Extended Data Fig. 9a. Highly expressed genes in each cell subpopulation are detailed in Extended Data Fig. 9b. UMAP plots of monocytes from individual patients and healthy donors are provided in Extended Data Fig. 9c. The proportion of the CD14_EGR1 subset was significantly increased in patients with SRC compared to patients with LN or healthy donors, whereas the proportions of the CD14_ISG and CD16_ISG subsets were higher in patients with LN (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ee). The expression of \u003cem\u003eEGR1\u003c/em\u003e in total monocytes was increased only in patients with SRC, while the expression of \u003cem\u003eISG15\u003c/em\u003e, a representative ISG, was highly elevated in patients with LN (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ef).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003ePathological role of CD14_EGR1 monocytes in tissue damage mediated by NF-\u0026kappa;B pathway activation\u003c/h2\u003e\n \u003cp\u003eTo further explore the characteristics of this specific CD14_EGR1 subset, we identified differentially expressed genes (DEGs) in this subset compared to other monocyte subpopulations (Supplementary Table\u0026nbsp;5). Pathway analysis of the DEGs (log\u003csub\u003e2\u003c/sub\u003e-fold change\u0026thinsp;\u0026gt;\u0026thinsp;0.5) showed predominant activation of the \u0026quot;TNF-alpha signaling via NF-\u0026kappa;B\u0026rdquo; pathway in the CD14_EGR1 subset (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ea). The expression levels of representative NF-\u0026kappa;B\u0026ndash;targeted genes such as \u003cem\u003eEGR1\u003c/em\u003e, \u003cem\u003eIL1B\u003c/em\u003e, \u003cem\u003eCCR1\u003c/em\u003e, and \u003cem\u003eSGK1\u003c/em\u003e are shown in Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eb. The results indicate that the expression of each gene was increased in the SRC group, with a similar distribution to \u003cem\u003eEGR1\u003c/em\u003e. The expression profiles of cell surface antigens based on CITE-seq indicated that the CD14_EGR1 subset highly expressed CD11b, CD38, and CD4 (Extended Data Fig.\u0026nbsp;10), suggesting that the subset has enhanced capacity for tissue migration and differentiation\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n \u003cp\u003eOn the basis of these gene expression profiles and surface antigen data, we hypothesized that the CD14_EGR1 subset possesses enhanced migratory capacity in tissues and contributes to renal damage. A sample of kidney tissue was obtained from a patient at the onset of SRC (patient ID: SSc-19). Pathological findings showed intimal thickening and luminal narrowing within arteries, fibrinoid necrosis of arterioles, red blood cell fragmentations, and focal tubular necrosis, which support the diagnosis of SRC (Extended Data Fig.\u0026nbsp;11a-d). Renal cells and total peripheral white blood cells from the same patient were independently analyzed on the BD Rhapsody\u0026reg; platform. The UMAP plots of the peripheral white blood cells and renal cells are shown in Extended Data Fig.\u0026nbsp;12a. Profiles of highly expressed genes (Extended Data Fig.\u0026nbsp;12b) and surface antigens (Extended Data Fig.\u0026nbsp;12c) for each cell population are also provided. We then subset monocytes, conventional dendritic cells (cDCs) and macrophages. The RNA expression profile of known gene markers\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e was used to divide these cells into five groups: CD14\u003csup\u003e+\u003c/sup\u003e monocytes (CD14_Mo), CD16\u003csup\u003e+\u003c/sup\u003e monocytes (CD16_Mo), cDCs, macrophages characterized by high expression of \u003cem\u003eTHBS1\u003c/em\u003e (THBS1_Mac), and macrophages characterized by high expression of \u003cem\u003eC1QC\u003c/em\u003e (C1QC_Mac). The C1QC_Mac subset was considered as kidney resident macrophages characterized by high expression of genes such as \u003cem\u003eC1QC\u003c/em\u003e, \u003cem\u003eCD81\u003c/em\u003e, and \u003cem\u003eCD74\u003c/em\u003e\u003csup\u003e\u003cem\u003e22\u003c/em\u003e\u003c/sup\u003e. UMAP plots derived from this subset analysis are presented in Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ec, divided by blood and renal cells. Profiles of highly expressed genes in myeloid subsets are provided in Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ed. In the THBS1_Mac subset, genes linked to vascular injury and fibrosis, such as \u003cem\u003eTHBS1\u003c/em\u003e\u003csup\u003e\u003cem\u003e23\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eIL1B\u003c/em\u003e\u003csup\u003e\u003cem\u003e\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/em\u003e\u003c/sup\u003e, and \u003cem\u003eLRG1\u003c/em\u003e\u003csup\u003e\u003cem\u003e25\u003c/em\u003e\u003c/sup\u003e, were highly expressed. DEGs were identified in the THBS1_Mac subset compared to other myeloid cell subpopulations (Supplementary Table 6), and subsequent pathway analysis revealed an enrichment of the \u0026ldquo;Interleukin-1 regulation of extracellular matrix\u0026rdquo; pathway in this subset (Extended Data Fig. 13). The expression levels of \u003cem\u003eEGR1\u003c/em\u003e and \u003cem\u003eTHBS1\u003c/em\u003e are shown as feature plots in Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ee. To estimate the cell trajectory from peripheral blood to kidney tissue, we conducted trajectory analysis using Monocle 3\u003csup\u003e26\u003c/sup\u003e. The root node was set to immature monocytes characterized by high expression of \u003cem\u003eS100A12\u003c/em\u003e and low expression of HLA-DR genes\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. The expression levels of \u003cem\u003eS100A12\u003c/em\u003e and \u003cem\u003eHLA-DRB1\u003c/em\u003e are shown as feature plots in Extended Data Fig. 14. CD14\u003csup\u003e+\u003c/sup\u003e monocytes, which have high \u003cem\u003eEGR1\u003c/em\u003e expression, showed a differentiation trajectory leading to the THBS1_Mac subset (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ef). We next performed transcriptional regulatory relationships unraveled by sentence-based text-mining (TRRUST) analysis\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e, a transcription factor analysis using DEGs in the CD14_EGR1 and THBS1_Mac subsets. The activation of RELA and NFKB1, members of the NF-\u0026kappa;B family\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e, was a shared transcriptional characteristic between these subsets (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eg). These data suggest that the CD14_EGR1 subset, characterized by activation of the NF-\u0026kappa;B\u0026ndash;related pathway, differentiates into the THBS1_Mac subset in the kidneys of SRC patients and contributes to severe renal damage through the expression of molecules crucial for vascular damage and fibrosis.\u003c/p\u003e\n \u003cp\u003eClinically, all patients with SRC in this study tested positive for anti-RNA polymerase III antibody (ARA), the autoantibody strongly associated with SRC\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. Therefore, we compared the frequency of the CD14_EGR1 subset according to the presence or absence of ARA. The proportion of the CD14_EGR1 subset was significantly higher in SRC patients than in those without, regardless of ARA positivity (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eh). These data suggest that enrichment of the CD14_EGR1 subset is due to the presence of SRC rather than to autoantibody profiles. In addition, we assessed changes in \u003cem\u003eEGR1\u003c/em\u003e expression during the clinical course of SRC. We collected PBMCs from a patient (patient ID: SSc-1) and conducted CITE-seq analysis at three different time points; three months before the onset of SRC, at the onset of SRC, and after the improvement of SRC. The UMAP plots of PBMCs in this longitudinal analysis are shown in Extended Data Fig. 15. The expression of \u003cem\u003eEGR1\u003c/em\u003e in total monocytes was highly upregulated at the onset of SRC, and decreased following treatment (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ei). Finally, we evaluated the association of the CD14_EGR1 subset with clinical features of SSc. The proportion of the CD14_EGR1 subset in SSc patients showed a positive correlation with the modified Rodnan skin score and systolic blood pressure, both of which are clinical indicators of SRC (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ej). These data suggest that \u003cem\u003eEGR1\u003c/em\u003e expression in CD14\u003csup\u003e+\u003c/sup\u003e monocytes may be a specific marker for SRC progression.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eEnrichment and functional implications of interferon gamma (IFN-\u0026gamma;)\u003c/strong\u003e\u0026ndash;\u003cstrong\u003eresponsive CD8\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e+\u003c/strong\u003e\u003c/sup\u003e \u003cstrong\u003eT cell subsets in SSc-ILD\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eThe results of the PCA and differential abundance analysis of PBMCs prompted us to conduct further analysis of CD4\u003csup\u003e+\u003c/sup\u003e T cells and CD8\u003csup\u003e+\u003c/sup\u003e T cells in patients with SSc-ILD. UMAP plots of CD4\u003csup\u003e+\u003c/sup\u003e T cells from SSc patients are shown in Extended Data Fig. 16a. Differential abundance analysis indicated the enrichment of CD4\u003csup\u003e+\u003c/sup\u003e T cells characterized by high expression of ISGs in patients with SSc-ILD compared to those without ILD, but no significant enrichment was found in comparison with healthy donors (Extended Data Fig. 16b-e).\u003c/p\u003e\n \u003cp\u003eUMAP plots of CD8\u003csup\u003e+\u003c/sup\u003e T cells from SSc patients with ILD and without ILD are shown in Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003ea. Six cellular clusters were identified: na\u0026iuml;ve CD8\u003csup\u003e+\u003c/sup\u003e T cells (CD8_T_ Na\u0026iuml;ve), central memory CD8\u003csup\u003e+\u003c/sup\u003e T cells characterized by high expression of \u003cem\u003eGATA3\u003c/em\u003e (CD8_TCM_GATA3), other central memory CD8\u003csup\u003e+\u003c/sup\u003e T cells (CD8_TCM), effector memory CD8\u003csup\u003e+\u003c/sup\u003e T cells characterized by high expression of type 2 ISGs (CD8_TEM_T2ISG), other effector memory CD8\u003csup\u003e+\u003c/sup\u003e T cells (CD8_TEM), and cytotoxically active CD8\u003csup\u003e+\u003c/sup\u003e T cells (CD8_CTL). Quantitative analysis of the relative distribution of each cellular subpopulation showed that CD8\u003csup\u003e+\u003c/sup\u003e memory T cell subsets, CD8_TCM, CD8_TCM_GATA3, CD8_TEM, and CD8_TEM_T2ISG, were abundant in patients with SSc-ILD (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eb). Differential abundance analysis revealed that the CD8_TEM_T2ISG subset was most enriched in patients with SSc-ILD (median log\u003csub\u003e2\u003c/sub\u003e-fold change: +1.2) (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003ec,d). The increase in CD8_TEM_T2ISG was consistently observed in patients with SSc-ILD when compared to the healthy donors (Extended Data Fig.\u0026nbsp;17a,b). To further investigate the characteristics of the CD8_TEM_T2ISG subset, DEGs of the CD8_TEM_T2ISG compared to other CD8\u003csup\u003e+\u003c/sup\u003e T cell subpopulations were identified (Supplementary Table 7). Pathway analysis of the DEGs highlighted significant enrichment of the \u0026ldquo;Interferon Gamma Response\u0026rdquo; pathway in the CD8_TEM_T2ISG subset (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003ee). IFN-\u0026gamma; is widely known to enhance tissue migration in CD8\u003csup\u003e+\u003c/sup\u003e T cells\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. We therefore examined the gene expression profiles of chemokine receptors in each CD8\u003csup\u003e+\u003c/sup\u003e T cell subset. \u003cem\u003eCXCR3\u003c/em\u003e and \u003cem\u003eCCR5\u003c/em\u003e, which are important for T cell migration in pathological conditions\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e, were highly expressed in the CD8_TEM_T2ISG subset (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003ef).\u003c/p\u003e\n \u003cp\u003eIn our study, the ratio of the CD8_TEM_T2ISG subset to the total CD8\u003csup\u003e+\u003c/sup\u003e T cell population was significantly higher in patients positive for anti-topoisomerase I antibody (ATA) or ARA compared to those negative for these two antibodies (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eg). Clinically, patients with SSc-ILD who are positive for ATA or ARA are known to have a greater risk of ILD progression compared to those positive for anti-centromere antibody\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. Therefore, we next investigated whether IFN-\u0026gamma;\u0026ndash;associated immunological changes in CD8\u003csup\u003e+\u003c/sup\u003e T cells contribute to lung damage in progressive SSc-ILD. Publicly available scRNA-seq datasets of the lung tissue derived from patients with advanced SSc-ILD and healthy donors\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e were analyzed, followed by a detailed subset analysis of CD8\u003csup\u003e+\u003c/sup\u003e T cells. UMAP plots of CD8\u003csup\u003e+\u003c/sup\u003e T cells in lung tissues from SSc-ILD patients and healthy donors are shown in Extended Data Fig. 18a. Using previously reported marker genes\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e, CD8\u003csup\u003e+\u003c/sup\u003e T cells in the lung tissue were divided into three groups: CD8\u003csup\u003e+\u003c/sup\u003e T cells characterized by high expression of type 2 ISG (CD8_T_T2ISG), GZMH (CD8_T_GZMH), or GZMK (CD8_T_GZMK). Highly expressed genes in each cell population are shown in Extended Data Fig. 18b. Differential abundance analysis revealed that the CD8_T_T2ISG subset was enriched in the lung tissue of SSc-ILD patients (median log\u003csub\u003e2\u003c/sub\u003e-fold change: +0.7), whereas the CD8_T_GZMH (median log\u003csub\u003e2\u003c/sub\u003e-fold change: -1.6) and CD8_T_GZMK (median log\u003csub\u003e2\u003c/sub\u003e-fold change: -0.7) subsets showed a decrease compared to healthy donors (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eh,i). The ratio of the CD8_T_T2ISG subset to the total lung CD8\u003csup\u003e+\u003c/sup\u003e T cell population was significantly higher in patients with SSc-ILD (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003ej). Among CD8\u003csup\u003e+\u003c/sup\u003e T cell populations in the lung, the module scores calculated using the set of IFN-\u0026gamma; signature genes from the Molecular Signatures Database (MSigDB)\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e were highest in the CD8_T_T2ISG subset (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003ek). The module scores representing the similarity of each cell subset to CD8_TEM_T2ISG were also highest in the CD8_T_T2ISG subset (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003ek). This similarity in cellular characteristics between peripheral blood and lung may explain that CD8\u003csup\u003e+\u003c/sup\u003e T cell populations with IFN-\u0026gamma; signature genes, with their high migratory capacity, play a role in the pathophysiology of progressive ILD.\u003c/p\u003e\n \u003cp\u003eIn summary, this study identified distinct immune abnormalities in PBMCs from patients with SSc, underlying SRC or ILD complications. There was characteristic enrichment of the CD14_EGR1 subset in SRC and the CD8_TEM_T2ISG subset in SSc-ILD. Our findings further suggest that the CD14_EGR1 subset differentiates into the THBS1_Mac subset and contributes to the renal damage in patients with SRC. Clinically, \u003cem\u003eEGR1\u003c/em\u003e expression in monocytes may serve as a novel biomarker for disease progression of SRC. CD8_TEM_T2ISG has high migratory capacity and is implicated in progressive lung damage in patients with SSc-ILD (Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe distribution of organ involvement in patients with autoimmune diseases is heterogeneous. In this study, we identified distinct immune abnormalities underlying the clinical heterogeneity of SSc, on the basis of single-cell transcriptome and surface protein profiles of PBMCs. Patients who were not receiving immunomodulatory drugs were recruited for this study. The enrichments of myeloid subsets in patients with SRC and of lymphoid subsets in patients with SSc-ILD highlight the distinct characteristics associated with these organ complications.\u003c/p\u003e \u003cp\u003eIn-depth subset analysis revealed the enrichment of a specific cellular population, CD14_EGR1, in the peripheral blood of patients with SRC. \u003cem\u003eEGR1\u003c/em\u003e is classified as an immediate early gene and encodes a transcription factor crucial for the differentiation of monocytes into macrophages\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. TGF-β stimulation upregulates \u003cem\u003eEGR1\u003c/em\u003e expression in fibroblasts and increases collagen production\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. Therefore, previous studies of EGR1 function in SSc have focused on its role in tissue fibroblasts\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. In this study, \u003cem\u003eEGR1\u003c/em\u003e expression in peripheral monocytes was significantly upregulated, and the pathway analysis indicated that NF-κB and type 1/2 interferon-related signaling were enriched in the CD14_EGR1 subset. The synergistic effect of these signaling pathways results in enhanced activation of monocytes and macrophages, leading to increased production of pro-inflammatory cytokines\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. Thus, the CD14_EGR1 subset is considered to be an activated monocyte subpopulation, suggesting another contributory role beyond tissue fibrosis in the pathogenesis of SRC.\u003c/p\u003e \u003cp\u003eTwo questions arise here: in the pathogenesis of SRC, how is the CD14_EGR1 subset induced peripherally, and how does this population contribute to organ damage? The pathogenesis of SRC is hypothesized to involve initial damage to the renal vascular endothelium, followed by activation of the renin\u0026ndash;angiotensin\u0026ndash;aldosterone system. A harmful cycle of renal artery constriction and increased renin production leads to severe hypertension and significant organ damage\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. In monocytes and macrophages, angiotensin II induces the expression of \u003cem\u003eEGR1\u003c/em\u003e\u003csup\u003e40\u003c/sup\u003e and activates NF-κB\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. In the context of ischemia-reperfusion injury, pattern recognition receptors\u0026ndash;mediated signaling triggered by damage\u0026ndash;associated molecular patterns (DAMPs), such as HMGB1, activates the NF-κB pathway\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e and induces \u003cem\u003eEGR1\u003c/em\u003e expression\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. These observations may answer the first question; factors associated with SRC, including angiotensin II, DAMPs, and ischemia-reperfusion injury, can be involved in the induction of the CD14_EGR1 subset in peripheral blood.\u003c/p\u003e \u003cp\u003eWith regard to the second question, CD11b\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e, CD4\u003csup\u003e19\u003c/sup\u003e, and CD38\u003csup\u003e20\u003c/sup\u003e, which are highly expressed surface antigens on the CD14_EGR1 subset, are known to facilitate monocyte adhesion, migration and differentiation. Considering gene expression and surface antigen profiles, the CD14_EGR1 subset is suggested to have an enhanced capacity for tissue migration and differentiation. In addition, trajectory analysis showed that the CD14_EGR1 subset differentiates into the THBS1_Mac subset in the kidney. These subsets share the activation state of several transcription factors which are major components of NF-κB, suggesting that angiotensin II, DAMPs, and ischemia-reperfusion injury may trigger the differentiation from the CD14_EGR1 subset into the THBS1_Mac subset in the kidney. THBS1 is a component of the extracellular matrix and plays a role in promoting cell adhesion, regulating angiogenesis, and modulating inflammatory responses\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. In an animal model of renal ischemia-reperfusion injury, macrophages that infiltrate the kidney express elevated levels of THBS1, contributing to tubular damage\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e. Other genes highly expressed in THBS1_Mac, such as \u003cem\u003eLRG1\u003c/em\u003e\u003csup\u003e\u003cem\u003e25\u003c/em\u003e\u003c/sup\u003e \u003cem\u003eand IL1B\u003c/em\u003e\u003csup\u003e\u003cem\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/em\u003e\u003c/sup\u003e, are also implicated in renal damage. Given these findings, the THBS1_Mac subset, differentiated from CD14_EGR1, may contribute to vascular and tubular damage, potentially explaining the pathogenesis of acute kidney injury in SRC. More interestingly from a clinical perspective, the expression of \u003cem\u003eEGR1\u003c/em\u003e in monocytes was highly upregulated at the onset of SRC, and it decreased following treatment. Currently, there are no suitable markers for monitoring disease progression in SRC. The changes in monocyte \u003cem\u003eEGR1\u003c/em\u003e expression observed over the clinical course of SRC implicate its potential as a biomarker for predicting progression of the disease.\u003c/p\u003e \u003cp\u003eIn patients with SSc-ILD, the CD8_TEM_T2ISG subset was enriched in peripheral blood. A subset with a similar gene expression profile, CD8_T_T2ISG, was also enriched in lung tissue. The CD8_TEM_T2ISG subset highly expressed IFN-γ response genes and showed increased expression of chemokine receptors such as \u003cem\u003eCXCR3\u003c/em\u003e and \u003cem\u003eCCR5\u003c/em\u003e. CXCL4, a ligand for CXCR3, is implicated in T cell migration\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. Furthermore, serum levels of CXCL4 are elevated in patients with SSc and correlate with lung fibrosis\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. CCR5 also facilitates the migration of CD8\u003csup\u003e+\u003c/sup\u003e T cells through its interaction with ligands such as CCL3 and CCL4\u003csup\u003e32\u003c/sup\u003e. These data suggest that the CD8_TEM_T2ISG subset have high tissue migratory capacity, which is at least partly influenced by the CXCL4\u0026ndash;CXCR3 or CCL3/CCL4\u0026ndash;CCR5 axis during these cells\u0026rsquo; migration into lung tissue. This hypothesis is further supported by the fact that the gene expression profiles of enriched CD8\u003csup\u003e+\u003c/sup\u003e T cells in patients with SSc-ILD are similar between the peripheral blood and lung tissue. In addition, CD8\u003csup\u003e+\u003c/sup\u003e T cells expressing high levels of CXCR3 contribute to lung injury in SSc-ILD\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e, implicating another role of the CD8_TEM_T2ISG subset in lung damage. The reduction in GZMH- and GZMB-expressing CD8\u003csup\u003e+\u003c/sup\u003e T cells in the peripheral blood and lung tissue of patients with SSc-ILD suggests that lung involvement extends beyond inflammation, which may be associated with the minimal efficacy of glucocorticoid therapy in SSc-ILD\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Consistent with these findings, a high prevalence of the CD8_TEM_T2ISG subset was observed in patients with SSc-ILD who were positive for ATA or ARA, both of which are autoantibodies linked to a poorer pulmonary prognosis\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn conclusion, scRNA-seq identified key cellular subpopulations associated with specific organ manifestations. Specifically, the CD14_EGR1 subset in SRC and the CD8_TEM_T2ISG subset in SSc-ILD may play crucial roles in the respective organ damage. Time-series analysis and tissue perturbation studies of these cellular subsets in larger cohorts will further clarify the pathogenesis of SSc, and demonstrate the potential of these subsets as therapeutic targets.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStudy participants\u003c/h2\u003e \u003cp\u003e Samples were collected from study participants who provided informed consent, in accordance with the Declaration of Helsinki and with approval from the ethics review board of the Graduate School of Medicine, Osaka University, Japan (No. 855). Consent was obtained to publish information such as age, sex, the name of medical center, and the diagnosis. Study participants received no compensation. Patients were diagnosed with systemic sclerosis according to the 2013 ACR/EULAR classification criteria\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. The diagnosis was confirmed by at least two rheumatologists.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003ePatient profiles\u003c/h2\u003e \u003cp\u003eTwenty-one patients diagnosed with SSc and six healthy donors were recruited for this study. None of the patients had received any immunosuppressive therapy. All patients were either admitted to or visited Osaka University Hospital, where they underwent a comprehensive assessment to rule out infectious diseases, neoplastic lesions, and any overlap of other systemic autoimmune diseases, before the 2013 ACR/EULAR classification criteria was applied. The presence of ILD was diagnosed based on clinical symptoms, computed tomography (CT) scan and pulmonary function tests. CT images were reviewed by at least two rheumatologists and one radiologist. SRC was diagnosed according to the UK Scleroderma Study Group guideline\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. Samples were included in the SRC group if they were collected from SSc patients within three months of SRC onset or at any time after the onset. Blood pressure and mRSS were measured on the day of blood collection. Four patients with LN were recruited for some analyses. Systemic lupus erythematosus was diagnosed according to the 2019 EULAR/ACR classification criteria\u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e, and LN was confirmed by renal biopsy\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003ePBMCs preparation\u003c/h2\u003e \u003cp\u003eTwenty milliliters of whole blood was collected into Na-heparin blood collection tubes (Terumo, Cat. No. VP-H070K). PBMCs were isolated using Leucosep (Greiner, Cat. No. 22788-013), then washed and resuspended in Cellbanker 1plus (ZENOAQ, Cat. No. CB023) to a concentration of 1.0 \u0026times; 10\u003csup\u003e7\u003c/sup\u003e cells/mL before storage at \u0026minus;\u0026thinsp;150\u0026deg;C.\u003c/p\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003eSingle-cell library construction (CITE-seq)\u003c/h2\u003e \u003cp\u003eCITE-seq was performed using the same antibodies as in our previous report\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Thawed PBMCs were treated with DNA-barcoded antibodies, and single-cell suspensions were processed using the 10x Genomics Chromium Controller (10x Genomics). The libraries were constructed according to the protocol outlined in the user guide of Chromium Single Cell 5\u0026rsquo; Reagent Kits v2 (Dual Index, Cat. No. PN-1000263) (10x Genomics). Briefly, up to 10,000 labeled live cells per sample were individually loaded into the 10x Genomics platform without sample mixing to generate a barcoded cDNA library for individual cells. Data quality control was conducted using a Bioanalyzer system (Agilent). Individual libraries were pooled and sequenced on the HiSeq 2500 or Novaseq 6000 platform (Illumina) to analyze gene and surface protein expression. Sequence information of CITE-seq is summarized in Supplementary Table\u0026nbsp;8.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eReference-based cell annotation and analysis of CITE-seq data\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRaw FASTQ files were aligned to the GRCh38 reference genome using CellRanger (version 6.0.6). Filtered HDF5 feature-barcode matrix files were generated using the CellRanger count to create a Seurat object. Data quality control, scaling, transformation, clustering, dimensionality reduction, differential expression analysis, and visualization were performed using the Seurat R package (V4.3.0). Cells with nFeature_RNA values less than 200 or greater than 5,000, or mitochondrial read percentages exceeding 20%, were removed. Data normalization and scaling were performed using the SCTransform function. Except for the time course analysis, only the initial samples collected during the clinical course were integrated. For the comparison between SRC, LN, and healthy donors, samples from patients diagnosed with SRC or LN were integrated with those from healthy donors. For the time course analysis of the SRC patient, samples collected at three different time points from the same individual were included. Each cell subpopulation was identified through two rounds of clustering. Initially, reference-based integration was applied to the query dataset using the public CITE-seq dataset of 211,000 human PBMCs as the reference\u003csup\u003e12\u003c/sup\u003e. The FindTransferAnchors function was employed to find anchors between the reference and the query datasets, using precomputed supervised PCA transformation for SCT-normalized data. The MapQuery function was used to transfer cell-type labels and protein data from the reference to the query datasets. Platelets and erythrocytes were excluded from the analysis. To identify subpopulations within each cell type, a second round of clustering was conducted on specific populations: monocytes (CD14 Mono, CD16 Mono, cDC1, and cDC2), CD8\u003csup\u003e+\u003c/sup\u003e T cells (CD8 Naive, CD8 TCM, and CD8 TEM), CD4\u003csup\u003e+\u003c/sup\u003e T cells (CD4 Naive, CD4 TCM, CD4 TEM, Treg, and CD4 CTL), B cells (B naive, B intermediate, and B memory), NK cells (NK and NK_CD56bright), and pDCs (pDC). The RunUMAP function was used to perform UMAP dimensional reduction with 30 precomputed spca dimensions. A nearest-neighbor graph using the 30 dimensions of the supervised PCA reduction was computed using the FindNeighbors function followed by the FindClusters function for cell clustering. The resultant UMAP was visualized using the DimPlot function. Each cluster was manually annotated using gene expression and surface protein data. Doublets were manually removed using surface protein data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePCA using cell composition of PBMCs\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePCA was performed using the PCA function in the FactoMineR package, with data scaled to unit variance. First, the proportion of each cell subpopulation defined in the subset analysis was calculated, along with other minor cell populations, all relative to the total PBMCs. The proportion of each cell subset was included as a variable in the PCA, except for populations with fewer than 100 total cells. Vectors representing each subpopulation were shown on a plane defined by the first two principal components (PC1 and PC2) using the fviz_pca_var function. Each study participant was represented as a single plot on the same plane according to their respective PC1 and PC2 values.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDifferential abundance analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDifferential abundance analysis was performed on PBMCs, monocytes, CD4\u003csup\u003e+\u003c/sup\u003e T cells, and CD8\u003csup\u003e+\u003c/sup\u003e T cells collected in this study, as well as lung CD8\u003csup\u003e+\u003c/sup\u003e T cells derived from public data\u003csup\u003e34\u003c/sup\u003e, using the miloR (version 3.15) package. These analyses were performed to detect groups of cells that are differentially abundant in different conditions by modeling the number of cells within the neighborhoods of a k-nearest neighbor (KNN) graph\u003csup\u003e17\u003c/sup\u003e. To adjust for cell number, up to 1,000 cells were randomly selected from each sample for differential abundance analysis. The buildGraph function was first used to construct a KNN graph on the basis of precomputed supervised PCA with k = 5, using 30 principal components. Using the makeNhoods function, cells were then grouped into neighborhoods according to their connectivity over the KNN graph. To test for differential abundance, Milo fitted a negative binomial generalized linear model to the counts for each neighborhood using TMM normalization. Age was used as a covariate in the testNhoods function. For visualization, the log\u003csub\u003e2\u003c/sub\u003e-fold change in cell numbers between two conditions in each neighborhood was calculated. Nodes representing neighborhoods that were considered statistically significant (\u0026alpha; \u0026lt; 0.2) were colored in red or blue.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDifferential gene expression analysis and gene set enrichment analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn specific cell subsets, DEGs were identified using the FindMarkers function. For the characterization of DEGs, gene set enrichment analysis was conducted on genes exhibiting a log\u003csub\u003e2\u003c/sub\u003e-fold change greater than 0.5, using the Enrichr, a web-based tool for analyzing gene sets\u003csup\u003e51\u003c/sup\u003e. The MSigDB Hallmark 2020\u003csup\u003e35\u003c/sup\u003e or BioPlanet 2019\u003csup\u003e52\u003c/sup\u003e were employed as the dataset and adjusted P-values for each pathway were calculated by the Benjamini\u0026ndash;Hochberg method. TRRUST Transcription Factors 2019\u003csup\u003e28\u003c/sup\u003e was used to determine the adjusted P-values for each transcription factor\u0026ndash;related pathway. Pathways not related to humans were excluded from the analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePreparation of kidney cells and whole-blood leukocytes for Abseq\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRenal tissue was obtained by needle biopsy from one patient at the onset of SRC (patient ID: SSc-19). The tissue was immediately washed with phosphate-buffered saline and processed into single cell suspension using the Tumor Dissociation Kit (human, Miltenyi Biotec). Enzyme R was excluded to preserve the cell-surface epitope. The sample was cut into small pieces with a maximal dimension of approximately 2 mm, combined with the enzyme mixture, and shaken at 37\u0026deg;C in a water bath at 160 rpm for 45 minutes. The sample was treated with DNase for 5 minutes at room temperature. No steps were taken to lyse red blood cells or remove dead cells.\u003c/p\u003e\n\u003cp\u003eTwo milliliters of Whole blood was collected from the same patient in an EDTA-2Na blood collection tube (Terumo, Cat. No. VP-Na052K), and the leukocytes were isolated using Polymorphprep (Serumwerk, Cat. No. 1895). The sample was washed and resuspended with Cellbanker 1plus (ZENOAQ, Cat. No. CB023) to a concentration of 2.0 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e cell/mL prior to scRNA-seq experiments.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSingle-cell library construction (Abseq)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRenal cells and total peripheral leukocytes were processed separately through the BD Rhapsody Express System (BD Biosciences, Catalog No. 665915). Thirty-five DNA-barcoded antibodies (detailed in Supplementary Table 10) were added to each cell suspension. Abseq libraries were constructed using WTA Reagent Kits (BD Biosciences, Cat. No. 665915). Approximately 10,000 peripheral leukocytes were loaded into the BD Rhapsody platform. All obtained renal cells were processed in an identical manner. Data quality control was performed using the Bioanalyzer (Agilent). The libraries were pooled for sequencing on the HiSeq 2500 or Novaseq 6000 platform (Illumina) to analyze gene and surface protein expression. Sequence information of Abseq is summarized in Supplementary Table 9.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eManual cell annotation and analysis of Abseq data\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRaw FASTQ files were aligned to the GRCh38 reference genome using the BD Rhapsody Sequence Analysis Pipeline (version 1.12). Distribution-based error correction-adjusted molecule counts were presented as gene expression data tables to establish a Seurat object. The Seurat R package (V4.3.0) was used for data quality control, scaling, transformation, clustering, dimensionality reduction, differential expression analysis, and visualization. A total of 16,081 cells were selected for further analysis on the basis of unique molecular identifiers for each cell and percentages of mitochondrial reads. Peripheral leukocytes with nFeature_RNA values less than 200 or greater than 5,000, or mitochondrial read percentages exceeding 20%, were excluded from the analysis. Similarly, kidney cells were removed if they had nFeature_RNA values less than 200 or greater than 5,000, or mitochondrial read percentages exceeding 40%. The data were normalized and scaled using the SCTransform function. The data from peripheral blood and kidney samples were integrated using reciprocal PCA. The RunUMAP function was used for UMAP dimensional reduction with 30 precomputed PCA dimensions. A nearest-neighbor graph was then constructed using the 30 PCA dimensions with the FindNeighbors function, followed by clustering using the FindClusters function. The UMAP was visualized using the DimPlot function. Each cluster was manually annotated using gene expression and surface protein data. Platelets and erythrocytes were removed from the analysis. Doublets were also removed using cell-surface protein data.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePseudotime analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe pseudotime of each cell and the cell trajectory were calculated using the Monocle 3 package\u003csup\u003e26\u003c/sup\u003e. The previously annotated Seurat object was imported into Monocle 3. Using the learn_graph function, we fitted a principal graph and plot the graph through the UMAP coordinates. The order_cells function was employed to calculate the pseudotime for each cell, with the root node set to the immature monocyte population characterized by high expression of S100A12 and low expression of HLA-DRB1\u003csup\u003e27\u003c/sup\u003e (Extended Data Fig. 14). The cell trajectory was visualized using the plot_cells function.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePublic data analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe scRNA-seq data of lung cells derived from SSc patients with advanced ILD and healthy donors were obtained from the gene expression omnibus under accession numbers GSE128169 and GSE128033. We used only lung tissue samples, excluding those labeled with hashtags designated for sample multiplexing. The Seurat object was subsequently created using the CreateSeuratObject function. The quality control of scRNA-seq data was performed as previously reported\u003csup\u003e34\u003c/sup\u003e. Data were normalized and scaled using the SCTransform function, followed by data integration using reciprocal PCA. The RunUMAP function was used for UMAP dimensional reduction with 30 precomputed PCA dimensions. A nearest-neighbor graph using the 30 dimensions of the PCA reduction was computed using the FindNeighbors function, followed by clustering using the FindClusters function. The UMAP was visualized using the DimPlot function. Each cluster was manually annotated using gene expression data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eModule scoring\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eModule scores for each cell were calculated using the AddModuleScore function. To assess the expression of type II ISGs in lung CD8\u003csup\u003e+\u003c/sup\u003e T cells, module scores were calculated using the \u0026ldquo;Interferon Gamma Response\u0026rdquo; gene set from MSigDB Hallmark 2020. To evaluate the similarity of each lung CD8\u003csup\u003e+\u003c/sup\u003e T cell subset to the peripheral CD8\u003csup\u003e+\u003c/sup\u003e T cell subpopulation, CD8_TEM_T2ISG, module scores were calculated using DEGs (fold change \u0026gt;0.5) of CD8_TEM_T2ISG. Gene scores for each subset were visualized using the Dotplot function according to cell-based scores.\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCount matrix data will be available at the Japanese Genotype-phenotype Archive (JGA) with unique accession codes\u0026nbsp;JGAS000XXX and JGAS000XXX (https://ddbj.nig.ac.jp/resource/jga-study/JGAS000XXX).\u003c/p\u003e\n\u003cp\u003eThe GRCh38 reference genome was obtained from NCBI (https://www.ncbi.nlm.nih.gov/assembly/GCF_000001405.26/).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eExperimental protocols, data analysis pipelines, analysis steps, functions, and parameters used are described in the Methods section. Custom code used in the paper is available at GitHub.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e(https://github.com/ShimagamiH/ShimagamiH_SSc_scRNAseq).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCho JH, Feldman M (2015) Heterogeneity of autoimmune diseases: pathophysiologic insights from genetics and implications for new therapies. Nat Med 21:730\u0026ndash;738. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1038/nm.3897\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1038/nm.3897\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVolkmann ER, Andreasson K, Smith V (2023) Systemic sclerosis. Lancet 401:304\u0026ndash;318. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1016/S0140-6736(22)01692-0\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1016/S0140-6736(22)01692-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRubio-Rivas M, Royo C, Simeon CP, Corbella X, Fonollosa V (2014) Mortality and survival in systemic sclerosis: systematic review and meta-analysis. Semin Arthritis Rheum 44:208\u0026ndash;219. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1016/j.semarthrit.2014.05.010\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1016/j.semarthrit.2014.05.010\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePope JE et al (2023) State-of-the-art evidence in the treatment of systemic sclerosis. Nat Rev Rheumatol 19:212\u0026ndash;226. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1038/s41584-023-00909-5\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1038/s41584-023-00909-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eApostolidis SA et al (2018) Single Cell RNA Sequencing Identifies HSPG2 and APLNR as Markers of Endothelial Cell Injury in Systemic Sclerosis Skin. Front Immunol 9:2191. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.3389/fimmu.2018.02191\u003c/span\u003e\u003cspan address=\"https://doi.org:10.3389/fimmu.2018.02191\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGur C et al (2022) LGR5 expressing skin fibroblasts define a major cellular hub perturbed in scleroderma. \u003cem\u003eCell\u003c/em\u003e 185, 1373\u0026ndash;1388 e1320 \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1016/j.cell.2022.03.011\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1016/j.cell.2022.03.011\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTabib T et al (2021) Myofibroblast transcriptome indicates SFRP2(hi) fibroblast progenitors in systemic sclerosis skin. Nat Commun 12:4384. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1038/s41467-021-24607-6\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1038/s41467-021-24607-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXue D et al (2022) Expansion of Fcgamma Receptor IIIa-Positive Macrophages, Ficolin 1-Positive Monocyte-Derived Dendritic Cells, and Plasmacytoid Dendritic Cells Associated With Severe Skin Disease in Systemic Sclerosis. Arthritis Rheumatol 74:329\u0026ndash;341. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1002/art.41813\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1002/art.41813\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGaydosik AM et al (2021) Single-cell transcriptome analysis identifies skin-specific T-cell responses in systemic sclerosis. Ann Rheum Dis 80:1453\u0026ndash;1460. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1136/annrheumdis-2021-220209\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1136/annrheumdis-2021-220209\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNishide M, Shimagami H, Kumanogoh A (2024) Single-cell analysis in rheumatic and allergic diseases: insights for clinical practice. Nat Rev Immunol. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1038/s41577-024-01043-3\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1038/s41577-024-01043-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003evan den Hoogen F et al (2013) 2013 classification criteria for systemic sclerosis: an American College of Rheumatology/European League against Rheumatism collaborative initiative. Arthritis Rheum 65:2737\u0026ndash;2747. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1002/art.38098\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1002/art.38098\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHao Y et al (2021) Integrated analysis of multimodal single-cell data. \u003cem\u003eCell\u003c/em\u003e 184, 3573\u0026ndash;3587 e3529 \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1016/j.cell.2021.04.048\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1016/j.cell.2021.04.048\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNehar-Belaid D et al (2020) Mapping systemic lupus erythematosus heterogeneity at the single-cell level. Nat Immunol 21:1094\u0026ndash;1106. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1038/s41590-020-0743-0\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1038/s41590-020-0743-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZheng L et al (2021) Pan-cancer single-cell landscape of tumor-infiltrating T cells. \u003cem\u003eScience\u003c/em\u003e 374, abe6474 \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1126/science.abe6474\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1126/science.abe6474\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNishide M et al (2023) Single-cell multi-omics analysis identifies two distinct phenotypes of newly-onset microscopic polyangiitis. Nat Commun 14:5789. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1038/s41467-023-41328-0\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1038/s41467-023-41328-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu X et al (2022) Single-Cell Sequencing of Immune Cell Heterogeneity in IgG4-Related Disease. Front Immunol 13:904288. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.3389/fimmu.2022.904288\u003c/span\u003e\u003cspan address=\"https://doi.org:10.3389/fimmu.2022.904288\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDann E, Henderson NC, Teichmann SA, Morgan MD, Marioni JC (2022) Differential abundance testing on single-cell data using k-nearest neighbor graphs. Nat Biotechnol 40:245\u0026ndash;253. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1038/s41587-021-01033-z\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1038/s41587-021-01033-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee SJ et al (2014) TLR4-mediated expression of Mac-1 in monocytes plays a pivotal role in monocyte adhesion to vascular endothelium. PLoS ONE 9:e104588. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1371/journal.pone.0104588\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1371/journal.pone.0104588\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhen A et al (2014) CD4 ligation on human blood monocytes triggers macrophage differentiation and enhances HIV infection. J Virol 88:9934\u0026ndash;9946. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1128/JVI.00616-14\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1128/JVI.00616-14\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMusso T et al (2001) CD38 expression and functional activities are up-regulated by IFN-gamma on human monocytes and monocytic cell lines. J Leukoc Biol 69:605\u0026ndash;612\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi C, Hua K (2022) Dissecting the Single-Cell Transcriptome Network of Immune Environment Underlying Cervical Premalignant Lesion, Cervical Cancer and Metastatic Lymph Nodes. Front Immunol 13:897366. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.3389/fimmu.2022.897366\u003c/span\u003e\u003cspan address=\"https://doi.org:10.3389/fimmu.2022.897366\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZimmerman KA et al (2019) Single-Cell RNA Sequencing Identifies Candidate Renal Resident Macrophage Gene Expression Signatures across Species. J Am Soc Nephrol 30:767\u0026ndash;781. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1681/ASN.2018090931\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1681/ASN.2018090931\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKaur S et al (2021) Functions of Thrombospondin-1 in the Tumor Microenvironment. Int J Mol Sci 22. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.3390/ijms22094570\u003c/span\u003e\u003cspan address=\"https://doi.org:10.3390/ijms22094570\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang H, Wu J, Ma L, Bai Y, Liu J (2023) The role of interleukin \u0026ndash;\u0026thinsp;1 family in fibrotic diseases. Cytokine 165:156161. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1016/j.cyto.2023.156161\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1016/j.cyto.2023.156161\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHong Q et al (2019) LRG1 Promotes Diabetic Kidney Disease Progression by Enhancing TGF-beta-Induced Angiogenesis. J Am Soc Nephrol 30:546\u0026ndash;562. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1681/ASN.2018060599\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1681/ASN.2018060599\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTrapnell C et al (2014) The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells. Nat Biotechnol 32:381\u0026ndash;386. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1038/nbt.2859\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1038/nbt.2859\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen ST et al (2022) A shift in lung macrophage composition is associated with COVID-19 severity and recovery. Sci Transl Med 14:eabn5168. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1126/scitranslmed.abn5168\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1126/scitranslmed.abn5168\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHan H et al (2018) TRRUST v2: an expanded reference database of human and mouse transcriptional regulatory interactions. Nucleic Acids Res 46:D380\u0026ndash;D386. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1093/nar/gkx1013\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1093/nar/gkx1013\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSun SC (2017) The non-canonical NF-kappaB pathway in immunity and inflammation. Nat Rev Immunol 17:545\u0026ndash;558. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1038/nri.2017.52\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1038/nri.2017.52\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWoodworth TG, Suliman YA, Li W, Furst DE, Clements P (2016) Scleroderma renal crisis and renal involvement in systemic sclerosis. Nat Rev Nephrol 12:678\u0026ndash;691. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1038/nrneph.2016.124\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1038/nrneph.2016.124\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eColditz IG, Watson DL (1992) The effect of cytokines and chemotactic agonists on the migration of T lymphocytes into skin. Immunology 76:272\u0026ndash;278\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNagarsheth N, Wicha MS, Zou W (2017) Chemokines in the cancer microenvironment and their relevance in cancer immunotherapy. Nat Rev Immunol 17:559\u0026ndash;572. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1038/nri.2017.49\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1038/nri.2017.49\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHoffmann-Vold AM et al (2017) Cardiopulmonary Disease Development in Anti-RNA Polymerase III-positive Systemic Sclerosis: Comparative Analyses from an Unselected, Prospective Patient Cohort. J Rheumatol 44:459\u0026ndash;465. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.3899/jrheum.160867\u003c/span\u003e\u003cspan address=\"https://doi.org:10.3899/jrheum.160867\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eValenzi E et al (2019) Single-cell analysis reveals fibroblast heterogeneity and myofibroblasts in systemic sclerosis-associated interstitial lung disease. Ann Rheum Dis 78:1379\u0026ndash;1387. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1136/annrheumdis-2018-214865\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1136/annrheumdis-2018-214865\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiberzon A et al (2015) The Molecular Signatures Database (MSigDB) hallmark gene set collection. Cell Syst 1:417\u0026ndash;425. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1016/j.cels.2015.12.004\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1016/j.cels.2015.12.004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNguyen HQ, Hoffman-Liebermann B, Liebermann DA (1993) The zinc finger transcription factor Egr-1 is essential for and restricts differentiation along the macrophage lineage. Cell 72:197\u0026ndash;209. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1016/0092-8674(93)90660-i\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1016/0092-8674(93)90660-i\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen SJ et al (2006) The early-immediate gene EGR-1 is induced by transforming growth factor-beta and mediates stimulation of collagen gene expression. J Biol Chem 281:21183\u0026ndash;21197. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1074/jbc.M603270200\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1074/jbc.M603270200\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBhattacharyya S et al (2008) Smad-independent transforming growth factor-beta regulation of early growth response-1 and sustained expression in fibrosis: implications for scleroderma. Am J Pathol 173:1085\u0026ndash;1099. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.2353/ajpath.2008.080382\u003c/span\u003e\u003cspan address=\"https://doi.org:10.2353/ajpath.2008.080382\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQiao Y et al (2013) Synergistic activation of inflammatory cytokine genes by interferon-gamma-induced chromatin remodeling and toll-like receptor signaling. Immunity 39:454\u0026ndash;469. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1016/j.immuni.2013.08.009\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1016/j.immuni.2013.08.009\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMeng Y, Chen C, Tian C, Du J, Li HH (2015) Angiotensin II-induced Egr-1 expression is suppressed by peroxisome proliferator-activated receptor-gamma ligand 15d-PGJ(2) in macrophages. Cell Physiol Biochem 35:689\u0026ndash;698. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1159/000369729\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1159/000369729\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKranzhofer R, Browatzki M, Schmidt J, Kubler W (1999) Angiotensin II activates the proinflammatory transcription factor nuclear factor-kappaB in human monocytes. Biochem Biophys Res Commun 257:826\u0026ndash;828. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1006/bbrc.1999.0543\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1006/bbrc.1999.0543\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlaaeldin R et al (2023) Azilsartan Modulates HMGB1/NF-kappaB/p38/ERK1/2/JNK and Apoptosis Pathways during Renal Ischemia Reperfusion Injury. \u003cem\u003eCells\u003c/em\u003e 12 \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.3390/cells12010185\u003c/span\u003e\u003cspan address=\"https://doi.org:10.3390/cells12010185\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYan SF et al (2000) Egr-1, a master switch coordinating upregulation of divergent gene families underlying ischemic stress. Nat Med 6:1355\u0026ndash;1361. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1038/82168\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1038/82168\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang W, Ren X, Chen X, Hong Q, Cai G (2024) Integrin beta1-rich extracellular vesicles of kidney recruit Fn1\u0026thinsp;+\u0026thinsp;macrophages to aggravate ischemia-reperfusion-induced inflammation. JCI Insight 9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1172/jci.insight.169885\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1172/jci.insight.169885\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMueller A et al (2008) CXCL4-induced migration of activated T lymphocytes is mediated by the chemokine receptor CXCR3. J Leukoc Biol 83:875\u0026ndash;882. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1189/jlb.1006645\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1189/jlb.1006645\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003evan Bon L et al (2014) Proteome-wide analysis and CXCL4 as a biomarker in systemic sclerosis. N Engl J Med 370:433\u0026ndash;443. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1056/NEJMoa1114576\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1056/NEJMoa1114576\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFujii H, Hasegawa M, Takehara K, Mukaida N, Sato S (2002) Abnormal expression of intracellular cytokines and chemokine receptors in peripheral blood T lymphocytes from patients with systemic sclerosis. Clin Exp Immunol 130:548\u0026ndash;556. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1046/j.1365-2249.2002.02017.x\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1046/j.1365-2249.2002.02017.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLynch BM et al (2016) UK Scleroderma Study Group (UKSSG) guidelines on the diagnosis and management of scleroderma renal crisis. Clin Exp Rheumatol 34:106\u0026ndash;109\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAringer M et al (2019) European League Against Rheumatism/American College of Rheumatology Classification Criteria for Systemic Lupus Erythematosus. \u003cem\u003eArthritis Rheumatol\u003c/em\u003e 71, 1400\u0026ndash;1412 (2019). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1002/art.40930\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1002/art.40930\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWeening JJ et al (2004) The classification of glomerulonephritis in systemic lupus erythematosus revisited. J Am Soc Nephrol 15:241\u0026ndash;250. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1097/01.asn.0000108969.21691.5d\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1097/01.asn.0000108969.21691.5d\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXie Z et al (2021) Gene Set Knowledge Discovery with Enrichr. Curr Protoc 1:e90. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1002/cpz1.90\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1002/cpz1.90\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHuang R et al (2019) The NCATS BioPlanet - An Integrated Platform for Exploring the Universe of Cellular Signaling Pathways for Toxicology, Systems Biology, and Chemical Genomics. Front Pharmacol 10:445. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.3389/fphar.2019.00445\u003c/span\u003e\u003cspan address=\"https://doi.org:10.3389/fphar.2019.00445\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4728677/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4728677/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAutoimmune rheumatic diseases present with diverse clinical manifestations that often complicate management strategies. Systemic sclerosis (SSc) is a representative disease with multiple organ manifestations affecting patients worldwide, and exploring the variation of immune abnormalities in this disease is of great interest. However, previous studies have focused on diseased tissues, and it remains largely unknown how cellular diversity links to clinical heterogeneity. Here, we perform single-cell transcriptome and surface proteome analyses of peripheral blood mononuclear cells (PBMCs) from 21 SSc patients who are not receiving immunomodulatory therapy and show that different clinical manifestations are associated with distinct immune abnormalities. Enrichment of a specific CD14\u003csup\u003e+\u003c/sup\u003e monocyte subset characterized by \u003cem\u003eEGR1\u003c/em\u003e expression is observed in patients with scleroderma renal crisis (SRC). Integrated analysis of PBMCs and kidney biopsy cells indicates that this monocyte subset directly differentiates into tissue-damaging macrophages under activation of NF-κB signaling. Clinically, \u003cem\u003eEGR1\u003c/em\u003e expression in monocytes is significantly upregulated at the onset of SRC and decreases after treatment, suggesting its potential as a biomarker for SRC. In patients with interstitial lung disease (ILD), a CD8\u003csup\u003e+\u003c/sup\u003e T cell subset with type II interferon signature is highly enriched in both peripheral blood and lung tissue of patients with progressive disease, suggesting that chemokine-driven migration of these cells is involved in ILD progression. Thus, distinct immune cell profiles at the single cell level reveal different directions of immune dysregulation between organ manifestations and provide insights for tailored treatment strategies.\u003c/p\u003e","manuscriptTitle":"Single-cell analysis reveals immune cell abnormalities underlying the clinical heterogeneity of systemic sclerosis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-22 10:40:43","doi":"10.21203/rs.3.rs-4728677/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-communications","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"NCOMMS","sideBox":"Learn more about [Nature Communications](http://www.nature.com/ncomms/)","snPcode":"","submissionUrl":"https://mts-ncomms.nature.com/","title":"Nature Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Communications","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"460c9c28-2874-4066-8348-d75baef14e68","owner":[],"postedDate":"July 22nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":34846369,"name":"Health sciences/Diseases/Rheumatic diseases/Connective tissue diseases/Systemic sclerosis"},{"id":34846370,"name":"Biological sciences/Immunology/Autoimmunity"}],"tags":[],"updatedAt":"2025-06-18T07:05:31+00:00","versionOfRecord":{"articleIdentity":"rs-4728677","link":"https://doi.org/10.1038/s41467-025-60034-7","journal":{"identity":"nature-communications","isVorOnly":false,"title":"Nature Communications"},"publishedOn":"2025-06-17 04:00:00","publishedOnDateReadable":"June 17th, 2025"},"versionCreatedAt":"2024-07-22 10:40:43","video":"","vorDoi":"10.1038/s41467-025-60034-7","vorDoiUrl":"https://doi.org/10.1038/s41467-025-60034-7","workflowStages":[]},"version":"v1","identity":"rs-4728677","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4728677","identity":"rs-4728677","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}