In vitro polarized macrophages ameliorate adverse cardiac remodeling in a mouse model of transverse aortic constriction

Ulugbek Yakhshimurodov; Kizuku Yamashita; Takuji Kawamura; Kenji Miki; Takura Taguchi; Shunsuke Saito; Imad Abugessaisa; Shigeru Miyagawa

doi:10.1016/j.reth.2026.101061

. 2026 Jan 9;31:101061. doi: 10.1016/j.reth.2026.101061

In vitro polarized macrophages ameliorate adverse cardiac remodeling in a mouse model of transverse aortic constriction

Ulugbek Yakhshimurodov ^a, Kizuku Yamashita ^a, Takuji Kawamura ^a, Kenji Miki ^b, Takura Taguchi ^a, Shunsuke Saito ^a, Imad Abugessaisa ^b,^c, Shigeru Miyagawa ^a,^b,^⁎

PMCID: PMC12818992 PMID: 41567728

Abstract

Introduction

Heart failure (HF) caused by pressure overload remains as one of the leading causes of morbidity and mortality worldwide, which can manifest itself in a wide range of clinical scenarios. Current therapeutic strategies are limited to lifestyle changes, pharmacological measures, and devices aimed at supporting heart function. This poses a challenge in the search for new strategies for disease management. Macrophages, constituting nearly 10 % of non-myocyte cells in a healthy heart are considered a means to fill this gap due to their pleiotropic phenotype, which extends beyond the well-known functions of phagocytosis and antigen presentation. In this study, we evaluated the efficacy of bone marrow mononuclear cell (BMNC)-derived macrophages (BMNC-Mφ) in treating a mouse model of transverse aortic constriction (TAC).

Methods

In in vitro experiments, BMNC were polarized into BMNC-Mφ using a previously established protocol. We then performed transcriptomic analysis to confirm BMNC-Mφ marker genes compared to BMNC. BMNC-Mφ phenotypes were further validated by flow cytometry and RT-qPCR. In in vivo experiments, all mice underwent TAC surgery (day 0). On days 7 and 14 post-TAC, mice in the experimental and control groups received intravenous injections of approximately 3 × 10⁶ BMNC-Mφ or PBS, respectively. Heart function was assessed weekly by transthoracic echocardiography at baseline and 7, 14, 21, and 28 days post-TAC. Additionally, we monitored in vivo transcriptome dynamics over time using time-resolved deep RNA sequencing profiles of heart tissues from healthy, 1 day post-TAC, 8 days post-TAC, and 16 days post-TAC mice. Time-course transcriptomic profiling was followed by histological analysis of excised hearts on day 28.

Results

BMNC-Mφ showed phenotype similar to that of resident cardiac macrophages, with increased expression of key anti-inflammatory macrophage markers, including Igf1, Arg1, Retnla, Ang2, Anxa2, and others. In vivo application of BMNC-Mφ further confirmed their potential to mitigate adverse cardiac remodeling in TAC model. Mice receiving BMNC-Mφ better tolerated mechanical stress, as reflected in preserved LV function (LVEF [52.3 % vs. 45.6 %, p = 0.0152], LVFS [22.6 % vs. 19.2 %, p = 0.0208], and LVIDs [2.65 mm vs. 3.2 mm, p = 0.0261]), as well as structure (fibrosis area [5.6 % vs. 10.67 %, p < 0.01]). In addition, BMNC-Mφ promoted angiogenesis (2120.4 ± 25.5 per mm² vs. 1512.4 ± 34 per mm², p < 0.05) and controlled cardiomyocyte growth, which was seen in the smaller short-axis diameter of cardiomyocytes in BMNC-Mφ-treated group (17.2 ± 0.18 μm vs. 19.45 ± 0.46 μm, p < 0.05).

Conclusion

The main conclusion drawn from our results is that BMNC-Mφ improved or at least preserved LV function and architecture through metabolic recovery, immunosuppression, organized cell cycle/proliferation, and fibrosis modulation.

Keywords: Heart failure, TAC model, Bone marrow, Macrophage, Transcriptomics

Graphical abstract

Highlights of the study

•
Transcriptomic profiling showed a close similarity between in vitro polarized BMNC-Mφ and resident cardiac macrophages.
•
BMNC-Mφ preserved LVEF, LVFS, and LVIDs, promoted angiogenesis, and reduced fibrosis area compared to the control group.
•
Pathways enriched in BMNC-Mφ, particularly those related to oxidative metabolism, were preserved in BMNC-Mϕ−treated LVs.
•
BMNC-Mφ ameliorated adverse cardiac remodelingvia metabolic recovery, immunosuppression, regulation of cell cycle and ECM.

List of abbreviations

BMNC -: bone marrow mononuclear cells
BMNC-Mφ -: BMNC-derived macrophages
BP -: biological process
BTK -: Bruton's tyrosine kinase
CC -: cellular component
CCR2 -: CC-motif chemokine receptor type 2
CD -: cluster differentiation
CVD -: cardiovascular diseases
DAMPs -: damage-associated molecular patterns
DEGs -: differentially expressed genes
ECM -: extracellular matrix
FDR -: false discovery rate
GOBP -: gene ontology biological processes
GSEA -: gene set enrichment analysis
HF -: heart failure
log₂FC -: log fold change
LRT -: likelihood ratio test
LV -: left ventricle
LVEF -: LV ejection fraction
LVFS -: LV fractional shortening
LVIDs -: LV internal diameter in systole
MF -: molecular function
NES -: normalized enrichment score
OXPHOS -: oxidative phosphorylation
PCA -: principal component analysis
PO -: pressure overload
RAAS -: renin-angiotensin-aldosterone system
RCM -: resident cardiac macrophages
RNA-seq -: RNA sequencing
ROS -: reactive oxygen species
RT-qPCR -: real-time quantitative polymerase chain reaction
TAC -: transverse aortic constriction
TTE -: transthoracic echocardiography

1. Introduction

Despite technological and scientific advances, heart failure (HF) remains an economic and social burden worldwide, which can manifest itself in a wide range of clinical phenotypes, from asymptomatic to decompensated states in humans [1]. One of the main reasons for HF, pressure overload (PO) resulting from valvular heart disease and systemic hypertension, causes the release of pro-inflammatory cytokines/chemokines and damage-associated molecular patterns (DAMPs), which in turn trigger the initial inflammatory response and attract monocytes/macrophages into the heart [2,3].

Transverse aortic constriction (TAC), simulating PO-induced cardiac hypertrophy and HF in experimental settings, despite some drawbacks, is the most valuable surgical approach for understanding the cellular and molecular mechanisms underlying this phenomenon, as well as for evaluating the safety and efficacy of new therapeutic strategies [4,5]. In response to acute mechanical stress and neurohumoral activation, various factors and complex multicellular interactions with well-evidenced cardiomyocytes, fibroblasts, and endothelial cells begin to regulate the situation [6]. The number of macrophages, constituting nearly 10 % of non-myocyte cells in a healthy heart, rapidly increases through the recruitment of monocytes positive for the CC-motif chemokine receptor type 2 (CCR2) and the expansion of resident CCR2⁻ macrophages [7,8]. CCR2⁻ resident cardiac macrophages (RCM) play a dominant role in the early phase of remodeling/compensation by inhibiting fibrosis and uncontrolled myocardial hypertrophy [[9], [10], [11]]. However, as peripheral blood monocyte infiltration continues, monocyte-derived CCR2⁺ macrophages become overwhelmingly abundant in the late phase of remodeling/decompensation, partially replacing the vanishing CCR2⁻ RCM and fostering extracellular matrix (ECM) production and cardiomyocyte growth [7,9,10,12].

Not only mechanical stress on the left ventricle (LV), but also neurohumoral responses (renin-angiotensin-aldosterone system [RAAS]) also modulate the immune cell profile in the myocardium. Angiotensin II mainly transmits signals through the CaMKIIδ/NF-κB/NLRP3 axis, promoting cardiomyocyte inflammation and CCR2⁺ macrophage recruitment, whereas aldosterone's contribution to the overall picture is achieved by means of the MR/IL-6/COX-2/MMPs signaling pathways [13]. The development of interstitial fibrosis and myocardial hypertrophy depends on both mechanical stress and activation of RAAS. Macrophage-mediated inflammation further exacerbates tissue damage and fosters adverse cardiac remodeling. Taken together, this evidence highlights the central role of resident and recruited immune cells in the onset and development of HF, making them attractive targets for new therapeutic strategies [13].

Consequently, distinct subsets of cardiac macrophages, possessing a broad range of functional activities beyond their well-known core capabilities of antigen presentation and phagocytosis, are the focus of cardiac immunology, and attempts are being made to modify immune response for various cardiovascular disease (CVD) scenarios [7]. In recent years, not only in situ modulation of host immune cells evolved, but preclinical and clinical studies have also explored the possibility of delivering in vitro treated stem and/or immune cells to the affected myocardium [14]. However, only a few studies, if any, have documented the efficacy and safety of in vitro polarized bone marrow mononuclear cell (BMNC)-derived macrophage (BMNC-Mφ) injections in the context of PO.

To address the above, in this study we investigated the efficacy of in vitro polarized macrophages [15] in preventing adverse cardiac remodeling in a mouse model of TAC. Differential gene expression analysis of transcriptomic profiles showed that BMNC-Mφ possess pro-reparative properties similar to RCM, with significant enrichment of Igf1, Retnla, Arg1, Anxa2, Ang2, Fabp5, Trem2, Lgals3, Folr2, Mrc1, Gdf15, etc., as well as substantial downregulation of Ly6c2, Ccr2, Il1b, Il6, Ifng, and Osm. Additionally, Gene set enrichment analysis (GSEA) [16] with Hallmark gene sets revealed that BMNC-Mφ were significantly enriched for metabolic pathways such as Oxidative Phosphorylation and Fatty Acid Metabolism, which remained preserved in BMNC-Mφ-treated LVs. The anti-inflammatory phenotype of BMNC-Mφ was further confirmed by flow cytometry and RT-qPCR with overexpression of CD206 and significant upregulation of Retnla, respectively. On days 7 and 14 after TAC, animals from the experimental and control groups were intravenously injected with BMNC-Mφ or PBS, respectively. We monitored the transcriptome profiles of mice 1 day before TAC (healthy), 1 day after TAC (surgery only), 8 days after TAC (surgery + BMNC-Mφ or PBS), and 16 days after TAC (surgery + BMNC-Mφ or PBS) using RNA sequencing (RNA-seq). We then assessed cardiac function and myocardial architecture using weekly transthoracic echocardiography (TTE) and histology, respectively. BMNC-Mφ treatment preserved systolic function, promoted angiogenesis, and reduced cardiac fibrosis compared to the control group. RNA-seq of the LV tissues taken at four time points representing six conditions shed light on the potential mechanisms underlying the observed functional and structural improvement following BMNC-Mφ administration. It was found that LVs receiving BMNC-Mφ tolerated TAC-induced PO better than hearts receiving placebo, by promoting immune suppression and metabolic recovery, degrading excess ECM, and strictly regulating cell cycle/proliferation. Our results confirmed that the delivery of in vitro polarized BMNC-Mφ can act in several ways during TAC-induced PO, allowing the myocardium to withstand hypertensive stress. We believe that our results may pave the way for future clinical studies and contribute to the current development in immunology-based therapies for HF.

2. Materials and methods

Ethical approval

All animal experiments were conducted in accordance with the guidelines of the National Institutes of Health and were approved by the Animal Care and Use Committee of the Graduate School of Medicine of The University of Osaka (Ethical Committee approval number: Animal Health Science 04-051-008). Adult male BALB/c mice aged 9–10 weeks (23–26 g) were purchased from Japan SLC Inc. (Osaka, Japan) and housed in groups of five under standard conditions with a 12-h light-dark cycle. The mice were kept in a room with controlled temperature (22 °C) and humidity (40 %), with free access to food and water. Mice with identical characteristics were used for the induction of macrophages from BMNC and for subsequent in vivo application.

2.1. BMNC-Mφ polarization

Mouse BMNC were polarized in vitro into BMNC-Mφ (Fig. 1a) using a protocol for induction of M2-like macrophages from mouse BMNC [15]. Briefly, 9-10-week-old male (23–26 g) BALB/c mice (Japan SLC, Inc.) were euthanized according to university guidelines, and long bones (femur and tibia) were excised. BMNC were isolated by density gradient centrifugation with Histopaque 1083 (Sigma Aldrich, 10831-100). After a single wash with PBS, the cells were seeded in complete DMEM (10 % FBS and 1 % P/S) supplemented with recombinant mouse M-csf (20 ng/mL, Peprotech, 315-02) and L-ascorbic acid (50 μg/mL, Sigma-Aldrich, A4403) and then incubated at 37 °C for 3 days. On day 4, the existing medium was aspirated and replaced with fresh medium containing M-csf (20 ng/mL), L-ascorbic acid (50 μg/mL), and recombinant mouse Il-4 (20 ng/mL, Peprotech, 214-14), and incubation was continued for another 2 days. On day 6, after 120–122 h of induction, the medium was removed, the cells were trypsinized (5 mL/cell culture dish, Gibco, 50-591-420), and the entire surface was gently scraped. The resulting cell suspension was collected and washed once with PBS. BMNC-Mφ were used either for further analysis or injected into mice that had undergone TAC as described below.

2.2. Transcriptomic profiling of BMNC-Mφ

To analyze the expressed gene markers of the resulting BMNC-Mφ, we performed deep RNA-seq. Total RNA was extracted from mouse BMNC and BMNC-Mφ using the miRNeasy Mini Kit (Qiagen, 217004) according to the manufacturer's instructions. Genomic DNA was removed by treatment with DNase I. Samples with RNA integrity number (RIN) > 8.0 were retained for library preparation (three biological replicates per sample, six in total). Stranded mRNA libraries were prepared using the TruSeq Stranded mRNA Library Prep Kit (Illumina). Sequencing was performed on the Illumina NovaSeq X Plus platform to obtain 151 bp paired reads, aiming for approximately 50–60 million reads per sample. Trimming of low-quality reads and adapters, followed by alignment of reads to the Mus Musculus reference genome (GRCm38.p4) using Trimmomatic (v0.39) and HISAT2 (v2.1.0) [17], respectively. Normalization and differential expression analyses were performed in R (v4.5.1) environment for statistical computing and graphics using the edgeR package (v4.6.3) [18]. Principal component analysis (PCA) was used to assess sample clustering and identify outliers between samples. Differentially expressed genes (DEGs) were identified using the likelihood ratio test (LRT) in edgeR, with p-values adjusted for multiple testing using the Benjamini-Hochberg procedure. GSEA of the DEGs was performed using the ClusterProfiler package (v4.16.0) [19]. We ran GSEA Hallmark Pathway for BMNC-Mφ. The number of permutations was set to 1000. Figures and statistical summaries were generated in R using base graphics and ggplot2. All metadata related to in vitro and in vivo RNA sequencing are provided in Supplementary Table 1.

2.3. Flow cytometry

Freshly harvested cells (BMNC and BMNC-Mφ) were distributed into 5-mL flow cytometry tubes (5 × 10⁵ cells per tube) and washed once with cold (4 °C) flow cytometry buffer (BD Bioscience, 554656) followed by incubation with anti-mouse CD16/32 antibody (1:100, Abcam, ab25235) in 100 μL of flow cytometry buffer at 4 °C for 30 min to block FcγIII and FcγII receptors. The samples were then incubated with anti-mouse CD11b [M1/70] APC-conjugated antibody (1:1000, Abcam, ab25482), anti-mouse CD206 [MMR] AF488-conjugated antibody (1:50, Bio Legend, 141710), anti-mouse F4/80 [BM8] PE-conjugated antibody (1:400, Invitrogen, 12-4801-82), anti-mouse MHC-II APC-conjugated antibody (0.03 μg/sample, Invitrogen, 17-5321-82) and anti-mouse CCR2 PE-conjugated antibody (10 μL/10⁶ cells, R&D, FAB5538P) and incubated at 4 °C for 30 min in a light-protected place. The cells were then washed once with flow cytometry buffer, resuspended in 500 μL of buffer and stained with DAPI (2 ng/μL, BD Pharmingen, 564907) as a viability marker. Unstained and IgG stained samples served as negative controls and were used for calibration. The expression of BMNC-Mφ extracellular markers was assessed on a BD Canto II flow cytometer. 10000 end-gated events were recorded for each sample, and the obtained data were processed via BD FACSDiva Software v8.0.1 and FlowJo v10. Appropriate compensation was performed before each experiment via compensation beads. Cell debris, doublets, and dead cells were excluded during the processing step.

2.4. Quantitative real time polymerase chain reaction (RT-qPCR) of BMNC-Mφ

Freshly harvested BMNC and BMNC-Mφ were lysed using QIAzol lysis reagent (Qiagen, 79306) and stored at −80 °C until use. Total RNA was extracted using the miRNeasy Mini Kit (50) (Qiagen, 217004) according to the manufacturer's instructions. Purified RNA was eluted in 30 μL, and RNA concentration was measured using Nanodrop (Thermo Scientific, USA), followed by reverse transcription of 1000 ng of RNA for cDNA synthesis using the SuperScript VILO cDNA synthesis kit (Invitrogen, 11754-050). The resulting cDNA (20 μL) was diluted 10-fold with 180 μL of RNase-free water and stored at −80 °C. RT-qPCR was performed using the QuantStudio 7 Pro (Applied Biosystems, Thermo Fisher Scientific) and TaqMan Gene Expression Assay (Thermo Fisher Scientific, 4331182). The following probes were used: Retnla (Mm00445109_m1), Tnfa (Mm00443258_m1), Cd68 (Mm03047343_m1), Tgfb1 (Mm01178820_m1), Hgf (Mm01135193_m1), Il6 (Mm00446190_m1), Il1b (Mm00434228_m1), Cd53 (Mm00514262_m1), and Gapdh (Mm99999915_g1). Briefly, 2.0 μL (10 ng) of cDNA was added to a 96-well MicroAmp Optical reaction plate (Applied Biosystems) with 10.0 μL Thunderbird Next Probe qPCR Mix (Toyobo, QPX-101), 1.0 μL TaqMan Assay, 2.0 μL 1x ROX, and 5.0 μL nuclease-free water to make a total reaction volume of 20.0 μL. Three technical replicates were performed for each target gene. RT-qPCR results were analyzed using the ΔΔCt method, with Gapdh as the reference gene. Relative quantification (RQ) values were calculated to compare gene expression levels. BMNC served as biological references for BMNC-Mφ.

2.5. Establishment of mouse transverse aortic constriction (TAC) model

TAC surgery was performed according to Rockman's description [20] with the aim of including 7–8 mice in each group, based on an expected survival rate of 70–80 % from previous studies. Mice were administered 2 % Metacam (Boehringer Ingelheim) subcutaneously at a dose of 5 mg/kg 15 min prior to anesthesia induction [21] and every 24 h for the first 2 days after TAC. After anesthesia with 3 % isoflurane in the chamber, the mice were intubated and mechanically ventilated (Kuboto Inc., Tokyo, Japan) at a respiratory rate of 110–120 breaths per minute and a tidal volume of 0.2–0.3 mL. Anesthesia was maintained throughout the procedure with 2 % isoflurane in room air. The depth of anesthesia was confirmed by pinching the hind paws, and the animals were placed in a supine position on a heating pad set to 37 °C. The limbs were secured with tape, and the fur on the torso was shaved. The skin in the surgical area was treated with three iodine/alcohol washes and left to dry. An upper sternotomy (∼8 mm) was performed to access the transverse aorta, and first the thymus and then the perivascular adipose tissue were carefully removed by slow dissection. A 7.0 silk thread was passed under the transverse aorta (between the brachiocephalic and left common carotid arteries), and a 27 G blunt needle was placed parallel to the middle arch and secured with a double knot. The transverse aorta was quickly ligated with 7.0 silk thread on a 27 G needle, latter was immediately removed, and two more knots were made to prevent loosening. The chest wall was closed using 5.0 absorbable nylon suture in order from the sternum to the skin. Anesthesia was then discontinued, and animals were placed on their belly. Mice were extubated once spontaneous breathing and limb movement resumed, then transferred to a clean cage and monitored for 24 h. All surgeries were performed by the same operator (UY).

2.6. Transthoracic echocardiography (TTE)

Heart function was assessed at baseline and at 7, 14, 21, and 28 days after TAC. M-mode echocardiography was performed using a Vivid-i imaging system (GE, Los Angeles, USA). The mice were anesthetized with 1.5 % isoflurane via a mask and placed on their backs on a heating pad, exposing the left chest wall to the examiner. LV ejection fraction (LVEF), LV fractional shortening (LVFS), and LV internal diameter in systole (LVIDs) were measured from M-mode short-axis view at the level of the papillary muscles. According to the American Society of Echocardiography, all measurements were taken over four consecutive cardiac cycles and averaged to minimize beat-to-beat variability and improve reproducibility [22].

2.7. BMNC-Mφ administration

Despite the technical difficulties and associated high mortality, we opted for two injections instead of one to maximize the effect of BMNC-Mφ on pressure-overloaded LV. Briefly, on days 7 and 14 after TAC, mice in the experimental and control groups either received freshly harvested 3 × 10⁶ BMNC-Mφ in 200 μl of PBS (carrier) or the same volume of carrier alone via tail vein injection, respectively. Mice were placed in an anesthesia box and induced with 3 % isoflurane, then maintained with 2 % isoflurane mixed with room air through a mask. Throughout the procedure, mice were placed on their right or left side on a heating pad to maintain body temperature at 37 °C. After the injection, the mice were moved to a clean cage, returned to the breeding room, and monitored for 6 h for the potential complications.

2.8. Cell tracking analysis of BMNC-Mφ

The distribution and localization of BMNC-Mφ in organs were assessed using fluorescent imaging. Freshly harvested BMNC-Mφ were stained using PKH26 Red Fluorescent Cell Linker Kits (Sigma Aldrich, PKH26GL) according to the manufacturer's instructions. PKH26-stained BMNC-Mφ were washed twice with PBS, resuspended at a concentration of 1.5 × 10⁷ cells/mL, and stored on ice until use. Mice on days 7 and 14 after TAC, as well as healthy mice of the same age, were administered the PKH26 BMNC-Mφ cells described above, with the latter serving as a control group. Twenty-four hours after injection, all mice were euthanized, and organs, including heart, lungs, liver, and spleen, were excised and fixed in 4 % paraformaldehyde (Nacalai Tesque) overnight, followed by treatment with 30 % sucrose. The dehydrated organs were then frozen in liquid nitrogen and cryosectioned at a thickness of 5 μm. Immunofluorescence staining was performed using primary and secondary antibodies. Actin filaments and nuclei were counterstained with AF488 phalloidin (1:400, Thermo Fisher Scientific, A12379) and Hoechst 33342 (1:100, Dojindo, Kumamoto, H342-10), respectively and then visualized under a BZ-X810 microscope (Keyence, Osaka, Japan).

2.9. Histopathological and immunohistochemical assessment

On day 28 after TAC, mice from the experimental (n = 8) and control (n = 8) groups were euthanized, and the extracted hearts were fixed in 10 % formalin and embedded in paraffin. Cardiac fibrosis was assessed using picrosirius red staining, and the area of fibrosis was calculated as a percentage of the total area of fibrosis relative to the total surface area of both ventricles using MetaMorph software v7.10.3. Neovascularization in the left ventricle was evaluated using CD31 (1:2000, Abcam, ab182981) immunohistochemical staining, and capillary density was calculated as the average number of CD31-positive vessels per mm² area across five random fields. The cross-sectional diameter of cardiomyocytes was measured using hematoxylin-eosin staining.

2.10. Transcriptomic profiling of healthy, 1 day post-TAC, and BMNC-Mφ- or PBS-treated left ventricles

To monitor transcriptome dynamics in vivo over time, we performed time-resolved deep RNA-seq profiles of heart tissues from healthy (without surgery and treatment), 1 day post-TAC (only surgery), 8-days post-TAC (surgery + BMNC-Mφ or PBS), and 16-days post-TAC (surgery + BMNC-Mφ or PBS) mice (three biological replicates in each condition, eighteen in total). All procedures and quality controls, including sample preparation, total RNA extraction, sequencing, library preparation, downstream analysis, and visualization described above for in vitro transcriptome profiling, were applied in this case as well. Analysis of differentially expressed gene overlap between contrasts was visualized using the UpSetR package (v1.4.0) in R. We ran gseGO for each of the gene ontology categories (Biological Process [BP], Cellular Component [CC], and Molecular Function [MF]) for LV tissues.

2.11. Analysis of the dynamic patterns of the differentially expressed genes

From the gene expression analysis of the in vivo experiment, we obtained a set of differentially expressed genes. To understand how these DEGs change their expression in different samples at each time points and find similar and dissimilar DEGs we took the set of DEGs as input to the R function degPatterns from DEGreport R package (v1.46.0) [23]. degPatterns() took as input the list of DEGs (expression matrix with gene names as raw and sample names as column) and a metadata file that contains detailed description about each sample. We prepared a metadata file containing the sample name (like the one used in the expression matrix), the time point (0d, 1d, 8d, 16d), the sample condition (healthy/TAC). The function predicts a set of clusters. Each cluster is composed of genes with similar expressions patterns (upregulated/downregulated). We further processed the output of the degPatterns() and grouped the clusters into four categories: early rapid response genes, gradual response genes, rapid response genes, and early slow response genes.

2.12. Statistical analysis

All data are presented as mean ± SEM or 95 % of Confidence Interval (CI). The unpaired t-test with Welch's correction was used to compare two independent groups. When data were paired (e.g., BMNC vs. BMNC-Mφ) or included repeated measurements, a mixed-effects model was used, followed by Sidak's multiple comparison test. Comparisons between three groups were performed using the Kruskal-Wallis test with Dunn's multiple comparison correction. Statistical analysis of RT-qPCR, flow cytometry, TTE, cardiac fibrosis, capillary density, and cardiomyocyte short-axis diameter was performed using GraphPad Prism (v10.6.1) (GraphPad Software, La Jolla, California, USA). Transcriptome analysis was performed in R (v4.5.1) using the edgeR (v4.6.3) package. DEGs were defined by a false discovery rate (FDR) < 0.05 and an absolute logarithmic change log₂ > 1, unless otherwise specified. Statistical significance was set at p < 0.05 for all other analyses.

3. Results

3.1. In vitro polarized BMNC-Mφ demonstrated an anti-inflammatory phenotype

To better understand the dynamic and functional state (phenotype) of macrophages, we performed RNA-seq of BMNC-Mφ (n = 3) and BMNC (n = 3), where the latter served as a control group. A total of 402,125,875 reads were obtained from deep RNA-seq of 6 in vitro replicates. PCA of normalized gene expression data showed that PC1 and PC2 accounted for 80 % and 7.3 % of the total variance, respectively (Fig. 1b). The main division along PC1 (on the x-axis) indicates that in vitro induction led to a significant and global shift in the gene expression profile of BMNC-Mφ replicates compared to their precursors. PC2 (on the y-axis) represents within-group variations, such as different macrophage polarization states, individual features, and minor technical effects. In vitro polarization resulted in more diverse transcriptional profile, as replicates in the BMNC group were clustered very closely compared to BMNC- Mφ samples (Fig. 1b).

The volcano plot was used to visualize DEGs in BMNC-Mφ and BMNC groups (Fig. 1c). To construct the graph, we used DEGs (19,372) that passed the filtering threshold of log₂ fold change >1 (log₂FC, on the x-axis) for biological significance and −log₁₀ (adjusted p-value <0.05, on the y-axis) for statistical significance. A total of 9,031 genes were differentially expressed, with 5,324 genes showing downregulation and 3,707 genes showing upregulation in BMNC-Mφ. Genes identifying the anti-inflammatory phenotype of macrophages, such as Retnla, Arg1, Folr2, Mrc1, Trem2, Lgals3, Fapb5, Igf1, Gdf15, Ang2, Anxa2, Gpnmb, and Spp1, were highly expressed, while genes encoding a pro-inflammatory phenotype, such as Ly6c2, Ccr2, Il1b, Il6, Osm, and Ifng, were significantly down-regulated in BMNC-Mφ compared to BMNC (Fig. 1c).

Hierarchical clustering and heatmap visualization of the 100 most significant DEGs demonstrated a clear separation between pre- and post-induction states (Fig. 1d). BMNC-Mφ showed striking enrichment of Arg1, Retnla, and Gpnmb, which are canonical markers of anti-inflammatory macrophages engaged in arginine metabolism, immune suppression, and tissue repair, respectively. This core signature was accompanied by further upregulation of the Igf1 and its regulator Igf2bp1, Ang2 (pro-angiogenic factor), Ch25h (macrophage state identifier), Ccl7 (chemotaxis), Mmp12/Mmp13 (tissue remodeling), and genes involved in immunomodulatory lipid signaling (Pla2g5, Pla2g2e) and oxidative stress protection (Akr1b8). In addition, among the most significant DEGs in BMNC-Mφ, there were a number of genes with unknown functions (e.g., Gm and Rik genes) and may represent new concepts of macrophage polarization. Overall, the heatmap visualization showed a clear transcriptional profile between predecessors and successors and thus confirmed the successful polarization of BMNC-Mφ toward an anti-inflammatory phenotype with therapeutic potential.

In GSEA genes were ranked by log₂FC (BMNC-Mφ vs. BMNC), and enrichment significance was assessed using normalized enrichment scores (NES) and FDR-corrected q-values. GSEA uncovered several significantly enriched Hallmark pathways, including Oxidative Phosphorylation (OXPHOS) and Fatty Acid Metabolism (reliance on mitochondrial OXPHOS, as seen in mature resident macrophages, which is important for long-term survival and functional activity in tissues) [24], mTORC1 Signaling (a key regulator of cellular metabolism and growth that is critical for differentiation, metabolic reprogramming towards OXPHOS, and control of immune responses) [25], Unfolded Protein Response and Protein Secretion (enhanced secretion of cytokines, chemokines, growth factors, and enzymes for establishing cell-to-cell communication and tissue remodeling) [26], Peroxisomes (enhance lipid metabolism and regulate oxidative stress) [27], and Cholesterol Homeostasis (for clearing cellular debris and maintaining lipid balance in tissues) [28], while E2F Targets and G2M Checkpoint (cell proliferation/cell cycle) [29], Heme Metabolism (heme synthesis/degradation and iron processing) [30], and Allograft Rejection (antigen presentation and T cell activation) [31] pathways were significantly reduced in BMNC-Mφ, collectively indicating successful transition to an oxidative, lipid-processing, secretory, and stress-adapted state with lower proliferation and antigen presentation programs (Fig. 2a).

Expression level of macrophage phenotype markers and growth factors was also confirmed using RT-qPCR (Fig. 2h). mRNA levels of Retnla, Cd68, and Cd53 were significantly upregulated (p < 0.05, p < 0.01, and p < 0.05, respectively) in BMNC-Mφ. Whereas genes encoding key pro-inflammatory cytokines such as Tnfa, Il1b, and Il6 were significantly downregulated (p < 0.001 for each) in BMNC-Mφ compared to BMNC. Although BMNC-Mφ did not show upregulation of Tgfb1 and Hgf, they were still capable of synthesizing and secreting these factors (Fig. 2h).

3.2. BMNC-Mφ exhibited macrophage surface markers

Flow cytometry showed that macrophage surface markers such as CD11b, F4/80, and CD206 were highly expressed in BMNC-Mφ (Fig. 2b and c). Almost all macrophages (96.9 %) were CD11b-positive (Fig. 2f), while double positivity for F4/80 and CD206 reached about 88 % (Fig. 2f). BMNC (Fig. 2d) and BMNC-Mφ (Fig. 2e) from the same batch were stained for CCR2 and MHC-II. The results were again consistent with the RNA-seq findings: about 50 % of BMNCs expressed MHC-II on their surface with 16 % MHC-II^high expression pattern (Fig. 2g). However, only one-fifth of BMNC-Mφ showed MHC-II expression (Fig. 2g). Although the rate (total) and pattern (low/high) of MHC-II expression were statistically significant between BMNC and BMNC-Mφ groups (p < 0.05 and p < 0.0001, respectively), CCR2 expression alone and in combination with MHC-II was insignificant before and after polarization (Fig. 2g).

3.3. BMNC-Mφ injection preserved LV systolic function and morphology

We initiated in vivo experiments with baseline TTE and LV tissue sampling for the first RNA-seq cohort (n = 3) one day before TAC surgery (Fig. 3a). Twenty-four hours after TAC, three additional mice were euthanized for RNA-seq II. On days 7 and 14 post-surgery, mice that had been randomly assigned to the experimental or control groups received BMNC-Mφ or PBS, respectively. All mice underwent weekly TTE for four weeks and were subsequently euthanized for histological analysis. Additional LV samples for RNA-seq III and IV were collected on days 8 and 16 post-TAC, respectively. Healthy (non-TAC) and 7 and 14 days post-TAC mice were injected with fluorescence-labeled BMNC-Mφ, and 24 h after injection, the animals were euthanized (Fig. 3a).

LV systolic function was assessed using TTE at baseline and 7, 14, 21, and 28 days after surgery. Overall, M-mode analysis in the parasternal short-axis view at the level of the papillary muscles revealed a profound and progressive decline in systolic function in mice from both groups during the 28-day observation period. However, the mixed-effects model revealed a significant interaction between time and column factor on LVEF and LVFS (p = 0.0152 and p = 0.0208, respectively), indicating that the decline in systolic function over time was better preserved with BMNC-Mφ injections compared to the control group (Fig. 3e and f). As shown in the figure, while baseline LVEF and LVFS values were close to each other (70.18 ± 0.56 % vs. 67.48 ± 0.86 % and 34.27 ± 0.43 % vs. 32.24 ± 0.64 %, respectively), one week after surgery they were more similar (56.72 ± 0.62 % vs 56.54 ± 1.7 % and 25.18 ± 0.36 % vs 25.21 ± 1.06 %). Although LVEF and LVFS in the control group continued to decline, the heart function of the mice in experimental group showed a gradual improvement after first injection (from 54.37 ± 1.62 % to 57.78 ± 1.5 % and from 23.89 ± 0.97 % to 25.99 ± 0.91 %, respectively). Heart function continued to rise after the second injection and peaked on day 21 with 60.14 ± 1.38 % (LVEF) and 27.57 ± 0.86 % (LVFS). However, during last week of follow-up, heart function began to decline again by day 28. Additional effects, such as time (p < 0.0001 for both LVEF and LVFS) and column factor (p = 0.0005 and p = 0.0009, respectively), were also significant between the experimental and control groups. LVIDs also changed over time. LIVDs levels increased during the first three weeks in both the control and experimental groups. However, by day 28, we observed a gradual decline in the BMNC-Mφ-treated group, while values in the control group continued to increase (Fig. 3g). The mixed-effects model also showed a significant interaction between the factors of time and column (p = 0.0261). Overall, BMNC-Mφ injections could at least partially mitigate adverse cardiac remodeling by more effectively preventing systolic dysfunction.

3.4. BMNC-Mφ were detected only in damaged hearts and reduced fibrosis area

We then performed routine histological analysis of the LV to determine whether the functional improvements in the LV observed on echocardiography were associated with structural improvements or, at least, with preservation of myocardial integrity. In myocardial damage, the decisive factors in disease progression are not only the percentage, but also the structural quality, fibrillar composition, and metabolic properties of fibrosis [13]. Hence, we first assessed the areas of fibrosis in the experimental and control groups. Picrosirius red staining showed noticeable fibrosis in both experimental and control group LVs (Fig. 4a and b). However, LVs treated with BMNC-Mφ (n = 8) had significantly fewer fibrotic areas compared to the control group LVs (n = 8) (5.6 ± 0.35 % vs. 10.67 ± 1.1 %, p < 0.01) (Fig. 4c).

Fig. 4 — **Histological evaluation of myocardial architecture and distribution of fluorescence-labeled BMNC-Mφ in the internal organs**

Representative images stained with picrosirius red showing fibrosis of the entire heart (**left panels**) and higher-magnification views of comparable regions (**right panels**) in PBS-treated (a) and BMNC-Mφ-treated (b) groups. (c) Quantification of fibrotic area across PBS-treated (n = 8) and BMNC-Mφ-treated (n = 8) groups. Representative images showing angiogenesis in randomly selected areas of the LV stained for CD31 in healthy (d), PBS-treated (e), and BMNC-Mφ-treated (f) groups, as well as quantitative assessment of capillary density per mm² (g). Five random images were taken from each heart, and the number of CD31-positive vessels was counted (n = 3–8). Images of randomly selected heart tissues stained with hematoxylin and eosin, highlighting the short axis diameter of cardiomyocytes in healthy (h), PBS-treated (i), and BMNC-Mφ-treated (j) groups, and statistical comparison between groups (k). Five random images were taken from each heart, and the short axis diameter of cardiomyocytes with the nucleus in the center was measured (n = 3–8). Distribution of PKH-26 stained BMNC-Mφ in the hearts (l), lungs (m), livers (n), and spleens (o) of healthy mice, mice 8 days after TAC, and mice 15 days after TAC. Phalloidin (F-actin, green), Hoechst (nuclei, blue), PKH26 (BMNC-Mφ, red). Scale bars, 500 μm (**a, b left panels**), 100 μm (**a, b right panels and l-o**), 40 μm (**d-f and h-j**). Magnifications, × 4 (**a, b left panels**), × 20 (**a, b right panels and l-o**), × 40 (**d-f and h-j**). All data are presented as mean ± SEM. ∗p < 0.05 and ∗∗p < 0.01 indicate statistically significant differences between groups. The unpaired t-test with Welch's correction (c) and Kruskal-Wallis test with Dunn's multiple comparison correction (**g, k**) were used for statistical comparison.

To further investigate the relationship between functional and structural changes, we performed immunohistochemical analysis of CD31 to quantify capillary density. Deparaffinized tissue sections from the LVs of healthy (non-TAC, n = 3), PBS-treated (n = 8), and BMNC-Mφ-treated (n = 8) mice were stained with CD31 (Fig. 4d–f) and CD31⁺ capillaries were counted in 5 random areas of each LV. The hearts of healthy animals showed the highest number of micro vessels per square millimeter (2427.8 ± 29.5 capillaries per mm²), followed by LVs treated with BMNC-Mφ (2120.4 ± 25.5 capillaries per mm²), while the PBS-treated group had significantly lower numbers (1512.4 ± 34 per mm²) (Fig. 4g). Although the Kruskal-Wallis test did not reveal significant differences between healthy controls and BMNC-Mφ-treated samples, the changes between healthy controls and PBS-treated groups, as well as between BMNC-Mφ- and PBS-treated groups, were statistically significant (p < 0.01 and p < 0.05, respectively) (Fig. 4g).

Assessment of cardiomyocyte short-axis diameter also showed a trend similar to capillary density: cardiomyocytes in a healthy heart were, as expected, the smallest in size (15.74 ± 0.08 μm), while LV muscles treated with BMNC-Mφ (17.2 ± 0.18 μm) and PBS (19.45 ± 0.46 μm), showed mild to moderate hypertrophy, respectively (Fig. 4h–j). Statistical analysis also revealed no significant difference between the healthy controls and the BMNC-Mφ treated group, while the healthy controls as well as BMNC-Mφ treated group differed significantly from the PBS treated group (p < 0.01 and p < 0.05, respectively) (Fig. 4k).

Next, we decided to check whether systemically administered BMNC-Mφ remained in internal organs, especially in the heart and lungs, since, in theory, macrophages must be in close proximity to cardiac tissue to ensure the observed functional and structural improvements. Although BMNC-Mφ were evenly distributed in the lungs (Fig. 4m), liver (Fig. 4n), and spleen (Fig. 4o), surprisingly, no fluorescently labeled BMNC-Mφ were detected in healthy myocardium (Fig. 4l), while heart sections 7 days post-TAC were more likely to attract BMNC-Mφ (Fig. 4l) compared to heart sections 14 days post-TAC (Fig. 4l). Though the relationship between TAC and liver damage was beyond the scope of this study, it is worth noting that TAC-induced PO strongly affected the shape of hepatocytes only in mice after TAC, which, in contrast, appeared normal in healthy controls (Fig. 4n). This means that mechanical stress on the LV not only affects the myocardium itself, but also systematically affects all tissues.

3.5. Differential expression analysis of RNA-seq reveal large set of differentially expressed genes

To elucidate the mechanisms underlying the functional and structural improvements observed in the BMNC-Mφ-treated groups, RNA-seq of the LVs was performed. A total of 18 samples representing 3 states (healthy, post-surgery, and post-surgery + BMNC-Mφ or PBS treatment) from 4 time points (non-TAC, 1 day post-TAC, 8 days post-TAC, and 16 days post-TAC) were prepared. A sum of 1,243,688,217 reads was obtained from 18 in vivo replicates. PCA of normalized gene expression data showed 38 % and 16.2 % of total variance on the x-axis (PC1) and y-axis (PC2), respectively (Fig. 5a). Replicates 1 day after TAC (LV1) were clearly separated from other samples, accounting for 38 % of the total variance of PC1. Compared to the BMNC-Mφ and BMNC replicates, the in vivo samples were more heterogeneous, as the samples did not cluster well. However, samples from healthy mice (LVH) clustered closely, almost overlapping. Replicates in the 16-day BMNC-Mφ-treated group (LV16-BMNC-Mφ) clustered well compared to their counterparts (LV16-PBS), indicating that BMNC-Mφ injection caused similar changes in the tissue transcriptome, especially in the later stages of the disease. The same was seen in the groups with an 8-day period: replicates treated with BMNC-Mφ (LV8-BMNC-Mφ) were clustered close to each other and closer to LVH replicates, while samples treated with PBS (LV8-PBS) were distant from each other and from LVH replicates (Fig. 5a). This discrepancy in transcriptome profiles was likely observed due to complex individual responses to TAC and treatment, as well as species-specific biological characteristics.

An UpSetR plot (Fig. 5b) was created to visualize overlapping DEGs between the most important experimental contrasts, including LV16-BMNC-Mφ vs. LV16-PBS, LV8-BMNC-Mφ vs. LV8-PBS, LV16-BMNC-Mφ vs. LVH, LV8-PBS vs. LV1, LV16-PBS vs. LV1, and LV1 vs. LVH (see Supplementary Fig. 1 for a complete list of contrasts). Each horizontal bar represents the total number of DEGs per contrast, and the vertical bars represent the size of the intersections of genes common to one or more contrasts. Although LV1 vs. LVH, LV8-PBS vs. LV1, and LV16-PBS vs. LV1 shared a common set of 2,280 DEGs, the following 902, 767, and 352 DEGs were unique to these same contrasts, respectively. A relatively small number of DEGs, i.e., 13 and 63, were unique to LV8-BMNC-Mφ vs. LV8-PBS and LV16-BMNC-Mφ vs. LVH, respectively. The number of genes common to multiple contrasts was much smaller, indicating that most transcriptional changes were contrast-specific rather than widespread across all conditions. Thus, most DEGs were unique to individual contrasts, highlighting the distinctive transcriptional responses associated with each experimental condition.

3.6. DEGs pattern analysis shows gene expression changes over time to TAC and BMNC-Mφ

Since we obtained a large number of DEGs from the RNA-seq data, we further investigated the expression dynamics and response patterns of LVs to PBS and BMNC-Mφ treatment according to the method described elsewhere [32]. We analyzed contrasts associated with LVH, LV1, LV8-BMNC-Mφ, and LV16-BMNC-Mφ states, where both temporal and therapeutic effects on gene expression dynamics were evaluated (Fig. 5c–f). 6,175 unique DEGs from the contrasts LV1 vs. LVH, LV8-BMNC-Mφ vs. LVH, LV16-BMNC-Mφ vs. LVH, LV8-BMNC-Mφ vs. LV1, LV16-BMNC-Mφ vs. LV1, and LV16-BMNC-Mφ vs. LV8-BMNC-Mφ formed 10 different groups (see Supplementary Table 2 for a complete list of unique DEGs in each group) according to their expression patterns (Supplementary Fig. 2). These 10 groups were further grouped into four subcategories: (1) Early rapid response (Fig. 5c, left panel), in which the expression behavior of most genes changed dramatically in response to TAC, indicating an immediate and significant effect of mechanical stress on the myocardium (groups 2, 3, 4, and 8 from Supplementary Fig. 2); (2) Rapid response (Fig. 5d, left panel), demonstrating continuous upregulation from 1 day post-TAC to 8 days post-TAC (groups 1 and 5 from Supplementary Fig. 2); (3) Gradual response (Fig. 5e, left panel) with two opposite gene dynamics (groups 7 and 10 from Supplementary Fig. 2); and (4) Early slow response (Fig. 5f, left panel) with a similar gene expression pattern up to 8 days post-TAC, but with a divergence at 16 days post-TAC (groups 6 and 9 from Supplementary Fig. 2).

We then performed Reactome pathway enrichment analysis [33] (based on DEGs with early rapid, rapid, and gradual responses) and Tissue expression enrichment analysis (based on DEGs involved in early rapid and early slow responses) to better understand the underlying biology. The results coincided with GSEA using GOBP gene sets (Fig. 6d–f). DEGs expressing an early transcriptional response after TAC were associated with pathways highlighting the coordinated activation of immune, inflammatory, and vascular signaling programs (Fig. 5c, right panel). Enrichment was mainly driven by pathways related to the innate immune system, including Neutrophil Degranulation, Chemokine Receptor Signaling, and GPCR-mediated Signal Transduction, indicating rapid engagement of immune effector mechanisms. Pathways related to cell surface interactions on the vascular wall and hemostasis were also significantly enriched, highlighting early interaction between immune activation and vascular remodeling. Meanwhile, analysis of DEGs showing a rapid expression response from day 1 to day 8 after TAC revealed enriched pathways responsible for the cell cycle and division, such as Sister Chromatid Separation, Mitotic Checkpoint, M phase, Cell Cycle, etc. (Fig. 5d, right panel). Further analysis of DEGs responding with a gradual expression pattern demonstrated a completely different scenario, in which pathways modulating extracellular matrix production and organization (Extracellular Matrix Organization, Collagen Formation, Elastic Fiber Formation, Extracellular Matrix Degradation, etc.) were enriched (Fig. 5e, right panel). Tissue expression enrichment analyses of DEGs involved in the early rapid response (Supplementary Fig. 2) and early slow response (Fig. 5f, right panel) also showed a discrepancy in tissue-specific expression: genes in the first expression pattern were predominantly expressed throughout the body, especially in components of the nervous system (Central Nervous System and Brain) and in blood cells (Macrophages, Bone Marrow-derived Macrophages, Leukocytes, and Hematopoietic cells), while genes with an early slow response pattern were mainly associated with the cardiovascular system and adipose tissue. In a literal sense, these four expression patterns may reflect an immediate immune response, in particular through the innate component (early rapid response), activation of cell cycle/proliferation machinery (rapid response), clearance of apoptotic cells and deposition/organization of extracellular matrix components (gradual response), and finally, attempts to restore oxidative metabolism in the damaged myocardium (early slow response).

Fig. 6 — **GSEA depicting differences between hearts treated with PBS and BMNC-Mφ**

GSEA using the GOBP sets on six experimental contrasts: (a) LV1 vs. LVH, (b) LV8-PBS vs. LV1, (c) LV16-PBS vs. LV1, (d) LV8-BMNC-Mφ vs. LV8-PBS, (e) LV16-BMNC-Mφ vs. LV16-PBS, and (f) LV16-BMNC-Mφ vs. LVH, representing the natural course of the disease (**a, b, c**), early (d) and late (e) treatment efficacy of BMNC-Mφ, and finally, the transcriptional proximity of hearts receiving 2 injections of BMNC-Mφ to the healthy state (f). All analyses were performed in R v4.5.1 using the edgeR (v4.6.3) and ClusterProfiler (v4.16.0) packages. DEGs were defined by a false discovery rate (FDR) < 0.05 and an absolute logarithmic change log₂ > 1. DEGs - differentially expressed genes; LV - left ventricle; LVH - healthy LV; LV1 - LV 1 day post-TAC; LV8-PBS - LV 8 days post-TAC treated with PBS; LV8-BMNC-Mφ - LV 8 days post-TAC treated with BMNC-Mφ; LV16-PBS - LV 16 days post-TAC treated with PBS; LV16-BMNC-Mφ - LV 16 days post-TAC treated with BMNC-Mφ; GOBP - Gene Ontology Biological Process; GSEA - Gene Set Enrichment Analysis.

3.7. GSEA shows a significant impact of BMNC-Mφ on the tissue transcriptome profile

GSEA using the MSigDB Gene Ontology Biological Process (GOBP) gene set on the LVH, LV1, LV8-PBS, LV8-BMNC-Mφ, LV16-PBS, and LV16-BMNC-Mφ transcriptome profiles showed that BMNC-Mφ were not only mechanically present in the damaged heart but also had a significant impact on the tissue transcriptome profile, attenuating the inflammatory response, controlling cell cycle/proliferation and fibrosis, and shifting myocardial metabolism toward oxidative phosphorylation. At first glance, in the PBS-treated groups, which represent the natural course of the disease, signs of acute inflammation, metabolic dysfunction, maladaptive remodeling, and fibrosis were most pronounced from early to late stages, indicating a chaotic response to PO. Meanwhile, BMNC-Mφ handled the situation well, as gene programs of controlled cell proliferation, mitochondrial restoration, balanced fibrosis, and immune regulation were among the 20 top GOPB pathways, emphasizing pro-regenerative remodeling. The contrast between LV1 and LVH (LV1 vs. LVH) represented an early response to TAC with strong enrichment of GOPB pathways responsible for leukocyte migration, chemotaxis, cytokine signaling, wound response, and Tnf production, indicating a massive sterile inflammation driven by innate immune cell recruitment and cytokine surge (Fig. 6a). On day 8 (LV8-PBS vs. LV1), the inflammatory milieu shifted toward ribosome activation/translation state (enrichment of Ribosome Biogenesis, rRNA Processing, and rRNA Metabolic Process, and cell cycle pathways), indicating likely increase in fibroblasts and/or immune cells, as well as protein synthesis, while inflammation persisted alongside growth programs (Fig. 6b). From days 1–16 (LV16-PBS vs. LV1), the immune response continued and remained active (increased Leukocyte Migration, Chemotaxis, Myeloid Leukocyte Activation), but with dominant aberrant cell proliferation (enhanced Chromosome Segregation, Nuclear Chromosome Segregation, etc.), creating a mixed and unfavorable environment for proliferative/fibrotic repair (Fig. 6c). In contrast, BMNC-Mφ injection could significantly alter the condition as early as 8 days after TAC (LV8-BMNC-Mφ vs. LV8-PBS). Although the comparison of LV8-BMNC-Mφ with LV8-PBS revealed clear signs of cell proliferation, it was organized in the form of a more rigorous cell cycle due to enriched Chromosome Organization (FDR = 6.2e−13), Regulation of Chromosome Segregation (FDR = 1.7e−09), Spindle Organization (FDR = 2.1e−09), Mitotic Spindle Checkpoint Signaling (FDR = 7.4e−08), Negative Regulation of Chromosome Organization (FDR = 8.2e−08), Mitotic Spindle Assembly Checkpoint Signaling (FDR = 2.1e−07), and Meiosis I Cell Cycle Process (FDR = 3.3e−07) (Fig. 6d). In addition, BMNC-Mφ stimulated the transition to highly efficient metabolic processes and differentiation states, as evidenced by up-regulated Cellular Respiration (FDR = 2.6e−10), Mitochondrial Respiratory Chain Complex Assembly (FDR = 3.1e−08), Oxidative Phosphorylation (FDR = 3.8e−08), Skeletal System Development (FDR = 2.2e−07), and Embryonic Skeletal System Morphogenesis (FDR = 3.1e−07) (Fig. 6d). Interestingly, immune pathways such as Leukocyte Migration, Cell Chemotaxis, Chemotaxis, Response to Molecule of Bacterial Origin, and Positive Regulation of Leukocyte Migration, which were noticeable in LV8-PBS vs. LV1 contrast, did not even make it into the top 20 GOBP pathways in LV8-BMNC-Mφ vs. LV8-PBS (Fig. 6b and d). The second BMNC-Mφ injection (LV16-BMNC-Mφ vs. LV16-PBS) further enhanced controlled cell proliferation and structural maturation - reflected by 15 of 20 top GOBP terms related to cell cycle regulation – while concurrently dampening the immune response (Fig. 6e) that persisted in PBS-treated hearts at day 16 post-TAC (Fig. 6c). The contrast between LV16-BMNC-Mφ and LVH reflecting the extent to which systemic delivery of BMNC-Mφ can restore the transcriptional profile of the damaged heart to the normal state, also provided incredible data showing that at that time, the hearts were transitioning to metabolic maturation and mitochondrial activation with no signs of inflammation (Fig. 6f). Overall, panels a–c (Fig. 6a–c) show the natural course of the disease after TAC: massive influx of innate immunity, translational/metabolic adaptation with ongoing leukocyte activity, progressive ECM deposition and fibrosis, while panels d–f (Fig. 6d–f), representing macrophage efficacy, highlighted macrophage-mediated rewiring: earlier attenuation of inflammatory chemotaxis, improvement in mitochondrial/metabolic parameters, stimulation of controlled proliferation/regeneration rather than inadequate fibrosis, ultimately leading to a more favorable resolution process in the myocardium compared to PBS-treated hearts.

4. Discussion

In this study, we confirmed the therapeutic efficacy of systemic administration of BMNC-Mφ in a mouse model of TAC. Several key findings were made in this study. First, a close functional similarity was found between the phenotypes of in vitro polarized and RCM. According to the recent review by Yang et al., cardiac macrophages present in a stable state and in diseases were classified into two groups: CCR2⁻ macrophages (further subdivided into TLF [Timd4, Lyve1, and Folr2] and MHC-II^high macrophages) originating from yolk sac, and CCR2⁺ macrophages (further subdivided into inflammatory, Trem2⁺, Isg⁺, Arg1⁺, and MHC-II^high macrophages), which are maintained by the recruitment of monocytes [8]. Interestingly, our in vitro polarized BMNC-Mφ also exhibited phenotypes similar to those CCR2⁻ and CCR2⁺ cardiac macrophage subgroups by upregulating the expression of Folr2, Spp1, Lgals3, Trem2, Fapb5, Arg1, and Gdf15. Moreover, other genes associated with anti-inflammatory phenotype, including Retnla, Igf1, Ch25h, and Mmp12/13 were also found among the top 100 DEGs in BMNC-Mφ (Fig. 1d), highlighting their potential to dampen pro-inflammatory cytokine production [34], promote cardiomyocyte survival and oxidative phosphorylation [6], stimulate efferocytosis and prevent foam cell formation [35], and degrade excess ECM [36,37]. Down-regulation of the genes encoding pro-inflammatory cytokines (Fig. 1c), especially oncostatin M (Osm), which was selectively expressed by inflammatory macrophages recruited to the only affected hearts and not detected in healthy human myocardium, further supported anti-inflammatory phenotype of BMNC-Mφ [2]. Although BMNC-Mφ did not fully match any of these subtypes of cardiac macrophages, they acquired many characteristics of self-renewing RCM [38]. This convergence between our in vitro polarized BMNC-Mφ and RCM can be explained by the remarkable plasticity of the macrophage lineage, in which signals from the environment and cytokines exert a significant influence on functional identity [39]. In the heart, recent studies using cutting-edge technology have identified several macrophage subpopulations characterized by anti-inflammatory, reparative, and pro-angiogenic gene expression programs, many of which were common to populations derived from embryonic cells and monocytes [38,40]. In vitro polarization of macrophages toward an anti-inflammatory phenotype using M-csf and Il-4 activates key signaling pathways such as PI3K/Akt/GSK-3β and JAK-STAT6-dependent transcriptional networks, respectively, which also contribute to anti-inflammatory behavior, growth factor production, and angiogenic support − characteristic functions of RCM [41]. Thus, despite differences in ontogeny, BMNC-Mφ can adopt a functional state that reflects the prevalent reparative phenotype necessary for cardiac tissue homeostasis. It is important to note that this convergence should be interpreted as a functional rather than ontological similarity, as BMNC-Mφ likely differ from RCM in epigenetic imprinting, long-term self-renewal capacity, etc. From a therapeutic perspective, the acquisition of these common functional properties may be sufficient to exert beneficial effects even in the absence of complete developmental identity.

GSEA of BMNC-Mφ indicated a transition from the proliferative, inflammatory, glycolytic state of BMNC to a terminally differentiated, lipid-processing, oxidative, secretory phenotype adapted to tissue homeostasis and stress resistance. This was due to the mTORC1-UPR-PPAR/LXR signaling pathway [9], enhanced OXPHOS and peroxisomal metabolism, and reduced inflammation caused by MYC-E2F-NFκB which is a characteristic feature of the metabolically and functionally maturated macrophages.

Second, systemic delivery of BMNC-Mφ led to functional (Fig. 3e–g) and structural improvements (Fig. 4b, f, 4j) which were fully consistent with those of a recent study in which inhibition of CCR2⁺ macrophage infiltration using the CCR2 antagonist RS-504393 in the early period after TAC (3–7 days) remarkably attenuated the adverse LV dilatation and systolic dysfunction observed 4 weeks post-TAC, with significantly lower LVIDs, LVIDd, end diastolic volume, cardiac interstitial fibrosis, and higher LVEF compared to the control group [7]. Our two-injection approach contrasts with the predominant use of single injections in virtually all preclinical and clinical trials of cell therapies, even though multiple injections have been shown to be more effective than single injections [42]. A recent study evaluating the role of RCM in response to hypertrophic stimuli revealed a significant increase in the number of cardiac macrophages 7 days after TAC, but not 4 weeks later with 12 clusters consisting solely of monocytes and macrophages [11]. Given that monocytes/macrophages were the most numerous immune cell population found within the myocardium in response to TAC in the early stages of the disease, we decided to administer BMNC-Mφ during the first two weeks after surgery. Unlike the aforementioned study, we did neither block the recruitment of peripheral monocytes to the damaged heart nor directly modify the recruited monocytes/macrophages toward a pro-repair phenotype, but BMNC-Mφ were able to successfully suppress leukocyte/monocyte migration and chemotaxis (Fig. 7a), modulate fibrosis by degrading excess ECM and altering the microenvironment (Fig. 7b), as well as promote cell cycle/proliferation control (Fig. 7c) and oxidative phosphorylation (Fig. 7d). But how can this be achieved? After TAC, the heart, especially the LV, undergoes sterile inflammation caused by mechanical stress, cell death, and DAMPs [4]. This, in turn, serves as chemoattractant, and monocytes/macrophages infiltrate and exacerbate inflammation, while RCM play a protective role. However, over time, the number of RCM vanishes, and therefore the influence of CCR2⁺ macrophages becomes more noticeable. In this context, given the pro-reparative features of BMNC-Mφ, therapeutically introduced BMNC-Mφ shifted the balance from pro-inflammatory (Tnf/Il-1β-rich) to pro-resolving/regenerative milieu (Il-10, Tgfb1, Vegfa, Igf1, and Relm-⍺ rich) [38], because macrophages can influence virtually all cells present in the myocardium (Fig. 7e). This reduced excessive leukocyte recruitment and cytokine storm, which otherwise exacerbated damage. Similarly, adverse cardiac remodeling, including LV hypertrophy and chamber dilation, was also attenuated by growth factors (Igf1, Ang2, Anxa2, Relm-⍺) highly up-regulated in BMNC-Mφ, which promote angiogenesis and adaptive remodeling. In particular, the tandem of Igf1 and Ang2 most likely led to an intense angiogenic process in the damaged myocardium. Despite contradictions regarding its role in angiogenesis, most studies to date show that Ang2 is relatively highly expressed in active areas of vascular remodeling and plays a key role in controlling endothelial remodeling and angiogenesis [43]. In contrast, Igf1, acting as an anabolic hormone, has a pleiotropic profile and controls the growth and metabolism of many cell types by means of either PI3K/AKT or RAS/MAPK pathways (Fig. 7f), and the cardiovascular system is no exception [44]. Exogenous treatment with Igf1 reduced scar size and improved cardiac function in the acute phase after myocardial infarction by altering the response of myeloid cells, stimulating an anti-inflammatory phenotype in bone marrow-derived macrophages [44]. Another recent study in which RCM-induced ablation or selective removal of Igf1 derived from RCM further emphasized the importance of endogenous or exogenous Igf1 in controlling adaptive growth of cardiomyocytes in response to hypertension [45].

Fig. 7 — **Key growth factors, cytokines, chemokines, and enzymes associated with macrophages and their signaling pathways and downstream effectors**

BMNC-Mφ injection prevented adverse cardiac remodeling by suppressing the inflammatory response (a), modulation of extracellular matrix/fibrosis production (b), controlling of cell cycle/proliferation (c), and stimulation of oxidative phosphorylation and fatty acid metabolism (d). Cross-cellular interactions between macrophages and cardiac as well as non-cardiac cells (e) [13,52,53]. The canonical Igf1 signaling pathway leading to metabolic restoration, new protein synthesis, angiogenesis, cell growth, and differentiation (f) [[54], [55], [56], [57]]. Direct and indirect effects of Arg1 on inflammatory response, cell proliferation, and collagen synthesis (g) [[58], [59], [60]]. Relm-⍺ also has multidirectional effects, including mitogenesis, angiogenesis, and immune modulation (h) [[61], [62], [63]]. Created in https://BioRender.com. *BTK - Bruton's tyrosine kinase; Relm-⍺ - resistin-like molecule alpha; Arg1 - arginase 1; Igf1 - insulin-like growth factor 1.*

Other potential mechanisms of adaptive cardiac remodeling in the experimental group after TAC were most likely associated with Arg1, Relm-⍺ (Retnla, Fizz1), and Gpnmb, which were enriched in BMNC-Mφ. Arg1 hydrolyzes arginine and stimulates anti-inflammatory metabolism in two ways: depletion of L-arginine indirectly leads to a decrease in iNos activity and directly leads to suppression of CD3ζ and therefore a decrease in TCR signals, while ornithine can be used in collagen synthesis and stimulate cell proliferation (Fig. 7g). Relm-⍺, another protein produced by anti-inflammatory macrophages, can also alter the situation through the BTK and PI3K/AKT/PLC pathways (Fig. 7h). Similarly, Gpnmb enhances cardiomyocyte contraction and reduces fibroblast activation [45]. Although there are fundamental differences in how they affect disease progression, the end results can be summarized as immunosuppression and tissue regeneration, which explains the pro-inflammatory chemotaxis/cytokine signature observed only in PBS-treated hearts (Fig. 6b and c).

BMNC-Mφ likely contributed to the removal of apoptotic cardiomyocytes and neutrophils, preventing secondary necrosis and inflammatory surge [46,47]. The anti-fibrotic effect of BMNC-Mφ was probably also based, at least in part, on a paracrine mechanism of secreted Mmp12/13, which remodels the ECM [36,37]. Without regulation, TAC-induced inflammation activates fibroblasts, causing excessive ECM production (collagens I, III), leading to diffuse myocardial fibrosis and thickening, which were observed in the PBS group (Fig. 4a and b). In addition, macrophage therapy has been shown to attenuate the differentiation of fibroblasts into myofibroblasts by altering the local cytokine environment (less IL-1β, more IL-10) [48,49]. Igf1 enriched in BMNC-Mφ also shifted energy production from glycolysis towards oxidative phosphorylation (Fig. 6d and e). Pro-inflammatory macrophages exacerbate metabolic stress by secreting cytokines that inhibit mitochondrial respiration (e.g., TNF-α suppresses oxidative phosphorylation, leading to mitochondrial dysfunction and ROS [reactive oxygen species] production). In contrast, anti-inflammatory macrophages stimulate angiogenesis, which restores oxygen delivery and further supports oxidative phosphorylation [6,50].

Third, tracking of fluorescence-labeled cells showed that systemically administered BMNC-Mφ were evenly distributed in virtually all organs of healthy, 8 days post-TAC, and 15 days post-TAC mice, with the exception of the healthy heart, where BMNC-Mφ were not detected (Fig. 4l). This means that BMNC-Mφ macrophages not only had an anti-inflammatory phenotype but were also sensitive to chemokines and/or DAMPs secreted by damaged myocardium. This was confirmed by the fact that hearts 8 days post-TAC attracted/retained more BMNC-Mφ (Fig. 4l) than hearts 15 days post-TAC (Fig. 4l), highlighting the correlation between the severity of inflammation and BMNC-Mφ chemotaxis: the more severe the inflammation, the more chemokines/DAMPs were released, and the more BMNC-Mφ were recruited. It is also worth noting that BMNC-Mφ were located near vascular pools, which means that they had a mechanism of cell adhesion and subsequent migration into the myocardium. Of course, these data were insufficient, and further research is needed to confirm these properties.

Last but not least, the transcriptional programs responsible for mitochondrial and metabolic recovery, which were enriched in the injected BMNC-Mφ (Fig. 2a), were preserved in the LVs that received BMNC-Mφ. For example, LV8-BMNC-Mφ vs. LV8-PBS, LV16-BMNC-Mφ vs. LV16-PBS, and LV16-BMNC-Mφ vs. LVH showed increased expression of GOBP terms related to fatty acid metabolism, oxidative phosphorylation, and mitochondrial repair (Fig. 6d–f). This means that BMNC-Mφ could successfully alter not only the intercellular environment but also change intracellular settings.

To summarize, the transcriptome of the introduced BMNC-Mφ was enriched with canonical pro-resolving markers (Arg1/Retnla/Gpnmb), trophic/metabolic mediators (Igf1, Ang2, Anxa2), extracellular matrix remodeling proteases (Mmp12/13, Adamtsl5), and lipid mediator enzymes (Pla2 family, Ch25h), the combination of which mechanistically explains the loss of GO terms for leukocyte migration/chemotaxis in LV8-BMNC-Mφ vs. LV8-PBS and LV16-BMNC-Mφ vs. LV16-PBS (Fig. 7a); reduced ECM/ossification signals in LVs treated with BMNC-Mφ vs. PBS-treated LVs (Fig. 7b); strictly regulated cell cycle/proliferation in BMNC-Mφ-treated samples (Fig. 7c); and the restoration of mitochondrial/oxidative phosphorylation gene programs in LV8-BMNC-Mφ and LV16-BMNC-Mφ hearts (Fig. 7d). This interpretation is consistent with the established roles of these factors in macrophage-mediated resolution, ECM remodeling, metabolic support, and controlled cell proliferation in the heart.

5. Conclusion

The complexity of the TAC-induced PO is embodied in the fact that TAC elevates LV afterload, thereby activating both local and systemic RAAS. Angiotensin II and aldosterone enhance vasoconstriction, sodium retention, and volume expansion, which further increase afterload and perpetuate RAAS activation, together forming a self-sustaining vicious cycle that leads to maladaptive cardiac remodeling in the form of interstitial fibrosis, as well as systolic and diastolic dysfunction, which gradually progress to HF [1,4,6]. In response, RCM subgroups attempt to inhibit myocardial fibrosis and uncontrolled cardiomyocyte hypertrophy in the early period after TAC. However, since mechanical stress and self-sustaining inflammation are inevitable, at later stages, the entire RCM population or part of it undergoes transcriptional and functional changes, and some of them are replaced by blood macrophages to maintain the balance between inflammation and fibrosis. In this context, our in vitro polarized BMNC-Mφ have shown promising results in preserving LV function and architecture. Indeed, further research is needed to better understand the underlying mechanisms and move toward clinical applications.

6. Study limitations

This study has several limitations. Most of our investigations were conducted in the early stages of TAC, specifically, cell injections, RNA sequencing, and histological analysis (cell-tracking), rather than in the later stages, as time-course studies showed that the number of macrophages increased 3 days post-TAC, reaching a peak at 1 week, and returned to baseline after 2 weeks [51]. In addition, to minimize redundancy, GSEA analysis was performed using only Gene Ontology gene sets (GOBP, GOCC, and GOMF) and only plots of chosen contrasts were included in the manuscript.

Author contributions

UY performed surgeries, conducted the experiments, analyzed the results, and wrote the initial draft of the manuscript. UY, KY, IA, and SM conceptualized the study design. KY, TK, IA, and SM supervised the study. KY, TK, KM, TT, SS, IA, and SM critically revised the manuscript. KM supervised the flow cytometry analysis. All the authors read and approved the final manuscript for submission. The authors declare that all coauthors fulfilling the authorship criteria are listed in the appropriate order and that none are omitted.

Code availability statement

All codes used to generate the figures and results are available in the GitHub.

Funding

This research was supported by Japan Agency for Medical Research and Development (AMED) under Grant Number JP23ym012809 and World Premier International Research Center Initiative (WPI), Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan.

Declaration of competing interest

None.

8. Acknowledgments

The authors express their sincere gratitude to Mr. Akima Harada and Ms. Lisa Fujimura for their valuable technical assistance, as well as to the Next Generation Sequencing core facility at the Research Institute for Microbial Diseases of The University of Osaka, for RNA sequencing. In addition, UY acknowledges the “El-Yurt Umidi” Foundation for the Training of Prospective Personnel under the President of the Republic of Uzbekistan, for providing financial support in pursuing postgraduate education in Japan.

Footnotes

Peer review under responsibility of the Japanese Society for Regenerative Medicine.

^{Appendix A}

Supplementary data to this article can be found online at https://doi.org/10.1016/j.reth.2026.101061.

Appendix A. Supplementary data

The following are the Supplementary data to this article.

Supplementary Table 1

Metadata of biological replicates used for in vitro and in vivo RNA-sequencing

mmc1.xlsx^{(11.3KB, xlsx)}

Supplementary Table 2

Unique differentially expressed genes in each group based on gene expression pattern analysis

mmc2.xlsx^{(404.3KB, xlsx)}

Supplementary Fig. 1 — **Schematic representation of 15 contrasts between six conditions**

RNA sequencing was performed on LV tissues from healthy subjects (LVH), 1 day post-TAC (LV1), 8 days post-TAC treated with PBS (LV8-PBS), 8 days post-TAC treated with BMNC-Mφ (LV8-BMNC-Mφ), 16 days post-TAC treated with PBS (LV16-PBS), and 16 days post-TAC treated with BMNC-Mφ (LV16-BMNC-Mφ). From these six conditions (three biological replicates in each, eighteen in total), 15 contrasts were created for subsequent analysis.

Supplementary Fig. 2 — **Gene expression patterns in healthy hearts, hearts 1 day post-TAC, 8 days post-TAC treated with BMNC-Mφ, and 16 days post-TAC treated with BMNC-Mφ**

Analysis of gene expression patterns using the DEGreport (v1.46.0) R package revealed 10 different gene expression dynamics among six contrasts (LV1 vs. LVH, LV8-BMNC-Mφ vs. LVH, LV16-BMNC-Mφ vs. LVH, LV8-BMNC-Mφ vs. LV1, LV16-BMNC-Mφ vs. LV1, LV16-BMNC-Mφ vs. LV8-BMNC-Mφ) with total 6175 unique DEGs. The y-axis represents the Z-score of gene abundance, and the x-axis represents days. Red dots and lines indicate the healthy state (without surgery), and blue dots and lines indicate the state after transverse aortic constriction surgery.

Supplementary Fig. 3 — **Tissue expression enrichment analysis of DEGs demonstrating an early rapid response expression pattern following TAC**

Analysis of tissue expression enrichment showed that genes with early rapid expression response after TAC were predominantly expressed throughout the body, especially, in components of the nervous system (*Central Nervous System* and *Brain*) and in blood cells (*Macrophages, Bone Marrow-derived Macrophages, Leukocytes*, and *Hematopoietic Cells*).

Data availability

The raw RNA-seq dataset obtained in this study has been deposited in NCBI Bioproject under the numbers PRJNA1260244 (in vitro) and PRJNA1337419 (in vivo) and is available without any restrictions. The raw data used to construct the plots are provided as supplementary information.

References

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Table 1

Metadata of biological replicates used for in vitro and in vivo RNA-sequencing

mmc1.xlsx^{(11.3KB, xlsx)}

Supplementary Table 2

Unique differentially expressed genes in each group based on gene expression pattern analysis

mmc2.xlsx^{(404.3KB, xlsx)}

Data Availability Statement

[bib1] 1.Richards D.A., Aronovitz M.J., Calamaras T.D., Tam K., Martin G.L., Liu P., et al. Distinct phenotypes induced by three degrees of transverse aortic constriction in mice. Sci Rep. 2019;9 doi: 10.1038/s41598-019-42209-7. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib2] 2.Martini E., Kunderfranco P., Peano C., Carullo P., Cremonesi M., Schorn T., et al. Single-cell sequencing of mouse heart immune infiltrate in pressure overload-driven heart failure reveals extent of immune activation. Circulation. 2019;140 doi: 10.1161/CIRCULATIONAHA.119.041694. [DOI] [PubMed] [Google Scholar]

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PERMALINK

In vitro polarized macrophages ameliorate adverse cardiac remodeling in a mouse model of transverse aortic constriction

Ulugbek Yakhshimurodov

Kizuku Yamashita

Takuji Kawamura

Kenji Miki

Takura Taguchi

Shunsuke Saito

Imad Abugessaisa

Shigeru Miyagawa

Abstract

Introduction

Methods

Results

Conclusion

Graphical abstract

Highlights of the study

List of abbreviations

1. Introduction

2. Materials and methods

Ethical approval

2.1. BMNC-Mφ polarization

Fig. 1.

2.2. Transcriptomic profiling of BMNC-Mφ

2.3. Flow cytometry

2.4. Quantitative real time polymerase chain reaction (RT-qPCR) of BMNC-Mφ

2.5. Establishment of mouse transverse aortic constriction (TAC) model

2.6. Transthoracic echocardiography (TTE)

2.7. BMNC-Mφ administration

2.8. Cell tracking analysis of BMNC-Mφ

2.9. Histopathological and immunohistochemical assessment

2.10. Transcriptomic profiling of healthy, 1 day post-TAC, and BMNC-Mφ- or PBS-treated left ventricles

2.11. Analysis of the dynamic patterns of the differentially expressed genes

2.12. Statistical analysis

3. Results

3.1. In vitro polarized BMNC-Mφ demonstrated an anti-inflammatory phenotype

Fig. 2.

3.2. BMNC-Mφ exhibited macrophage surface markers

3.3. BMNC-Mφ injection preserved LV systolic function and morphology

Fig. 3.

3.4. BMNC-Mφ were detected only in damaged hearts and reduced fibrosis area

Fig. 4.

3.5. Differential expression analysis of RNA-seq reveal large set of differentially expressed genes

Fig. 5.

3.6. DEGs pattern analysis shows gene expression changes over time to TAC and BMNC-Mφ

Fig. 6.

3.7. GSEA shows a significant impact of BMNC-Mφ on the tissue transcriptome profile

4. Discussion

Fig. 7.

5. Conclusion

6. Study limitations

Author contributions

Code availability statement

Funding

Declaration of competing interest

8. Acknowledgments

Footnotes

Appendix A. Supplementary data

Supplementary Fig. 1.

Supplementary Fig. 2.

Supplementary Fig. 3.

Data availability

References

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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