Search Results (9,573)

Biological cardiovascular vulnerability is defined as an imaging-derived construct integrating myocardial functional impairment, coronary microvascular dysfunction, and modeled hemodynamic burden, including global longitudinal strain, coronary flow reserve, and derived vascular indices. To evaluate whether advanced echocardiographic and coronary Doppler imaging parameters identify biological cardiovascular vulnerability associated with the severity and complications of infective endocarditis beyond conventional structural findings. In this retrospective single-center cohort study, we analyzed consecutive patients with definite infective endocarditis who underwent advanced echocardiographic and coronary Doppler imaging. Comprehensive transthoracic and transesophageal echocardiography assessed vegetation characteristics, left ventricular function, global longitudinal strain (GLS), diastolic indices, right ventricular function, and pulmonary artery systolic pressure. Coronary microvascular function was evaluated noninvasively using transthoracic Doppler-derived coronary flow reserve (CFR) of the left anterior descending artery. Associations with disease severity and perivalvular complications were evaluated using multivariable regression analysis. Reduced coronary flow reserve was independently associated with the composite severe infective endocarditis phenotype, as defined by perivalvular complications, severe valvular dysfunction, or endocarditis team-guided urgent surgical indication. Coronary flow reserve correlated inversely with vegetation size (r = −0.39; p = 0.002) and regurgitation severity (r = −0.36; p = 0.004). Notably, the inverse association between coronary flow reserve and vegetation size showed substantial interindividual variability, particularly among patients with similar vegetation dimensions, suggesting heterogeneity in microvascular vulnerability beyond structural lesion burden. Despite relatively preserved mean arterial pressure across age groups, advanced imaging revealed progressive increases in systemic vascular resistance, declining wall shear stress, impaired microvascular flow, and reduced myocardial reserve. Imaging-derived cardiovascular vulnerability profiles frequently diverged from chronological age, highlighting heterogeneity in cardiovascular reserve despite apparently stable conventional hemodynamic parameters. Advanced echocardiographic and coronary Doppler imaging characterize a spectrum of biological cardiovascular vulnerability that is associated with clinically adjudicated severity in infective endocarditis, rather than serving as independent prognostic predictors. Full article

During elections, information manipulation on social media has accelerated the use of artificial intelligence, yet the evidence is difficult to interpret without an integrated view of methods, data, and evaluation. We mapped 557 English-language journal articles from Scopus and Web of Science, combining performance indicators, science mapping, and a focused full-text synthesis of highly cited papers. The literature grows sharply after 2019, peaks in 2025, and shows geographically uneven production, with collaboration structured around a small set of hubs. The thematic structure suggests that, during the pandemic era, infodemic-related research served as a catalyst, intensifying scientific attention to fake news and disinformation and expanding the associated detection and monitoring agendas. In addition, socio-political harm constructs such as hate speech, extremism, and polarization appear as recurrent and structurally central targets, highlighting that election-relevant work often extends beyond veracity assessment toward monitoring discourse risks. Blockchain also emerges as a novel and adjacent integrity theme, aligned with authenticity and provenance-oriented mitigation rather than mainstream detection pipelines. AI for electoral disinformation is not reducible to veracity classification, as influential studies also target automation and coordinated behavior, verification support, diffusion analysis, and estimation frameworks that focus on exposure and impact. Evaluation remains heterogeneous and is often shaped by benchmark settings, making high accuracy values hard to compare and potentially misleading when labeling quality, topic leakage, or context shift are not characterized. Overall, the findings motivate evaluation protocols that align operational objectives with modeling roles and explicitly address robustness to temporal and platform changes, asymmetric error costs during election windows, and representativeness across electoral contexts and languages, while also guiding future work on emerging integrity challenges and governance-relevant deployment settings. Full article

Density functional theory (DFT) was used to investigate how bisubstitution doping in graphene alters its electronic structure and interfacial stability with two model lignocellulosic binders, carboxymethylcellulose (CMC), and a representative aromatic fragment (LCmA). The properties were evaluated at the ωB97X-D/LANL2DZ level for pristine graphene and its bisubstitution-doped variants with nitrogen (graphene-2N) and sulfur (graphene-2S), integrating frontier orbitals, electrostatic potential (ESP) maps, electronic localization functions (ELF/LOL), and QTAIM topology. Doping with 2N markedly reduces the HOMO–LUMO gap from 0.16052 eV (graphene) to 0.10560 eV (−34.2%), while 2S reduces it to 0.14222 eV (−11.4%), evidencing different electronic activation mechanisms. The interaction energies show doping-controlled selectivity: In pristine graphene, adsorption strongly favors LCmA ($\mathsf{\Delta }{E}_{int}$ = −99.3 kcal·mol⁻¹) over CMC (−23.7 kcal·mol⁻¹); in graphene-2N, CMC coupling intensifies (−93.7 kcal·mol⁻¹) while maintaining a high interaction with LCmA (−74.3 kcal·mol⁻¹); and in graphene-2S, CMC remains favorable (−71.9 kcal·mol⁻¹) while LCmA falls to a practically marginal regime (−4.1 kcal·mol⁻¹). QTAIM the presence of confirms closed-layer interactions in all complexes (∇²Pc > 0, H > 0, |V|/G < 1), with |V|/G close to unity for graphene–LCmA (0.994) and less compaction when doped with 2N (0.760 for 2N–LCmA). The bisubstitution modulates the electronic heterogeneity of the basal plane and redefines the binder–surface compatibility, favoring the multipoint anchoring of polar ligands in 2N and penalizing efficient aromatic stacking in 2S. Full article

Objective: This study examined the frequency of entosis in solid tumors of various origins (colorectal cancer, breast cancer, and lung cancer) and its association with clinical and pathological characteristics. It also examined survival and copy number alterations (CNAs) in genes associated with stem cells. The aim was to assess the potential prognostic value of entotic events in tumors. Methods: A total of 238 patients were included: 96 with colorectal cancer (CRC), 45 with lung cancer (LC), and 97 with breast cancer (BC). Entotic cell-in-cell (CIC) structures were evaluated on hematoxylin–eosin–stained slides using Mackay’s criteria. A CIC frequency >0.1 per 20 high-power fields was considered positive. Clinicopathological parameters, overall survival (CRC), metastasis-free survival (LC and BC), and CNA profiles of stemness-related genes were analyzed. Amplifications of MAP1LC3A and other chromosomal loci were assessed. Results: CRC demonstrated the highest entosis rate, more than two-fold higher compared with BC and LC (p < 0.05). Entosis correlated with high tumor grade (G3) in CRC (p = 0.03). In LC, CIC-positive tumors were more frequent in patients with lymph-node metastases (p = 0.02), whereas in BC, the opposite trend was observed (p = 0.02). It was noted that in patients with stage III–IV LC, the frequency of entosis was significantly higher than in patients with stage I–II cancer (p = 0.03). CIC-positive status was associated with poorer overall survival in CRC (p = 0.03) and reduced metastasis-free survival in LC (p = 0.011). In breast cancer, no statistically significant survival differences were observed. Tumors harboring two or more stemness-gene amplifications showed significantly higher entosis frequency regardless of tumor site. A strong association was identified between entosis and MAP1LC3A amplification. Conclusions: Enosis is not a random morphological phenomenon but a process associated with unfavorable tumor characteristics, high malignancy, reduced survival, and amplification of stem cell-related genes. The results of this study confirm the working hypothesis that entosis may contribute to the emergence of aneuploid clones of tumor cells, including those containing amplifications of stem cell-associated genes. This positions entosis as a potential factor in tumor genetic heterogeneity, which is particularly important in the context of therapeutic selection pressure. The observed association between high entosis frequency and the presence of ≥2 stem cell gene amplifications, as well as its association with poor prognosis in colorectal and lung cancer, highlights its potential value as a prognostic indicator. Furthermore, MAP1LC3A amplification data may serve as a molecular marker of entotic activity and a potential therapeutic target. Full article

Green finance has emerged as a crucial instrument for driving the macroeconomic transition toward a low-carbon economy, yet its specific transmission mechanisms warrant deeper empirical scrutiny. Leveraging China’s Green Finance Reform and Innovation Pilot Zones as a quasi-natural experiment, this scientific study employs a staggered difference-in-differences (DID) framework using provincial panel data from 2009 to 2023. To overcome the limitations of unidimensional metrics, we developed a comprehensive Industrial Structure Upgrading Index (ISUI) that integrates structural rationalization, advancement, and greening. The empirical findings reveal that the green finance pilot policy exerts a significant and positive impact on the ISUI. This core result remains robust under a series of rigorous checks, including the Callaway and Sant’Anna (CS-DID) estimator. Mechanism analyses demonstrate a dual “push–pull” dynamic: Green Credit Intensity (GCI) acts as the primary mediating channel by directing targeted financial resources (financial pull), while stringent environmental regulation positively moderates this effect (administrative push). Furthermore, the moderating role of digital finance is statistically non-significant, underscoring the policy’s broad inclusiveness and its independence from regional digital infrastructure. Heterogeneity estimations identify a clear structural catch-up effect, with more pronounced benefits observed in resource-dependent regions and areas with historically lower innovation capacities. Ultimately, these findings indicate that coordinating targeted financial incentives with environmental oversight can effectively drive multidimensional industrial upgrading, providing valuable evidence for sustainable transition strategies. Full article

This paper presents a taxonomy-based survey of AI-driven network optimization mechanisms relevant to the transition from fifth generation (5G) to sixth generation (6G) mobile communication systems. In contrast to earlier generational shifts that are often described as technology replacement cycles, the 5G-to-6G evolution is increasingly characterized in the literature as a prolonged period of coexistence, hybrid operation, and progressive integration of new capabilities across radio, edge, core, and service layers. To structure this transition, the paper organizes prior work into a transition-oriented taxonomy covering migration strategies, AI-enabled closed-loop control, RAN disaggregation and edge intelligence, core virtualization and slice orchestration, spectrum-aware coexistence, service-driven requirements, and security-aware governance. Rather than introducing a new optimization algorithm or an experimentally validated architecture, the contribution of this survey is analytical and integrative. Specifically, it consolidates fragmented research directions into a reference view of how AI-driven control mechanisms are distributed across spectrum, RAN, edge, and core domains during hybrid 5G–6G operation. In addition, the paper includes a structured evidence synthesis of performance trends, deployment maturity signals, and recurring methodological limitations reported across the literature. The review indicates that meeting anticipated 6G objectives, including ultra-low latency, high reliability, scalability, and improved energy efficiency, depends less on isolated enhancements at individual protocol layers and more on coordinated cross-layer optimization supported by AI-native control loops. At the same time, the surveyed literature reveals persistent gaps in service-to-control mapping, security-aware orchestration, interoperability across heterogeneous domains, and reproducible evaluation methodologies for hybrid 5G–6G environments. The survey is intended to provide researchers, network operators, and standardization stakeholders with a structured analytical basis for assessing how AI-driven optimization can support the staged evolution from 5G systems toward 6G-ready infrastructures. Full article

This paper examines the connection between Environmental, Social, and Governance (ESG) factors and the risk of geopolitics, as defined by the Geopolitical Risk (GPR) index. The concept of geopolitical risk is conventionally defined as the direct result of political incidents, war, and international tensions. The current study argues that the concept should be understood in a more structural and sustainable manner, relating to the underlying forces driving geopolitical risk. The main research question is whether and how the three pillars of ESG factors contribute to explaining and understanding cross-country and over-time variations in geopolitical risk. In an effort to avoid information loss associated with the ESG index’s aggregate nature, the three factors are considered separately and the three pillars are analyzed individually. The empirical context is a balanced cross-country panel dataset including 42 countries over the 2000–2023 time period. Data for the three factors are obtained from the World Bank dataset to standardize and compare data across countries and over time. The GPR index measures the level of geopolitical risk and is defined by Dario Caldara and Matteo Iacoviello. The GPR index captures the level of geopolitical tensions by analyzing media signals. The combination of the three sources enables direct connections and correlations among the three factors and the internationally recognized GPR index. The paper uses an integrated methodological approach that combines results from three distinct methods. The first method uses panel data analysis to estimate average marginal effects while controlling for unobserved heterogeneity. The second method uses clustering to identify structural patterns and divide countries into groups based on their unique characteristics and risk profiles. The third method uses machine learning regressions and nonparametric analysis to capture the complex relationships and interactions in the data. The three-step method is used for each pillar to ensure consistency and comparability. The results suggest that the three factors contribute to the GPR index in a unique manner. The environment and energy structure contribute to the GPR index as a risk multiplier; the social factor relates to exposure to instability; and the governance factor is a central stabilizing factor. The paper makes a unique contribution to the literature by defining the three factors and their relationship to the GPR index in a clear, sustainable manner. Full article

Large insurance claims handling is a complex, knowledge-intensive process that requires the analysis of heterogeneous information sources and the reuse of past experience distributed across multiple organizational data sources. Consequently, a significant portion of decision-making knowledge is embedded in historical claims records and internal documents, making systematic access and reuse challenging. This paper presents Enterprise Knowledge Assistant (EKA), a collaborative multi-agent AI system designed to act as a sparring partner for large claims handlers. EKA integrates claims structured and unstructured data with an archive of more than five thousand historical cases related to claims management, enabling retrieval, interpretation, and synthesis of relevant past cases and decision patterns. The system is organized as a set of specialized AI agents, each responsible for distinct tasks including claim context analysis, knowledge extraction, document synthesis, and interaction with human users. Through agent collaboration, EKA provides decision support by analyzing comparable historical cases, uncovering hidden correlations, and extracting insurance wisdom, while keeping the human expert firmly in control. The paper describes the system architecture and reports an industrial case study evaluating EKA in a real insurance environment. Results indicate improved knowledge reuse and reduced analysis effort in large claims handling. Full article

Background/Objectives: The fundamental classification based on white, brown, pink, and beige adipose tissue morphology together with fat vacuole content released into the tumor microenvironment incompletely defines breast cancer-associated adipose tissue (BCAAT) heterogeneity and does not sufficiently explain its controversial impact on invasion, recurrence, or survival in breast cancer (BC). We aim to expand BCAAT characterization by systematically evaluating stromal cellular elements within peritumoral adipose tissue, including CD34-positive fibroblasts, smooth muscle actin (SMA)-positive myofibroblasts, inflammatory cells, and microvascular structures to define distinct BCAAT subgroups. Methods: CD34 and smooth muscle actin (SMA) double immunohistochemistry was performed on 109 BC tissue specimens from patients aged 35 to 79 years old, followed by microscopic evaluation of cellular and vascular components inside peritumor adipose tissue. Microscopic findings were then correlated to age, body mass index (BMI), lymphovascular (LVI) and perineural invasion (PnI), recurrence (R), and tertiary lymphoid structures (TLSs). Results: Four BCAAT subtypes have been identified as fibroblast-rich (F^Rich_BCAAT), myofibroblast-rich (MyoF^Rich_BCAAT), vascular-rich (V^Rich_BCAAT), and mixed-vascular and inflammatory-rich (VI^Rich_BCAAT). The F^Rich_BCAAT subtype predominates for the age subgroup 35 to 49 years old and is a significantly worse prognostic factor for survival (p = 0.022). For the age subgroup of 50 to 69 years old, the VI^Rich_BCAAT subtype significantly influences PnI (p = 0.05) but not survival (Log-rank test, z = 0.57, p = 0.57). V^Rich_BCAAT was significantly impactful for BC patient survival aged 70 to 75 years old (p = 0.043). BMI did not correlate with any of the BCAAT subtypes but was strongly correlated with prognostic markers for each BCAAT subtype. Conclusions: Based on immunohistochemically detected cellular and vascular components, four microscopic BCAAT subtypes were identified. Three of four BCCAT subtypes specifically affect BC patient prognosis and survival depending on age. Full article

This work presents INTELLECTUM as a reference architecture and design-time evaluation framework for multi-entity XR–AI–digital twin systems. Rather than optimizing a specific implementation, the paper formalizes architectural invariants, event semantics, and coordination mechanisms that precede and inform system realization. INTELLECTUM provides a conceptual framework for structuring interactions across physical and virtual environments, emphasizing human-centered design, immersive digital twins, and collaborative extended-reality workspaces. The technical specification defines core architectural components, human integration modalities via WebXR and heterogeneous sensor networks, and representative usage scenarios within smart city ecosystems. By enabling AI-assisted urban planning, interactive simulation, and multi-actor coordination, INTELLECTUM positions itself as an XR-based architectural foundation for next-generation smart city platforms. Full article

Lossless image compression is pivotal for deep-space exploration. Considering the requirements of deep-space exploration for a high compression ratio and real-time processing, traditional image compression algorithms have garnered significant attention. However, existing algorithms struggle with real-time processing speed and compression degradation in high-noise regions, failing to meet the throughput demands of next-generation sensors. To address these challenges, this paper proposes a high-throughput and noise-resilient lossless image compression architecture, named HT-NRC, for deep-space CMOS cameras. First, to overcome the throughput bottleneck, we introduce a parallel processing method, which is built on index-based dispatch and Reorder mechanism. This is achieved by dynamically distributing pixel streams into parallel cores and utilizing a Reorder Buffer for sequence restoration. Second, to mitigate low compression efficiency in noisy backgrounds, we present a Heterogeneous Dual-Path Coding scheme. This system adaptively separates structural information for predictive coding and stochastic noise for raw packing with Bit-Plane Slicing (BPS) strategy. The proposed architecture was implemented on a Xilinx Virtex-7 FPGA (Xilinx, Inc., San Jose, CA, USA). Operating at 100 MHz, the system achieves a processing throughput of 414.7 Mpixel/s and a high average compression ratio under deep-space image datasets, while consuming an estimated total on-chip power of only 2.1 W. Experimental results show that our proposed method substantially outperforms existing baseline methods. Specifically, compared to the optimized serial JPEG-LS implementation processing one pixel per clock cycle, our parallel architecture achieves an approximately 314.7% increase in processing throughput. Full article

The loss of estrogen following menopause is associated with a marked increase in cardiometabolic risk, accompanied by adverse changes in lipid metabolism, insulin sensitivity, vascular function, and systemic inflammatory tone. Emerging evidence suggests that estrogen signaling interacts with chromatin regulatory mechanisms, including DNA methylation, histone modifications, and chromatin remodeling, across multiple metabolic tissues. In this review, we examine current evidence linking estrogen receptor signaling to epigenetic modulation in cardiovascular, hepatic, adipose, vascular, and immune systems. We propose that epigenetic remodeling represents a plausible and testable mechanistic framework connecting estrogen depletion to cardiometabolic disease progression, while acknowledging that much of the mechanistic evidence derives from preclinical and in vitro systems and that direct longitudinal validation in human cardiovascular tissues remains limited. We further explore how this framework may contribute to understanding the “estrogen paradox” and the heterogeneous outcomes of hormone replacement therapy (HRT), particularly within the context of the timing hypothesis. Finally, we evaluate pharmacologic and lifestyle interventions, including structured exercise, dietary modulation, and cardiometabolic therapeutics, through the lens of potential epigenetic influence. Clarifying tissue-specific and immune-integrated chromatin responses to estrogen loss will be essential for advancing precision strategies aimed at improving cardiometabolic health in postmenopausal women. Full article

Background: Frontal lobe involvement represents an important but heterogeneously expressed feature across neurodegenerative and vascular cognitive disorders. While frontal atrophy has been described in Alzheimer’s disease (AD), detailed volumetric assessment of frontal subregions across Alzheimer’s disease, amnestic mild cognitive impairment (aMCI), and vascular dementia (VaD) remains insufficiently characterized. The aim of this study was to evaluate frontal lobe and frontal subregional volumetric alterations across these diagnostic groups using automated MRI-based volumetry. Methods: This cross-sectional study included 120 participants divided into four groups: AD, VaD, aMCI, and cognitively healthy controls (n = 30 per group). All participants underwent standardized neuropsychological assessment and 3T brain MRI. Automated volumetric analysis of the frontal lobe and its subregions was performed using the Vol2Brain pipeline. Group differences in total intracranial volume–adjusted frontal volumes were assessed using analysis of covariance, controlling for age and sex, followed by Bonferroni-corrected post hoc comparisons. False discovery rate (FDR) correction was applied across subregional comparisons. Results: A significant main effect of diagnostic group was observed for total frontal lobe volume, with lower adjusted volumes in patients with AD compared with aMCI and cognitively healthy controls. After correction for multiple comparisons, only total frontal lobe volume remained statistically significant. At the nominal level, group differences were observed in several frontal subregions, predominantly involving prefrontal and orbitofrontal areas. However, these findings did not survive FDR correction and should be interpreted as exploratory. No consistent frontal volumetric pattern was observed in VaD. Receiver operating characteristic analysis demonstrated moderate discriminatory ability of total frontal lobe volume for distinguishing AD from cognitively healthy controls. Conclusions: Automated MRI-based volumetry revealed global frontal lobe reduction in Alzheimer’s disease, whereas subregional findings were exploratory after correction for multiple testing. Frontal volumetric measures did not demonstrate a characteristic pattern in VaD. Global frontal volume may provide complementary structural information within clinically define cognitive disorders. Full article

Background: Persistent endodontic infections remain a significant challenge in root canal therapy, primarily due to the complexity of root canal anatomy and the formation of resistant microbial biofilms. Conventional irrigants, including sodium hypochlorite and chlorhexidine, show limited penetration into dentinal tubules and reduced efficacy against mature biofilms, contributing to treatment failure. Electrically charged lipid nanoparticles (ECLNs), such as cationic solid lipid nanoparticles, nanostructured lipid carriers, and liposomes, have emerged as potential adjunctive systems to enhance intracanal antimicrobial delivery. This focused narrative review, informed by a structured literature search, aimed to synthesize and critically evaluate preclinical and exploratory clinical evidence regarding the use of electrically charged lipid nanoparticles for antibiotic delivery and biofilm control in root canal disinfection. Methods: A structured literature search of PubMed, Scopus, and Web of Science (2010–2026) identified 312 records, of which 20 studies met the inclusion criteria and were included in qualitative synthesis. The majority of included studies were in vitro investigations, followed by ex vivo studies using extracted human teeth, with only a limited number of exploratory animal or clinical studies. Overall, the level of evidence was predominantly preclinical. Results: Across studies, ECLNs demonstrated enhanced antimicrobial efficacy compared with free antibiotics or non-charged formulations, with improved biofilm interaction, enhanced penetration into dentinal tubules, and sustained antimicrobial release. However, most investigations relied on mono-species Enterococcus faecalis biofilm models, and substantial heterogeneity in nanoparticle formulation and methodology was observed. Clinical evidence remains scarce. Conclusions: Although these findings about ECLNs suggest a promising experimental adjunct for root canal disinfection, current evidence remains largely preclinical and insufficient to support routine clinical application. Standardized formulations, clinically relevant multispecies biofilm models, and well-designed controlled clinical trials are required to establish safety, efficacy, and translational feasibility. Full article

The mammalian heart rapidly loses regenerative capacity after birth and responds to myocardial infarction (MI) with scar formation and development of interstitial fibrosis. Cardiac fibroblasts orchestrate extracellular matrix (ECM) remodeling and cell–cell communication during development and injury; however, how fibroblast heterogeneity and fibroblast communication networks differ between regenerative neonatal and non-regenerative adult hearts remains incompletely defined. We performed scRNA-seq analysis on metabolically active CD45⁻/CD31⁻ nonmyocyte cells from the left ventricles of normal neonatal (P3) and adult (P84) mice to probe heterogeneity in a cardiac fibroblast-enriched population. We identified five transcriptionally distinct cardiac fibroblast subclusters (CF0-CF4) demonstrating different distributions across ages, including an adult-enriched immune/complement-associated program (CF0); an ECM structural-associated program present across ages (CF1); and neonatal-enriched contractile/ECM-remodeling (CF2), Wnt-modulating matrix-regulatory (CF3), and proliferative (CF4) programs. Matrisome category scoring revealed age-dependent divergence in ECM programs: neonatal fibroblasts showed higher enrichment of core matrisome components (particularly collagens and proteoglycans), whereas adult fibroblasts were relatively enriched for matrisome-associated categories, including ECM regulators and secreted factors. Ligand–receptor inference using CellChat demonstrated a broad reduction in fibroblast–fibroblast interaction strength and information flow in adult networks, and adult-enriched signaling was dominated by immune/chemotactic pathways. Finally, projection of subcluster marker programs onto an independent bulk RNA-seq dataset of cardiac fibroblasts 3 days after MI revealed that adult injury partially recapitulates neonatal-associated programs, including activation of the contractile/ECM-remodeling program (CF2) and robust induction of a cell-cycle-associated program (CF4), but lacks an additional neonatal-specific injury program associated with the Wnt-modulating subset (CF3), which was weakly induced or absent in adults. This cardiac fibroblast-enriched single-cell study defines age-dependent fibroblast states, ECM specialization, and communication network architecture that distinguish regenerative neonatal from non-regenerative adult hearts. It also provides a framework to interpret divergent stromal responses after MI and to prioritize fibroblast programs for regenerative and anti-fibrotic strategies. Full article