Search Results (635)

Chronic heart failure [CHF] is a progressive clinical syndrome characterized by structural and functional impairment of the myocardium, in which energy metabolic remodeling plays a central role. Increasing evidence suggests that metabolic disturbances in CHF are not only a consequence of reduced cardiac output but also active regulators of epigenetic remodeling, thereby contributing to disease progression. Key metabolites, including α-ketoglutarate, acetyl-CoA, NAD⁺, S-adenosylmethionine, succinate, and 2-hydroxyglutarate, influence the activity of DNA methyltransferases, histone-modifying enzymes, and other chromatin regulators, thereby linking metabolic status to transcriptional control. Through these mechanisms, metabolic abnormalities promote persistent activation of pathological gene programs associated with cardiomyocyte hypertrophy, fibrosis, inflammation, apoptosis, and mitochondrial dysfunction, forming a self-reinforcing metabolic–epigenetic feedback loop in CHF. Although current guideline-directed medical therapies improve symptoms and clinical outcomes, they do not directly target this metabolic–epigenetic axis. Traditional Chinese medicine (TCM), including bioactive compounds, herbal formulas, patent medicines, and injections, has demonstrated potential in preclinical studies to modulate myocardial energy metabolism, improve mitochondrial function, and influence epigenetic regulators such as SIRT1, AMPK, and TET/JmjC-dependent pathways. However, most available evidence is derived from experimental models, and causal relationships between metabolite regulation, epigenetic remodeling, and cardiac functional improvement remain insufficiently validated. This review summarizes current knowledge on metabolite-driven epigenetic regulation in CHF and evaluates emerging evidence on the role of TCM in modulating this network. We also critically discuss key limitations, including reliance on non-clinical models, incomplete pharmacokinetic understanding, and insufficient causal validation. Finally, we propose future directions based on multi-omics integration, single-cell and spatial technologies, and systems biology approaches to facilitate mechanistic clarification and translational development of metabolism-targeted strategies for CHF. Full article

Background: Diabetic cardiomyopathy (DCM) is characterized by metabolic dysfunction, inflammation, extracellular matrix (ECM) remodeling, and myocardial fibrosis. Increasing evidence suggests that ferroptosis-associated oxidative injury may contribute to cardiac remodeling; however, the interaction between ferroptosis-related pathways and fibrosis-associated molecular networks remains incompletely understood. This study explored the ferroptosis–fibrosis axis using an integrative transcriptomic and systems pharmacology framework. Methods: Differentially expressed genes were identified from the GSE5406 myocardial transcriptomic dataset comparing nonfailing donor hearts with ischemic and idiopathic cardiomyopathy samples and analyzed using functional enrichment, protein–protein interaction, and disease-association approaches. Cross-dataset comparison and exploratory sample-level external evaluation were performed using the independent GSE263297 DCM-related dataset. Candidate genes were further evaluated by receiver operating characteristic (ROC) analysis and machine learning-based feature selection using least absolute shrinkage and selection operator (LASSO), random forest, and support vector machine-recursive feature elimination (SVM-RFE). Representative compounds associated with fibrosis-, oxidative stress-, inflammation-, and ferroptosis-related pathways were subsequently assessed by molecular docking against TGFBR1, STAT3, GPX4, AKT1, SMAD3, and ACSL4. Results: Transcriptomic analyses highlighted ECM organization, collagen-containing ECM, and fibrosis-related pathways as dominant biological themes. Cross-dataset comparison showed partial preservation of transcriptional patterns between independent myocardial cohorts, with 20 of 51 evaluated genes demonstrating concordant expression direction across datasets. ROC analysis identified LUM and ASPN as having the highest area under the curve (AUC) values among candidate genes, whereas COL1A1, COL1A2, and COL3A1 also showed elevated AUC values. Machine learning analyses identified FCN3, HOPX, CNN1, and GLUL as the core signature consistently prioritized across all three algorithms, whereas LUM was additionally identified by two of three algorithms. Internal validation yielded a cross-validated AUC of 0.934 (95% CI: 0.820–1.000), and exploratory sample-level external evaluation of the four-gene signature in GSE263297 yielded an AUC of 0.673 (95% CI: 0.380–0.967). Exploratory docking analyses suggested potential structural compatibility between several candidate compounds and fibrosis-, inflammation-, and ferroptosis-associated targets, with comparatively lower predicted binding-energy values observed for selected ligand–target combinations. Conclusions: The findings are consistent with a fibrosis-dominant remodeling signature and suggest potential network-level links between ferroptosis-associated processes and cardiac fibrosis. These observations should be regarded as exploratory and hypothesis-generating and require validation in independent cohorts and experimental studies. Full article

Background: Sepsis-induced cardiomyopathy (SICM) is a life-threatening complication driven by inflammatory cascades. Current genetic studies are restricted to single-trait analyses that cannot capture the shared genetic architecture spanning from immune dysregulation to structural myocardial damage. Methods: We applied genomic structural equation modeling to integrate genome-wide association study (GWAS) summary statistics for six phenotypes—sepsis, cardiac troponin I, left ventricular ejection fraction (LVEF), left ventricular diastolic strain rate, right ventricular peak ejection rate, and heart failure—constructing a latent factor for the shared genetic basis of SICM-related phenotypes. Downstream analyses included multivariate GWAS, fine-mapping (SuSiE/FINEMAP), sparse canonical correlation analysis-based transcriptome-wide association study (sCCA-TWAS) with FOCUS prioritization, MAGMA gene-set enrichment, cell-type enrichment (CELLECT), spatial transcriptomic mapping (gsMap), and stratified LD score regression (S-LDSC). Results: The model showed adequate fit (CFI = 0.936), with left ventricular diastolic strain rate and LVEF anchoring the factor most strongly (λ = 0.811 and 0.636, respectively). Multivariate GWAS identified 4220 lead variants, of which 4197 did not reach genome-wide significance in any constituent single-trait GWAS. Cross-referencing sCCA-TWAS with FOCUS fine-mapping prioritized 39 genes spanning inflammatory transduction, gap junction remodeling, proteostatic defense, and energy sensing. AMPK signaling was recurrently captured across fine-mapping and transcriptome-wide analyses. CELLECT identified cardiac muscle cells as the sole significant cell type. Conclusions: This study provides the first integrative multi-trait genetic framework for the shared genetic basis of SICM-related phenotypes, identifying AMPK as a recurrently captured pleiotropic hub at the inflammation–metabolism intersection and providing a foundation for future biomarker and mechanistic investigations. Full article

Heart failure (HF) is fundamentally a disease of energetic insufficiency, in which impaired mitochondrial efficiency, maladaptive metabolic remodeling, and disrupted intercellular signaling converge at the organ level to limit cardiac performance. Despite advances in pharmacologic and device-based therapies, current treatment paradigms largely modulate hemodynamics or neurohormonal pathways rather than directly restoring myocardial bioenergetic capacity. Emerging evidence positions extracellular vesicles (EVs) as endogenous regulators of cardiac energy homeostasis, capable of orchestrating coordinated metabolic and mitochondrial adaptations across cardiac and non-cardiac cell populations. This review advances a system-level framework in which EVs are conceptualized as bioenergetic therapeutics, i.e., active biological agents that reprogram cellular energy utilization, substrate flexibility, and mitochondrial efficiency, rather than passive carriers of isolated molecular cargo. We synthesize preclinical evidence demonstrating EV-mediated modulation of oxidative phosphorylation, glycolytic balance, redox signaling, and mitochondrial dynamics, and examine how these effects scale from cellular and small-animal models to clinically relevant heart failure phenotypes. Importantly, we highlight organ-level integration, wherein EV signaling interfaces with vascular, immune, and metabolic networks to reshape myocardial energetic demand and supply. By bridging mechanistic insights with translational considerations, this review addresses the central question of how EV-driven bioenergetic reprogramming can be deployed within contemporary HF treatment paradigms. We propose EV-based strategies as complementary or synergistic interventions capable of restoring energetic resilience, reframing heart failure therapy beyond structural repair toward systemic metabolic renewal. Full article

Background: Cardiac hypertrophy, a major feature of heart failure, is closely linked to metabolic remodeling and energy deficiency. Lysine lactylation (Kla), a recently discovered post-translational modification (PTM), has been implicated in various cellular processes. However, its specific role in cardiac hypertrophy remains poorly understood. Methods: We conducted quantitative proteomics and Kla PTM analysis on left ventricular tissues from both sham-operated and aortic banding-induced hypertrophic mouse hearts. Protein samples were extracted, enriched for lactylation, and subjected to mass spectrometry. Bioinformatic analyses were performed to uncover pathways and protein–protein interactions (PPI) related to Kla-modified proteins. Results: Our lactylome analysis identified 159 Kla-modified sites across 80 proteins, with 72 proteins exhibiting elevated Kla levels, particularly in mitochondrial and sarcomeric proteins. Pathway enrichment analysis highlighted significant involvement of fatty acid metabolism, the tricarboxylic acid (TCA) cycle, and cardiomyopathy-related pathways, underscoring the role of Kla in energy metabolism and cardiac remodeling. PPI analysis further revealed the central role of metabolic and structural proteins in the hypertrophic response. Conclusions: Our study provides the comprehensive analysis of Kla in cardiac hypertrophy, revealing its significant role in modulating proteins involved in mitochondrial energy metabolism and sarcomeric structure. Our findings provide a comprehensive overview of the lactylation landscape in cardiac hypertrophy and reveal extensive lactylation changes in proteins associated with mitochondrial metabolism and sarcomeric organization. These observations suggest a potential link between Kla and cardiac hypertrophy, which warrants further functional investigation. Full article

Global plastic production has led to widespread contamination by micro- and nanoplastics, with polystyrene nanoplastics (PSNPs) increasingly being detected in human biological samples, including blood and cardiac tissue. Given the critical role of mitochondria in cardiac energy metabolism, this study investigated whether 100 nm PSNPs interact with mitochondria and affect mitochondrial function in H9c2 cardiomyoblasts. Cellular uptake and intracellular distribution were examined, followed by an evaluation of mitochondrial ultrastructure, intracellular and mitochondrial reactive oxygen species (ROS) production, mitochondrial membrane potential, mitochondrial dynamics and mitophagy-related gene expression, mitochondrial DNA copy number, and metabolic function. PSNPs were internalized but did not directly localize to mitochondria within 24 h. No significant cytotoxicity, increase in intracellular or mitochondrial ROS production, or alteration in basal metabolic activity was observed. However, PSNP exposure resulted in intracellular accumulation, an altered mitochondrial ultrastructure characterized by crista loosening and vacuole-like structural changes. These changes were accompanied by reduced mitochondrial membrane potential; the upregulation of mitochondrial dynamics-related genes, including optic atrophy 1 (Opa1) and dynamin-related protein 1 (Drp1); the suppression of PTEN-induced kinase 1 (PINK1)/Parkin RBR E3 ubiquitin protein ligase (Parkin)-mediated mitophagy-related genes; and decreased maximal respiratory capacity. Lactate production and the extracellular acidification rate remained unchanged, suggesting that compensatory glycolysis was not activated. These findings indicate that PSNP exposure induces early mitochondrial structural and functional alterations without substantial cell damage, suggesting a potential reduction in cardiac adaptive capacity under PSNP-induced stress conditions. Full article

Cardiovascular disease (CVD) is the leading cause of mortality worldwide. The healthy adult heart depends on flexible energy use, but a diseased or injured heart is associated with a loss of flexibility and metabolic remodeling. Since metabolism plays a central role in cardiac health and disease, there is a growing need to understand how metabolic reprogramming contributes to cardiac dysfunction and impaired CM maturation. Human-induced pluripotent stem-cell-derived cardiomyocytes (hiPSC-CMs) are widely used as a platform to study human cardiac development and disease mechanisms. However, current models are limited by metabolic and structural immaturity. This review provides an overview of the dynamic shifts in cardiac metabolic states from fetal development to senescence, while delineating the metabolic signatures of healthy versus disease states. These metabolic switches are orchestrated by a complex interplay of upstream signals driven by variations in substrate availability, post-translational modifications and key transcriptional regulatory networks, which ultimately regulate downstream cardiac remodeling and pathological cascades. As cardiac metabolic function is affected by a coordinated multicellular network, this review also includes the metabolic crosstalk between CMs and non-CMs, including fibroblasts, endothelial cells and immune cells. In addition, various strategies to further mature hiPSC-CMs are summarized to enhance their metabolic profiles. Investigating cardiac metabolic shifts bridges developmental biology, stem cell biology, and regenerative cardiology by revealing how energy metabolism governs cellular identity, maturation, and regenerative potential. These insights are essential for improving stem-cell-derived CMs for disease modeling, drug discovery, and heart repair. Full article

Wearable electrocardiogram (ECG) monitoring enables continuous cardiovascular assessment, yet signals acquired in ambulatory environments are inevitably corrupted by baseline wander, electrode motion artifacts, and muscle interference, which obscure diagnostically critical waveform features. Existing deep learning denoisers rely on heuristic attention mechanisms and time-domain-only losses, lacking principled control over what information the network retains or discards. To address this limitation, we propose EFIB-Net, an information bottleneck-guided multi-resolution network for robust ECG denoising. The framework introduces two complementary components: an efficient frequency-guided attention module that derives temporal attention weights directly from the energy distribution of parallel multi-resolution convolutional branches, requiring only four learnable parameters while providing physically interpretable feature selection that naturally highlights QRS complexes, and a variational information bottleneck constraint at the encoder–decoder bottleneck that forces the latent representation to retain only reconstruction-relevant information and discard noise, guided by a spectral–temporal composite loss. To the best of our knowledge, we are among the first to explicitly introduce the information bottleneck principle into deep-learning-based ECG signal denoising. Experiments on the MIT-BIH Arrhythmia Database show that EFIB-Net outperforms ten traditional and deep learning baselines across four standard metrics—signal-to-noise ratio (SNR), root mean square error, percentage root-mean-square difference, and correlation coefficient; at an input SNR of −5 dB it reaches $8.12$ dB output SNR, surpassing the strongest attention-based competitor by 1.77 dB ($p<0.01$) while using only 0.45 M parameters and 10.8 ms inference latency per segment; downstream evaluation further demonstrates that the denoised signals achieve 99.18% R-peak detection sensitivity and 91.26% heartbeat classification F1-score, both within approximately one percentage point of the clean-signal upper bound, making it practical for real-time cardiac monitoring on resource-constrained wearable devices. Zero-shot cross-database evaluation on the QT Database further confirms generalizability, with only 0.54 dB degradation without retraining. Full article

Circulating ketone bodies (KBs), particularly β-hydroxybutyrate (β-HB), have emerged as metabolites with dual roles as both oxidative fuels and metabolic signaling molecules. Beyond serving as an alternative energy substrate, β-HB regulates diverse pathways involved in oxidative stress, inflammation, and mitochondrial function. However, the clinical implications of circulating KBs remain uncertain. This review summarizes current evidence regarding the potential role of KBs in glycemic progression and diabetic cardiomyopathy (DCM). Epidemiologic and experimental studies report conflicting associations between KB levels and the progression to hyperglycemia or type 2 diabetes, with some findings suggesting that elevated KB levels may reflect a metabolically favorable phenotype or a compensatory mechanism, whereas others indicate links to worsening glycemia. Similarly, studies in DCM have produced divergent results, with β-HB reported to improve mitochondrial function and cardiac performance in some models while contributing to metabolic inflexibility and adverse cardiac remodeling in others. We discuss potential mechanisms underlying these discrepancies and propose that the metabolic effects of β-HB are context-dependent, influenced by factors such as circulating concentration, the mode of ketosis induction, and the underlying metabolic or disease stage. Understanding these contextual determinants may help clarify whether β-HB represents an adaptive metabolic signal or a maladaptive substrate shift in cardiometabolic disease. Full article

Lactate was traditionally considered a metabolic by-product of anaerobic glycolysis, mainly associated with tissue hypoxia and muscle fatigue. However, increasing evidence has redefined lactate as a multifunctional metabolic intermediate and signaling molecule involved in exercise-induced systemic adaptations. During physical activity, circulating lactate levels rise markedly when skeletal muscle production exceeds systemic clearance, allowing lactate to act as an exercise-responsive metabolite, or exerkine, and as a mediator of cardiometabolic adaptation. In the cardiovascular system, lactate serves not only as an efficient substrate for myocardial energy production but also as a regulator of vascular tone, endothelial function, angiogenesis, inflammation, and cardiac remodeling. These effects occur through receptor-dependent and receptor-independent mechanisms, including activation of hydroxycarboxylic acid receptor 1 (HCAR1/GPR81), modulation of intracellular redox balance, and histone or non-histone protein lactylation. This review summarizes current evidence on lactate in cardiovascular physiology and disease, focusing on myocardial lactate metabolism, HCAR1/GPR81 signaling, protein lactylation, extracellular vesicle communication, gut microbiota interactions, and therapeutic implications in heart failure, atherosclerosis, and diabetic cardiomyopathy. Although lactate is also produced under resting, postprandial, and pathological conditions, exercise is characterized by the amplitude and kinetics of lactatemia, coordinated hormonal and hemodynamic responses, and transient high-concentration signaling. These features support exercise-derived lactate as a context-dependent cardiovascular exerkine. Full article

Background/Objectives: Coronary artery disease (CAD) is a leading cause of cardiovascular morbidity and mortality worldwide. Type 2 diabetes mellitus (T2DM) further increases CAD risk through metabolic disturbances and endothelial dysfunction. Adropin, S100A1, and SERCA2b are important regulators of endothelial function, energy metabolism, and calcium homeostasis. This study aimed to investigate the gene and protein expression levels of these biomarkers in CAD patients with and without T2DM. Methods: Gene and protein expression levels of adropin (ENHO), S100A1, and SERCA2b were evaluated in peripheral blood samples obtained from healthy controls (n = 50), CAD patients (n = 46), and CAD patients with T2DM (CAD+T2DM) (n = 40). Gene expression was determined using real-time PCR, while protein levels were measured with ELISA. Additionally, in silico bioinformatics analyses, such as protein–protein interaction networks and pathway enrichment analyses, were performed to explore potential molecular relationships among these biomarkers. Results: Adropin and ENHO gene expression levels were significantly lower in CAD patients and inversely related to the SYNTAX score. S100A1 levels were also reduced, and SERCA2b gene expression was significantly decreased, especially in the CAD+T2DM group. Bioinformatics analyses revealed that these molecules participate in interconnected pathways related to calcium signaling, cardiac muscle contraction, and metabolic regulation. Conclusions: These findings demonstrate links between altered levels of adropin, S100A1, and SERCA2b and CAD with or without T2DM. However, these observations are preliminary and need validation in larger prospective studies and mechanistic research before drawing definitive conclusions about their clinical utility, disease progression, or prognostic value. Full article

Doxorubicin (DOX) is a potent chemotherapeutic drug, whose clinical application is largely restricted by dose-dependent cardiotoxicity (DIC). Dracocephalum moldavica L. is a classic medicinal and edible plant with obvious cardiovascular protective effects; however, the role of its total flavonoids (TFDM) in DIC remains unclear. This study explored the cardioprotective effect of TFDM on DOX-induced myocardial injury and its mechanism related to mitochondrial quality control. We established in vivo and in vitro DIC models and adopted echocardiography, detection of cardiac injury and oxidative stress indicators, transmission electron microscopy, mitochondrial functional assessment and Western blotting, with AMPK knockdown performed for mechanism verification. Results showed that TFDM effectively improved cardiac function, reduced myocardial oxidative stress and apoptosis, and maintained mitochondrial ultrastructure and energy metabolism. TFDM activated the AMPK/PGC1α signaling axis to facilitate mitochondrial biogenesis, and AMPK silencing eliminated the protective effect of TFDM. In conclusion, AMPK/PGC-1α pathway is a primary key pathway involved in TFDM’s protective effects, which provides an experimental basis for the development of Dracocephalum moldavica L. as a functional food and adjuvant agent against DIC. Full article

Four-dimensional (4D) flow cardiovascular magnetic resonance assesses advanced haemodynamic parameters like kinetic energy (KE), vorticity, and viscous energy loss (vEL). However, gradient-based metrics (vorticity, vEL) are highly sensitive to partial volume effects near the fluid–tissue boundary. This study investigated the impact of systematic contour boundary offsets on these parameters to standardise analysis. Five cases underwent 4D flow imaging. Deep learning-derived automated segmentations of the cardiac chambers were generated. Haemodynamics were analysed using three contouring methods: the baseline mask, a one-voxel inward offset, and a two-voxel inward offset. KE, vorticity, and vEL decreased progressively with larger offsets. KE declined modestly with erosion (by approximately 18% and 35% at one- and two-voxel offsets, respectively), a reduction commensurate with the loss of integration volume rather than the removal of boundary artefacts. By contrast, the gradient-based metrics were disproportionately sensitive to boundary proximity. In the left ventricle, mean full-cycle vorticity decreased from 249.6 ± 79.9 s⁻¹ (baseline) to 157.0 ± 60.4 s⁻¹ (two-voxel offset; Hedges’ g 2.11), whilst vEL decreased from 549.4 ± 303.0 µW to 351.3 ± 230.0 µW (Hedges’ g 2.00). A one-voxel inward offset optimally reduces boundary noise for sensitive gradient-based parameters. While KE analysis remains satisfactory using unmodified baseline contours, we recommend the uniform application of a one-voxel offset across all parameters to ensure methodological simplicity and pipeline standardisation. Full article

Transcatheter edge-to-edge repair (TEER) is a recent minimally invasive method of managing mitral regurgitation (MR) in dogs with myxomatous mitral valve disease (MMVD). As the goal of intervention is to minimize MR severity, this study aimed to determine the association between reduced MR and changes in myocardial work indices after TEER in dogs. Ten client-owned dogs with moderate-to-severe MR were enrolled in the study, and all underwent TEER with multimodal imaging guidance. Myocardial work was analyzed before and after the procedure, and the MR severity, transmitral pressure gradients, left atrial and ventricular measurements, and index of myocardial work (GWI: the total myocardial work during systole; GCW: work contributing to LV ejection; GWW: ineffective work that contributes to no forward displacement; and GWE: ratio of constructive work to total work) were calculated. TEER significantly reduced MR severity in the majority of dogs, and this MR decrease was associated with a greater efficiency of myocardial work, more constructive work, and less wasted energy. No significant negative associations of moderate post-procedure gradients with short-term clinical outcomes emerged. TEER-mediated reduction in MR improves myocardial function in dogs. However, long-term studies are also needed to examine the effects of residual MR and transmitral gradients on cardiac function and clinical outcome. Full article

Heart failure (HF) is a complex clinical syndrome characterized not only by impaired cardiac function but also by profound disturbances in myocardial energy metabolism. AMP-activated protein kinase (AMPK), a central cellular energy sensor, plays a critical role in maintaining metabolic homeostasis by coordinating pathways involved in substrate utilization, mitochondrial function, autophagy, and stress adaptation. Experimental evidence supports a cardioprotective role of AMPK activation, including improved energetic efficiency, attenuation of pathological remodeling, and enhanced cellular resilience. However, emerging data indicate that AMPK signaling is highly context-dependent, with its effects varying according to HF phenotype, disease stage, and isoform-specific activity. While indirect AMPK modulation through established therapies such as metformin and sodium-glucose cotransporter 2 (SGLT2) inhibitors has demonstrated clinical benefit, the specific contribution of AMPK to these effects remains incompletely defined. Furthermore, direct pharmacological activation is limited by challenges including tissue specificity, off-target effects, and potential adverse outcomes associated with sustained activation. This review provides a comprehensive overview of AMPK signaling in HF, focusing on its role in metabolic remodeling, mitochondrial regulation, and interaction with key cardioprotective pathways. We also examine current clinical and translational evidence and discuss emerging strategies aimed at achieving isoform-selective and tissue-specific modulation. Collectively, these insights support a shift from broad AMPK activation toward precision-based therapeutic approaches tailored to the disease context. Full article