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Introduction: Ischemic heart disease is a leading cause of death worldwide, and its importance is increasing with the aging population. The aim of this study was to evaluate the accuracy of SurvTrace, a survival analysis model using the Transformer—a state-of-the-art deep learning method—for predicting recurrent cardiovascular events and stratifying high-risk patients. The model's performance was compared to that of a conventional scoring system utilizing real-world data from cardiovascular patients. Methods: This study consecutively enrolled patients who underwent percutaneous coronary intervention (PCI) at the Department of Cardiovascular Medicine, University of Tokyo Hospital, between 2005 and 2019. Each patient's initial PCI at our hospital was designated as the index procedure, and a composite of major adverse cardiovascular events (MACE) was monitored for up to two years post-index event. Data regarding patient background, clinical presentation, medical history, medications, and perioperative complications were collected to predict MACE. The performance of two models—a conventional scoring system proposed by Wilson et al. and the Transformer-based model SurvTrace—was evaluated using Harrell's c-index, Kaplan–Meier curves, and log-rank tests. Results: A total of 3938 cases were included in the study, with 394 used as the test dataset and the remaining 3544 used for model training. SurvTrace exhibited a mean c-index of 0.72 (95% confidence intervals (CI): 0.69–0.76), which indicated higher prognostic accuracy compared with the conventional scoring system's 0.64 (95% CI: 0.64–0.64). Moreover, SurvTrace demonstrated superior risk stratification ability, effectively distinguishing between the high-risk group and other risk categories in terms of event occurrence. In contrast, the conventional system only showed a significant difference between the low-risk and high-risk groups. Conclusion: This study based on real-world cardiovascular patient data underscores the potential of the Transformer-based survival analysis model, SurvTrace, for predicting recurrent cardiovascular events and stratifying high-risk patients. [ABSTRACT FROM AUTHOR]

Intravascular ultrasound (IVUS) is a diagnostic modality used during percutaneous coronary intervention. However, specialist skills are required to interpret IVUS images. To address this issue, we developed a new artificial intelligence (AI) program that categorizes vessel components, including calcification and stents, seen in IVUS images of complex lesions. When developing our AI using U-Net, IVUS images were taken from patients with angina pectoris and were manually segmented into the following categories: lumen area, medial plus plaque area, calcification, and stent. To evaluate our AI's performance, we calculated the classification accuracy of vessel components in IVUS images of vessels with clinically significantly narrowed lumina (< 4 mm2) and those with severe calcification. Additionally, we assessed the correlation between lumen areas in manually-labeled ground truth images and those in AI-predicted images, the mean intersection over union (IoU) of a test set, and the recall score for detecting stent struts in each IVUS image in which a stent was present in the test set. Among 3738 labeled images, 323 were randomly selected for use as a test set. The remaining 3415 images were used for training. The classification accuracies for vessels with significantly narrowed lumina and those with severe calcification were 0.97 and 0.98, respectively. Additionally, there was a significant correlation in the lumen area between the ground truth images and the predicted images (ρ = 0.97, R2 = 0.97, p < 0.001). However, the mean IoU of the test set was 0.66 and the recall score for detecting stent struts was 0.64. Our AI program accurately classified vessels requiring treatment and vessel components, except for stents in IVUS images of complex lesions. AI may be a powerful tool for assisting in the interpretation of IVUS imaging and could promote the popularization of IVUS-guided percutaneous coronary intervention in a clinical setting. [ABSTRACT FROM AUTHOR]

Increased transforming growth factor-β (TGF-β) signaling contributes to the pathophysiology of aortic aneurysm in Marfan syndrome (MFS). Recent reports indicate that a small but significant number of inflammatory cells are infiltrated into the aortic media and adventitia in MFS. However, little is known about the contribution of myeloid cells to aortic aneurysmal formation. In this study, we ablated the TGF-β type II receptor gene Tgfbr2 in myeloid cells of Fbn1C1039G/+ MFS mice (Fbn1C1039G/+;LysM-Cre/+;Tgfbr2fl/fl mice, hereinafter called Fbn1C1039G/+;Tgfbr2MyeKO) and evaluated macrophage infiltration and TGF-β signaling in the aorta. Aneurysmal formation with fragmentation and disarray of medial elastic fibers observed in MFS mice was significantly ameliorated in Fbn1C1039G/+;Tgfbr2MyeKO mice. In the aorta of Fbn1C1039G/+;Tgfbr2MyeKO mice, both canonical and noncanonical TGF-β signals were attenuated and the number of infiltrated F4/80-positive macrophages was significantly reduced. In vitro, TGF-β enhanced the migration capacity of RAW264.7 macrophages. These findings suggest that TGF-β signaling in myeloid cells promotes aortic aneurysmal formation and its inhibition might be a novel therapeutic target in MFS. [ABSTRACT FROM AUTHOR]

Emerging evidence has suggested a potential impact of gut microbiota on the pathophysiology of heart failure (HF). However, it is still unknown whether HF is associated with dysbiosis in gut microbiota. We investigated the composition of gut microbiota in patients with HF to elucidate whether gut microbial dysbiosis is associated with HF. We performed 16S ribosomal RNA gene sequencing of fecal samples obtained from 12 HF patients and 12 age-matched healthy control (HC) subjects, and analyzed the differences in gut microbiota. We further compared the composition of gut microbiota of 12 HF patients younger than 60 years of age with that of 10 HF patients 60 years of age or older. The composition of gut microbial communities of HF patients was distinct from that of HC subjects in both unweighted and weighted UniFrac analyses. Eubacterium rectale and Dorea longicatena were less abundant in the gut microbiota of HF patients than in that of HC subjects. Compared to younger HF patients, older HF patients had diminished proportions of Bacteroidetes and larger quantities of Proteobacteria. The genus Faecalibacterium was depleted, while Lactobacillus was enriched in the gut microbiota of older HF patients. These results suggest that patients with HF harbor significantly altered gut microbiota, which varies further according to age. New concept of heart-gut axis has a great potential for breakthroughs in the development of novel diagnostic and therapeutic approach for HF. [ABSTRACT FROM AUTHOR]

Cardiac stem cells or precursor cells regenerate cardiomyocytes; however, the mechanism underlying this effect remains unclear. We generated CreLacZ mice in which more than 99.9% of the cardiomyocytes in the left ventricular field were positive for 5-bromo-4-chloro-3-indolyl-β--galactoside (X-gal) staining immediately after tamoxifen injection. Three months after myocardial infarction (MI), the MI mice had more X-gal-negative (newly generated) cells than the control mice (3.04 ± 0.38/mm2, MI; 0.47 ± 0.16/mm2, sham; p < 0.05). The cardiac side population (CSP) cell fraction contained label-retaining cells, which differentiated into X-gal-negative cardiomyocytes after MI. We injected a leukemia inhibitory factor (LIF)-expression construct at the time of MI and identified a significant functional improvement in the LIF-treated group. At 1 month after MI, in the MI border and scar area, the LIF-injected mice had 31.41 ± 5.83 X-gal-negative cardiomyocytes/mm2, whereas the control mice had 12.34 ± 2.56 X-gal-negative cardiomyocytes/mm2 (p < 0.05). Using 5-ethynyl-2'-deoxyurinide (EdU) administration after MI, the percentages of EdU-positive CSP cells in the LIF-treated and control mice were 29.4 ± 2.7% and 10.6 ± 3.7%, respectively, which suggests that LIF influenced CSP proliferation. Moreover, LIF activated the Janus kinase (JAK)signal transducer and activator of transcription (STAT), mitogen-activated protein kinase/extracellular signal-regulated (MEK)extracellular signal-regulated kinase (ERK), and phosphatidylinositol 3-kinase (PI3K)–AKT pathways in CSPs in vivo and in vitro. The enhanced green fluorescent protein (EGFP)-bone marrow-chimeric CreLacZ mouse results indicated that LIF did not stimulate cardiogenesis via circulating bone marrow-derived cells during the 4 weeks following MI. Thus, LIF stimulates, in part, stem cell-derived cardiomyocyte regeneration by activating cardiac stem or precursor cells. This approach may represent a novel therapeutic strategy for cardiogenesis. [ABSTRACT FROM AUTHOR]

Identification of cognate ligands for G protein-coupled receptors (GPCRs) provides a starting point for understanding novel regulatory mechanisms. Although GPCR ligands have typically been evaluated through the activation of heterotrimeric G proteins, recent studies have shown that GPCRs signal not only through G proteins but also through β-arrestins. As such, monitoring β-arrestin signaling instead of G protein signaling will increase the likelihood of identifying currently unknown ligands, including β-arrestin-biased agonists. Here, we developed a cell-based assay for monitoring ligand-dependent GPCR-β-arrestin interaction via β-lactamase enzyme fragment complementation. Inter alia, β-lactamase is a superior reporter enzyme because of its cell-permeable fluorescent substrate. This substrate makes the assay non-destructive and compatible with fluorescence-activated cell sorting (FACS). In a reporter cell, complementary fragments of β-lactamase (α and ω) were fused to β-arrestin 2 and GPCR, respectively. Ligand stimulation initiated the interaction of these chimeric proteins (β-arrestin-α and GPCR-ω), and this inducible interaction was measured through reconstituted β-lactamase activity. Utilizing this system, we screened various mammalian tissue extracts for agonistic activities on human bombesin receptor subtype 3 (hBRS3). We purified peptide E as a low-affinity ligand for hBRS3, which was also found to be an agonist for the other two mammalian bombesin receptors such as gastrin-releasing peptide receptor (GRPR) and neuromedin B receptor (NMBR). Successful purification of peptide E has validated the robustness of this assay. We conclude that our newly developed system will facilitate the discovery of GPCR ligands. [ABSTRACT FROM AUTHOR]

G protein-coupled receptors (GPCRs) play a critical role in many physiological systems and represent one of the largest families of signal-transducing receptors. The number of GPCRs at the cell surface regulates cellular responsiveness to their cognate ligands, and the number of GPCRs, in turn, is dynamically controlled by receptor endocytosis. Recent studies have demonstrated that GPCR endocytosis, in addition to affecting receptor desensitization and resensitization, contributes to acute G protein-mediated signaling. Thus, endocytic GPCR behavior has a significant impact on various aspects of physiology. In this study, we developed a novel GPCR internalization assay to facilitate characterization of endocytic GPCR behavior. We genetically engineered chimeric GPCRs by fusing HaloTag (a catalytically inactive derivative of a bacterial hydrolase) to the N-terminal end of the receptor (HT-GPCR). HaloTag has the ability to form a stable covalent bond with synthetic HaloTag ligands that contain fluorophores or a high-affinity handle (such as biotin) and the HaloTag reactive linker. We selectively labeled HT-GPCRs at the cell surface with a HaloTag PEG ligand, and this pulse-chase covalent labeling allowed us to directly monitor the relative number of internalized GPCRs after agonist stimulation. Because the endocytic activities of GPCR ligands are not necessarily correlated with their agonistic activities, applying this novel methodology to orphan GPCRs, or even to already characterized GPCRs, will increase the likelihood of identifying currently unknown ligands that have been missed by conventional pharmacological assays. [ABSTRACT FROM AUTHOR]

Myocarditis is a critical inflammatory disorder which causes life-threatening conditions. No specific or effective treatment has been established. DPP-4 inhibitors have salutary effects not only on type 2 diabetes but also on certain cardiovascular diseases. However, the role of a DPP-4 inhibitor on myocarditis has not been investigated. To clarify the effects of a DPP-4 inhibitor on myocarditis, we used an experimental autoimmune myocarditis (EAM) model in Balb/c mice. EAM mice were assigned to the following groups: EAM mice group treated with a DPP-4 inhibitor (linagliptin) (n = 19) and those untreated (n = 22). Pathological analysis revealed that the myocardial fibrosis area ratio in the treated group was significantly lower than in the untreated group. RT-PCR analysis demonstrated that the levels of mRNA expression of IL-2, TNF-α, IL-1β and IL-6 were significantly lower in the treated group than in the untreated group. Lymphocyte proliferation assay showed that treatment with the DPP-4 inhibitor had no effect on antigen-induced spleen cell proliferation. Administration of the DPP-4 inhibitor remarkably suppressed cardiac fibrosis and reduced inflammatory cytokine gene expression in EAM mice. Thus, the agents present in DPP-4 inhibitors may be useful to treat and/or prevent clinical myocarditis. [ABSTRACT FROM AUTHOR]

Background: Although periodontitis is a risk factor for cardiovascular disease (CVD), the influence of periodontitis on Marfan syndrome (MFS) with CVD is unclear. The aim of this study was to assess the relationship between periodontal bacterial burden and MSF with CVD. Methods and Results: The subjects were patients with MFS with CVD (n = 47); age and gender matched non-MFS CVD patients (n = 48) were employed as controls. Full-mouth clinical measurements, including number of teeth, probing of pocket depth (PD), bleeding on probing (BOP) and community periodontal index (CPI) were recorded. We also evaluated the existence of three periodontal pathogens, Porphyromonas gingivalis, Aggregatibacter actinomycetemcomitans, and Prevotella intermedia using polymerase chain reaction assays. Serum antibody titers against the pathogens were also measured. We revealed that MFS with CVD patients had periodontitis more frequently than the age and gender matched non-MFS CVD control subjects. MFS with CVD patients had significantly severer periodontitis, fewer remaining teeth and deeper PD compared to the non-MFS CVD controls. Furthermore, the serum antibody titer level against Prevotella intermedia was significantly lower in MFS plus CVD patients compared to the non-MFS CVD patients. Conclusion: Periodontitis may influence the pathophysiology of cardiovascular complications in MFS patients. A specific periodontal pathogen might be a crucial therapeutic target to prevent CVD development. [ABSTRACT FROM AUTHOR]

Infusion of bone marrow-derived mononuclear cells (BMMNC) has been reported to ameliorate cardiac dysfunction after acute myocardial infarction. In this study, we investigated whether infusion of BMMNC is also effective for non-ischemic heart failure model mice and the underlying mechanisms. Intravenous infusion of BMMNC showed transient cardioprotective effects on animal models with dilated cardiomyopathy (DCM) without their engraftment in heart, suggesting that BMMNC infusion improves cardiac function via humoral factors rather than their differentiation into cardiomyocytes. Using conditioned media from sorted BMMNC, we found that the cardioprotective effects were mediated by growth hormone (GH) secreted from myeloid (Gr-1(+)) cells and the effects was partially mediated by signal transducer and activator of transcription 3 in cardiomyocytes. On the other hand, the GH expression in Gr-1(+) cells was significantly downregulated in DCM mice compared with that in healthy control, suggesting that the environmental cue in heart failure might suppress the Gr-1(+) cells function. Activin A was upregulated in the serum of DCM models and induced downregulation of GH levels in Gr-1(+) cells and serum. Furthermore, humoral factors upregulated in heart failure including angiotensin II upregulated activin A in peripheral blood mononuclear cells (PBMNC) via activation of NFκB. Similarly, serum activin A levels were also significantly higher in DCM patients with heart failure than in healthy subjects and the GH levels in conditioned medium from PBMNC of DCM patients were lower than that in healthy subjects. Inhibition of activin A increased serum GH levels and improved cardiac function of DCM model mice. These results suggest that activin A causes heart failure by suppressing GH activity and that inhibition of activin A might become a novel strategy for the treatment of heart failure. [ABSTRACT FROM AUTHOR]

Background: Although periodontitis is a risk factor for cardiovascular disease (CVD), the influence of periodontitis on Marfan syndrome (MFS) with CVD is unclear. The aim of this study was to assess the relationship between periodontal bacterial burden and MSF with CVD. Methods and Results: The subjects were patients with MFS with CVD (n = 47); age and gender matched non-MFS CVD patients (n = 48) were employed as controls. Full-mouth clinical measurements, including number of teeth, probing of pocket depth (PD), bleeding on probing (BOP) and community periodontal index (CPI) were recorded. We also evaluated the existence of three periodontal pathogens, Porphyromonas gingivalis, Aggregatibacter actinomycetemcomitans, and Prevotella intermedia using polymerase chain reaction assays. Serum antibody titers against the pathogens were also measured. We revealed that MFS with CVD patients had periodontitis more frequently than the age and gender matched non-MFS CVD control subjects. MFS with CVD patients had significantly severer periodontitis, fewer remaining teeth and deeper PD compared to the non-MFS CVD controls. Furthermore, the serum antibody titer level against Prevotella intermedia was significantly lower in MFS plus CVD patients compared to the non-MFS CVD patients. Conclusion: Periodontitis may influence the pathophysiology of cardiovascular complications in MFS patients. A specific periodontal pathogen might be a crucial therapeutic target to prevent CVD development. [ABSTRACT FROM AUTHOR]

The generalization of deep neural network algorithms to a broader population is an important challenge in the medical field. We aimed to apply self-supervised learning using masked autoencoders (MAEs) to improve the performance of the 12-lead electrocardiography (ECG) analysis model using limited ECG data. We pretrained Vision Transformer (ViT) models by reconstructing the masked ECG data with MAE. We fine-tuned this MAE-based ECG pretrained model on ECG-echocardiography data from The University of Tokyo Hospital (UTokyo) for the detection of left ventricular systolic dysfunction (LVSD), and then evaluated it using multi-center external validation data from seven institutions, employing the area under the receiver operating characteristic curve (AUROC) for assessment. We included 38,245 ECG-echocardiography pairs from UTokyo and 229,439 pairs from all institutions. The performances of MAE-based ECG models pretrained using ECG data from UTokyo were significantly higher than that of other Deep Neural Network models across all external validation cohorts (AUROC, 0.913-0.962 for LVSD, p < 0.001). Moreover, we also found improvements for the MAE-based ECG analysis model depending on the model capacity and the amount of training data. Additionally, the MAE-based ECG analysis model maintained high performance even on the ECG benchmark dataset (PTB-XL). Our proposed method developed high performance MAE-based ECG analysis models using limited ECG data., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Sawano et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Coronary angiography (CAG) is still considered the reference standard for coronary artery assessment, especially in the treatment of acute coronary syndrome (ACS). Although aging causes changes in coronary arteries, the age-related imaging features on CAG and their prognostic relevance have not been fully characterized. We hypothesized that a deep neural network (DNN) model could be trained to estimate vascular age only using CAG and that this age prediction from CAG could show significant associations with clinical outcomes of ACS. A DNN was trained to estimate vascular age using ten separate frames from each of 5,923 CAG videos from 572 patients. It was then tested on 1,437 CAG videos from 144 patients. Subsequently, 298 ACS patients who underwent percutaneous coronary intervention (PCI) were analysed to assess whether predicted age by DNN was associated with clinical outcomes. Age predicted as a continuous variable showed mean absolute error of 4 years with R squared of 0.72 (r = 0.856). Among the ACS patients stratified by predicted age from CAG images before PCI, major adverse cardiovascular events (MACE) were more frequently observed in the older vascular age group than in the younger vascular age group (p = 0.017). Furthermore, after controlling for actual age, gender, peak creatine kinase, and history of heart failure, the older vascular age group independently suffered from more MACE (hazard ratio 2.14, 95% CI 1.07 to 4.29, p = 0.032). The vascular age estimated based on CAG imaging by DNN showed high predictive value. The age predicted from CAG images by DNN could have significant associations with clinical outcomes in patients with ACS., Competing Interests: The authors have declared that no competing interests exist.