Clinical valve thrombosis and arterial embolism in a cancer patient after transcatheter aortic valve replacement

The number of cancer patients with severe aortic stenosis and atrial fibrillation (AF) is increasing in the aging population. Transcatheter aortic valve replacement (TAVR) is an established treatment option for severe aortic stenosis with high surgical risk, including individuals with cancer. Antithrombotic therapy should be considered for post-TAVR or AF patients. However, antithrombotic management in cancer patients remains challenging due to the increased risk of both thromboembolism and bleeding. We present a case of clinical valve thrombosis and arterial embolism after transcatheter aortic valve replacement in an elderly patient with a history of metastatic pancreatic cancer and permanent atrial fibrillation under treatment of single antiplatelet therapy. Warfarin treatment after successful surgical thrombectomy to the occluded arteries improved clinical valve thrombosis, although the long-term outcome remains unclear. This case demonstrates that novel management algorithms for thromboembolism and bleeding in elderly cancer patients with AF and valvular heart disease are urgently needed.

An explainable artificial intelligence-enabled electrocardiogram analysis model for the classification of reduced left ventricular function

Aims

The black box nature of artificial intelligence (AI) hinders the development of interpretable AI models that are applicable in clinical practice. We aimed to develop an AI model for classifying patients of reduced left ventricular ejection fraction (LVEF) from 12-lead electrocardiograms (ECG) with the decision-interpretability.

Methods and results

We acquired paired ECG and echocardiography datasets from the central and co-operative institutions. For the central institution dataset, a random forest model was trained to identify patients with reduced LVEF among 29 907 ECGs. Shapley additive explanations were applied to 7196 ECGs. To extract the model's decision criteria, the calculated Shapley additive explanations values were clustered for 192 non-paced rhythm patients in which reduced LVEF was predicted. Although the extracted criteria were different for each cluster, these criteria generally comprised a combination of six ECG findings: negative T-wave inversion in I/V5-6 leads, low voltage in I/II/V4-6 leads, Q wave in V3-6 leads, ventricular activation time prolongation in I/V5-6 leads, S-wave prolongation in V2-3 leads, and corrected QT interval prolongation. Similarly, for the co-operative institution dataset, the extracted criteria comprised a combination of the same six ECG findings. Furthermore, the accuracy of seven cardiologists' ECG readings improved significantly after watching a video explaining the interpretation of these criteria (before, 62.9% ± 3.9% vs. after, 73.9% ± 2.4%; P = 0.02).

Conclusion

We visually interpreted the model's decision criteria to evaluate its validity, thereby developing a model that provided the decision-interpretability required for clinical application.

NLRP3 Inflammasome Activation Through Heart-Brain Interaction Initiates Cardiac Inflammation and Hypertrophy During Pressure Overload

BACKGROUND

Mechanical stress on the heart, such as high blood pressure, initiates inflammation and causes hypertrophic heart disease. However, the regulatory mechanism of inflammation and its role in the stressed heart remain unclear. IL-1β (interleukin-1β) is a proinflammatory cytokine that causes cardiac hypertrophy and heart failure. Here, we show that neural signals activate the NLRP3 (nucleotide-binding domain, leucine-rich-containing family, pyrin domain-containing 3) inflammasome for IL-1β production to induce adaptive hypertrophy in the stressed heart.

METHODS

C57BL/6 mice, knockout mouse strains for NLRP3 and P2RX7 (P2X purinoceptor 7), and adrenergic neuron-specific knockout mice for SLC17A9, a secretory vesicle protein responsible for the storage and release of ATP, were used for analysis. Pressure overload was induced by transverse aortic constriction. Various animal models were used, including pharmacological treatment with apyrase, lipopolysaccharide, 2'(3')-O-(4-benzoylbenzoyl)-ATP, MCC950, anti-IL-1β antibodies, clonidine, pseudoephedrine, isoproterenol, and bisoprolol, left stellate ganglionectomy, and ablation of cardiac afferent nerves with capsaicin. Cardiac function and morphology, gene expression, myocardial IL-1β and caspase-1 activity, and extracellular ATP level were assessed. In vitro experiments were performed using primary cardiomyocytes and fibroblasts from rat neonates and human microvascular endothelial cell line. Cell surface area and proliferation were assessed.

RESULTS

Genetic disruption of NLRP3 resulted in significant loss of IL-1β production, cardiac hypertrophy, and contractile function during pressure overload. A bone marrow transplantation experiment revealed an essential role of NLRP3 in cardiac nonimmune cells in myocardial IL-1β production and cardiac phenotype. Pharmacological depletion of extracellular ATP or genetic disruption of the P2X7 receptor suppressed myocardial NLRP3 inflammasome activity during pressure overload, indicating an important role of ATP/P2X7 axis in cardiac inflammation and hypertrophy. Extracellular ATP induced hypertrophic changes of cardiac cells in an NLRP3- and IL-1β-dependent manner in vitro. Manipulation of the sympathetic nervous system suggested sympathetic efferent nerves as the main source of extracellular ATP. Depletion of ATP release from sympathetic efferent nerves, ablation of cardiac afferent nerves, or a lipophilic β-blocker reduced cardiac extracellular ATP level, and inhibited NLRP3 inflammasome activation, IL-1β production, and adaptive cardiac hypertrophy during pressure overload.

CONCLUSIONS

Cardiac inflammation and hypertrophy are regulated by heart-brain interaction. Controlling neural signals might be important for the treatment of hypertensive heart disease.

Deep learning-based age estimation from chest X-rays indicates cardiovascular prognosis

BACKGROUND

In recent years, there has been considerable research on the use of artificial intelligence to estimate age and disease status from medical images. However, age estimation from chest X-ray (CXR) images has not been well studied and the clinical significance of estimated age has not been fully determined.

METHODS

To address this, we trained a deep neural network (DNN) model using more than 100,000 CXRs to estimate the patients' age solely from CXRs. We applied our DNN to CXRs of 1562 consecutive hospitalized heart failure patients, and 3586 patients admitted to the intensive care unit with cardiovascular disease.

RESULTS

The DNN's estimated age (X-ray age) showed a strong significant correlation with chronological age on the hold-out test data and independent test data. Elevated X-ray age is associated with worse clinical outcomes (heart failure readmission and all-cause death) for heart failure. Additionally, elevated X-ray age was associated with a worse prognosis in 3586 patients admitted to the intensive care unit with cardiovascular disease.

CONCLUSIONS

Our results suggest that X-ray age can serve as a useful indicator of cardiovascular abnormalities, which will help clinicians to predict, prevent and manage cardiovascular diseases.

Age prediction from coronary angiography using a deep neural network: Age as a potential label to extract prognosis-related imaging features

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.

Automatic Detection of Left Ventricular Dilatation and Hypertrophy from Electrocardiograms Using Deep Learning

Left ventricular dilatation (LVD) and left ventricular hypertrophy (LVH) are risk factors for heart failure, and their detection improves heart failure screening. This study aimed to investigate the ability of deep learning to detect LVD and LVH from a 12-lead electrocardiogram (ECG). Using ECG and echocardiographic data, we developed deep learning and machine learning models to detect LVD and LVH. We also examined conventional ECG criteria for the diagnosis of LVH. We calculated the area under the receiver operating characteristic (AUROC) curve, sensitivity, specificity, and accuracy of each model and compared the performance of the models. We analyzed data for 18,954 patients (mean age (standard deviation): 64.2 (16.5) years, men: 56.7%). For the detection of LVD, the value (95% confidence interval) of the AUROC was 0.810 (0.801-0.819) for the deep learning model, and this was significantly higher than that of the logistic regression and random forest methods (P < 0.001). The AUROCs for the logistic regression and random forest methods (machine learning models) were 0.770 (0.761-0.779) and 0.757 (0.747-0.767), respectively. For the detection of LVH, the AUROC was 0.784 (0.777-0.791) for the deep learning model, and this was significantly higher than that of the logistic regression and random forest methods and conventional ECG criteria (P < 0.001). The AUROCs for the logistic regression and random forest methods were 0.758 (0.751-0.765) and 0.716 (0.708-0.724), respectively. This study suggests that deep learning is a useful method to detect LVD and LVH from 12-lead ECGs.

The Effectiveness of a Deep Learning Model to Detect Left Ventricular Systolic Dysfunction from Electrocardiograms

Deep learning models can be applied to electrocardiograms (ECGs) to detect left ventricular (LV) dysfunction. We hypothesized that applying a deep learning model may improve the diagnostic accuracy of cardiologists in predicting LV dysfunction from ECGs. We acquired 37,103 paired ECG and echocardiography data records of patients who underwent echocardiography between January 2015 and December 2019. We trained a convolutional neural network to identify the data records of patients with LV dysfunction (ejection fraction < 40%) using a dataset of 23,801 ECGs. When tested on an independent set of 7,196 ECGs, we found the area under the receiver operating characteristic curve was 0.945 (95% confidence interval: 0.936-0.954). When 7 cardiologists interpreted 50 randomly selected ECGs from the test dataset of 7,196 ECGs, their accuracy for predicting LV dysfunction was 78.0% ± 6.0%. By referring to the model's output, the cardiologist accuracy improved to 88.0% ± 3.7%, which indicates that model support significantly improved the cardiologist diagnostic accuracy (P = 0.02). A sensitivity map demonstrated that the model focused on the QRS complex when detecting LV dysfunction on ECGs. We developed a deep learning model that can detect LV dysfunction on ECGs with high accuracy. Furthermore, we demonstrated that support from a deep learning model can help cardiologists to identify LV dysfunction on ECGs.

Pathogenic Basis of Thromboinflammation and Endothelial Injury in COVID-19: Current Findings and Therapeutic Implications

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become a global pandemic with a great impact on social and economic activities, as well as public health. In most patients, the symptoms of COVID-19 are a high-grade fever and a dry cough, and spontaneously resolve within ten days. However, in severe cases, COVID-19 leads to atypical bilateral interstitial pneumonia, acute respiratory distress syndrome, and systemic thromboembolism, resulting in multiple organ failure with high mortality and morbidity. SARS-CoV-2 has immune evasion mechanisms, including inhibition of interferon signaling and suppression of T cell and B cell responses. SARS-CoV-2 infection directly and indirectly causes dysregulated immune responses, platelet hyperactivation, and endothelial dysfunction, which interact with each other and are exacerbated by cardiovascular risk factors. In this review, we summarize current knowledge on the pathogenic basis of thromboinflammation and endothelial injury in COVID-19. We highlight the distinct contributions of dysregulated immune responses, platelet hyperactivation, and endothelial dysfunction to the pathogenesis of COVID-19. In addition, we discuss potential therapeutic strategies targeting these mechanisms.

Deep learning model to detect significant aortic regurgitation using electrocardiography: Detection model for aortic regurgitation

BACKGROUND

Aortic regurgitation (AR) is a common heart disease, with a relatively high prevalence of 4.9% in the Framingham Heart Study. Because the prevalence increases with advancing age, an upward shift in the age distribution may increase the burden of AR. To provide an effective screening method for AR, we developed a deep learning-based artificial intelligence algorithm for the diagnosis of significant AR using electrocardiography (ECG).

METHODS

Our dataset comprised 29,859 paired data of ECG and echocardiography, including 412 AR cases, from January 2015 to December 2019. This dataset was divided into training, validation, and test datasets. We developed a multi-input neural network model, which comprised a two-dimensional convolutional neural network (2D-CNN) using raw ECG data and a fully connected deep neural network (FC-DNN) using ECG features, and compared its performance with the performances of a 2D-CNN model and other machine learning models. In addition, we used gradient-weighted class activation mapping (Grad-CAM) to identify which parts of ECG waveforms had the most effect on algorithm decision making.

RESULTS

The area under the receiver operating characteristic curve of the multi-input model (0.802; 95% CI, 0.762-0.837) was significantly greater than that of the 2D-CNN model alone (0.734; 95% CI, 0.679-0.783; p<0.001) and those of other machine learning models. Grad-CAM demonstrated that the multi-input model tended to focus on the QRS complex in leads I and aVL when detecting AR.

CONCLUSIONS

The multi-input deep learning model using 12-lead ECG data could detect significant AR with modest predictive value.

Automatic detection of vessel structure by deep learning using intravascular ultrasound images of the coronary arteries

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.

Deep Learning Algorithm to Detect Cardiac Sarcoidosis From Echocardiographic Movies

BACKGROUND

Because the early diagnosis of subclinical cardiac sarcoidosis (CS) remains difficult, we developed a deep learning algorithm to distinguish CS patients from healthy subjects using echocardiographic movies.Methods and Results:Among the patients who underwent echocardiography from January 2015 to December 2019, we chose 151 echocardiographic movies from 50 CS patients and 151 from 149 healthy subjects. We trained two 3D convolutional neural networks (3D-CNN) to identify CS patients using a dataset of 212 echocardiographic movies with and without a transfer learning method (Pretrained algorithm and Non-pretrained algorithm). On an independent set of 41 echocardiographic movies, the area under the receiver-operating characteristic curve (AUC) of the Pretrained algorithm was greater than that of Non-pretrained algorithm (0.842, 95% confidence interval (CI): 0.722-0.962 vs. 0.724, 95% CI: 0.566-0.882, P=0.253). The AUC from the interpretation of the same set of 41 echocardiographic movies by 5 cardiologists was not significantly different from that of the Pretrained algorithm (0.855, 95% CI: 0.735-0.975 vs. 0.842, 95% CI: 0.722-0.962, P=0.885). A sensitivity map demonstrated that the Pretrained algorithm focused on the area of the mitral valve.

CONCLUSIONS

A 3D-CNN with a transfer learning method may be a promising tool for detecting CS using an echocardiographic movie.

Diagnosing heart failure from chest X-ray images using deep learning

 

The development of deep learning technology has enabled machines to achieve high-level accuracy in interpreting medical images. While many previous studies have examined the detection of pulmonary nodules and cardiomegaly in chest X-rays using deep learning, the application of this technology to heart failure remains rare. In this study, we investigated the performance of a deep learning algorithm in terms of diagnosing heart failure using images obtained from chest X-rays. We used 952 chest X-ray images from a labeled database published by the National Institutes of Health. Two cardiologists respectively verified and relabeled these images, for a total of 260 “normal” and 378 “heart failure” images, and the remainder were discarded because they had been incorrectly labeled. In this study “heart failure” was defined as “cardiomegaly or congestion”, in a chest X-ray with cardiothoracic ratio (CTR) over 50% or radiographic presence of pulmonary edema. To enable the machine to extract a sufficient number of features from the images, we used the general machine learning approach called data augmentation and transfer learning. Owing mostly to this technique and the adequate relabeling process, we established a model to detect heart failure in chest X-ray by applying deep learning, and obtained an accuracy of 82%. Sensitivity and specificity to heart failure were 75% and 94.4%, respectively. Furthermore, heatmap imaging allowed us to visualize decisions made by the machine. The figure shows randomly selected examples of the prediction probabilities and heatmaps of the chest X-rays from the dataset. The original image is on the left and its heatmap is on the right, with its prediction probability written below. The red areas on the heatmaps show important regions, according to which the machine determined the classification. While some images with ambiguous radiolucency such as (e) and (f) were prone to be misdiagnosed by this model, most of the images like (a)–(d) were diagnosed correctly. Deep learning can thus help support the diagnosis of heart failure using chest X-ray images.

Heatmaps and probabilities of prediction

Funding Acknowledgement

Type of funding source: Public grant(s) – National budget only. Main funding source(s): JSPS KAKENHI

Erratum: Diagnosing Heart Failure from Chest X-Ray Images Using Deep Learning

An error appeared in the article entitled "Diagnosing Heart Failure from Chest X-Ray Images Using Deep Learning" by Takuya Matsumoto, Satoshi Kodera, Hiroki Shinohara, Hirotaka Ieki, Toshihiro Yamaguchi, Yasutomi Higashikuni, Arihiro Kiyosue, Kaoru Ito, Jiro Ando, Eiki Takimoto, Hiroshi Akazawa, Hiroyuki Morita, Issei Komuro (Vol. 61, No. 4, 781-786, 2020). The Figure 5on page 784 should be replaced by the following figure.

Diagnosing Heart Failure from Chest X-Ray Images Using Deep Learning

The development of deep learning technology has enabled machines to achieve high-level accuracy in interpreting medical images. While many previous studies have examined the detection of pulmonary nodules in chest X-rays using deep learning, the application of this technology to heart failure remains rare. In this paper, we investigated the performance of a deep learning algorithm in terms of diagnosing heart failure using images obtained from chest X-rays. We used 952 chest X-ray images from a labeled database published by the National Institutes of Health. Two cardiologists verified and relabeled a total of 260 "normal" and 378 "heart failure" images, with the remainder being discarded because they had been incorrectly labeled. Data augmentation and transfer learning were used to obtain an accuracy of 82% in diagnosing heart failure using the chest X-ray images. Furthermore, heatmap imaging allowed us to visualize decisions made by the machine. Deep learning can thus help support the diagnosis of heart failure using chest X-ray images.

Toll-Like Receptor 9 Plays a Pivotal Role in Angiotensin II-Induced Atherosclerosis

Background Toll-like receptor ( TLR ) 9 recognizes bacterial DNA , activating innate immunity, whereas it also provokes inflammation in response to fragmented DNA released from mammalian cells. We investigated whether TLR 9 contributes to the development of vascular inflammation and atherogenesis using apolipoprotein E-deficient ( Apoe ^-/-) mice. Methods and Results Tlr9-deficient Apoe ^-/- ( Tlr9 ^-/- Apoe ^-/-) mice and Apoe ^-/- mice on a Western-type diet received subcutaneous angiotensin II infusion (1000 ng/kg per minute) for 28 days. Angiotensin II increased the plasma level of double-stranded DNA, an endogenous ligand of TLR 9, in these mice. Genetic deletion or pharmacologic blockade of TLR 9 in angiotensin II-infused Apoe ^-/- mice attenuated atherogenesis in the aortic arch ( P<0.05), reduced the accumulation of lipid and macrophages in atherosclerotic plaques, and decreased RNA expression of inflammatory molecules in the aorta with no alteration of metabolic parameters. On the other hand, restoration of TLR 9 in bone marrow in Tlr9 ^-/- Apoe ^-/- mice promoted atherogenesis in the aortic arch ( P<0.05). A TLR 9 agonist markedly promoted proinflammatory activation of Apoe ^-/- macrophages, partially through p38 mitogen-activated protein kinase signaling. In addition, genomic DNA extracted from macrophages promoted inflammatory molecule expression more effectively in Apoe ^-/- macrophages than in Tlr9 ^-/- Apoe ^-/- macrophages. Furthermore, in humans, circulating double-stranded DNA in the coronary artery positively correlated with inflammatory features of coronary plaques determined by optical coherence tomography in patients with acute myocardial infarction ( P<0.05). Conclusions TLR 9 plays a pivotal role in the development of vascular inflammation and atherogenesis through proinflammatory activation of macrophages. TLR 9 may serve as a potential therapeutic target for atherosclerosis.

Biodegradable Extremely-Small-Diameter Vascular Graft Made of Silk Fibroin can be Implanted in Mice

Aim: Synthetic vascular grafts are widely used in surgical revascularization, mainly for medium- to large-sized vessels. However, synthetic grafts smaller than 6 mm in diameter are associated with a high incidence of thrombosis. In this study, we evaluated silk fibroin, a major protein of silk, with high biocompatibility and biodegradability, as a useful material for extremely-small-diameter vascular grafts.

Methods: A small-sized (0.9 mm inner diameter) graft was braided from a silk fibroin thread. The right carotid arteries of 8- to 14-week-old male C57BL/6 mice were cut at the midpoint, and fibroin grafts (5- to 7-mm in length) were transplanted using a cuff technique with polyimide cuffs. The grafts were harvested at different time points and analyzed histologically.

Results: CD31+ endothelial cells had already started to proliferate at 2 weeks after implantation. At 4 weeks, neointima had formed with α-smooth muscle actin+ cells, and the luminal surface was covered with CD31+ endothelial cells. Mac3+ macrophages were accumulated in the grafts. Graft patency was confirmed at up to 6 months after implantation.

Conclusion: This mouse model of arterial graft implantation enables us to analyze the remodeling process and biocompatibility of extremely-small-diameter vascular grafts. Biodegradable silk fibroin might be applicable for further researches using genetically modified mice.

Single-Nucleotide-Resolution Computing and Memory in Living Cells

The ability to process and store information in living cells is essential for developing next-generation therapeutics and studying biology in situ. However, existing strategies have limited recording capacity and are challenging to scale. To overcome these limitations, we developed DOMINO, a robust and scalable platform for encoding logic and memory in bacterial and eukaryotic cells. Using an efficient single-nucleotide-resolution Read-Write head for DNA manipulation, DOMINO converts the living cells' DNA into an addressable, readable, and writable medium for computation and storage. DOMINO operators enable analog and digital molecular recording for long-term monitoring of signaling dynamics and cellular events. Furthermore, multiple operators can be layered and interconnected to encode order-independent, sequential, and temporal logic, allowing recording and control over the combination, order, and timing of molecular events in cells. We envision that DOMINO will lay the foundation for building robust and sophisticated computation-and-memory gene circuits for numerous biotechnological and biomedical applications.

Advancing CRISPR-Based Programmable Platforms beyond Genome Editing in Mammalian Cells

Human diseases are caused by dysregulation of cellular biological programs that are encoded in DNA. Unveiling the endogenous programs and encoding new programs into the genome are key to creating novel diagnostic and therapeutic strategies. CRISPR/Cas9, originally identified in bacteria, has revolutionized genome editing in mammalian cells. Recent advances in CRISPR technologies have provided new programmable platforms for modifying cell function and behavior. CRISPR-based transcriptional regulators and modified gRNAs have enabled multiplexed regulation and visualization of genome dynamics with spatiotemporal precision. Using these toolkits, genome-scale screening platforms can identify key genetic elements or combinations thereof that modulate phenotypes in mammalian cells. In addition, imaging platforms for multiplexed genomic labeling have been created to study the conformation and dynamics of chromatin in living cells, which are essential for genome function. Furthermore, CRISPR-based computation and memory platforms have been built in living mammalian cells by using DNA as a data processing and storage medium to regulate and monitor cellular behaviors. The conditional regulation of CRISPR-based parts has enabled the design of complex multilayered biological programs. CRISPR-based memory platforms can continuously record biological events as mutations in defined DNA loci. By making use of base editors, CRISPR-based computation and memory platforms have been interconnected to perform logic operations based on past events. These technologies open up new avenues for understanding biological phenomena and designing mammalian cells as living machines for biomedical applications.

Vildagliptin, a DPP-4 Inhibitor, Attenuates Endothelial Dysfunction and Atherogenesis in Nondiabetic Apolipoprotein E-Deficient Mice

Dipeptidyl peptidase-4 (DPP-4) inhibitors are novel antidiabetic agents with possible vascular protection effects. Endothelial dysfunction is an initiation step in atherogenesis. The purpose of this study was to investigate whether vildagliptin (Vilda) attenuates the development of endothelial dysfunction and atherosclerotic lesions in nondiabetic apolipoprotein E-deficient (ApoE^-/-) mice. Eight-week-old nondiabetic ApoE^-/- mice fed a Western-type diet received Vilda (50 mg/kg/day) for 20 weeks or 8 weeks. After 20 weeks of treatment, Vilda administration reduced atherogenesis in the aortic arch as determined by en face Sudan IV staining compared with the vehicle group (P < 0.05). Vilda also reduced lipid accumulation (P < 0.05) and vascular cell adhesion molecule-1 (VCAM-1) expression (P < 0.05) and tended to decrease macrophage infiltration (P = 0.05) into atherosclerotic plaques compared with vehicle. After 8 weeks of treatment, endothelium-dependent vascular reactivity was examined. Vilda administration significantly attenuated the impairment of endothelial function in nondiabetic ApoE^-/- mice compared with the vehicle group (P < 0.05). Vilda treatment did not alter metabolic parameters, including blood glucose level, in both study protocols. To investigate the mechanism, aortic segments obtained from wild-type mice were incubated with exendin-4 (Ex-4), a glucagon-like peptide-1 (GLP-1) analog, in the presence or absence of lipopolysaccharide (LPS). Ex-4 attenuated the impairment of endothelium-dependent vasodilation induced by LPS (P < 0.01). Furthermore, Ex-4 promoted phosphorylation of eNOS at Ser1177 which was decreased by LPS in human umbilical endothelial cells (P < 0.05). Vilda inhibited the development of endothelial dysfunction and prevented atherogenesis in nondiabetic ApoE^-/- mice. Our results suggested that GLP-1-dependent amelioration of endothelial dysfunction is associated with the atheroprotective effects of Vilda.

Structure-function-guided exploration of the antimicrobial peptide polybia-CP identifies activity determinants and generates synthetic therapeutic candidates

Antimicrobial peptides (AMPs) constitute promising alternatives to classical antibiotics for the treatment of drug-resistant infections, which are a rapidly emerging global health challenge. However, our understanding of the structure-function relationships of AMPs is limited, and we are just beginning to rationally engineer peptides in order to develop them as therapeutics. Here, we leverage a physicochemical-guided peptide design strategy to identify specific functional hotspots in the wasp-derived AMP polybia-CP and turn this toxic peptide into a viable antimicrobial. Helical fraction, hydrophobicity, and hydrophobic moment are identified as key structural and physicochemical determinants of antimicrobial activity, utilized in combination with rational engineering to generate synthetic AMPs with therapeutic activity in a mouse model. We demonstrate that, by tuning these physicochemical parameters, it is possible to design nontoxic synthetic peptides with enhanced sub-micromolar antimicrobial potency in vitro and anti-infective activity in vivo. We present a physicochemical-guided rational design strategy to generate peptide antibiotics.

Activation of Toll-Like Receptor 9 Impairs Blood Flow Recovery After Hind-Limb Ischemia

Background: Peripheral artery disease causes significant functional disability and results in impaired quality of life. Ischemic tissue injury releases various endogenous ligands for Toll-like receptors (TLRs), suggesting the involvement of TLRs in blood flow recovery. However, the role of TLR9, which was originally known as a sensor for bacterial DNA, remains unknown. This study investigated the role of TLR9 in blood flow recovery in the ischemic limb using a mouse hind-limb ischemia model. Methods and Results: Unilateral femoral artery ligation was performed in TLR9-deficient (Tlr9 ^-/-) mice and wild-type mice. In wild-type mice, femoral artery ligation significantly increased mRNA expression of TLR9 in the ischemic limb (P < 0.001) and plasma levels of cell-free DNA (cfDNA) as determined by single-stranded DNA (ssDNA) (P < 0.05) and double-stranded DNA (dsDNA) (P < 0.01), which are endogenous ligands for TLR9, compared with the sham-operated group. Laser Doppler perfusion imaging demonstrated significantly improved ratio of blood flow in the ischemic to non-ischemic limb in Tlr9 ^-/- mice compared with wild-type mice at 2 weeks after ligation (P < 0.05). Tlr9 ^-/- mice showed increased capillary density and reduced macrophage infiltration in ischemic limb. Genetic deletion of TLR9 reduced the expression of TNF-α, and attenuated NF-κB activation in ischemic muscle compared with wild-type mice (P < 0.05, respectively) at 3 days after the surgery. ODN1826, a synthetic agonistic oligonucleotide for TLR9, or plasma obtained from mice with ischemic muscle promoted the expression of TNF-α in wild-type macrophages (P < 0.05), but not in Tlr9 ^-/- macrophages. ODN1826 also activated NF-κB signaling as determined by the degradation of IκBα in wild-type macrophages (P < 0.05), but not in Tlr9 ^-/- macrophages. In vitro experiments using human umbilical vein endothelial cells demonstrated that TNF-α, or conditioned medium obtained from wild-type macrophages treated with ODN1826 accelerated cell death as determined by MTS assay (P < 0.05 and P < 0.01, respectively). Conclusion: Our results suggest that ischemic muscle releases cfDNA, which activates TLR9 and enhances inflammation, leading to impairment of blood flow recovery in the ischemic limb. cfDNA-TLR9 signaling may serve as a potential therapeutic target in ischemic limb disease.

Ticagrelor, a P2Y12 antagonist, attenuates vascular dysfunction and inhibits atherogenesis in apolipoprotein-E-deficient mice

BACKGROUND AND AIMS

Ticagrelor reduces cardiovascular events in patients with acute coronary syndrome (ACS). Recent studies demonstrated the expression of P2Y12 on vascular cells including endothelial cells, as well as platelets, and suggested its contribution to atherogenesis. We investigated whether ticagrelor attenuates vascular dysfunction and inhibits atherogenesis in apolipoprotein E-deficient (apoe^-/-) mice.

METHODS

Eight-week-old male apoe^-/- mice were fed a western-type diet (WTD) supplemented with 0.1% ticagrelor (approximately 120 mg/kg/day). Non-treated animals on WTD served as control. Atherosclerotic lesions were examined by en-face Sudan IV staining, histological analyses, quantitative RT-PCR analysis, and western blotting. Endothelial function was analyzed by acetylcholine-dependent vasodilation using aortic rings. Human umbilical vein endothelial cells (HUVEC) were used for in vitro experiments.

RESULTS

Ticagrelor treatment for 20 weeks attenuated atherosclerotic lesion progression in the aortic arch compared with control (p < 0.05). Ticagrelor administration for 8 weeks attenuated endothelial dysfunction (p < 0.01). Ticagrelor reduced the expression of inflammatory molecules such as vascular cell adhesion molecule-1, macrophage accumulation, and lipid deposition. Ticagrelor decreased the phosphorylation of JNK in the aorta compared with control (p < 0.05). Ticagrelor and a JNK inhibitor ameliorated impairment of endothelium-dependent vasodilation by adenosine diphosphate (ADP) in wild-type mouse aortic segments. Furthermore, ticagrelor inhibited the expression of inflammatory molecules which were promoted by ADP in HUVEC (p < 0.001). Ticagrelor also inhibited ADP-induced JNK activation in HUVEC (p < 0.05).

CONCLUSIONS

Ticagrelor attenuated vascular dysfunction and atherogenesis through the inhibition of inflammatory activation of endothelial cells. These effects might be a potential mechanism by which ticagrelor decreases cardiovascular events in patients with ACS.

Inhibition of activated factor X by rivaroxaban attenuates neointima formation after wire-mediated vascular injury

Accumulating evidence suggests that activated factor X (FXa), a key coagulation factor, plays an important role in the development of vascular inflammation through activation of many cell types. Here, we investigated whether pharmacological blockade of FXa attenuates neointima formation after wire-mediated vascular injury. Transluminal femoral artery injury was induced in C57BL/6 mice by inserting a straight wire. Rivaroxaban (5mg/kg/day), a direct FXa inhibitor, was administered from one week before surgery until killed. At four weeks after surgery, rivaroxaban significantly attenuated neointima formation in the injured arteries compared with control (P<0.01). Plasma lipid levels and blood pressure were similar between the rivaroxaban-treated group and non-treated group. Quantitative RT-PCR analyses demonstrated that rivaroxaban reduced the expression of inflammatory molecules (e.g., IL-1β and TNF-α) in injured arteries at seven days after surgery (P<0.05, respectively). In vitro experiments using mouse peritoneal macrophages demonstrated that FXa increased the expression of inflammatory molecules (e.g., IL-1β and TNF-α), which was blocked in the presence of rivaroxaban (P<0.05). Also, in vitro experiments using rat vascular smooth muscle cells (VSMC) demonstrated that FXa promoted both proliferation and migration of this cell type (P<0.05), which were blocked in the presence of rivaroxaban. Inhibition of FXa by rivaroxaban attenuates neointima formation after wire-mediated vascular injury through inhibition of inflammatory activation of macrophages and VSMC.

Advancing therapeutic applications of synthetic gene circuits

Synthetic biology aims to introduce new sense-and-respond capabilities into living cells, which would enable novel therapeutic strategies. The development of regulatory elements, molecular computing devices, and effector screening technologies has enabled researchers to design synthetic gene circuits in many organisms, including mammalian cells. Engineered gene networks, such as closed-loop circuits or Boolean logic gate circuits, can be used to program cells to perform specific functions with spatiotemporal control and restoration of homeostasis in response to the extracellular environment and intracellular signaling. In addition, genetically modified microbes can be designed as local delivery of therapeutic molecules. In this review, we will discuss recent advances in therapeutic applications of synthetic gene circuits, as well as challenges and future opportunities for biomedicine.

Obesity-induced DNA released from adipocytes stimulates chronic adipose tissue inflammation and insulin resistance

Obesity stimulates chronic inflammation in adipose tissue, which is associated with insulin resistance, although the underlying mechanism remains largely unknown. Here we showed that obesity-related adipocyte degeneration causes release of cell-free DNA (cfDNA), which promotes macrophage accumulation in adipose tissue via Toll-like receptor 9 (TLR9), originally known as a sensor of exogenous DNA fragments. Fat-fed obese wild-type mice showed increased release of cfDNA, as determined by the concentrations of single-stranded DNA (ssDNA) and double-stranded DNA (dsDNA) in plasma. cfDNA released from degenerated adipocytes promoted monocyte chemoattractant protein-1 (MCP-1) expression in wild-type macrophages, but not in TLR9-deficient (Tlr9 (-/-) ) macrophages. Fat-fed Tlr9 (-/-) mice demonstrated reduced macrophage accumulation and inflammation in adipose tissue and better insulin sensitivity compared with wild-type mice, whereas bone marrow reconstitution with wild-type bone marrow restored the attenuation of insulin resistance observed in fat-fed Tlr9 (-/-) mice. Administration of a TLR9 inhibitory oligonucleotide to fat-fed wild-type mice reduced the accumulation of macrophages in adipose tissue and improved insulin resistance. Furthermore, in humans, plasma ssDNA level was significantly higher in patients with computed tomography-determined visceral obesity and was associated with homeostasis model assessment of insulin resistance (HOMA-IR), which is the index of insulin resistance. Our study may provide a novel mechanism for the development of sterile inflammation in adipose tissue and a potential therapeutic target for insulin resistance.

Dipeptidyl peptidase-4 inhibitor, linagliptin, ameliorates endothelial dysfunction and atherogenesis in normoglycemic apolipoprotein-E deficient mice

BACKGROUND

Dipeptidyl peptidase-4 (DPP-4) inhibitors have vasoprotective effects. This study investigated whether a recently approved DPP-4 inhibitor, linagliptin (Lina), suppresses atherogenesis in non-diabetic apolipoprotein-E deficient (ApoE(-/-)) mice, and examined its effects on endothelial function.

METHODS AND RESULTS

Lina (10mg/kg/day) was administered orally to ApoE(-/-) mice for 20 weeks. Lina reduced atherogenesis without alteration of metabolic parameters including blood glucose level compared with control (P<0.05). Results of immunohistochemical analyses and quantitative RT-PCR demonstrated that Lina significantly decreased inflammatory molecule expression and macrophage infiltration in the atherosclerotic aorta. Lina administration to ApoE(-/-) mice for 9 weeks ameliorated endothelium-dependent vasodilation compared with that in untreated mice. Plasma active glucagon-like peptide-1 (GLP-1) level was significantly higher in the treated group (P<0.05). Exendin-4 (Ex-4), a GLP-1 analog, ameliorated endothelium-dependent vasodilation impaired by palmitic acid (PA) in wild-type mouse aortic segments. Ex-4 promoted phosphorylation of eNOS(Ser1177) and Akt, both of which were abrogated by PA, in human umbilical vein endothelial cells. In addition, Lina administration to ApoE(-/-) mice decreased oxidative stress, as determined by urinary 8-OHdG secretion and NADPH oxidase subunit expression in the abdominal aorta.

CONCLUSION

Lina inhibited atherogenesis in non-diabetic ApoE(-/-) mice. Amelioration of endothelial dysfunction associated with a reduction of oxidative stress by GLP-1 contributes to the atheroprotective effects of Lina.

Pioglitazone Reduces Vascular Lipid Accumulation in Angiotensin II-Induced Hypertensive Rat

AIM

In an insulin-resistant state, excess lipids may accumulate in various non-adipose tissues, leading to histological and functional damage. It has been suggested that peroxisome proliferator-activated receptor-gamma (PPARγ) may ameliorate disorganized lipid balance. In the current study, we analyzed whether pioglitazone, an agonist of PPARγ, reduces angiotensin II-induced vascular lipid accumulation.

METHODS

Angiotensin II was infused into rats at doses of 0.7 mg/kg/day via a subcutaneously implanted osmotic minipump for 7 consecutive days. Pioglitazone was orally given at a dose of 2.5 mg/kg/day for 7 days.

RESULTS

Pioglitazone significantly reduced angiotensin II-induced enhanced lipid deposition and superoxide production in the adventitia of the aorta, as detected by oil red O and dihydroethidium (DHE) staining, respectively. Increased DHE signals, some observed at the site of lipid deposition, were mainly localized in ED-1-positive monocytes/macrophages. Angiotensin II-induced upregulation of the expression of LDL receptor and Nox1 was inhibited by pioglitazone treatment. In addition, angiotensin II significantly reduced the expression of PCSK9, and this reduction was ameliorated by pioglitazone. On the other hand, pioglitazone did not significantly alter the expression of the phosphorylated forms of AMPKα and ACC, which was downregulated by angiotensin II.

CONCLUSIONS

Pioglitazone treatment suppressed excess lipid accumulation and superoxide production in the aorta in an angiotensin II-induced rat model of hypertension.

Rivaroxaban, a novel oral anticoagulant, attenuates atherosclerotic plaque progression and destabilization in ApoE-deficient mice

OBJECTIVE

Activated factor X (FXa) plays a key role in the coagulation cascade, whereas accumulating evidence suggests that it also contributes to the pathophysiology of chronic inflammation on the vasculature. In this study, we assessed the hypothesis that rivaroxaban (Riv), a direct FXa inhibitor, inhibits atherogenesis by reducing macrophage activation.

METHODS AND RESULTS

Expression levels of PAR-1 and PAR-2, receptors for FXa, increased in the aorta of apolipoprotein E-deficient (ApoE(-/-)) mice compared with wild-type mice (P < 0.01, P < 0.05, respectively). Administration of Riv (5 mg/kg/day) for 20 weeks to 8-week-old ApoE(-/-) mice reduced atherosclerotic lesion progression in the aortic arch as determined by en-face Sudan IV staining compared with the non-treated group (P < 0.05) without alteration of plasma lipid levels and blood pressure. Histological analyses demonstrated that Riv significantly decreased lipid deposition, collagen loss, macrophage accumulation and matrix metallopeptidase-9 (MMP-9) expression in atherosclerotic plaques in the aortic root. Quantitative RT-PCR analyses using abdominal aorta revealed that Riv significantly reduced mRNA expression of inflammatory molecules, such as MMP-9, tumor necrosis factor-α (TNF-α). In vitro experiments using mouse peritoneal macrophages or murine macrophage cell line RAW264.7 demonstrated that FXa increased mRNA expression of inflammatory molecules (e.g., interleukin (IL)-1β and TNF-α), which was blocked in the presence of Riv.

CONCLUSIONS

Riv attenuates atherosclerotic plaque progression and destabilization in ApoE(-/-) mice, at least in part by inhibiting pro-inflammatory activation of macrophages. These results indicate that Riv may be particularly beneficial for the management of atherosclerotic diseases, in addition to its antithrombotic activity.

Midterm follow-up after retrievable inferior vena cava filter placement in venous thromboembolism patients with or without malignancy

BACKGROUND

A clear indication and strategy for placement of retrievable inferior vena cava filters (IVCFs) have not been established. This study was designed to evaluate the efficacy and disadvantages of the retrievable IVCF use particularly in venous thromboembolism (VTE) patients with malignancy.

HYPOTHESIS

Retrievable IVCFs might be safe and useful in VTE patients with malignancy.

METHODS

The study population consisted of 56 consecutive patients undergoing IVCF placement at our institution from January 1, 2008 to December 31, 2011. Prognostic data were retrospectively reviewed in April 2013.

RESULTS

Mean follow-up period was 584.6 (range, 1-1857) days. Twenty-six of the 56 patients had a malignancy. In 16 of the 30 patients without malignancy, the filter was retrieved, whereas the other 14 patients eventually received permanent implantation. There was no significant difference in the survival rate between the retrieval group and the nonretrieval group in the nonmalignancy patients (1-year survival rates, 94% vs 85%). In patients with malignancy, the nonretrieval group showed a significantly lower survival rate (P < 0.01). The 1-year and 2-year survival rates were 100% vs 46% and 100% vs 18%, respectively. There was no medical record of pulmonary thromboembolism occurrence or recurrence. All deaths in the patients with malignancy were malignancy related. In 4 of 5 malignancy patients who could undergo tumor resection surgery, adequate thrombus regression enabled us to retrieve the IVCF after surgery.

CONCLUSIONS

Permanent use of a retrievable IVCF is relatively safe in short- or midterm follow-up regardless of malignancy status. Retrievable filter use might be reasonable in malignancy patients.

Toll-like receptor-2 mediates adaptive cardiac hypertrophy in response to pressure overload through interleukin-1β upregulation via nuclear factor κB activation

BACKGROUND

Inflammation is induced in the heart during the development of cardiac hypertrophy. The initiating mechanisms and the role of inflammation in cardiac hypertrophy, however, remain unclear. Toll-like receptor-2 (TLR2) recognizes endogenous molecules that induce noninfectious inflammation. Here, we examined the role of TLR2-mediated inflammation in cardiac hypertrophy.

METHODS AND RESULTS

At 2 weeks after transverse aortic constriction, Tlr2(-/-) mice showed reduced cardiac hypertrophy and fibrosis with greater left ventricular dilatation and impaired systolic function compared with wild-type mice, which indicated impaired cardiac adaptation in Tlr2(-/-) mice. Bone marrow transplantation experiment revealed that TLR2 expressed in the heart, but not in bone marrow-derived cells, is important for cardiac adaptive response to pressure overload. In vitro experiments demonstrated that TLR2 signaling can induce cardiomyocyte hypertrophy and fibroblast and vascular endothelial cell proliferation through nuclear factor-κB activation and interleukin-1β upregulation. Systemic administration of a nuclear factor-κB inhibitor or anti-interleukin-1β antibodies to wild-type mice resulted in impaired adaptive cardiac hypertrophy after transverse aortic constriction. We also found that heat shock protein 70, which was increased in murine plasma after transverse aortic constriction, can activate TLR2 signaling in vitro and in vivo. Systemic administration of anti-heat shock protein 70 antibodies to wild-type mice impaired adaptive cardiac hypertrophy after transverse aortic constriction.

CONCLUSIONS

Our results demonstrate that TLR2-mediated inflammation induced by extracellularly released heat shock protein 70 is essential for adaptive cardiac hypertrophy in response to pressure overload. Thus, modulation of TLR2 signaling in the heart may provide a novel strategy for treating heart failure due to inadequate adaptation to hemodynamic stress.

HMGB1 plays a critical role in vascular inflammation and lesion formation via toll-like receptor 9

OBJECTIVE

Endogenous ligands such as high-mobility group box 1 (HMGB1) and nucleic acids are released by dying cells and bind to Toll-like receptors (TLRs). As TLR9 is involved in both microbial and sterile inflammation by detecting both bacterial and endogenous DNA, we investigated its role in inflammation and lesion formation in a mouse model of vascular injury.

METHODS AND RESULTS

C57BL/6 (WT) and TLR9 KO mice were subjected to wire-mediated vascular injury. Anti-HMGB1 antibody and purified HMGB1 protein were chronically delivered around the injured arteries by gelatin hydrogel, and neointima formation at 4 weeks after injury was evaluated. In addition, the same vascular injury was performed in bone-marrow chimeric mice (WT bone marrow into TLR KO mice; TLR9 KO bone marrow into WT mice). We also evaluated the production of inflammatory cytokines by mouse macrophages in response to HMGB1 and CpG-ODN. In wild-type mice after vascular injury, anti-HMGB1 antibody significantly reduced neointima formation and HMGB1 protein accelerated neointima hyperplasia. HMGB1 failed to accelerate lesion formation in TLR9 KO mice. The bone marrow transplantation study revealed that TLR9 in bone marrow-derived cells played a fundamental role in neointima formation. In vitro, HMGB1 and CpG-ODN synergistically induced the production of inflammatory cytokines by macrophages.

CONCLUSIONS

HMGB1 serves as an endogenous mediator of inflammation and lesion formation via the TLR9 pathway in response to vascular injury. Blockade of HMGB1 and/or TLR9 may represent a novel approach to treating atherosclerosis.

The ATP-binding cassette transporter ABCG2 protects against pressure overload-induced cardiac hypertrophy and heart failure by promoting angiogenesis and antioxidant response

OBJECTIVE

ATP-binding cassette transporter subfamily G member 2 (ABCG2), expressed in microvascular endothelial cells in the heart, has been suggested to regulate several tissue defense mechanisms. This study was performed to elucidate its role in pressure overload-induced cardiac hypertrophy.

METHODS AND RESULTS

Pressure overload was induced in 8- to 12-week-old wild-type and Abcg2-/- mice by transverse aortic constriction (TAC). Abcg2-/- mice showed exaggerated cardiac hypertrophy and ventricular remodeling after TAC compared with wild-type mice. In the early phase after TAC, functional impairment in angiogenesis and antioxidant response in myocardium was found in Abcg2-/- mice. In vitro experiments demonstrated that ABCG2 regulates transport of glutathione, an important endogenous antioxidant, from microvascular endothelial cells. Besides, glutathione transported from microvascular endothelial cells in ABCG2-dependent manner ameliorated oxidative stress-induced cardiomyocyte hypertrophy. In vivo, glutathione levels in plasma and the heart were increased in wild-type mice but not in Abcg2-/- mice after TAC. Treatment with the superoxide dismutase mimetic ameliorated cardiac hypertrophy in Abcg2-/- mice after TAC to the same extent as that in wild-type mice, although cardiac dysfunction with impaired angiogenesis was observed in Abcg2-/- mice.

CONCLUSION

ABCG2 protects against pressure overload-induced cardiac hypertrophy and heart failure by promoting angiogenesis and antioxidant response.

Vascular antispastic medication should take priority over other antihypertensives after coronary artery bypass grafting using a radial artery conduit

Radial artery conduits have recently been used more often in coronary artery bypass grafting because of their potentially better long-term patency than saphenous vein conduits. However, vasospasm of the radial artery conduit due to its nature as a muscular artery has always been of concern and a variety of vasodilators have empirically been used to reduce the risk of spasm. When a patient who was preoperatively taking antihypertensive agents undergoes coronary artery bypass using a radial artery graft, and if he/she is not hypertensive postoperatively, it is not always easy to decide what medication to start with. We report a case of a patient with a radial artery graft who did not receive vasodilators after surgery due to hypotension. The patient developed vasospasm of the radial artery conduit which did not respond to direct injection of vasodilators into the conduit but recovered after taking oral vasodilators for four weeks.

The ATP-Binding Cassette Transporter BCRP1/ABCG2 Plays a Pivotal Role in Cardiac Repair After Myocardial Infarction Via Modulation of Microvascular Endothelial Cell Survival and Function

Objective— To clarify the impact of breast cancer resistance protein 1 (BCRP1)/ATP-binding cassette transporter subfamily G member 2 (ABCG2) expression on cardiac repair after myocardial infarction (MI).

Methods and Results— The ATP-binding cassette transporter BCRP1/ABCG2 is expressed in various organs, including the heart, and may regulate several tissue defense mechanisms. BCRP1/ABCG2 was mainly expressed in endothelial cells of microvessels in the heart. MI was induced in 8- to 12-week-old wild-type (WT) and Bcrp1/Abcg2 knockout (KO) mice by ligating the left anterior descending artery. At 28 days after MI, the survival rate was significantly lower in KO mice than in WT mice because of cardiac rupture. Echocardiographic, hemodynamic, and histological assessments showed that ventricular remodeling was more deteriorated in KO than in WT mice. Capillary, myofibroblast, and macrophage densities in the peri-infarction area at 5 days after MI were significantly reduced in KO compared with WT mice. In vitro experiments demonstrated that inhibition of BCRP1/ABCG2 resulted in accumulation of intracellular protoporphyrin IX and impaired survival of microvascular endothelial cells under oxidative stress. Moreover, BCRP1/ABCG2 inhibition impaired migration and tube formation of endothelial cells.

Conclusion— BCRP1/ABCG2 plays a pivotal role in cardiac repair after MI via modulation of microvascular endothelial cell survival and function.

Serum osteoprotegerin levels and long-term prognosis in subjects with stable coronary artery disease

BACKGROUND

Osteoprotegerin (OPG) is a secretory glycoprotein which belongs to the tumor necrosis factor receptor family. OPG immunoreactivity was demonstrated in normal blood vessels and in early atherosclerotic lesions. In a previous study, we showed that high serum OPG levels are associated with progression of coronary artery disease (CAD).

OBJECTIVES

The present study was designed to assess the association between serum OPG level and long-term prognosis in patients with stable coronary artery disease.

METHODS

We performed a prospective, observational cohort study in 225 subjects to examine whether serum OPG levels can predict cardiovascular mortality. The median OPG levels were 1.02 ng mL(-1) at baseline.

RESULTS

During the follow-up (61 + or - 25 months), 27 deaths occurred including 13 cardiovascular deaths. When the subjects were divided into three groups according to serum OPG level, the group with high serum OPG showed a higher risk for cardiovascular mortality. A Multivariate Cox proportional hazards model indicated that the higher risk of cardiovascular death in the high OPG level group remained significant (hazards ratio of 7.44, 95%CI 0.92-60.30, highest vs. lowest OPG tertile). In contrast, serum OPG levels were not associated with non-cardiovascular mortality.

CONCLUSIONS

Our data show that serum OPG levels are an independent predictor of cardiovascular mortality in patients with stable coronary artery disease.

Difference of culprit plaque composition between patients with and without pre-infarction angina: an intravascular ultrasound radiofrequency analysis

AIMS

This study was performed to assess the differences in culprit plaque composition between patients with and without pre-infarction angina (PA) by using spectral analysis of intravascular ultrasound (IVUS) radiofrequency (RF) data.

METHODS AND RESULTS

Of 57 patients consecutively admitted to our institution with acute myocardial infarction, pre-intervention IVUS RF data of culprit plaques were obtained and analysed in 35 patients after percutaneous aspiration thrombectomy. Among the 35 patients, 21 patients had PA. Culprit plaques of patients without PA consisted of a higher percentage of the necrotic core component than those with PA (minimum lumen area [MLA]) site, 21.2+/-8.9% versus 9.9+/-9.8%, p=0.0015; entire culprit lesion, 18.9+/-6.3% versus 12.0+/-9.6%, p=0.023). In contrast, culprit plaques of patients with PA contained a higher percentage of the fibrofatty component than those without PA (MLA site, 21.0+/-12.0% versus 11.5+/-7.6%, p=0.013; entire culprit lesion, 16.8+/-7.9% versus 12.1+/-5.5%, p=0.062). There was no significant difference in quantitative parameters between the patients with and without PA.

CONCLUSIONS

Culprit plaques of patients with PA were different from those without PA. Plaque composition may play an important role in the occurrence of PA.