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Abstract: Vladimir Petrovich Demikhov, a Soviet physiologist and surgeon, made meticulous attempts at reviving heart and lung transplantation in the last century. Herein, we present an English translation of Demikhov''s 1969 paper of Transplantation of the Heart, Lungs and other Organs (published in Eksperimental''naia Khirurgiia i Anesteziologiia), which represented a synopsis of his experiences with experimental transplantation. A brief account of Demikhov''s life and contributions to transplant medicine is also given. [Copyright &y& Elsevier]

A paradigm shift in cancer treatment occurred with the advent of immune checkpoint inhibitors (ICI). ICI therapy has improved tumor response and increased overall survival in patients with solid tumors and hematologic malignancies. While ICI therapy has improved overall patient outcomes in oncology, it has also introduced novel adverse effects called immune-related adverse effects (irAEs). Studies have shown that the development of irAEs is associated with improved overall survival, but certain irAEs like pneumonitis and myocarditis are life threatening, and could result in death if not identified and treated early. Therefore, it is important for radiologists to be aware of complications arising from ICI administration, especially those related to the heart and lungs as they are associated with greater mortality. This paper will review the imaging features of cardiothoracic toxicities, recurrent and chronic irAEs, and atypical tumor responses associated with irAEs. • Imaging plays a key role in identifying the cardiothoracic complications of immunotherapy. • Some cardiothoracic complications are associated with high mortality and imaging plays a crucial role in their diagnosis. • Early detection of complications can prompt early initiation of treatment, allowing patients to continue immunotherapy. [ABSTRACT FROM AUTHOR]

This paper aims to provide an important update on the recent preclinical and clinical trials using cell therapy strategies and engineered heart tissues for the treatment of postinfarction left ventricular remodeling and heart failure. In addition to the authors' own works and opinions on the roadblocks of the field, they discuss novel approaches for cardiac remuscularization via the activation of proliferative mechanisms in resident cardiomyocytes or direct reprogramming of somatic cells into cardiomyocytes. This paper's main mindset is to present current and future strategies in light of their implications for the design of future patient trials with the ultimate objective of facilitating the translation of discoveries in regenerative myocardial therapies to the clinic. [ABSTRACT FROM AUTHOR]

The National Heart, Lung, and Blood Institute convened a workshop in August 2021 to identify opportunities in pediatric and congenital cardiovascular research that would improve outcomes for individuals with congenital heart disease across the lifespan. A subsidiary goal was to provide feedback on and visions for the Pediatric Heart Network. This paper summarizes several key research opportunities identified in the areas of: data quality, access, and sharing; aligning cardiovascular research with patient priorities (eg, neurodevelopmental and psychological impacts); integrating research within clinical care and supporting implementation into practice; leveraging creative study designs; and proactively enriching diversity of investigators, participants, and perspectives throughout the research process. [ABSTRACT FROM AUTHOR]

• COBC model is established. • Key nodes determined by the Fiedler-value method are usually more effective in forming consensus and reducing the behaviors against hearts. • The yield level and identification level, which make up the population traits, have different impacts on stable states. This paper explores the co-evolution of individual behaviors and opinions in social networks to understand how consensus or disagreement is formed by the proposed COBC model. Behavior evolution reflects memory of past behaviors, inner behaviors generated from opinions, and conformity behaviors from neighbors. Opinion evolution depends on the utility. Furthermore, the concepts of the untruthfulness index and stable states are given. Finally, we analyze the effect of different factors on stable states. The results show that key nodes determined by the Fiedler-value method which ranks nodes by their weighted frequency in circles are usually more effective in forming consensus and reducing the behaviors against hearts. Besides, the yield level and identification level, which make up the population traits, have different impacts on stable states, which answers the puzzles of Axelrod and Abelson. [ABSTRACT FROM AUTHOR]

The IFMIF-DONES Facility is built with the purpose of irradiating materials under DEMO Tokamak-like conditions and is a first-of-a-kind project that is foreseen to be built in Granada, Spain. A systematic top-down approach is used to design its Systems and to aid the harmonization and interaction between them. One of these main systems is the Test Systems which serves as the meeting point for other major systems such as the Lithium System (LS) and Accelerator Systems (AS), while also providing a connection to the Facilities for Complementary Experiments (FCE) for additional irradiation campaigns to take place. The Test Cell is a confined space for the experiments to take place, with critical functions for operation and safety. The TC is a subsystem serving as a convergent space for other systems, therefore the design of the TC has to fulfil the needs and requirements of the connecting systems also. In this paper, the design evolution of the Test Cell is discussed in detail from the early concept to the last more mature design, while also describing the connecting systems and the challenges these provide. [ABSTRACT FROM AUTHOR]

The Framingham Heart Study is the longest-running cardiovascular epidemiological study, starting in 1948. This paper gives an overview of the various cohorts, collected data, and most important research findings to date. In brief, the Framingham Heart Study, funded by the National Institutes of Health and managed by Boston University, spans 3 generations of well phenotyped White persons and 2 cohorts comprised of racial and ethnic minority groups. These cohorts are densely phenotyped, with extensive longitudinal follow-up, and they continue to provide us with important information on human cardiovascular and noncardiovascular physiology over the lifespan, as well as to identify major risk factors for cardiovascular disease. This paper also summarizes some of the more recent progress in molecular epidemiology and discusses the future of the study. [ABSTRACT FROM AUTHOR]

The Cardiovascular Disease in Women Committee of the American College of Cardiology convened a working group to develop a consensus regarding the continuing rise of mortality rates in young women aged 35 to 54 years. Heart disease mortality rates in young women continue to increase. Young women have increased mortality secondary to ischemic heart disease (IHD) compared with comparably aged men and similar mortality to that observed among older women. The authors reviewed the published evidence, including observational and mechanistic/translational data, and identified knowledge gaps pertaining to young women. This paper provides clinicians with pragmatic, evidence-based management strategies for young women at risk for IHD. Next-step research opportunities are outlined. This report presents highlights of the working group review and a summary of suggested research directions to advance the IHD field in the next decade. [ABSTRACT FROM AUTHOR]

In the past decades, H 2 has attracted significant attention as a potentially low, zero, or negative-emissions fuel depending on how it is produced. However, how H 2 will evolve in terms of its production, demand, and transport is not very clear. To help fill this gap, we developed a Python-based tool called the Hydrogen Economy Assessment & Resource Tool (HEART), specifically focused on the Association of Southeast Asian Nations (ASEAN) region. The tool consists of three parts: a user-friendly GUI, a default database consisting of costs and emissions for various supply/demand pathways, and an analysis and optimization engine. Users can use the default data and/or user inputs to run case studies for insightful results. The analysis and optimization engine can carry out techno-enviro-economic analysis for H 2 production and H 2 transport, project H 2 demand, and carry out the optimization and planning of H 2 supply chain over a long-term period. In this paper, we introduce the framework of HEART, the workflow of various projects, and show the capabilities and strengths of HEART through a case study. The case study indicates the tool can provides many useful results, like the landed cost and carbon footprint of H 2. Most importantly, by using HEART, H 2 supply chain pathways to meet projected demand can be obtained and optimized for total cost or total emissions. [Display omitted] • A Python-based tool is developed for hydrogen economy planning and optimization. • The framework, workflow, and capabilities of HEART is introduced. • Hydrogen supply chains for multiple sectors are planned for an ASEAN case study. [ABSTRACT FROM AUTHOR]

Heart and lung procurements are multiphased processes often accompanied by an array of complex logistics. Approaches to donor evaluation and management, organ procurement, and organ preservation vary among individual procurement teams. Because early graft failure remains a major cause of mortality in contemporary thoracic organ transplant recipients, we sought to establish some standardization in the procurement process. This paper, in this vein, represents an international consensus statement on donor heart and lung procurement and is designed to serve as a guide for physicians, surgeons, and other providers who manage donors to best optimize the clinical status for the procurement of both heart and lungs for transplantation. Donation after brain death (DBD) and donation after circulatory determination death (referred to as donation after circulatory death [DCD] for the remainder of the paper) for both heart and lung transplantation will be discussed in this paper. Although the data available on DCD heart donation are limited, information regarding the surgical technique for procurement is included within this consensus statement. Furthermore, this paper will focus on adult DBD and DCD heart and lung procurement. Currently, no certification, which is either recognized and/or endorsed by the transplant community at large, exists for the training of a cardiothoracic procurement surgeon. Nevertheless, establishing a training curriculum and credentialing requirements are beyond the scope of this paper. [ABSTRACT FROM AUTHOR]

Tebuconazole (TEB) is an important fungicide that belongs to the triazole family. It is widely used in agriculture and its use has experienced a tremendous increase in the last decade. The long-term exposure of humans to this pesticide is a real threat because it is stable in water and soil. The association between long-term exposure to TEB and damage of several biological systems, including hepatotoxicity and cardiotoxicity is evident, however, acute toxicological studies to reveal the toxicity of TEB are limited. This research paper addressed the acute exposure of TEB in murine hearts, cardiomyocytes, and human cardiomyocytes derived from an induced pluripotent stem cell (hiPSC-CMs), spelling out TEB's impact on electromechanical properties of the cardiac tissue. In ex vivo experiments, TEB dose dependently, caused significant electrocardiogram (ECG) remodeling with prolonged PR and QTc interval duration. The TEB was also able to change the action potential waveform in murine cardiomyocytes and hiPSC-CMs. These effects were associated with the ability of the compound to block the L-type calcium current (IC 50 = 33.2 ± 7.4 μmol.l−1) and total outward potassium current (IC 50 = 5.7 ± 1.5 μmol.l−1). TEB also increased the sodium/calcium exchanger current in its forward and reverse modes. Additionally, sarcomere shortening and calcium transient in isolated cardiomyocytes were enhanced when cells were exposed to TEB at 30 μmol.l−1. Combined, our results demonstrated that acute TEB exposure affects the cardiomyocyte's electro-contractile properties and triggers the appearance of ECG abnormalities. [ABSTRACT FROM AUTHOR]

This study analyzes Chinese liáo-mèi dialogues, in which the suitor attempts to make the heart of his target lover flutter. The language used in such dialogues tends to be highly metaphorical and creative in nature. This paper first reviews studies of metaphorical creativity, and then proposes a cognitive-emotive perspective from which this topic can be examined. Based on twenty liáo-mèi examples, this study shows that the act of causing a stir in one's heart is performed using multiple layers of meaning making: namely, cognitive mechanisms (e.g., image schemas, primary metaphors, and complex conceptual metaphors), connections between the utterances in the unfolding verbal interaction (i.e., co-text), emotive meaning (e.g., admiration, affection), and a sociocultural lens which assists in understanding and filtering out inappropriate speech and actions. The emotive meaning of metaphorical creativity in liáo-mèi dialogues is closely connected with the image-schematic and metaphorical dynamics of the discourse. • Suggests a cognitive-emotive perspective on metaphorical creativity. • Analyzes metaphorical creativity of Chinese liáo-mèi dialogues. • Shows bodily, cognitive, emotive, verbal, and sociocultural components that shape the creative process. • Reveals how affective-emotive, image-schematic and metaphorical dynamics are closely connected in such discourse. [ABSTRACT FROM AUTHOR]

Many factors and molecular pathways are involved in the pathogenesis of arterial hypertension. The increase in blood pressure may be determined by the properties of specific gene products and their associated action with environmental factors. In recent years, much attention has been paid to the Wnt/β-catenin signaling pathway which is essential for organ damage repair and homeostasis. Deregulation of the activity of the Wnt/β-catenin pathway may be directly or indirectly related to myocardial hypertrophy, as well as to cardiomyocyte remodeling and remodeling processes in pathological states of this organ. There are reports pointing to the role of the Wnt/β-catenin pathway in the course and development of organ complications in conditions of arterial hypertension. This paper presents the current state of knowledge of the role of the Wnt/β-catenin pathway in the regulation of arterial pressure and its impact on the physiology and the development of the complications of arterial hypertension in the heart. [ABSTRACT FROM AUTHOR]

• Human errors in Isotope Separation On-Line (ISOL) facility is performed. • Integrated approach of Hierarchical Task Analysis and Human Reliability Analysis is used. • A modified HEART approach is proposed. • HEART, SPAR-H, and CREAM are compared to each other. SPES (Selective Production of Exotic Species) is a second-generation Isotope Separation On-Line (ISOL) facility for advanced nuclear physics applications, currently under construction at INFN (National Institute of Nuclear Physics) of Legnaro, Italy. Despite the potentially important safety implications of human errors for ISOL facilities, only a limited number of studies addressing this issue have been performed worldwide. This paper tries to address this need by means of an integrated approach of Hierarchical Task Analysis (HTA) and three human error quantification methods: HEART (in an enhanced version), SPAR-H, and CREAM. The application of multiple Human Reliability Analysis (HRA) methods adds credibility to the analysis results and, for the present paper, this is required because the methods are applied to different performance conditions than typical, i.e. for operators in a nuclear power plant control room. The study emphasizes the potential range of task failure probabilities obtained in the analyses, rather than best-estimate values. Since the facility is being constructed, with elements such as the human-machine interface still undergoing design, some of the inputs typically required by HRA methods were not available; consequently, the produced HEP estimates may not fully represent future performance. The obtained results allowed informing some safety-enhancing recommendations that, coming at early stage, could be considered for implementation by the facility designers and managers. [ABSTRACT FROM AUTHOR]

• Risk analysis for cargo tank cracking on oil/chemical tanker ship. • The Bow tie method for performing risk analysis is adopted under the Dempster–Shafer (D-S) evidence theory – Human Error Assessment and Reduction Technique (HEART). • Enhancing safety awareness about the risk of cargo tank cracking on oil/chemical tanker ships. Oil/chemical tanker ships are designed to transport liquefied chemicals in a series of discrete cargo tanks. Even a minor crack in the cargo tanks can have catastrophic consequences financially, and for the marine environment and human life. For oil/chemical tanker shipping operations, risk analysis is of great importance to improve safety and minimise risk at the operational level during the transportation of chemical cargo. This paper focuses on the risk of cargo tank cracking on oil/chemical tanker ships. The robust bow-tie risk analysis method is adopted under the Dempster–Shafer (D-S) evidence theory – Human Error Assessment and Reduction Technique (HEART) approach. In Bow-tie, which analyses the possible causes and consequences of failures, the top event is determined as the risk of cargo tank cracking on an oil/chemical tanker. The probabilities of basic events are calculated with D-S evidence-based HEART, where expert opinions are combined. Besides the theoretical contribution, the outputs of the paper provide practical contributions to oil/chemical tanker owners and operators, safety researchers, safety inspectors, and superintendents by providing the information needed to minimise the risk associated with cargo tank cracks in oil/chemical tankers. [ABSTRACT FROM AUTHOR]

Automatic and accurate segmentation of the whole heart structure from 3D cardiac images plays an important role in helping physicians diagnose and treat cardiovascular disease. However, the time-consuming and laborious manual labeling of the heart images results in the inefficiency of utilizing the existing CT or MRI for training the deep learning network, which decrease the accuracy of whole heart segmentation. However, multi-modality data contains multi-level information of cardiac images due to different imaging mechanisms, which is beneficial to improve the segmentation accuracy. Therefore, this paper proposes a cascaded framework with cross-modality transfer learning for whole heart segmentation (CM-TranCaF), which consists of three key modules: modality transfer network (MTN), U-shaped multi-attention network (MAUNet) and spatial configuration network (SCN). In MTN, MRI images are transferred from MRI domain to CT domain, to increase the data volume by adopting the idea of adversarial training. The MAUNet is designed based on UNet, while the attention gates (AGs) are integrated into the skip connection to reduce the weight of background pixels. Moreover, to solve the problem of boundary blur, the position attention block (PAB) is also integrated into the bottom layer to aggregate similar features. Finally, the SCN is used to finetune the segmentation results by utilizing the anatomical information between different cardiac substructures. By evaluating the proposed method on the dataset of the MM-WHS challenge, CM-TranCaF achieves a Dice score of 91.1% on the testing dataset. The extensive experimental results prove the effectiveness of the proposed method compared to other state-of-the-art methods. [Display omitted] • The CM-TranCaF framework improves heart segmentation, transferring MRI to CT while preserving heart shape using the MTN module. MAUNet addresses class imbalances and boundary clarity, and SCN module uses spatial relations to boost segmentation accuracy. Achieving a 91.1% Dice score and a 14.386 mm Hausdorff Distance on the MM-WHS dataset, our method demonstrates competitive performance against other techniques. [ABSTRACT FROM AUTHOR]

The endogenous and dietary agent, alpha lipoic acid (ALA), is evaluated for its capacity to induce a broad spectrum of adaptive responses via hormetic dose responses and their underlying mechanisms. ALA was shown to induce hormetic effects in a wide range of experimental models within in vitro and in vivo experimental settings which included direct exposure and pre- and post-conditioning experimental protocols. The hormetic effects occur in a broad range of organ systems, including the brain, heart, kidney and other tissues, with possible public health and clinical/therapeutic applications linked to reducing the onset and progression of neurogenerative diseases and also in the preservation of sperm health and functionality during cryopreservation. This paper provides the first integrated assessment of ALA-induced hormetic dose responses. Underlying mechanisms that mediated the occurrence of ALA-induced hormetic effects involved the induction of low levels of ROS that activate key cell signaling antioxidant (e.g. Nrf2) pathways. [Display omitted] • First paper assessing capacity of ALA to induce hormetic dose responses. • ALA was shown to induce hormetic effects in a wide range of experimental models. • Experiments included direct exposure and pre- and post-conditioning protocols. • ALA induced protective effects via hormesis in a broad range of tissues/cell types. • Mechanisms involving low levels of ROS activate key cell signaling pathways. [ABSTRACT FROM AUTHOR]

Objectives: We sought to identify and consider methodological issues that may have limited or confounded investigations into links between depression and acute coronary syndrome (ACS) events.Methods: We reviewed salient research studies to identify such issues.Results: Against previous conclusions, we found that lifetime depression is unlikely to have any primary ACS impact, while we clarify that 'incident depression' (depression commencing at variable periods around the time of the ACS event) appears to confer a greater risk than non-incident depression. As the time periods of incident depressions are likely to have quite differing causes, evaluating any consolidated risk period appears unwise. It remains unclear whether it is 'depression' that provides the risk for ACS events or a higher order factor. Variable use of depression measures and failure to evaluate depressive sub-types have further limited clarification. The response by ACS patients to antidepressant medication appears limited, and it remains to be determined whether exposure to an antidepressant might be a contributing factor. Finally, studies may have focused on an excessively refined association, and neglected to recognise that depression is associated with a wide range of vascular events, suggesting that a broader conceptual model may be required.Limitations: The authors have considered only a limited set of studies in preparing this review, with the critique relying at times on subjective interpretation.Conclusions: After decades of research pursuing links between depression and ACS events explanatory links remain obscure, presumably reflecting a range of methodological issues that we have discussed in this paper . [ABSTRACT FROM AUTHOR]

• To present a very recent systematic survey about online heart monitoring systems. • To highlight the number of remote technologies enabled to aid cardiac patient and family. • The IoT-based techniques found are identified and its advances and open issues are discussed. • This survey is interesting both for researchers and health professionals. The Internet of Health Things promotes personalized and higher standards of care. Its application is diverse and attracts the attention of a substantial section of the scientific community. This approach has also been applied by people looking to enhance quality of life by using this technology. In this paper, we perform a survey that aims to present and analyze the advances of the latest studies based on medical care and assisted environment. We focus on articles for online monitoring, detection, and support of the diagnosis of cardiovascular diseases. Our research covers published manuscripts in scientific journals and recognized conferences since the year 2015. Also, we present a reference model based on the evaluation of the resources used from the selected studies. Finally, our proposal aims to help future enthusiasts to discover and enumerate the required factors for the development of a prototype for online heart monitoring purposes. [ABSTRACT FROM AUTHOR]

In this paper we present a compact version of the Heart iteration. One that computes low-rank approximations of large sparse matrices. The new iteration is a restarted Krylov method that is based on explicit restarts and Gram–Schmidt orthogonalizations. It is a simple algorithm that requires a minimal amount of computer storage as well as a minimal number of matrix–vector products per iteration. Yet it enjoys a fast rate of convergence. Numerical experiments illustrate the usefulness of the proposed approach. [ABSTRACT FROM AUTHOR]

• Gas bubbles in a non-Newtonian fluid under the influence of an external acoustic. • It transforms the generalized RP-equation for viscoelastic fluids. • A wide range of physical parameter values to address convergence issues. • Response Surface Methodology (RSM) is employed to investigate. • Rheological fluid on the pressure threshold required for inertial cavitation. Ultrasound imaging, or sonography, utilizes high-frequency sound waves to create images of the internal structures of the human body. It is widely applied in medical diagnostics due to its non-invasive nature and real-time capabilities. Ultrasound waves are emitted into the body, and their reflections are captured to generate detailed images of organs, tissues, fetuses during pregnancy, and more. The interaction between sound waves and biological tissues and issues related to propagation, reflection, and absorption of ultrasound are crucial considerations for improving image quality and safety. It is frequently used to keep an eye on the health and development of the fetus throughout pregnancy. The examination of several organs, including the heart, liver, kidneys, and blood arteries, is also done to look for anomalies, tumors, and other diseases. The dynamics of spherical gas bubbles within a non-Newtonian fluid exposed to an external sonic field are examined in this paper. The mathematical model offers a useful foundation for examining bubble behavior since it incorporates the additional stress tensor of a tangent hyperbolic fluid. The generalized RP problem may be transformed into an ordinary differential equation that can be solved using numerical methods, allowing a large range of parameter values to be investigated and resolving convergence difficulties. Particularly noteworthy are the numerical results for long acoustic cycles. The link between input and output variables is also investigated using an experimental methodology closely related to sensitivity analysis, which is important for possible device development. This innovative approach offers a fresh perspective on the subject. [ABSTRACT FROM AUTHOR]

We introduce Branched Latent Neural Maps (BLNMs) to learn finite dimensional input–output maps encoding complex physical processes. A BLNM is defined by a simple and compact feedforward partially-connected neural network that structurally disentangles inputs with different intrinsic roles, such as the time variable from model parameters of a differential equation, while transferring them into a generic field of interest. BLNMs leverage latent outputs to enhance the learned dynamics and break the curse of dimensionality by showing excellent in-distribution generalization properties with small training datasets and short training times on a single processor. Indeed, their in-distribution generalization error remains comparable regardless of the adopted discretization during the testing phase. Moreover, the partial connections, in place of a fully-connected structure, significantly reduce the number of tunable parameters. We show the capabilities of BLNMs in a challenging test case involving biophysically detailed electrophysiology simulations in a biventricular cardiac model of a pediatric patient with hypoplastic left heart syndrome. The model includes a 1D Purkinje network for fast conduction and a 3D heart-torso geometry. Specifically, we trained BLNMs on 150 in silico generated 12-lead electrocardiograms (ECGs) while spanning 7 model parameters, covering cell-scale, organ-level and electrical dyssynchrony. Although the 12-lead ECGs manifest very fast dynamics with sharp gradients, after automatic hyperparameter tuning the optimal BLNM, trained in less than 3 h on a single CPU, retains just 7 hidden layers and 19 neurons per layer. The resulting mean square error is on the order of 1 0 − 4 on an independent test dataset comprised of 50 additional electrophysiology simulations. In the online phase, the BLNM allows for 5000x faster real-time simulations of cardiac electrophysiology on a single core standard computer and can be employed to solve inverse problems via global optimization in a few seconds of computational time. This paper provides a novel computational tool to build reliable and efficient reduced-order models for digital twinning in engineering applications. The Julia implementation is publicly available under MIT License at https://github.com/StanfordCBCL/BLNM.jl. [ABSTRACT FROM AUTHOR]

Organ transplantation is the ultimate option to treat terminal illness by transplanting the deceased or damaged organs with healthy organs for improving the patient's life expectancy. The number of organs needed and the organs available for transplantation vary enormously. The tremendous advancements in utilizing big data analytics in the healthcare system make it efficient to explore decision-making information. To make optimal decisions in organ transplantation, this paper proposes a modified convolutional neural network-hybrid extreme learning machine (MCNN-HELM) based prediction model. The proposed MCNN-HELM model utilizes three different real-time datasets as inputs which contain records of liver, heart, and lung transplantation details of the donor and recipient. At first, the missing values and inaccurate data present in real-time datasets are removed via pre-processing. The pre-processed data are then trained using the MCNN-HELM model that efficiently determines the suitable donor for the recipient by minimizing the waiting time of the recipient for the matching organ donor. Moreover, the MCNN-HELM model gives initial preference to patients with high-risk rates to improve their quality of life. The proposed MCNN-HELM model achieves training accuracy of 97.5% with a computational time of 2.2 s, while the precision value of estimated factual outcomes, potential outcomes, and the accuracy of the best donor type are obtained by 16.3582, 16.1401, and 0.6784 which are more efficient than other state-of-the-art methods. [ABSTRACT FROM AUTHOR]

The next generation of implantable leadless pacemakers will require vibrational energy harvesters in order to increase the lifetime of the pacemaker. This paper reports for the first time the use of a piezoelectric MEMS linear energy harvester device that fits inside a pacemaker capsule. The silicon based MEMS cantilever device uses CMOS compatible Aluminum Nitride as the piezoelectric layer. The developed harvester operates based on a shock-induced vibration that is generated from the low frequency (60–240 beats per minute) high acceleration (>1 g) vibration of the heart. The off-resonance, high g impulses force the high-frequency harvester to oscillate at its resonant frequency. A power density of 97 and 454 μW cm −3 g −2 was achieved for a heart rate of 60 and 240 beats per minute respectively. The forced oscillation causes the linear harvester to dampen after 100–200 ms which reduces the average power compared to a typical sinusoidal excitation. A two and four cantilever system occupies 35% and 70% of the overall volume of the capsule while obtaining 2.98 and 5.96 μW respectively at a heart rate of 60 bpm respectively and 1 g acceleration. The results in this paper demonstrate that a shock-induced linear MEMS harvester can produce enough electrical energy from the vibration of a heart to power a leadless pacemaker while maintaining a small volume. [ABSTRACT FROM AUTHOR]

This paper presents a novel method of classifying heart conditions from an electrocardiography (ECG) signal. For this purpose, the R-R intervals of ECG signal are analyzed by Gamma distribution parameters and classified into normal (NR) or abnormal (AN) ECG waves. For the normal ECG waves, the heart condition is further investigated by analyzing the dynamic behavior of heart activity based on the correlation between successive R-R intervals and long-term analysis. The classification of heart conditions is made by estimating the conditional class probabilities using class probability output networks (CPONs). The simulation for classifying heart conditions using the MIT-BIH data sets reveals that the proposed approach is effective for classifying heart conditions and allows more accurate classification than the existing classifiers such as the k-NN and SVM. [ABSTRACT FROM AUTHOR]

• Full 4D PC-MRI data processing system. • Summary of a seven year collaboration. • Software binaries available. • Comprehensive blood flow analysis. Image, graphical abstract 4D PC-MRI enables the assessment of blood flow velocity vectors of one heart beat. These time-dependent, three-dimensional data allow for a comprehensive analysis and contain plenty of information. So far, 4D PC-MRI is used for research purposes. One reason is a lack of standardized, easy-to-use evaluation software, which is crucial for potential application in clinical routine. In this system's paper, we present our software Bloodline , a tool combining advanced visual exploration and analysis of 4D PC-MRI data. We will put emphasis on design decisions and requirements that arose from the close collaboration with cardiologists and radiologists. The tool provides a guided data processing and evaluation workflow. The pre-processing pipeline comprises generic data import, artifact correction, vessel segmentation, surface as well as centerline extraction, cardiac cycle definition, and landmark specification. Bloodline integrates advanced visualization techniques and facilitates a dataset evaluation within ten minutes. Qualitative and quantitative flow analysis methods are provided. The focus lies on the detection and characterization of vortices, which are correlated to cardiovascular diseases. [ABSTRACT FROM AUTHOR]

Abstract Although its economic, cultural and biological importance, many genes haven't been depicted, sequenced or analyzed to date for Camelus dromedarius. In the present paper, the full-length c-DNA of a novel CYP2J2 (GenBank accession number MH511989) was cloned from liver, heart, and kidney mRNA by RACE-PCR. The full-length c-DNA of the cloned CYP2J2 was sequenced and analyzed using bioinformatics methods. The full-length c-DNA sequence was 2135 bp with no introns. The open reading frame (ORF) had 1341 nucleotides which coded for a putative protein of 446 amino acids. The deduced protein is located in the endoplasmic reticulum. It has two transmembrane regions. The nucleotides and deduced amino acids sequences of the cloned CYP2J2 were 1400 nucleotides and 47 amino acids shorter than the predicted homolog respectively. This study is the first description of the putative CYP2J2 gene, which opens the way to a new investigation-so far-never accomplished in Camelus dromedarius. Graphical abstract Unlabelled Image [ABSTRACT FROM AUTHOR]

• Q-markers of YTC against MI was uncovered; • Extraction process of YTC was optimized; • HPLC fingerprint of optimized YTC was established. Myocardial ischemia (MI), a condition in which the heart is unable to function due to insufficient blood and oxygen supply, is a major cause of death from coronary heart disease (CHD). Yiqi Tongluo capsule (YTC) is a Chinese patent drug which commonly used for treatment of MI in clinic. However, the related active components of YTC for treatment of MI were still uncovered. This paper is aimed to study the quality markers (Q-markers) of YTC and further optimize the extraction process of YTC based on Q-markers, providing research foundation for the further modern pharmaceutical preparations of YTC. We firstly used UPLC-QTOF-MS to analyze the constituents of YTC absorbed in blood, then isoprenaline (ISO) induced H9c2 cell model was used further screen the active constituents with protective effects on cardiomyocytes. After that, the orthogonal table (L9 (34)) was used to optimize the extraction process with three levels of 4 factors (water addition, immersion time, extraction time and decoction times). Finally, the HPLC fingerprint of 15 batches of optimized YTC was established. In our present study, a total of 33 components were identified in YTC, of which 10 components were absorbed in blood. Among the 10 components, 8 compounds had significant protective effects on ISO stimulated H9c2 cells, including Paeoniflorin, Ferulic acid, Calycosin, Senkyunolide A, N-butylphthalide, Z-ligustilide, Levistilide A, and Astragaloside IV, which were considered as the Q-markers of YTC. The optimized extraction process based on Q-marker as follows: soaking 1 h, then adding 8 times water to extract 3 times by decoction, each extraction lasts 1.5 h. The HPLC fingerprint of optimized YTC was established with 15 batches of YTC samples, and the optimized YTC samples has no significant toxicity to the heart, liver, spleen, lungs, and brain tissues of rats. [ABSTRACT FROM AUTHOR]

CO 2 fixed fire extinguishing system activation accidents may occur as a result of unintentional system activation or human error. Crew members present in the area could suffer serious consequences, including death, if CO 2 gas is released into a protected compartment such as the engine room, CO 2 room, or cargo area. It is therefore crucial to investigate and address the causes of such accidents. The use of Dempster-Shafer (D-S) theory and the Human Error Assessment and Reduction Technique (HEART) to the Human Reliability Analysis (HRA) of CO 2 fixed fire extinguishing system activation accidents is discussed in this study. On the one hand, D-S theory allows for uncertainty-based reasoning and can be extremely advantageous, especially when analysing complex systems where there are many potential challenges. On the other hand, HEART is an organised method to examine and reduce human error in high-risk systems. Together, these techniques provide a powerful tool for identifying and addressing the underlying causes of CO 2 fixed fire extinguishing system activation accidents. The study revealed that the total human error probability (HEP) for the CO 2 fixed fire extinguishing system was 3.10E-01 and the reliability of human performance for the given process was 6.90E-01. The results of this paper highlight many factors such as equipment failure, inadequate training, and poor maintenance practices, as well as factors contributing to the risk of accidental system activation. By addressing these factors, the probability of CO 2 -fixed fire suppression system activation accidents can be significantly reduced. • Integration of Dempster-Shafer theory (D-S) and HEART for Human Reliability Analysis (HRA). • HRA of fixed CO2 fire extinguishing system activation process. • Increasing safety awareness of fixed-CO2 fire system risks onboard. [ABSTRACT FROM AUTHOR]

CO 2 fixed fire extinguishing system activation accidents may occur as a result of unintentional system activation or human error. Crew members present in the area could suffer serious consequences, including death, if CO 2 gas is released into a protected compartment such as the engine room, CO 2 room, or cargo area. It is therefore crucial to investigate and address the causes of such accidents. The use of Dempster-Shafer (D-S) theory and the Human Error Assessment and Reduction Technique (HEART) to the Human Reliability Analysis (HRA) of CO 2 fixed fire extinguishing system activation accidents is discussed in this study. On the one hand, D-S theory allows for uncertainty-based reasoning and can be extremely advantageous, especially when analysing complex systems where there are many potential challenges. On the other hand, HEART is an organised method to examine and reduce human error in high-risk systems. Together, these techniques provide a powerful tool for identifying and addressing the underlying causes of CO 2 fixed fire extinguishing system activation accidents. The study revealed that the total human error probability (HEP) for the CO 2 fixed fire extinguishing system was 3.10E-01 and the reliability of human performance for the given process was 6.90E-01. The results of this paper highlight many factors such as equipment failure, inadequate training, and poor maintenance practices, as well as factors contributing to the risk of accidental system activation. By addressing these factors, the probability of CO 2 -fixed fire suppression system activation accidents can be significantly reduced. • Integration of Dempster-Shafer theory (D-S) and HEART for Human Reliability Analysis (HRA). • HRA of fixed CO2 fire extinguishing system activation process. • Increasing safety awareness of fixed-CO2 fire system risks onboard. [ABSTRACT FROM AUTHOR]

Ligusticum chuanxiong Hort. (Chuanxiong, LC), as an important traditional Chinese medicine (TCM), can not only be used as a monarch herb but also be used as a classic "Yin-Jing" (引经) medicine in compound prescriptions, e.g., Buyang Huanwu Decoction (BHD). Although LC has the effect of guiding components into the brain in BHD, there is still a lack of scientific evidence on this "Yin-Jing" effects. Herein, we used pharmacokinetics and tissue distributions to investigate "Yin-Jing" effects of LC. To simplify the study, four major constituents in BHD, i.e., Calycosin (CA), astragaloside IV (AI), paeoniflorin (PA), and amygdalin (AM) were combined to form a simple compound (abbreviated as CAPA here) to replace the original BHD in this paper. The Yin-Jing medical property of LC was confirmed by the compatibility of CAPA with LC or its different fractions (Fr. A ∼ Fr. F). To explore the "Yin-Jing" medical property of LC via pharmacokinetics and tissue distributions by ultra-performance liquid chromatography-triple quadrupole mass spectrometry (UPLC-QQQ-MS). The contents of CA, AI, PA, and AM were simultaneously determined by the established and validated UPLC-QQQ-MS method in different rat tissues and plasma after administration of CAPA with the combination of LC or Fr. A ∼ Fr. F. The pharmacokinetic parameters, e.g., T max , C max , AUC 0–t and MRT 0–t , were calculated to evaluate the efficiency of "Yin-Jing". The C max and AUC 0–t of CA, AI, PA, and AM were remarkably increased in rat brain tissues compared with those of the control group after compatibility of LC. This demonstrated that LC has the Yin-Jing effects on brain tissues. Additionally, Fr. B or Fr. C might be the material basis by specifically studying the distributions of CA, AI, PA, and AM in brain tissue based on mutual compatibility. The effects of Fr. B and Fr. C on distributions of these constituents in other tissues or plasma was also studied to verify the effects of Yin-Jing of LC. The results showed that the same upward trend is found in heart, liver and plasma, but the intensity is insignificant as that in brain tissue. Furthermore, the C max and AUC 0–t of some analytes in the rat spleen, lung, and kidney were significantly decreased compared with the control group (P < 0.05 or 0.01). LC has the function of Yin-Jing, especially guiding the components into the brain tissue. Moreover, Fr. B and Fr. C is suggested to be the pharmacodynamic material basis for the effect of Yin-Jing of LC. These finding explained that it was recommended to add LC into some prescriptions for treating cardiovascular and cerebrovascular diseases caused by Qi deficiency and blood stasis. This has laid a certain foundation for the research on the Yin-Jing efficacy of LC to better clarify the theory of TCM and guide the clinical application of Yin-Jing drugs. [Display omitted] • To explore the Yin-Jing property of LC by pharmacokinetics and tissue distribution. • A UPLC-MS method was established for the determination of analytes in rat tissues and plasma. • LC has the Yin-Jing function, particularly guiding components into the brain. • Fr. B or Fr. C maybe the material basis of LC for its Yin-Jing efficacy. [ABSTRACT FROM AUTHOR]

• A novel 3D Split&Shuffle-GAN model for 3D medical image generation is proposed, and new inflation strategies are developed to facilitate training of 3D medical generation models. The proposed model significantly improves image generation quality: 14.7 improvements on Frechet Inception Distance with only 48.5% parameters of the baseline. • We conducted comprehensive experiments on both the Heart Coronary CT and Brain MRI images, which verifies the effectives and wide applicability to multiple organs. • Real-world test data has been utilized in this paper: Stanford AIMI Coronary Calcium and Alzheimer's Disease Neuroimaging Initiative. This collaborates the real-world application potential of our technical solution. Background and Objective : The generation of three-dimensional (3D) medical images has great application potential since it takes into account the 3D anatomical structure. Two problems prevent effective training of a 3D medical generative model: (1) 3D medical images are expensive to acquire and annotate, resulting in an insufficient number of training images, and (2) a large number of parameters are involved in 3D convolution. Methods : We propose a novel GAN model called 3D Split&Shuffle-GAN. To address the 3D data scarcity issue, we first pre-train a two-dimensional (2D) GAN model using abundant image slices and inflate the 2D convolution weights to improve the initialization of the 3D GAN. Novel 3D network architectures are proposed for both the generator and discriminator of the GAN model to significantly reduce the number of parameters while maintaining the quality of image generation. Several weight inflation strategies and parameter-efficient 3D architectures are investigated. Results : Experiments on both heart (Stanford AIMI Coronary Calcium) and brain (Alzheimer's Disease Neuroimaging Initiative) datasets show that our method leads to improved 3D image generation quality (14.7 improvements on Frchet inception distance) with significantly fewer parameters (only 48.5% of the baseline method). Conclusions : We built a parameter-efficient 3D medical image generation model. Due to the efficiency and effectiveness, it has the potential to generate high-quality 3D brain and heart images for real use cases. [ABSTRACT FROM AUTHOR]

Remote heart rate estimation aims to predict cardiac activity signals from facial videos without any physical contact, which has been showing promising results recently. However, existing estimation methods based on deep convolutional networks only focus on the rigid receptive field, while ignoring potential spatial correlations of different facial regions, which obviously cannot reduce the overfitting caused by various noise and motion interference unrelated to cardiac activity. To address these issues, this paper proposes PhysGCN, an end-to-end spatiotemporal graph convolutional network with the hyperbolic embedding, to coordinate the contributions of intra- and inter-frame features of facial videos for long-term heart rate estimation. Specifically, firstly, we convert the facial video captured by the vision system into a graph-structure spatiotemporal map, and use the link set of the graph to determine and lock the spatial relative positions of multiple skin sub-regions formed by intra-frame face segmentation and projection. Secondly, to purify the signal and prevent the interference from heart rate irrelevant features, we integrate and measure the similarity between sub-regions within the graph in a non-Euclidean space by a hyperbolic embedding module, which can characterize the correlation more distinctly compared to the plane space. Finally, we dynamically and elaborately orchestrate the inherent temporal and learned spatial features in a graph convolutional module to obtain reliable heart rate waveforms. We conduct extensive comparative experiments and ablation studies on multiple public datasets to verify the superiority and robustness of our method. Experiments show that our method can effectively estimate heart rate from facial videos, and its performance surpasses or matches the state-of-the-art methods. [ABSTRACT FROM AUTHOR]

• As a result of the poor classification results of myocardial fibrosis material in DE-MRI, the research offers an end-to-end myocardial fibrosis tissue detection approach relying on transformer. • When compared to the segmentation technique without canvas matching, boosting the independence assessment and annotations position compared improves performance by 1.76%, 1.27%, 0.93%, and -1.17 mm on Dice, PPV, SEN, and HD. • Experimental findings demonstrate that the mAP of the recognition system in this study is 84.97%, which is higher than the standard benchmark approaches. • The model can effectively improve the efficiency and accuracy of image segmentation and classification. The segmentation and categorization of fibrotic tissue in time-lapse enhanced MRI scanning are quite challenging, and it is mainly done manually for myocardial DE-MRI images. On the other hand, DE-MRI instructions for segmenting and classifying cardiac hypertrophy are complex and prone to inaccuracy. Developing cardiac DE-MRI classification and prediction methods is crucial. This paper introduces a self-supervised myocardial histology segmentation algorithm with multi-scale portrayal consistency to address the degree of sophistication of cardiology DE-MRI. The model retrieves multi-scale representations from multiple expanded viewpoints using a Siamese system and uses resemblance learning instruction to achieve unlabeled representations. The DE-MRI data train the network weights to generate a superior segmentation effect by accurately reflecting the exact scale information. The paper provides an end-to-end method for detecting myocardial fibrosis tissue using a Transformer as a result of the poor classification outcomes of myocardial fibrosis substance in DE-MRI. A deep learning model is created using the Pre-LN Transformer decoded simultaneously with the Multi-Scale Transformer backbone structure developed in this paper. In addition, the joint regression cost, which incorporates the CIoU Loss and the L1 Loss, is used to determine the distance between forecast blocks and labels. Increasing the independent evaluation and annotations position compared enhances performance compared to the segmentation method without canvas matching by 1.76%, 1.27%, 0.93%, and -1.17 mm on Dice, PPV, SEN, and HD, respectively. Based on the strongest of the three single-scale representation methodologies, the segmentation model in this study is enhanced by 0.71%, 0.79%, and 1.47%, as well as -1.49 mm on Dice, PPV, SEN, and HD, respectively. The effectiveness and reliability of the segmentation model are confirmed. Additionally, testing results show that this study's recognition system's mAP is 84.97%, which is greater than the benchmark techniques used in most other studies. The framework converges round is compressed by 18.1% compared to the DETR detection approach, and the identification rate is improved by 3.5%, proving the strategy's value. The self-supervised cardiac fibrosis segmentation method with multi-scale portrayal consistency and end-to-end myocardial histology categorization is introduced in this study. To solve the challenges of segmentation and myocardial fibrosis identification in cardiology DE-MRI, a Transformer-based detection approach is put forth. It may address the issue of the myocardial scarring material's low accuracy in segmentation and classification in DE-MRI, as well as provide clinicians with a fibrosis diagnosis that is supplementary to the conventional therapy of heart ailments. [ABSTRACT FROM AUTHOR]

Background: The Hospital Admission Risk Program (HARP) Cardiac Coach Program at Royal Melbourne Hospital has evolved to include a Greek and Italian service, developed in response to the diverse local community and supported by evidence that Culturally and Linguistically Diverse (CALD) groups both perceive health and respond to health care services and information, differently. This paper aims to evaluate if a phone-based cardiac coaching program can be adapted to the Greek and Italian populations using the English cohort as a comparator.Methods: We retrospectively analysed cardiovascular risk profiles at recruitment into and at discharge from the program. Patients (n=383) were recruited after an acute coronary event or intervention between June 2011 and June 2013. Recruitment was into the English (n=301 patients (79%)) Greek (40 (10%)) or Italian (42 (11%)) model. Data was collected on demographic information and risk factor status at entry and discharge from the program: waist circumference, weight, height, lipid profile, HbA1c, smoking status and physical activity. A comparison of the proportion of patients meeting the defined targets across the English, Italian and Greek cohorts was performed, with multivariate logistic regression analysis applied to adjust for differences in baseline variables.Results: There were baseline differences in age, smoking history, total cholesterol and cholesterol fractions, diastolic blood pressure, weight and physical activity between the cohorts. At discharge, the proportion of patients meeting targets within each cohort were similar.Conclusion: A phone-based integrated disease management program can be adapted to CALD patients, achieving comparable outcomes as compared with an English-speaking cohort. Health services need to respond to their local needs and be flexible in program delivery in order to benefit as many patients as possible. [ABSTRACT FROM AUTHOR]

Fire onboard passenger ships is a major hazard not only for the personnel, passengers, and the environment, but also for the vessel itself. Therefore, the response actions carried out by crewmembers after a fire has been detected onboard a passenger vessel are of outermost importance. SAFEMODE project aims to promote contemporary safety thinking through a collection of carefully selected Human Factors (HFs) Fact Sheets that includes the most-known HFs techniques for accident investigations, to help accident investigators and safety managers within maritime organisations. Therefore, this paper proposes to apply two of the above-mentioned Fact Sheets, namely Hierarchical Task Analysis (HTA) and Human Error Assessment and Reduction Technique (HEART). Hence, this paper initially demonstrates how HTA can be applied to model the human response actions to a fire onboard a passenger vessel, and secondly, it utilises a systematic human error reduction and prediction approach, namely HEART, to predict and quantify which errors are likely to occur. Results from this paper reveal that six human response errors are most likely to occur, with a Human Error Probability of 0.16 according to the HEART analysis. Finally, this paper also suggests remedial measures to mitigate each error identified. • This paper applies the HTA and HEART techniques. • Human actions for fire detection on passenger vessels. • Six human response errors are most likely to occur. • Suggestion of remedial measures to mitigate each error are proposed. [ABSTRACT FROM AUTHOR]

Cardiac resident macrophages play vital roles in heart development, homeostasis, repair, and regeneration. Recent studies documented the hematopoietic potential of cardiac endothelium that supports the generation of cardiac macrophages and peripheral blood cells in mice. However, the conclusion was not strongly supported by previous genetic tracing studies, given the non-specific nature of conventional Cre- loxP tracing tools. Here, we develop an intercellular genetic labeling system that can permanently trace heart-specific endothelial cells based on cell-cell interaction in mice. Results from cell-cell contact-mediated genetic fate mapping demonstrate that cardiac endothelial cells do not exhibit hemogenic potential and do not contribute to cardiac macrophages or other circulating blood cells. This Matters Arising paper is in response to Shigeta et al. (2019), published in Developmental Cell. See also the response by Liu and Nakano (2023), published in this issue. [Display omitted] • Generation of intercellular genetic recording system to label neighboring cells • Genetic tracing of endocardium and coronary endothelial cells by cell-cell contact • Cardiac endothelium does not have hematopoietic potential in development • Cell-cell contact-mediated labeling enhances the specificity of genetic tracing In this Matters Arising article, Liu and Jin et al. re-evaluate the model that the developing endocardium is hemogenic and generates cardiac macrophages and circulating blood cells, which was proposed by Shigeta et al. By using an intercellular genetic tracing system that enables specific labeling of cardiac endothelium, they find that the cardiac endothelium does not have hematopoietic activity during heart development. [ABSTRACT FROM AUTHOR]

In the present paper the behaviour of human cardiac tissue during cryo-ablation is simulated with a finite difference algorithm which solves the Pennes' equation including the phase change during freezing of the cardiac tissues. The evolution of temperatures at different points is calculated and the movement of the ice front is obtained from simulation results. All phenomena related to heat transfer in living tissue are considered: heat conduction, heat release and absorption due to heat capacity, metabolism and blood perfusion. Although the geometry and the assumed boundary conditions are quite simple, the structure of the developed model can be easily adapted to more complex geometries. Model results show for instance that with a power of 10 W tissues distant 0.5 mm from the probe are ablated, while the other tissues more than 0.5 mm remain at −20 °C, so undamaged The results also show that the outcome of cryo-ablation treatment depends on many parameters: operational parameters such as the power heat absorbed by the probe (i.e. the mass flow rate of the cryo-fluid) and the duration of therapy application; biothermal parameters such as metabolic heat flux and blood perfusion; thermophysical properties of the tissue. Among these the effects of both blood perfusion and metabolic rate result less influencing. The numerical model presented could be useful to estimate the best conditions for the application of the probe during treatment and the possible change of the cure parameters to adapt the therapy to different patients. [ABSTRACT FROM AUTHOR]

The diagnosis of cardiovascular diseases is quite important in the field of medical community. An important physiological signal of human body is heart sound and it arises due to the blood turbulence and pulsing of cardiac structures. For the early diagnosis of heart diseases, the analysis of heart sounds play an important role as they contain a huge quantity of pathological information associated with heart. To detect heart sounds, Phonocardiogram (PCG) is used as it is a highly useful and non-invasive technique and can be easily analyzed well. In this paper, some efficient models are proposed for the classification of PCG signals. Two important and robust conglomerated models are proposed initially, wherein the first strategy utilizes the concept of semi-supervised Non-negative Matrix Factorization (NMF) along with Brain Storming (BS) optimization algorithm and an advanced version of BS termed as Advanced BS (ABS) is proposed and then it is merged with Genetic Programming (GP) so that new algorithms such as BS-GP and ABS-GP are formed and finally the features selected through it are fed to classification through machine learning. The second strategy utilizes the concept of using three dimensionality reduction techniques along with Fuzzy C-means (FCM) clustering and then an Advanced Sine-Cosine (ASC) optimization algorithm with three different modifications is proposed for the purpose of feature selection and finally it is classified. Deep learning techniques were also employed in the study such as the usage of an Attention based Bidirectional Long Short-Term Memory (A-BLSTM), Ordinal Variational Autoencoder (O-VAE), Conditional Variational Autoencoders (CVAE), Hyperspherical CVAE (H-CVAE) and the Restricted Boltzmann Machine based Deep Belief Network (RBM-DBN) for the classification of PCG signals. The experiment is conducted on a publicly available dataset and results show that a high classification accuracy of 95.39% is obtained for the semi-supervised NMF concept with ABS-GP technique and Support Vector Machine (SVM) classifier. [ABSTRACT FROM AUTHOR]

Auscultation is often the first clinical analysis realized by doctors when patients have any symptoms related to a heart disease. In a typical scenario of auscultation, heart sounds are interfered by lung sounds both frequency and time domain. This fact causes mixtures that are composed of heart and lung sounds. In this paper, a non-negative matrix factorization (NMF) approach to extract heart sounds from mixtures composed of heart and lung sounds is addressed. Specifically, three contributions motivated by the clustering principle are presented: two of these clusterings are based on spectral content and one is based on temporal content in order to discriminate heart and lung sounds. The first spectral clustering measures the spectral similarity between the bases factorized from NMF and those ones belonging to a dictionary created from a training database composed of only isolated heart sounds. The second spectral clustering analyzes how the energy of the bases, provided by NMF, is distributed along the frequency. The temporal clustering is based on the activations provided by NMF in order to find repetitive temporal patterns hidden in these activations using an estimated heart rate of the mixture in the low frequency range. Evaluation shows that the proposed method obtains promising results and outperforms recent non-based-NMF and based-NMF state-of-the-arts methods. [ABSTRACT FROM AUTHOR]

Objective of the present paper is to review applications of Doppler ultrasonography in sheep. Principles of Doppler ultrasonography and their physiological background are initially presented, as well as haemodynamic parametres that can be used for evaluation of the findings. In sheep, Doppler ultrasonography has been used in clinical work primarily for examination of the reproductive system and of foetuses. It has also been used in studies, where sheep had served as model for studying various conditions in human physiology or medicine, e.g., examination of the heart, which can be performed by conventional Doppler echocardiography or tissue Doppler imaging. Main uses of the modality include evaluation of changes in follicular blood flow in measuring uterine and ovarian blood flow and for determining changes in blood perfusion during various reproductive stages; blood flows in the umbilical artery have also been measured, which can have a clinical application in identifying pregnancies at risk, as well as a model for human medicine. As technology advances, use of Doppler ultrasonography will increase. With more frequent use, new diagnostic and therapeutic approaches will arise, which would be based on estimating functional status (as evidenced by blood perfusion) of the organs examined. [ABSTRACT FROM AUTHOR]

Interpretation of ultrasound videos of the fetal heart is crucial for the antenatal diagnosis of congenital heart disease (CHD). We believe that automated image analysis techniques could make an important contribution towards improving CHD detection rates. However, to our knowledge, no previous work has been done in this area. With this goal in mind, this paper presents a framework for tracking the key variables that describe the content of each frame of freehand 2D ultrasound scanning videos of the healthy fetal heart. This represents an important first step towards developing tools that can assist with CHD detection in abnormal cases. We argue that it is natural to approach this as a sequential Bayesian filtering problem, due to the strong prior model we have of the underlying anatomy, and the ambiguity of the appearance of structures in ultrasound images. We train classification and regression forests to predict the visibility, location and orientation of the fetal heart in the image, and the viewing plane label from each frame. We also develop a novel adaptation of regression forests for circular variables to deal with the prediction of cardiac phase. Using a particle-filtering-based method to combine predictions from multiple video frames, we demonstrate how to filter this information to give a temporally consistent output at real-time speeds. We present results on a challenging dataset gathered in a real-world clinical setting and compare to expert annotations, achieving similar levels of accuracy to the levels of inter- and intra-observer variation. [ABSTRACT FROM AUTHOR]

While ventricular electromechanics is extensively studied in both physiological and pathological conditions, four-chamber heart models have only been addressed recently; most of these works however neglect atrial contraction. Indeed, as atria are characterized by a complex anatomy and a physiology that is strongly influenced by the ventricular function, developing computational models able to capture the physiological atrial function and atrioventricular interaction is very challenging. In this paper, we propose a biophysically detailed electromechanical model of the whole human heart that considers both atrial and ventricular contraction. Our model includes: (i) an anatomically accurate whole-heart geometry; (ii) a comprehensive myocardial fiber architecture; (iii) a biophysically detailed microscale model for the active force generation; (iv) a 0D closed-loop model of the circulatory system, fully-coupled with the mechanical model of the heart; (v) the fundamental interactions among the different core models , such as the mechano-electric feedback or the fibers-stretch and fibers-stretch-rate feedbacks; (vi) specific constitutive laws and model parameters for each cardiac region. Concerning the numerical discretization, we propose an efficient segregated-intergrid-staggered scheme that includes a computationally efficient strategy to handle the non-conductive regions. We also propose extending recent stabilization techniques – regarding the circulation and the fibers-stretch-rate feedback – to the whole heart, demonstrating their cruciality for obtaining a stable formulation in a four-chamber scenario. We are able to reproduce the healthy cardiac function for all the heart chambers, in terms of pressure–volume loops, time evolution of pressures, volumes and fluxes, and three-dimensional cardiac deformation, with volumetric indexes within reference ranges for cardiovascular magnetic resonance. We also show the importance of considering atrial contraction, fibers-stretch-rate feedback and the proposed stabilization techniques, by comparing the results obtained with and without these features in the model. In particular, we show that the fibers-stretch-rate feedback, often neglected due to the numerical challenges that it entails, plays a fundamental role in the regulation of the blood flux ejected by ventricles. The proposed model represents the state-of-the-art electromechanical model of the iHEART ERC project – an Integrated Heart Model for the Simulation of the Cardiac Function – and is a fundamental step toward the building of physics-based digital twins of the human heart. • We propose a novel whole-heart electromechanical model including atrial contraction. • Physiological atrial eight-shaped pressure–volume loops. • Numerical results within reference ranges for cardiovascular magnetic resonance. • Fibers-stretch-rate feedback essential to avoid unphysiologically large fluxes. • Crucial interplay among accurate mathematical models and stable numerical methods. [ABSTRACT FROM AUTHOR]

Abstract: The purpose of this paper is to provide an overview of the life of the physician and theologian Michael Servetus and to discuss his analysis of the pulmonary circulation. Writers have praised Servetus for his commitment to educating his colleagues about what he heralded as the truth, and criticized him for his perceived arrogance. Servetus made contributions to the fields of geography, astrology, theology, and medicine. This paper refers to the translation of a portion of Servetus' book Christianismi Restitutio by Charles D. O'Malley. [Copyright &y& Elsevier]

Abstract: Radiotherapy treatment, like many other fields of medicine, has changed significantly in the last decade with the introduction of more advanced technology and automation. This change has often resulted in aspects of the system which cannot be automated due to technological feasibility and local implementation constraints. This has resulted in a requirement for significant human interaction. This combination of human operations and automation has introduced new error pathways. Traditionally, recommendations to improve the safety of such systems are typically made after the analysis of an adverse event or a significant series of incidents. In contrast, adopting a proactive approach to safety would enable prior identification of potential errors and the specification of appropriate defences against them, thus avoiding costs associated with adverse outcomes. In this paper, a modified version of the proactive Human Reliability Assessment (HRA) method Human Error Assessment and Reduction Technique (HEART) was used to analyse a critical nursing task within a modern radiotherapy system. The modified technique used a participative team approach to complete the assessment in contrast to the normal approach, which uses a single expert assessor. The HEART technique quantifies the likelihood of unreliability of a task and ranks the conditions which most affect the successful completion of that task. HEART has been proposed as a potentially useful HRA tool for applications in healthcare, but such applications have not previously been formally documented. As a result of the modified HEART analysis reported in this paper, remedial measures were identified which were both cost effective and easy to implement. [Copyright &y& Elsevier]

Summary: Anatomical and functional studies of the autonomic innervation in the lung and the heart of the bichirs are lacking. The present review paper describes the presence of nerve fibers located in the muscle layers of the lung and its submucosa, the collection of unipolar neurons found in the submucosal and muscle layers of the glottis in a bichir species (Polypterus bichir bichir). Putative oxygen chemoreceptive, neuroepithelial cells (NECs) in the lung mucosa are also included. The latter share many immunohistochemical characteristics similar to those observed in the carotid body and neuroepithelial bodies of mammals. A packed collection of paraganglion cells is located within the trunk of the pulmonary vagus nerves. The paper also examines the occurrence of intracardiac neurons and nerve fibers in the heart of the above species. These studies show that various neurotransmitters may indicate different patterns of innervation in the lung and the heart of the bichirs. However, there is still much to be discovered about the lung and cardiovascular nervous control of these primitive fishes. [Copyright &y& Elsevier]

Proffered Papers: Proffered papers 12: Artificial Intelligence and automation OC-0224: Fully automated heart dose calculation from cine MV images recorded during breast cancer treatments S.S. Andreasen, C. Muurholm, S. Skouboe, H. Spejlborg, B. Offersen, P.R. Poulsen. [Extracted from the article]

Proffered Papers: Proffered papers 8: Cardiac toxicity OC-0198: Heart sparing radiotherapy in breast cancer: the importance of baseline cardiac risks S. Schönecker, A. Gaasch, C. Simonetto, M. Eidemüller, D. Reitz, M. Pazos, M. Rottler, P. Freislederer, M. Braun, N. Harbeck, M. Niyazi, C. Belka, S. Corradini. [Extracted from the article]

Proffered Papers: Proffered papers 8: Cardiac toxicity OC-0196: Cardiac sub-volume targeting demonstrates regional radiosensitivity in the mouse heart K. Butterworth, K. Williams, M. Van Herk, A. McWilliam, M. Aznar, S. McMahon, E. Vasques Osorio, K. Edgar, G. Walls, E. Gill, M. Ghita. [Extracted from the article]

Abstract: This paper describes the measurement and reconstruction of the leaflet geometry for a pericardial heart valve. Tasks involved include mapping the leaflet geometries by laser digitizing and reconstructing the 3D freeform leaflet surface based on a laser scanned profile. The challenge is to design a prosthetic valve that maximizes the benefits offered to the recipient as compared to the normally operating naturally-occurring valve. This research was prompted by the fact that artificial heart valve bioprostheses do not provide long life durability comparable to the natural heart valve, together with the anticipated benefits associated with defining the valve geometries, especially the leaflet geometries for the bioprosthetic and human valves, in order to create a replicate valve fabricated from synthetic materials. Our method applies the concept of reverse engineering in order to reconstruct the freeform surface geometry. A Brown & Shape coordinate measuring machine (CMM) equipped with a HyMARC laser-digitizing system was used to measure the leaflet profiles of a Baxter Carpentier-Edwards® pericardial heart valve. The computer software, Polyworks was used to pre-process the raw data obtained from the scanning, which included merging images, eliminating duplicate points, and adding interpolated points. Three methods, creating a mesh model from cloud points, creating a freeform surface from cloud points, and generating a freeform surface by B-splines are presented in this paper to reconstruct the freeform leaflet surface. The mesh model created using Polyworks can be used for rapid prototyping and visualization. To fit a freeform surface to cloud points is straightforward but the rendering of a smooth surface is usually unpredictable. A surface fitted by a group of B-splines fitted to cloud points was found to be much smoother. This method offers the possibility of manually adjusting the surface curvature, locally. However, the process is complex and requires additional manipulation. Finally, this paper presents a reverse engineered design for the pericardial heart valve which contains three identical leaflets with reconstructed geometry. [Copyright &y& Elsevier]