Mcnultyclark9170

women farmers had low awareness of zoonotic diseases. In conclusion, the priorities of national disease control programs do not fully match priorities of farmers. Such participatory tools should therefore, play a pivotal role when designing sustainable livestock health interventions. Copyright © 2019 Alemu, Desta, Kinati, Mulema, Gizaw and Wieland.Objective The aim of this feasibility study was to investigate methemoglobin modulation in vivo as a potential magnetic resonance imaging (MRI) gadolinium based contrast agent (GBCA) alternative. Recently, gadolinium tissue deposition was identified and safety concerns were raised after adverse effects were discovered in canines and humans. Because of this, alternative contrast agents are warranted. One potential alternative is methemoglobinemia induction, which can create T1-weighted signal in vitro. Canines with hereditary methemoglobinemia represent a unique opportunity to investigate methemoglobin modulation. Our objective was to determine if methemoglobinemia could create high intravascular T1-signal in vivo with reversal using methylene blue. Methods To accomplish this study, a 1.5-year-old male-castrated mixed breed canine with hereditary methemoglobinemia underwent 3T-MRI/MRA with T1-weighted sequences including 3D-T1-weighted Magnetization Prepared Rapid Acquisition Gradient Echo (MPRAGE) and 3D-Time 1.54 ± 0.16-fold) but not in carotid arteries (2.12 ± 0.10 vs. 2.16 ± 0.11, p = 0.07, 0.98 ± 0.03-fold). On 3D-TOF, visible signal change was in IVVP (1.64 ± 0.14 vs. 1.09 ± 0.11, p less then 0.001, 1.50 ± 0.11-fold) and there was moderate change in external jugular vein signal (1.51 ± 0.13 vs. 1.19 ± 0.08, p less then 0.001, 1.27 ± 0.07-fold). There were also small but significant differences in ventral spinal arterial signal (2.00 ± 0.12 vs. 1.78 ± 0.10, p = 0.002, 1.13 ± 0.10-fold) but not carotid arteries (2.03 ± 0.17 vs. 1.99 ± 0.17, p = 0.15, 1.02 ± 0.04-fold). Conclusion Methemoglobin modulation produces intravascular contrast on T1-weighted MRI in vivo. Additional studies are warranted to optimize methemoglobinemia induction, sequence parameters for maximal tissue contrast, and safety parameters prior to clinical implementation. Copyright © 2019 McNally, Jaffey, Kim, Alexander, Shumway, Cohn, Parker and Day.Cardiac imaging plays an important role in the diagnosis of cardiovascular disease (CVD). check details Until now, its role has been limited to visual and quantitative assessment of cardiac structure and function. However, with the advent of big data and machine learning, new opportunities are emerging to build artificial intelligence tools that will directly assist the clinician in the diagnosis of CVDs. This paper presents a thorough review of recent works in this field and provide the reader with a detailed presentation of the machine learning methods that can be further exploited to enable more automated, precise and early diagnosis of most CVDs. Copyright © 2020 Martin-Isla, Campello, Izquierdo, Raisi-Estabragh, Baeßler, Petersen and Lekadir.Cardiovascular conditions remain the leading cause of mortality and morbidity worldwide, with genotype being a significant influence on disease risk. Cardiac imaging-genetics aims to identify and characterize the genetic variants that influence functional, physiological, and anatomical phenotypes derived from cardiovascular imaging. High-throughput DNA sequencing and genotyping have greatly accelerated genetic discovery, making variant interpretation one of the key challenges in contemporary clinical genetics. Heterogeneous, low-fidelity phenotyping and difficulties integrating and then analyzing large-scale genetic, imaging and clinical datasets using traditional statistical approaches have impeded process. Artificial intelligence (AI) methods, such as deep learning, are particularly suited to tackle the challenges of scalability and high dimensionality of data and show promise in the field of cardiac imaging-genetics. Here we review the current state of AI as applied to imaging-genetics research and discuss outstanding methodological challenges, as the field moves from pilot studies to mainstream applications, from one dimensional global descriptors to high-resolution models of whole-organ shape and function, from univariate to multivariate analysis and from candidate gene to genome-wide approaches. Finally, we consider the future directions and prospects of AI imaging-genetics for ultimately helping understand the genetic and environmental underpinnings of cardiovascular health and disease. Copyright © 2020 de Marvao, Dawes and O'Regan.Novel anticancer medicines, including targeted therapies and immune checkpoint inhibitors, have greatly improved the management of cancers. However, both conventional and new anticancer treatments induce cardiac adverse effects, which remain a critical issue in clinic. Cardiotoxicity induced by anti-cancer treatments compromise vasospastic and thromboembolic ischemia, dysrhythmia, hypertension, myocarditis, and cardiac dysfunction that can result in heart failure. Importantly, none of the strategies to prevent cardiotoxicity from anticancer therapies is completely safe and satisfactory. Certain clinically used cardioprotective drugs can even contribute to cancer induction. Since G protein coupled receptors (GPCRs) are target of forty percent of clinically used drugs, here we discuss the newly identified cardioprotective agents that bind GPCRs of adrenalin, adenosine, melatonin, ghrelin, galanin, apelin, prokineticin and cannabidiol. We hope to provoke further drug development studies considering these GPCRs as potential targets to be translated to treatment of human heart failure induced by anticancer drugs. Copyright © 2020 Audebrand, Désaubry and Nebigil.Mitophagy plays a major role in heart physiology. Impairment of Parkin-dependent mitophagy in heart is known to be deleterious. Obesity is a known cardiovascular risk factor. Impaired autophagy has been reported in models of obesity or hyperlipidemia/hypercholesterolemia; however less is known regarding obesity and mitophagy. The aim of this study was to evaluate the regulation of Parkin expression in hearts of mice fed a high fat diet. Interestingly, we found a significant decrease in Parkin protein in hearts of HFD mice compared those fed a low-fat diet. This was associated with mitochondrial dysfunction in the context of ischemia/reperfusion (I/R). This downregulation was not associated with a decrease in Parkin mRNA expression. We did not detect any change in the degradation rate of Parkin and only a slight decrease in its translation. The reduction of Parkin protein abundance in HFD hearts remains a mystery and will need further studies. However, Parkin depletion in the setting of obesity may contribute to cardiovascular risk.