We further validated in MIHA cell that the total cholesterol (TC) level in GRB10-Mut was significantly reduced compared with GRB10-WT; p = 0.0005. Likewise, the reversed palmitic acid (PA) induced lipid droplet formation in GRB10-Mut was more effective than in GRB10-WT. These results suggest that rs1800504 of GRB10 variant may be associated with the blood lipids and then may also related to the risk of CHD in patients with T2DM.Objective The study objective was to evaluate the effect of en bloc arch reconstruction with frozen elephant trunk (FET) technique for acute type A aortic dissection. Methods 41 patients with acute Stanford type A dissection underwent en bloc arch reconstruction combined with FET implantation between April 2018 and August 2020. The mean age of the patients was 46 ± 13 years, and 9 patients were female. One patient had Marfan syndrome. Six patients had pericardial tamponade, 9 had pleural effusion, 5 had transient cerebral ischemic attack, and 3 had chronic kidney disease. Results The hospital mortality rate was 9.8% (4 patients). 2 (4.9%) patients had stroke, 23 (56.1%) had acute kidney injury, and 5 (12.2%) had renal failure requiring hemodialysis. During follow-up, the rate of complete false lumen thrombosis was 91.6% (33/36) around the FET, 69.4% (25/36) at the diaphragmatic level, and 27.8% (10/36) at the superior mesenteric artery level. The true lumen diameter at the same three levels of the descending aorta increased significantly while the false lumen diameter reduced at the two levels pulmonary bifurcation and the diaphragm. The 1-, 2-and 3-year actuarial survival rates were 90.2% [95% confidence interval (CI), 81.2-99.2], 84.2% (95% CI, 70.1-98.3) and 70.2% (95% CI, 42.2-98), respectively. Conclusions In patients with acute type A dissection, en bloc arch reconstruction with FET technique appeared to be feasible and effective with early clinical follow-up results. Future studies including a large sample size and long-term follow-up are required to evaluate the efficacy.Background Previous studies suggested that myocardial work (MW) may identify abnormalities in the left ventricular (LV) function and establish a more sensitive index for LV dysfunction at the early stage. This study aimed to explore the value of global and regional MW parameters in predicting high-risk stable coronary artery disease (SCAD) patients with normal wall motion and preserved LV function. Patients and Methods A total of 131 patients, who were clinically diagnosed as SCAD with normal wall motion and LV function, were finally included in this study. Global MW parameters, including global work index (GWI), global constructive work (GCW), global waste work (GWW), and global work efficiency (GWE) were measured with non-invasive LV pressure-strain loops constructed from speckle-tracking echocardiography. Regional myocardial work index (RWI) and work efficiency (RWE) were also calculated according to the perfusion territory of each major coronary artery. All patients underwent coronary angiography and wererespectively (P less then 0.001). When we combined RWI in two or three perfusion regions, the diagnostic performance of SCAD was improved (P less then 0.001). Conclusions Both global and regional MW parameters have great potential in non-invasively predicting high-risk SCAD patients with normal wall motion and preserved LV function, contributing to the early identification of high-risk patients who may benefit from revascularization therapy.Plaque erosion (PE) is one of the most important pathological mechanisms underlying acute coronary syndrome (ACS). The incidence of PE is being increasingly recognized owing to the development and popularization of intracavitary imaging. Unlike traditional vulnerable plaques, eroded plaques have unique pathological characteristics. Moreover, recent studies have revealed that there are differences in the physiopathological mechanisms, biomarkers, and clinical outcomes between PE and plaque rupture (PR). Accurate diagnosis and treatment of eroded plaques require an understanding of the pathogenesis of PE. In this review, we summarize recent scientific discoveries of the pathological characteristics, mechanisms, biomarkers, clinical strategies, and prognosis in patients with PE.Notch signaling is a highly conserved signaling system that is required for embryonic development and regeneration of organs. When the signal is lost, maldevelopment occurs and leads to a lethal state. Delivering exogenous genetic materials encoding Notch into cells can reestablish downstream signaling and rescue cellular functions. In this study, we utilized the negatively charged and FDA approved polymer poly(lactic-co-glycolic acid) to encapsulate Notch Intracellular Domain-containing plasmid in nanoparticles. We show that primary human umbilical vein endothelial cells (HUVECs) readily uptake the nanoparticles with and without specific antibody targets. We demonstrated that our nanoparticles are non-toxic, stable over time, and compatible with blood. We further demonstrated that HUVECs could be successfully transfected with these nanoparticles in static and dynamic environments. Lastly, we elucidated that these nanoparticles could upregulate the downstream genes of Notch signaling, indicating that the payload was viable and successfully altered the genetic downstream effects.Neutron stars (NSs) are extraordinary not only because they are the densest form of matter in the visible Universe but also because they can generate magnetic fields ten orders of magnitude larger than those currently constructed on earth. The combination of extreme gravity with the enormous electromagnetic (EM) fields gives rise to spectacular phenomena like those observed on August 2017 with the merger of a binary neutron star system, an event that generated a gravitational wave (GW) signal, a short γ -ray burst (sGRB), and a kilonova. This event serves as the highlight so far of the era of multimessenger astronomy. In this review, we present the current state of our theoretical understanding of compact binary mergers containing NSs as gleaned from the latest general relativistic magnetohydrodynamic simulations. Such mergers can lead to events like the one on August 2017, GW170817, and its EM counterparts, GRB 170817 and AT 2017gfo. In addition to exploring the GW emission from binary black hole-neutron star and neutron star-neutron star mergers, we also focus on their counterpart EM signals. In particular, we are interested in identifying the conditions under which a relativistic jet can be launched following these mergers. Such a jet is an essential feature of most sGRB models and provides the main conduit of energy from the central object to the outer radiation regions. Jet properties, including their lifetimes and Poynting luminosities, the effects of the initial magnetic field geometries and spins of the coalescing NSs, as well as their governing equation of state, are discussed. Lastly, we present our current understanding of how the Blandford-Znajek mechanism arises from merger remnants as the trigger for launching jets, if, when and how a horizon is necessary for this mechanism, and the possibility that it can turn on in magnetized neutron ergostars, which contain ergoregions, but no horizons.We propose a tool-use model that enables a robot to act toward a provided goal. It is important to consider features of the four factors; tools, objects actions, and effects at the same time because they are related to each other and one factor can influence the others. The tool-use model is constructed with deep neural networks (DNNs) using multimodal sensorimotor data; image, force, and joint angle information. To allow the robot to learn tool-use, we collect training data by controlling the robot to perform various object operations using several tools with multiple actions that leads different effects. Then the tool-use model is thereby trained and learns sensorimotor coordination and acquires relationships among tools, objects, actions and effects in its latent space. We can give the robot a task goal by providing an image showing the target placement and orientation of the object. Using the goal image with the tool-use model, the robot detects the features of tools and objects, and determines how to act to reproduce the target effects automatically. Then the robot generates actions adjusting to the real time situations even though the tools and objects are unknown and more complicated than trained ones.Tactile hands-only training is particularly important for medical palpation. Generally, equipment for palpation training is expensive, static, or provides too few study cases to practice on. We have therefore developed a novel haptic surface concept for palpation training, using ferrogranular jamming. The concept's design consists of a tactile field spanning 260 x 160 mm, and uses ferromagnetic granules to alter shape, position, and hardness of palpable irregularities. Granules are enclosed in a compliant vacuum-sealed chamber connected to a pneumatic system. A variety of geometric shapes (output) can be obtained by manipulating and arranging granules with permanent magnets. The tactile hardness of the palpable output can be controlled by adjusting the chamber's vacuum level. A psychophysical experiment (N = 28) investigated how people interact with the palpable surface and evaluated the proposed concept. Untrained participants characterized irregularities with different position, form, and hardness through pow that the concept can render irregularities with different position, form, and hardness, and that users are able to locate and characterize these through palpation. Participants experienced an improvement in palpation skills throughout the experiment, which indicates the concepts feasibility as a palpation training device.The storytelling lens in human-computer interaction has primarily focused on personas, design fiction, and other stories crafted by designers, yet informal personal narratives from everyday people have not been considered meaningful data, such as storytelling from older adults. Storytelling may provide a clear path to conceptualize how technologies such as social robots can support the lives of older or disabled individuals. To explore this, we engaged 28 older adults in a year-long co-design process, examining informal stories told by older adults as a means of generating and expressing technology ideas and needs. This paper presents an analysis of participants' stories around their prior experience with technology, stories shaped by social context, and speculative scenarios for the future of social robots. From this analysis, we present suggestions for social robot design, considerations of older adults' values around technology design, and promotion of participant stories as sources for design knowledge and shifting perspectives of older adults and technology.While earlier research in human-robot interaction pre-dominantly uses rule-based architectures for natural language interaction, these approaches are not flexible enough for long-term interactions in the real world due to the large variation in user utterances. In contrast, data-driven approaches map the user input to the agent output directly, hence, provide more flexibility with these variations without requiring any set of rules. However, data-driven approaches are generally applied to single dialogue exchanges with a user and do not build up a memory over long-term conversation with different users, whereas long-term interactions require remembering users and their preferences incrementally and continuously and recalling previous interactions with users to adapt and personalise the interactions, known as the lifelong learning problem. https://www.selleckchem.com/products/Cyclopamine.html In addition, it is desirable to learn user preferences from a few samples of interactions (i.e., few-shot learning). These are known to be challenging problems in machine learning, while they are trivial for rule-based approaches, creating a trade-off between flexibility and robustness.