Coronavirus disease 2019 (COVID-19), a disease caused by the novel betacoronavirus (SARS-CoV-2), has become a global pandemic threat. The potential involvement of COVID-19 in central nervous system ...(CNS) has attracted considerable attention due to neurological manifestations presented throughout the disease process. In addition, SARS-CoV-2 is structurally similar to SARS-CoV, and both bind to the angiotensin-converting enzyme 2 (ACE2) receptor to enter human cells. Thus, cells expressing ACE2, such as neurons and glial cells may act as targets and are thus vulnerable to SARS-CoV-2 infection. Here, we have reviewed the neurological characteristics of COVID-19 and summarized possible mechanisms of SARS-CoV-2 invasion of the CNS. COVID-19 patients have presented with a number of different neurological symptoms such as headache, dizziness, hyposmia, and hypogeusia during the course of illness. It has also been reported recently that some cases of COVID-19 have presented with concurrent acute cerebrovascular disease (acute ischemic stroke, cerebral venous sinus thrombosis, cerebral hemorrhage, subarachnoid hemorrhage), meningitis/encephalitis, acute necrotizing hemorrhagic encephalopathy, and acute Guillain–Barré syndrome. Furthermore, SARS-CoV-2 RNA detected in a cerebrospinal fluid specimen of a patient with COVID-19 have provided direct evidence to support the theory of neurotropic involvement of SARS-CoV-2. However, the underlying neurotropic mechanisms of SARS-CoV-2 are yet to be established. SARS-CoV-2 may affect CNS through two direct mechanisms (hematogenous dissemination or neuronal retrograde dissemination) or via indirect routes. The underlying mechanisms require further elucidation in the future.
•VNS may be effective in treating a wider range of brain diseases.•VNS can exert its effect through the anti-inflammatory and central mechanisms.•The liver, spleen, gut, and brain are involved in the ...anti-inflammatory mechanisms.•The central mechanisms are related to monoamine, GABA, BDNF-TrkB, CBF and functional connectivity of brain regions.
Brain diseases, including neurodegenerative, cerebrovascular and neuropsychiatric diseases, have posed a deleterious threat to human health and brought a great burden to society and the healthcare system. With the development of medical technology, vagus nerve stimulation (VNS) has been approved by the Food and Drug Administration (FDA) as an alternative treatment for refractory epilepsy, refractory depression, cluster headaches, and migraines. Furthermore, current evidence showed promising results towards the treatment of more brain diseases, such as Parkinson’s disease (PD), autistic spectrum disorder (ASD), traumatic brain injury (TBI), and stroke. Nonetheless, the biological mechanisms underlying the beneficial effects of VNS in brain diseases remain only partially elucidated. This review aims to delve into the relevant preclinical and clinical studies and update the progress of VNS applications and its potential mechanisms underlying the biological effects in brain diseases.
We derive a set of nontrivial relations between second-order transport coefficients which follow from the second law of thermodynamics upon considering a regime close to uniform rotation of the ...fluid. We demonstrate that an extension of hydrodynamics by spin variable is equivalent to modifying conventional hydrodynamics by a set of second-order terms satisfying the relations we derived. We point out that a novel contribution to the heat current orthogonal to vorticity and temperature gradient reminiscent of the thermal Hall effect is constrained by the second law.
Recently, more and more smart homes have become one of important parts of home infrastructure. However, most of the smart home applications are not interconnected and remain isolated. They use the ...cloud center as the control platform, which increases the risk of link congestion and data security. Thus, in the future, smart homes based on edge computing without using cloud center become an important research area. In this paper, we assume that all applications in a smart home environment are composed of edge nodes and users. In order to maximize the utility of users, we assume that all users and edge nodes are placed in a market and formulate a pricing resource allocation model with utility maximization. We apply the Lagrangian method to analyze the model, so an edge node (provider in the market) allocates its resources to a user (customer in the market) based on the prices of resources and the utility related to the preference of users. To obtain the optimal resource allocation, we propose a pricing-based resource allocation algorithm by using low-pass filtering scheme and conform that the proposed algorithm can achieve an optimum within reasonable convergence times through some numerical examples.
An increasing number of people undergo anesthesia and surgery. Perioperative neurocognitive and depressive disorders are common central nervous system complications with similar pathogeneses. These ...conditions pose a deleterious threat to human health and a significant societal burden. In recent years, numerous studies have focused on the role of the gut microbiota and its metabolites in the central nervous system via the gut-brain axis. Its involvement in perioperative neurocognitive and depressive disorders has attracted considerable attention. This review aimed to elucidate the role of the gut microbiota and its metabolites in the pathogenesis of perioperative neurocognitive and depressive disorders, as well as the value of targeted interventions and treatments.
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•Microbiota-gut-brain axis plays a crucial role in perioperative neurocognitive disorders.•Microbiota-gut-brain axis plays a crucial role in perioperative depressive disorders.•Gut microbiota-based interventions may offer promising therapeutic avenues for these disorders.
The coherence factor (CF) is defined as the ratio of coherent power to incoherent power received by the radar aperture. The incoherent power is computed by the multi-antenna receiver based only on ...the spatial variable. In this respect, it is a 1-D CF, and thereby the image sidelobes in down-range cannot be effectively suppressed. We propose a 2-D CF by supplementing the 1-D CF by an incoherent sum dealing with the frequency dimension. In essence, we employ both spatial diversity and frequency diversity which, respectively, enhance imaging quality in cross-range and range. Simulations and experimental results are provided to demonstrate the performance advantages of the proposed approach.
Recent progress in compressive sensing underscores the importance of exploiting intrinsic structures in sparse signal reconstruction. In this letter, we propose a Markov random field (MRF) prior in ...conjunction with fast iterative shrinkage-thresholding algorithm (FISTA) for image reconstruction. The MRF prior is used to represent the support of sparse signals with clustered nonzero coefficients. The proposed approach is applied to the inverse synthetic aperture radar (ISAR) imaging problem. Simulations and experimental results are provided to demonstrate the performance advantages of this approach in comparison with the standard FISTA and existing MRF-based methods.
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