Aplastic anemia (AA) is an autoimmune disorder characterized by bone marrow and peripheral blood pancytopenia. Different environmental and genetical conditions could be effective in an outbreak of this disease. The exact pathogenesis of this disease, however, is still idiopathic. The present study is based on Pubmed database information (2002–2021) using the words “Aplastic Anemia,” “Hematopoietic Stem Cells niche,” “Signaling pathway,” “Cytokines,” and “Immuno cells.” In this disease, both hematopoietic stem cells and mesenchymal stromal cells are impaired, which is associated with impaired hematopoiesis and decreased hematopoietic cells. Inflammatory cytokines increase, which changes the ratio of T lymphocytes and leads to disease progression. In addition, the most common mechanism of AA is damage by the immune system, which leads to increased apoptosis in progenitor cells. We have shown in this review that the disease involves quantitative defects in stem cell numbers and qualitative abnormalities in the function of these cells and the activity of many different cellular and molecular factors can damage hematopoietic cells and the protective substrate of these cells in this disease.
In this paper, we propose a joint radio and core resource allocation framework for NFV-enabled networks. In the proposed system model, the goal is to maximize energy efficiency (EE), by guaranteeing end-to-end (E2E) quality of service (QoS) for different service types. To this end, we formulate an optimization problem in which power and spectrum resources are allocated in the radio part. In the core part, the chaining, placement, and scheduling of functions are performed to ensure the QoS of all users. This joint optimization problem is modeled as a Markov decision process (MDP), considering time-varying characteristics of the available resources and wireless channels. A soft actor-critic deep reinforcement learning (SAC-DRL) algorithm based on the maximum entropy framework is subsequently utilized to solve the above MDP. Numerical results reveal that the proposed joint approach based on SAC-DRL algorithm could significantly reduce energy consumption compared to the case in which R-RA and NFV-RA problems are optimized separately.
After freezing the first phase of the fifth generation of wireless networks (5G) standardization, it finally goes live now and the roll out of the commercial launch (most in fixed 5G broadband services) and migration has been started. However, some challenges are arising in the deployment, integration of each technology, and the interoperability in the network of the communication service providers (CSPs). At the same time, the evolution of 5G is not clear and many questions arise such as whether 5G has long-term evolution or when 5G will change to a next-generation one. This paper provides long-term migration options and paths towards 5G considering many key factors such as the cost, local/national data traffic, marketing, and the standardization trends in the radio access network (RAN), the transport network (TN), the core network (CN), and E2E network. Moreover, we outline some 5G evolution road maps emphasizing on the technologies, standards, and the service time lines. The proposed migration paths can be the answer to some CSPs' concerns about how to do long-term migration to 5G and beyond.
Introduction: Radiotherapy is one of the most common cancer treatment modalities. The goal of this study was to establish the rates and causes of radiotherapy interruptions in cancer patients at Ahvaz Golestan Hospital.Methods: In this retrospective study, the data were collected during period from 2012 to 2013, from cancer patients who received radiation therapy at Golestan Hospital. Demographic characteristics and radiotherapy interruption frequency and reasons were reviewed and analyzed. Results: Among 1476 cases, 70.7% of patients had no radiotherapy interruption. The most common cause of treatment interruption was equipment damages and/or maintenance in 29.5% of patients. There were statistically significant relations between radiotherapy interruption with site of cancer (P=0.014) and living place of patients (P=0.006), respectively.Conclusion: Generally, treatment interruption at our center was not much higher than other centers; however, the most common cause of treatment interruption was equipment damages and/or maintenance, which was higher than most centers.
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