β-Amyloid (Aβ)-induced neuronal toxicity in Alzheimer's disease (AD) is associated with complex mechanisms. Thus, a multi-target approach might be suitable for AD treatment. Following our previous study on the neuroprotective effects of red ginseng oil extract, its major compounds, including linoleic acid (LA), β-sitosterol (BS), and stigmasterol (SS), were examined to elucidate the mechanism of anti-apoptosis and anti-inflammation in Aβ25-35-stimulated PC12 cells. The results showed that the three compounds mitigated Aβ25-35 toxicity by regulating oxidative stress, apoptotic responses, and pro-inflammatory mediators. LA and SS strongly regulated intrinsic apoptosis markers, such as mitochondrial membrane potential, intracellular Ca2+, Bax/Bcl-2 ratio, and caspases-9, -3, and -8. However, BS blocked only the intrinsic apoptotic pathway, particularly by suppressing Ca2+ accumulation. Furthermore, all three compounds downregulated iNOS and phospho-nuclear factor-κB, but only LA and SS inhibited the expression of cyclooxygenase-2 and phospho-IκB. In assays to evaluate MAPK expression for confirming upstream signal pathways, BS decreased the phosphorylation of p38 and ERK, but not JNK, while SS markedly decreased the phosphorylation of all three MAPKs, and LA clearly decreased the phosphorylation of ERK and JNK, but not p38. These results indicate that LA, BS, and SS act as neuroprotectives against Aβ25-35-induced injury by distinct molecular mechanisms, indicating their preventive and/or therapeutic potential to treat AD.

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This study aimed to organize the system features of decision support technologies targeted at nursing practice into assessment, problem identification, care plans, implementation, and outcome evaluation. It also aimed to identify the range of the five stage-related sequential decision supports that computerized clinical decision support systems provided. MEDLINE, CINAHL, and EMBASE were searched. A total of 27 studies were reviewed. The system features collected represented the characteristics of each category from patient assessment to outcome evaluation. Several features were common across the reviewed systems. For the sequential decision support, all of the reviewed systems provided decision support in sequence for patient assessment and care plans. Fewer than half of the systems included problem identification. There were only three systems operating in an implementation stage and four systems in outcome evaluation. Consequently, the key steps for sequential decision support functions were initial patient assessment, problem identification, care plan, and outcome evaluation. Providing decision support in such a full scope will effectively help nurses' clinical decision making. By organizing the system features, a comprehensive picture of nursing practice-oriented computerized decision support systems was obtained; however, the development of a guideline for better systems should go beyond the scope of a literature review.

β-site amyloid precursor protein cleaving enzyme 1 (BACE1) plays a role in generating amyloid β (Aβ), thus playing a major part early in the pathogenesis of Alzheimer's disease (AD). BACE1 has emerged as a crucial therapeutic target for decreasing the Aβ concentration in the AD brain. To explore natural BACE1 inhibitors, the present study concentrated on isoflavones, including genistein, formononetin, glycitein, daidzein, and puerarin. In this study, in vitro anti-AD activities were assessed using BACE1 inhibition assays, as well as enzyme kinetic predictions. Molecular docking analysis was applied to design potential BACE1 inhibitors. Among the major isoflavones, genistein exerted a notable BACE1 inhibition through reversible noncompetitive mechanism, while other compounds were less potent against BACE1. The docking study revealed that genistein had negative binding energy (-8.5 kcal/mol) and was stably positioned in the allosteric domains of BACE1 residues. It interacted with important amino acid residues in BACE1, such as ASN37, GLN73, and TRP76, through hydrogen bonding. The results suggested that genistein may be beneficial for preventing and/or treating AD. Furthermore, it may provide potential guidelines for the design of new BACE1 inhibitors.

Cloud computing has received a lot of attention from both researcher and developer in last decade due to its unique structure of providing services to the user. As the digitalization of world, heterogeneous devices, and with the emergence of Internet of Things (IoT), these IoT devices produce different type of data with distinct frequency, which require real‐time and latency sensitive services. This provides great challenge to cloud computing framework. Fog computing is a new framework to accompaniment cloud platform and is proposed to extend services to the edge of the network. In fog computing, the entire user's tasks are offloaded to distributed fog nodes to the edge of network to avoid delay sensitivity. We select fog computing network dwell different set of fog nodes to provide required services to the users. Allocation of defined resource to the users in order to achieve optimal result is a big challenge. Therefore, we propose dynamic resource allocation strategy for cloud, fog node, and users. In the framework, we first formulate the ranks of fog node using TOPSIS to identify most suitable fog node for the incoming request. Simultaneously logistic regression calculates the load of individual fog node and updates the result to send back to the broker for next decision. Simulation results demonstrate that the proposed scheme undoubtedly improves the performance and give accuracy of 98.25%.