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Interferon types-I/II (IFN-αβ/γ) secretions are well-established antiviral host defenses. The human immunodeficiency virus (HIV) particles are known to prevail following targeted cellular interferon secretion. CD4 T-lymphocytes are the primary receptor targets for HIV entry, but the virus has been observed to hide (be latent) successfully in these cells through an alternate entry route via interactions with LFA1.

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EEG reveals key features of binocular color fusion and rivalry.

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School of Information Science and Technology, Yunnan Normal University, Kunming, China; Yuxi Key Laboratory of Mental Health Examination, Yuxi 653100, Yunnan, China; Engineering Research Center of Computer Vision and Intelligent Control Technology, Department of Education of Yunnan Province, Kunming, China. Electronic address:

Differences in the brain sensitivity to color responses may cause significant differences in the latency and amplitude of the electroencephalographic (EEG) component. This paper investigated the electroencephalography features of binocular color fusion and binocular color rivalry when watching stereoscopic three-dimensional (3D) displays. EEG experiments were conducted on a conventional 3D display platform.

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Previous investigations have revealed the role of GABAergic and serotonergic systems in the modulation of pain behavior. This research aimed to examine the effects of intracerebroventricular (i.c.

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Aluminum Induces Neurotoxicity through the MicroRNA-98-5p/Insulin-like Growth Factor 2 Axis.

ACS Chem Neurosci

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Department of Occupational Health, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi 030001, China.

Aluminum is a well-known and widely distributed environmental neurotoxin. This study aimed to investigate the effect of miR-98-5p targeting insulin-like growth factor 2 (IGF2) on aluminum neurotoxicity. Thirty-two Sprague-Dawley rats were randomly divided into four groups and administered 0, 10, 20, and 40 μmol/kg maltol aluminum [Al(mal)], respectively.

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SecEdge: A novel deep learning framework for real-time cybersecurity in mobile IoT environments.

Heliyon

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Department of Natural and Engineering Sciences, College of Applied Studies and Community Services, King Saud University, Riyadh, 11633, Saudi Arabia.

The rapid growth of Internet of Things (IoT) devices presents significant cybersecurity challenges due to their diverse and resource-constrained nature. Existing security solutions often fall short in addressing the dynamic and distributed environments of IoT systems. This study aims to propose a novel deep learning framework, SecEdge, designed to enhance real-time cybersecurity in mobile IoT environments.

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