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1.
J Headache Pain ; 25(1): 29, 2024 Mar 08.
Article in English | MEDLINE | ID: mdl-38454376

ABSTRACT

BACKGROUND: Energy metabolism disorders and neurogenic inflammation play important roles in the central sensitization to chronic migraine (CM). AMP-activated protein kinase (AMPK) is an intracellular energy sensor, and its activation regulates inflammation and reduces neuropathic pain. However, studies on the involvement of AMPK in the regulation of CM are currently lacking. Therefore, this study aimed to explore the mechanism underlying the involvement of AMPK in the central sensitization to CM. METHODS: Mice with recurrent nitroglycerin (NTG)-induced CM were used to detect the expression of AMPK protein in the trigeminal nucleus caudalis (TNC). Following intraperitoneal injection of the AMPK activator 5-aminoimidazole-4-carboxyamide ribonucleoside (AICAR) and inhibitor compound C, the mechanical pain threshold, activity level, and pain-like behaviors in the mice were measured. The expression of calcitonin gene-related peptide (CGRP) and cytokines, M1/M2 microglia, and NF-κB pathway activation were detected after the intervention. RESULTS: Repeated NTG injections resulted in a gradual decrease in AMPK protein expression, and the negative regulation of AMPK by increased ubiquitin-like plant homeodomain and RING finger domain 1 (UHRF1) expression may counteract AMPK activation by increasing ADP/ATP. AICAR can reduce the hyperalgesia and pain-like behaviors of CM mice, improve the activity of mice, reduce the expression of CGRP, IL-1ß, IL-6, and TNF-α in the TNC region, and increase the expression of IL-4 and IL-10. Moreover, AMPK in TNC was mainly located in microglia. AICAR could reduce the expression of inducible NO synthase (iNOS) in M1 microglia and increase the expression of Arginase 1 (Arg1) in M2 microglia by inhibiting the activation of NF-κB pathway. CONCLUSIONS: AMPK was involved in the central sensitization of CM, and the activation of AMPK reduced neuroinflammation in NTG-induced CM mice. AMPK may provide new insights into interventions for energy metabolism disorders and neurogenic inflammation in migraine.


Subject(s)
Migraine Disorders , Nitroglycerin , Mice , Animals , Nitroglycerin/adverse effects , Microglia/metabolism , AMP-Activated Protein Kinases/metabolism , NF-kappa B/metabolism , Calcitonin Gene-Related Peptide/metabolism , Central Nervous System Sensitization/physiology , Neurogenic Inflammation/metabolism , Pain/metabolism , Migraine Disorders/chemically induced , Migraine Disorders/drug therapy , Migraine Disorders/metabolism
2.
Sensors (Basel) ; 20(4)2020 Feb 22.
Article in English | MEDLINE | ID: mdl-32098444

ABSTRACT

With the continuous development of science and engineering technology, our society has entered the era of the mobile Internet of Things (MIoT). MIoT refers to the combination of advanced manufacturing technologies with the Internet of Things (IoT) to create a flexible digital manufacturing ecosystem. The wireless communication technology in the Internet of Things is a bridge between mobile devices. Therefore, the introduction of machine learning (ML) algorithms into MIoT wireless communication has become a research direction of concern. However, the traditional key-based wireless communication method demonstrates security problems and cannot meet the security requirements of the MIoT. Based on the research on the communication of the physical layer and the support vector data description (SVDD) algorithm, this paper establishes a radio frequency fingerprint (RFF or RF fingerprint) authentication model for a communication device. The communication device in the MIoT is accurately and efficiently identified by extracting the radio frequency fingerprint of the communication signal. In the simulation experiment, this paper introduces the neighborhood component analysis (NCA) method and the SVDD method to establish a communication device authentication model. At a signal-to-noise ratio (SNR) of 15 dB, the authentic devices authentication success rate (ASR) and the rogue devices detection success rate (RSR) are both 90%.

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