Role of the P2 × 7 receptor in neurodegenerative diseases and its pharmacological properties.

Neurodegenerative diseases seriously affect patients' physical and mental health, reduce their quality of life, and impose a heavy burden on society. However, their treatment remains challenging. Therefore, exploring factors potentially related to the pathogenesis of neurodegenerative diseases and improving their diagnosis and treatment are urgently needed. Recent studies have shown that P2 × 7R plays a crucial role in regulating neurodegenerative diseases caused by neuroinflammation. P2 × 7R is an adenosine 5'-triphosphate ligand-gated cation channel receptor present in most tissues of the human body. An increase in P2 × 7R levels can affect the progression of neurodegenerative diseases, and the inhibition of P2 × 7R can alleviate neurodegenerative diseases. In this review, we comprehensively describe the biological characteristics (structure, distribution, and function) of this gene, focusing on its potential association with neurodegenerative diseases, and we discuss the pharmacological effects of drugs (P2 × 7R inhibitors) used to treat neurodegenerative diseases.

The Role of Iron Metabolism in Sepsis-associated Encephalopathy: a Potential Target.

Sepsis-associated encephalopathy (SAE) is an acute cerebral dysfunction secondary to infection, and the severity can range from mild delirium to deep coma. Disorders of iron metabolism have been proven to play an important role in a variety of neurodegenerative diseases by inducing cell damage through iron accumulation in glial cells and neurons. Recent studies have found that iron accumulation is also a potential mechanism of SAE. Systemic inflammation can induce changes in the expression of transporters and receptors on cells, especially high expression of divalent metal transporter1 (DMT1) and low expression of ferroportin (Fpn) 1, which leads to iron accumulation in cells. Excessive free Fe2+ can participate in the Fenton reaction to produce reactive oxygen species (ROS) to directly damage cells or induce ferroptosis. As a result, it may be of great help to improve SAE by treatment of targeting disorders of iron metabolism. Therefore, it is important to review the current research progress on the mechanism of SAE based on iron metabolism disorders. In addition, we also briefly describe the current status of SAE and iron metabolism disorders and emphasize the therapeutic prospect of targeting iron accumulation as a treatment for SAE, especially iron chelator. Moreover, drug delivery and side effects can be improved with the development of nanotechnology. This work suggests that treating SAE based on disorders of iron metabolism will be a thriving field.

NLRP3 inflammasome in cognitive impairment and pharmacological properties of its inhibitors.

Cognitive impairment is a multifactorial and multi-step pathological process that places a heavy burden on patients and the society. Neuroinflammation is one of the main factors leading to cognitive impairment. The inflammasomes are multi-protein complexes that respond to various microorganisms and endogenous danger signals, helping to initiate innate protective responses in inflammatory diseases. NLRP3 inflammasomes produce proinflammatory cytokines (interleukin IL-1ß and IL-18) by activating caspase-1. In this review, we comprehensively describe the structure and functions of the NLRP3 inflammasome. We also explore the intrinsic relationship between the NLRP3 inflammasome and cognitive impairment, which involves immune cell activation, cell apoptosis, oxidative stress, mitochondrial autophagy, and neuroinflammation. Finally, we describe NLRP3 inflammasome antagonists as targeted therapies to improve cognitive impairment.

Mechanotransductive receptor Piezo1 as a promising target in the treatment of fibrosis diseases.

Fibrosis could happen in every organ, leading to organic malfunction and even organ failure, which poses a serious threat to global health. Early treatment of fibrosis has been reported to be the turning point, therefore, exploring potential correlates in the pathogenesis of fibrosis and how to reverse fibrosis has become a pressing issue. As a mechanism-sensitive cationic calcium channel, Piezo1 turns on in response to changes in the lipid bilayer of the plasma membrane. Piezo1 exerts multiple biological roles, including inhibition of inflammation, cytoskeletal stabilization, epithelial-mesenchymal transition, stromal stiffness, and immune cell mechanotransduction, interestingly enough. These processes are closely associated with the development of fibrotic diseases. Recent studies have shown that deletion or knockdown of Piezo1 attenuates the onset of fibrosis. Therefore, in this paper we comprehensively describe the biology of this gene, focusing on its potential relevance in pulmonary fibrosis, renal fibrosis, pancreatic fibrosis, and cardiac fibrosis diseases, except for the role of drugs (agonists), increased intracellular calcium and mechanical stress using this gene in alleviating fibrosis.

Hsp22 pretreatment protects against LPS-induced hippocampal injury by alleviating neuroinflammation and apoptosis by regulating the NLRP3/Caspase1/IL-1ß signaling pathway in mice.

Neuroinflammation is an important reason for the occurrence and development of cognitive impairment. The Lentiviral vector Hsp22 was constructed for intracerebroventricular injection pretreatment, LPS was used to induce the cognitive impairment model in mice, and the Morris water maze was used to examine the changes in cognitive behavior in mice. LPS was used to induce BV-2 microglial cells, and plasmid pretreatment was used to overexpress Hsp22. HE staining, Nissl staining, immunohistochemistry, immunofluorescence, ELISA and protein blotting were used to examine microglial activation, changes in inflammatory factors, changes in pathway proteins and apoptosis. The results showed that LPS induced microglial expression of NLRP3/Caspase-1/IL-1ß signaling pathway protein Iba1, and the inflammatory protein and inflammatory factors IL-1ß, IL-6 and TNF-α, the expression of Bax increased significantly, Bcl2 expression decreased, and the learning and memory abilities of mice decreased significantly. Preconditioning with the Hsp22-overexpressing lentivirus attenuated LPS-induced activation of hippocampal microglia, the expression of inflammatory factors and pathway proteins, and apoptosis, and improved cognitive impairment in mice. In addition, plasmid-mediated Hsp22 overexpression reversed LPS-induced inflammation. These findings suggest that Hsp22 overexpression is a promising method for the treatment of cognitive impairment.

Future directions in ventilator-induced lung injury associated cognitive impairment: a new sight.

Mechanical ventilation is a widely used short-term life support technique, but an accompanying adverse consequence can be pulmonary damage which is called ventilator-induced lung injury (VILI). Mechanical ventilation can potentially affect the central nervous system and lead to long-term cognitive impairment. In recent years, many studies revealed that VILI, as a common lung injury, may be involved in the central pathogenesis of cognitive impairment by inducing hypoxia, inflammation, and changes in neural pathways. In addition, VILI has received attention in affecting the treatment of cognitive impairment and provides new insights into individualized therapy. The combination of lung protective ventilation and drug therapy can overcome the inevitable problems of poor prognosis from a new perspective. In this review, we summarized VILI and non-VILI factors as risk factors for cognitive impairment and concluded the latest mechanisms. Moreover, we retrospectively explored the role of improving VILI in cognitive impairment treatment. This work contributes to a better understanding of the pathogenesis of VILI-induced cognitive impairment and may provide future direction for the treatment and prognosis of cognitive impairment.

Diabetic peripheral neuropathy: pathogenetic mechanisms and treatment.

Diabetic peripheral neuropathy (DPN) refers to the development of peripheral nerve dysfunction in patients with diabetes when other causes are excluded. Diabetic distal symmetric polyneuropathy (DSPN) is the most representative form of DPN. As one of the most common complications of diabetes, its prevalence increases with the duration of diabetes. 10-15% of newly diagnosed T2DM patients have DSPN, and the prevalence can exceed 50% in patients with diabetes for more than 10 years. Bilateral limb pain, numbness, and paresthesia are the most common clinical manifestations in patients with DPN, and in severe cases, foot ulcers can occur, even leading to amputation. The etiology and pathogenesis of diabetic neuropathy are not yet completely clarified, but hyperglycemia, disorders of lipid metabolism, and abnormalities in insulin signaling pathways are currently considered to be the initiating factors for a range of pathophysiological changes in DPN. In the presence of abnormal metabolic factors, the normal structure and function of the entire peripheral nervous system are disrupted, including myelinated and unmyelinated nerve axons, perikaryon, neurovascular, and glial cells. In addition, abnormalities in the insulin signaling pathway will inhibit neural axon repair and promote apoptosis of damaged cells. Here, we will discuss recent advances in the study of DPN mechanisms, including oxidative stress pathways, mechanisms of microvascular damage, mechanisms of damage to insulin receptor signaling pathways, and other potential mechanisms associated with neuroinflammation, mitochondrial dysfunction, and cellular oxidative damage. Identifying the contributions from each pathway to neuropathy and the associations between them may help us to further explore more targeted screening and treatment interventions.

A Survey of Modulation Classification Using Deep Learning: Signal Representation and Data Preprocessing.

Modulation classification is one of the key tasks for communications systems monitoring, management, and control for addressing technical issues, including spectrum awareness, adaptive transmissions, and interference avoidance. Recently, deep learning (DL)-based modulation classification has attracted significant attention due to its superiority in feature extraction and classification accuracy. In DL-based modulation classification, one major challenge is to preprocess a received signal and represent it in a proper format before feeding the signal into deep neural networks. This article provides a comprehensive survey of the state-of-the-art DL-based modulation classification algorithms, especially the techniques of signal representation and data preprocessing utilized in these algorithms. Since a received signal can be represented by either features, images, sequences, or a combination of them, existing algorithms of DL-based modulation classification can be categorized into four groups and are reviewed accordingly in this article. Furthermore, the advantages as well as disadvantages of each signal representation method are summarized and discussed.

miR-103a-3p Could Attenuate Sepsis-Induced Liver Injury by Targeting HMGB1.

The liver is one of the most vulnerable organs during sepsis. Current studies have proven that microRNAs play important roles in injury and inflammation. The current study aimed to investigate the role of miR-103 in septic liver injury. The sepsis model was established by cecal ligation and puncture in mice. Then, the mice were divided into four groups: normal group, sepsis group, sepsis + miR-103a-3p agomir group, and sepsis + negative control group. Liver injury was observed by hematoxylin-eosin staining and electron microscopic studies. The sepsis-induced apoptosis in liver tissues was assessed by TUNEL staining. The levels of inflammatory cytokines in liver tissues were determined by enzyme-linked immunosorbent assay kits. The targeted gene of miR-103a-3p in cells was predicted by bioinformatics algorithm and confirmed by dual-luciferase reporter assay. The expression of miR-103a-3p, HMBG1, and the apoptosis-relative proteins was examined by quantitative real-time polymerase chain reaction and Western blotting. miR-103a-3p was downregulated in liver tissues of sepsis animals. miR-103a-3p agomir could alleviate liver injury including the tissue injury and mitochondrial damage, inhibit the secretion of inflammatory factors, and decrease the apoptosis of liver cells. The high-mobility group B1 (HMGB1) was overregulated in sepsis, and it was a downstream target gene of miR-103a-3p. The results of the rescue assay confirmed that miR-103a-3p had a protection role in septic liver injury by targeting HMGB1. In summary, HMGB1 was one of the genes targeted by miR-103a-3p, which played roles in septic injury. These data may provide novel insight for the identification of new target and treatment strategies for septic liver injury.

L-Theanine Attenuates Isoflurane-Induced Injury in Neural Stem Cells and Cognitive Impairment in Neonatal Mice.

The neurodevelopmental toxicity of isoflurane has been proved by many studies, which makes it essential to explore the underline mechanisms and search for protective agents to attenuate its neurotoxcity. Accumulating evidence showed that L-theanine had neuroprotective effects on injured neurons and the developing brain. The present study was designed to investigate whether L-theanine could attenuate isoflurane-induced damage in neural stem cells and cognitive impairment in young mice, and to discuss the role of protein kinase B (Akt)-glycogen synthase kinase 3ß (GSK-3ß) signaling pathway in this process. Multipotential neural stem cells (NSCs) and C57BL/6J mice were treated with either gas mixture, isoflurane, or L-theanine 30 min prior to isoflurane exposure, respectively. NSC viability was detected by CCK-8 assay. NSC proliferation and apoptosis were assessed by immunofluorescence and terminal deoxynucleotidyl transferase-mediated deoxyuridine triphosphate nick-end labeling (TUNEL) assay, respectively. The levels of cleaved caspase-3 and phosphorylated (p)-Akt and p-GSK-3ß in NSCs were tested by Western blotting. Cognitive function of mice was tested by Morris Water Maze at postnatal day (P) 30-35. The results indicated that isoflurane exposure inhibited NSC viability and proliferation, promoted NSC apoptosis as well as increased caspase-3 activation and down-regulated the expressions of p-Akt and p-GSK-3ß in NSCs, and that isoflurane exposure on neonatal mice would induce late cognitive impairment. Pretreatment with L-theanine could attenuate isoflurane-caused damage in NSCs and cognitive deficits in young mice. Addinonally, the protective effects of L-theanine on isoflurane-injured NSCs could be reversed by Akt inhibitor Triciribine. Our data showed that pretreatment with L-theanine eliminated the NSC damage and cognitive impairment induced by isoflurane exposure, and that the neuroprotective effect of L-theanine was associated with the Akt-GSK-3ß signaling pathway.

Modulation Classification Based on Signal Constellation Diagrams and Deep Learning.

Deep learning (DL) is a new machine learning (ML) methodology that has found successful implementations in many application domains. However, its usage in communications systems has not been well explored. This paper investigates the use of the DL in modulation classification, which is a major task in many communications systems. The DL relies on a massive amount of data and, for research and applications, this can be easily available in communications systems. Furthermore, unlike the ML, the DL has the advantage of not requiring manual feature selections, which significantly reduces the task complexity in modulation classification. In this paper, we use two convolutional neural network (CNN)-based DL models, AlexNet and GoogLeNet. Specifically, we develop several methods to represent modulated signals in data formats with gridlike topologies for the CNN. The impacts of representation on classification performance are also analyzed. In addition, comparisons with traditional cumulant and ML-based algorithms are presented. Experimental results demonstrate the significant performance advantage and application feasibility of the DL-based approach for modulation classification.